Sample records for interactive soil moisture
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Evaluating Land-Atmosphere Interactions with the North American Soil Moisture Database
NASA Astrophysics Data System (ADS)
Giles, S. M.; Quiring, S. M.; Ford, T.; Chavez, N.; Galvan, J.
2015-12-01
The North American Soil Moisture Database (NASMD) is a high-quality observational soil moisture database that was developed to study land-atmosphere interactions. It includes over 1,800 monitoring stations the United States, Canada and Mexico. Soil moisture data are collected from multiple sources, quality controlled and integrated into an online database (soilmoisture.tamu.edu). The period of record varies substantially and only a few of these stations have an observation record extending back into the 1990s. Daily soil moisture observations have been quality controlled using the North American Soil Moisture Database QAQC algorithm. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.
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Evaluation of Long-term Soil Moisture Proxies in the U.S. Great Plains
NASA Astrophysics Data System (ADS)
Yuan, S.; Quiring, S. M.
2016-12-01
Soil moisture plays an important role in land-atmosphere interactions through both surface energy and water balances. However, despite its importance, there are few long-term records of observed soil moisture for investigating long-term spatial and temporal variations of soil moisture. Hence, it is necessary to find suitable approximations of soil moisture observations. 5 drought indices will be compared with simulated and observed soil moisture over the U.S. Great Plains during two time periods (1980 - 2012 and 2003 - 2012). Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Z Index (zindex) and Crop Moisture Index (CMI) will be calculated by PRISM data. The soil moisture simulations will be derived from NLDAS. In situ soil moisture will be obtained from North American Soil Moisture Database. The evaluation will focus on three main aspects: trends, variations and persistence. The results will support further research investigating long-term variations in soil moisture-climate interactions.
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The moisture response of soil heterotrophic respiration: Interaction with soil properties.
USDA-ARS?s Scientific Manuscript database
Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...
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USDA-ARS?s Scientific Manuscript database
Precipitation limits primary production by affecting soil moisture, and soil type interacts with soil moisture to determine soil water availability to plants. We used ALMANAC, a process-based model, to simulate switchgrass (Panicum virgatum var. Alamo) biomass production in Central Texas under thre...
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Soil Moisture Project Evaluation Workshop
NASA Technical Reports Server (NTRS)
Gilbert, R. H. (Editor)
1980-01-01
Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.
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Soil moisture: Some fundamentals. [agriculture - soil mechanics
NASA Technical Reports Server (NTRS)
Milstead, B. W.
1975-01-01
A brief tutorial on soil moisture, as it applies to agriculture, is presented. Information was taken from books and papers considered freshman college level material, and is an attempt to briefly present the basic concept of soil moisture and a minimal understanding of how water interacts with soil.
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NASA Astrophysics Data System (ADS)
Tang, J.; Riley, W. J.
2017-12-01
Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.
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Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates
NASA Astrophysics Data System (ADS)
Mohanty, B.; Neelam, M.
2017-12-01
The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.
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USDA-ARS?s Scientific Manuscript database
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern...
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Persistence and memory timescales in root-zone soil moisture dynamics
Khaled Ghannam; Taro Nakai; Athanasios Paschalis; Andrew C. Oishi; Ayumi Kotani; Yasunori Igarashi; Tomo' omi Kumagai; Gabriel G. Katul
2016-01-01
The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however,...
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NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A.
2014-01-01
We present an observational analysis examining soil moisture control on surface energy dynamics and planetary boundary layer characteristics. Understanding soil moisture control on land-atmosphere interactions will become increasingly important as climate change continues to alter water availability. In this study, we analyzed 4 years of data from the Santa Rita Creosote Ameriflux site. We categorized our data independently in two ways: (1) wet or dry seasons and (2) one of the four cases within a two-layer soil moisture framework for the root zone based on the presence or absence of moisture in shallow (0-20 cm) and deep (20-60 cm) soil layers. Using these categorizations, we quantified the soil moisture control on surface energy dynamics and planetary boundary layer characteristics using both average responses and linear regression. Our results highlight the importance of deep soil moisture in land-atmosphere interactions. The presence of deep soil moisture decreased albedo by about 10%, and significant differences were observed in evaporative fraction even in the absence of shallow moisture. The planetary boundary layer height (PBLh) was largest when the whole soil profile was dry, decreasing by about 1 km when the whole profile was wet. Even when shallow moisture was absent but deep moisture was present the PBLh was significantly lower than when the entire profile was dry. The importance of deep moisture is likely site-specific and modulated through vegetation. Therefore, understanding these relationships also provides important insights into feedbacks between vegetation and the hydrologic cycle and their consequent influence on the climate system.
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USDA-ARS?s Scientific Manuscript database
Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...
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Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin
Increasing air temperatures are expected to continue in the future. The relation between soil moisture and near surface air temperature is significant for climate change and climate extremes. Evaluation of the relations between soil moisture and temperature was performed by devel...
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State of the Art in Large-Scale Soil Moisture Monitoring
NASA Technical Reports Server (NTRS)
Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;
2013-01-01
Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.
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First and Higher Order Effects on Zero Order Radiative Transfer Model
NASA Astrophysics Data System (ADS)
Neelam, M.; Mohanty, B.
2014-12-01
Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.
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NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A.; Vivoni, E. R.; Franz, T. E.; Anderson, C.
2013-12-01
Human impacts on desert ecosystems have wide ranging effects on the hydrologic cycle which, in turn, influence interactions between the critical zone and the atmosphere. In this contribution, we utilize cosmic-ray soil moisture sensors at three human-modified semiarid ecosystems in the North American monsoon region: a buffelgrass pasture in Sonora, Mexico, a woody-plant encroached savanna ecosystem in Arizona, and a woody-plant encroached shrubland ecosystem in New Mexico. In each case, landscape heterogeneity in the form of bare soil and vegetation patches of different types leads to a complex mosaic of soil moisture and land-atmosphere interactions. Historically, the measurement of spatially-averaged soil moisture at the ecosystem scale (on the order of several hundred square meters) has been problematic. Thus, new advances in measuring cosmogenically-produced neutrons present an opportunity for observational and modeling studies in these ecosystems. We discuss the calibration of the cosmic-ray soil moisture sensors at each site, present comparisons to a distributed network of in-situ measurements, and verify the spatially-aggregated observations using the watershed water balance method at two sites. We focus our efforts on the summer season 2013 and its rainfall period during the North American monsoon. To compare neutron counts to the ground sensors, we utilized an aspect-elevation weighting algorithm to compute an appropriate spatial average for the in-situ measurements. Similarly, the water balance approach utilizes precipitation, runoff, and evapotranspiration measurements in the footprint of the cosmic-ray sensors to estimate a spatially-averaged soil moisture field. Based on these complementary approaches, we empirically determined a relationship between cosmogenically-produced neutrons and the spatially-aggregated soil moisture. This approach may improve upon existing methods used to calculate soil moisture from neutron counts that typically suffer from increasing errors for higher soil moisture content. We also examined the effects of sub-footprint variability in soil moisture on the neutron readings by comparing two of the sites with large variations in topographically-mediated surface flows. Our work also synthesizes seasonal soil moisture dynamics across the desert ecosystems and attempts to tease out differences due to land cover alterations, including the seasonal greening in each study site occurring during the North American monsoon.
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NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Zulia M.
Uncertainty of predicted change in precipitation frequency and intensity motivates the scientific community to better understand, quantify, and model the possible outcome of dryland ecosystems. In pulse dependent ecosystems (i.e. monsoon driven) soil moisture is tightly linked to atmospheric processes. Here, I analyze three overarching questions; Q1) How does soil moisture presence or absence in a shallow or deep layer influence the surface energy budget and planetary boundary layer characteristics?, Q2) What is the role of vegetation on ecosystem albedo in the presence or absence of deep soil moisture?, Q3) Can we develop empirical relationships between soil moisture and the planetary boundary layer height to help evaluate the role of future precipitation changes in land surface atmosphere interactions? . To address these questions I use a conceptual framework based on the presence or absence of soil moisture in a shallow or deep layer. I define these layers by using root profiles and establish soil moisture thresholds for each layer using four years of observations from the Santa Rita Creosote Ameriflux site. Soil moisture drydown curves were used to establish the shallow layer threshold in the shallow layer, while NEE (Net Ecosystem Exchange of carbon dioxide) was used to define the deep soil moisture threshold. Four cases were generated using these thresholds: Case 1, dry shallow layer and dry deep layer; Case 2, wet shallow layer and dry deep layer; Case 3, wet shallow layer and wet deep layer, and Case 4 dry shallow and wet deep layer. Using this framework, I related data from the Ameriflux site SRC (Santa Rita Creosote) from 2008 to 2012 and from atmospheric soundings from the nearby Tucson Airport; conducted field campaigns during 2011 and 2012 to measure albedo from individual bare and canopy patches that were then evaluated in a grid to estimate the influence of deep moisture on albedo via vegetation cover change; and evaluated the potential of using a two-layer bucket model and empirical relationships to evaluate the link between deep soil moisture and the planetary boundary layer height under changing precipitation regime. My results indicate that (1) the presence or absence of water in two layers plays a role in surface energy dynamics, (2) soil moisture presence in the deep layer is linked with decreased ecosystem albedo and planetary boundary layer height, (3) deep moisture sustains vegetation greenness and decreases albedo, and (4) empirical relationships are useful in modeling planetary boundary layer height from dryland ecosystems. Based on these results we argue that deep soil moisture plays an important role in land surface-atmosphere interactions.
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The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation
NASA Astrophysics Data System (ADS)
Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.
2013-08-01
Soil moisture status in land surface models (LSMs) can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX) model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC), which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a) degradation of the incoming high-energy neutron flux with soil depth, (b) creation of fast neutrons at each depth in the soil, and (c) scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS), and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.
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Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships
NASA Astrophysics Data System (ADS)
Haghighi, Erfan; Kirchner, James W.
2017-07-01
Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.
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Cornelius, Mary L; Osbrink, Weste L A
2010-06-01
This study examined the influence of soil type and moisture availability on termite foraging behavior. Physical properties of the soil affected both tunneling behavior and shelter tube construction. Termites tunneled through sand faster than top soil and clay. In containers with top soil and clay, termites built shelter tubes on the sides of the containers. In containers with sand, termites built shelter tubes directly into the air and covered the sides of the container with a layer of sand. The interaction of soil type and moisture availability affected termite movement, feeding, and survival. In assays with moist soils, termites were more likely to aggregate in top soil over potting soil and peat moss. However, termites were more likely to move into containers with dry peat moss and potting soil than containers with dry sand and clay. Termites were also significantly more likely to move into containers with dry potting soil than dry top soil. In the assay with dry soils, termite mortality was high even though termites were able to travel freely between moist sand and dry soil, possibly due to desiccation caused by contact with dry soil. Evaporation from potting soil and peat moss resulted in significant mortality, whereas termites were able to retain enough moisture in top soil, sand, and clay to survive for 25 d. The interaction of soil type and moisture availability influences the distribution of foraging termites in microhabitats.
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NASA Technical Reports Server (NTRS)
Baker, David R.; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo; Simpson, Joanne
2000-01-01
Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.
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Morgado, Rui G; Gomes, Pedro A D; Ferreira, Nuno G C; Cardoso, Diogo N; Santos, Miguel J G; Soares, Amadeu M V M; Loureiro, Susana
2016-02-01
A main source of uncertainty currently associated with environmental risk assessment of chemicals is the poor understanding of the influence of environmental factors on the toxicity of xenobiotics. Aiming to reduce this uncertainty, here we evaluate the joint-effects of two pesticides (chlorpyrifos and mancozeb) on the terrestrial isopod Porcellionides pruinosus under different soil moisture regimes. A full factorial design, including three treatments of each pesticide and an untreated control, were performed under different soil moisture regimes: 25%, 50%, and 75% WHC. Our results showed that soil moisture had no effects on isopods survival, at the levels assessed in this experiment, neither regarding single pesticides nor mixture treatments. Additivity was always the most parsimonious result when both pesticides were present. Oppositely, both feeding activity and biomass change showed a higher sensitivity to soil moisture, with isopods generally showing worse performance when exposed to pesticides and dry or moist conditions. Most of the significant differences between soil moisture regimes were found in single pesticide treatments, yet different responses to mixtures could still be distinguished depending on the soil moisture assessed. This study shows that while soil moisture has the potential to influence the effects of the pesticide mixture itself, such effects might become less important in a context of complex combinations of stressors, as the major contribution comes from its individual interaction with each pesticide. Finally, the implications of our results are discussed in light of the current state of environmental risk assessment procedures and some future perspectives are advanced. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Effect of Soil Water Potential on Growth of Apple Trees Infected with Pratylenchus penetrans
Jaffee, B. A.; Mai, W. F.
1979-01-01
Malling-Merton 106 apple rootstocks inoculated with Pratylenchus penetrans, or uninoculated, were grown in a growth chamber in pots of loamy sand maintained at two moisture levels, 0 to -0.4 bar or 0 to -10 bars. Either inoculation or low soil moisture suppressed shoot growth and increased root necrosis. However, the nematode-soil moisture interaction was not significant. PMID:19305552
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Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method
2010-01-25
2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and
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NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.
2015-06-01
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate scale soil moisture estimates from the cosmic-ray sensing (CRS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower and runoff flumes used to close the water balance. We found an excellent agreement between the CRS method and the distributed sensor network (RMSE of 0.009 and 0.013 m3 m-3 at SRER and JER) at the hourly time scale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was obtained in soil moisture changes estimated from the CRS and watershed water balance methods (RMSE = 0.001 and 0.038 m3 m-3 at SRER and JER), with deviations due to bypassing of the CRS measurement depth during large rainfall events. This limitation, however, was used to show that drier-than-average conditions at SRER promoted plant water uptake from deeper layers, while the wetter-than-average period at JER resulted in leakage towards deeper soils. Using the distributed sensor network, we quantified the spatial variability of soil moisture in the CRS footprint and the relation between evapotranspiration and soil moisture, in both cases finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US. Furthermore, soil moisture spatial variability was related to evapotranspiration in a manner consistent with analytical relations derived using the CRS method, opening up new possibilities for understanding land-atmosphere interactions.
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Evaluation of a Soil Moisture Data Assimilation System Over West Africa
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.
2009-05-01
A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
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NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Z. M.; Papuga, S. A.
2013-12-01
In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.
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NASA Astrophysics Data System (ADS)
Haghighi, E.; Kirchner, J. W.; Entekhabi, D.
2016-12-01
The relationship between soil moisture and evapotranspiration (ET) fluxes is an important component of land-atmosphere interactions controlling hydrology-climate feedback processes. Important as this relationship is, it remains empirical and physical mechanisms governing its dynamics are insufficiently studied. This is particularly of importance for semiarid regions (currently comprising about half of the Earth's land surface) where the shallow surface soil layer is the primary source of ET and direct evaporation from bare soil is likely a large component of the total flux. Hence, ET-soil moisture coupling in these regions is hypothesized to be strongly influenced by soil evaporation and associated mechanisms. Motivated by recent progress in mechanistic modeling of localized heat and mass exchange rates from bare soil surfaces covered by cylindrical bluff-body elements, we developed a physically based ET model explicitly incorporating coupled impacts of soil moisture and vegetation-induced turbulence in the near-surface region. Model predictions of ET and its partitioning were in good agreement with measured data and suggest that the strength and nature of ET-soil moisture interactions in sparsely vegetated areas are strongly influenced by aerodynamic (rather than radiative) forcing namely wind speed and near-surface turbulence generation as a function of vegetation type and cover fraction. The results demonstrated that the relationship between ET and soil moisture varies from a nonlinear function (the dual regime behavior) to a single moisture-limited regime (linear relationship) by increasing wind velocity and enhancing turbulence generation in the near-surface region (small-scale woody vegetation species of low cover fraction). Potential benefits of this study for improving accuracy and predictive capabilities of remote sensing techniques when applied to semiarid environments will also be discussed.
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Shuhua Yi; David McGuire; Jennifer Harden; Eric Kasischke; Kristen Manies; Larr Hinzman; Anna Liljedahl; Jim Randerson; Heping Liu; Vladimire Romanovsky; Sergei Marchenko; Yongwon Kim
2009-01-01
Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were...
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Causes of Long-Term Drought in the United States Great Plains
NASA Technical Reports Server (NTRS)
Schubert, Siegfried D.; Suarez, Max J.; Pegion, Philip J.; Koster, Randal D.; Bacmeister, Julio T.
2003-01-01
This study examines the causes of long term droughts in the United States Great Plains (USGP). The focus is on the relative roles of slowly varying SSTs and interactions with soil moisture. The results from ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to- Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) show that the SSTs account for about 1/3 of the total low frequency rainfall variance in the USGP. Results from idealized experiments with climatological SST suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a five-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the deep soil is forced by white noise and damped with a time scale of about 2 years. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.
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Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Zulia Mayari; Papuga, Shirley Anne; Swetish, Jessica Blaine; van Leeuwen, Willem Jan Dirk; Szutu, Daphne; Hartfield, Kyle
2014-05-01
As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.
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NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data
NASA Technical Reports Server (NTRS)
Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih; Parinussa, Robert
2014-01-01
There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.
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Alba, Christina; NeSmith, Julienne E; Fahey, Catherine; Angelini, Christine; Flory, Stephen Luke
2017-03-01
Abiotic global change drivers affect ecosystem structure and function, but how they interact with biotic factors such as invasive plants is understudied. Such interactions may be additive, synergistic, or offsetting, and difficult to predict. We present methods to test the individual and interactive effects of drought and plant invasion on native ecosystems. We coupled a factorial common garden experiment containing resident communities exposed to drought (imposed with rainout shelters) and invasion with a field experiment where the invader was removed from sites spanning a natural soil moisture gradient. We detail treatments and their effects on abiotic conditions, including soil moisture, light, temperature, and humidity, which shape community and ecosystem responses. Ambient precipitation during the garden experiment exceeded historic norms despite severe drought in prior years. Soil moisture was 48% lower in drought than ambient plots, but the invader largely offset drought effects. Additionally, temperature and light were lower and humidity higher in invaded plots. Field sites spanned up to a 10-fold range in soil moisture and up to a 2.5-fold range in light availability. Invaded and resident vegetation did not differentially mediate soil moisture, unlike in the garden experiment. Herbicide effectively removed invaded and resident vegetation, with removal having site-specific effects on soil moisture and light availability. However, light was generally higher in invader-removal than control plots, whereas resident removal had less effect on light, similar to the garden experiment. Invasion mitigated a constellation of abiotic conditions associated with drought stress in the garden experiment. In the field, where other factors co-varied, these patterns did not emerge. Still, neither experiment suggested that drought and invasion will have synergistic negative effects on ecosystems, although invasion can limit light availability. Coupling factorial garden experiments with field experiments across environmental gradients will be effective for predicting how multiple stressors interact in natural systems.
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Uncertain soil moisture feedbacks in model projections of Sahel precipitation
NASA Astrophysics Data System (ADS)
Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra
2017-06-01
Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.
Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes (positive feedback), in others they dampen them (negative feedback). The impact of those feedbacks is in some cases of comparable amplitude to the projected precipitation changes themselves. In other words, we show, over a subset of climate models, how land-atmosphere interactions may be a cause of uncertainty in model projections of precipitation; we emphasize the need to evaluate these processes carefully in current and next-generation climate model simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/19627','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/19627"><span>Variation among four white ash families in response to competition and allelopathy</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>George Rink; J.W. Van Sambeek</p> <p>1987-01-01</p> <p>Analysis of three environmental variables affecting seedling growth of four half-sib white ash families was dominated by a three-way interaction between soil moisture stress, fescue leachate, and family. Of these, soil moisture stress contributed by far the most to the interaction and resulted in an average growth decline of 62%. Although fescue leachate appeared to be...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3052C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3052C"><span>Effect of soil moisture on diurnal convection and precipitation in Large-Eddy Simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cioni, Guido; Hohenegger, Cathy</p> <p>2017-04-01</p> <p>Soil moisture and convective precipitation are generally thought to be strongly coupled, although limitations in the modeling set-up of past studies due to coarse resolutions, and thus poorly resolved convective processes, have prevented a trustful determination of the strength and sign of this coupling. In this work the soil moisture-precipitation feedback is investigated by means of high-resolution simulations where convection is explicitly resolved. To that aim we use the LES (Large Eddy Simulation) version of the ICON model with a grid spacing of 250 m, coupled to the TERRA-ML soil model. We use homogeneous initial soil moisture conditions and focus on the precipitation response to increase/decrease of the initial soil moisture for various atmospheric profiles. The experimental framework proposed by Findell and Eltahir (2003) is revisited by using the same atmospheric soundings as initial condition but allowing a full interaction of the atmosphere with the land-surface over a complete diurnal cycle. In agreement with Findell and Eltahir (2003) the triggering of convection can be favoured over dry soils or over wet soils depending on the initial atmospheric sounding. However, total accumulated precipitation is found to always decrease over dry soils regardless of the employed sounding, thus highlighting a positive soil moisture-precipitation feedback (more rain over wetter soils) for the considered cases. To understand these differences and to infer under which conditions a negative feedback may occur, the total accumulated precipitation is split into its magnitude and duration component. While the latter can exhibit a dry soil advantage, the precipitation magnitude strongly correlates with the surface latent heat flux and thus always exhibits a wet soil advantage. The dependency is so strong that changes in duration cannot offset it. This simple argument shows that, in our idealised setup, a negative feedback is unlikely to be observed. The effects of other factors on the soil moisture-precipitation coupling, namely cloud radiative effects, large-scale forcing, winds, and plants are investigated by conducting further sensitivity experiments. All the experiments support a positive soil moisture-precipitation feedback. References: -Findell, K. L., and E. A. Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions. part I: Framework development. Journal of Hydrometeorology, 4 (3), 552-569.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840005567','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840005567"><span>A simulation study of scene confusion factors in sensing soil moisture from orbital radar</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.</p> <p>1983-01-01</p> <p>Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17158615','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17158615"><span>Response of Nitrosospira sp. strain AF-like ammonia oxidizers to changes in temperature, soil moisture content, and fertilizer concentration.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Avrahami, Sharon; Bohannan, Brendan J M</p> <p>2007-02-01</p> <p>Very little is known regarding the ecology of Nitrosospira sp. strain AF-like bacteria, a unique group of ammonia oxidizers within the Betaproteobacteria. We studied the response of Nitrosospira sp. strain AF-like ammonia oxidizers to changing environmental conditions by applying molecular methods and physiological measurements to Californian grassland soil manipulated in the laboratory. This soil is naturally high in Nitrosospira sp. strain AF-like bacteria relative to the much-better-studied Nitrosospira multiformis-like ammonia-oxidizing bacteria. Increases in temperature, soil moisture, and fertilizer interacted to reduce the relative abundance of Nitrosospira sp. strain AF-like bacteria, although they remained numerically dominant. The overall abundance of ammonia-oxidizing bacteria increased with increasing soil moisture and decreased with increasing temperature. Potential nitrification activity was altered by interactions among temperature, soil moisture, and fertilizer, with activity tending to be higher when soil moisture and temperature were increased. The increase in potential nitrification activity with increased temperature was surprising, given that the overall abundance of ammonia-oxidizing bacteria decreased significantly under these conditions. This observation suggests that (i) Nitrosospira sp. strain AF-like bacteria may respond to increased temperature with an increase in activity, despite a decrease in abundance, or (ii) that potential nitrification activity in these soils may be due to organisms other than bacteria (e.g., archaeal ammonia oxidizers), at least under conditions of increased temperature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1828661','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1828661"><span>Response of Nitrosospira sp. Strain AF-Like Ammonia Oxidizers to Changes in Temperature, Soil Moisture Content, and Fertilizer Concentration▿</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Avrahami, Sharon; Bohannan, Brendan J. M.</p> <p>2007-01-01</p> <p>Very little is known regarding the ecology of Nitrosospira sp. strain AF-like bacteria, a unique group of ammonia oxidizers within the Betaproteobacteria. We studied the response of Nitrosospira sp. strain AF-like ammonia oxidizers to changing environmental conditions by applying molecular methods and physiological measurements to Californian grassland soil manipulated in the laboratory. This soil is naturally high in Nitrosospira sp. strain AF-like bacteria relative to the much-better-studied Nitrosospira multiformis-like ammonia-oxidizing bacteria. Increases in temperature, soil moisture, and fertilizer interacted to reduce the relative abundance of Nitrosospira sp. strain AF-like bacteria, although they remained numerically dominant. The overall abundance of ammonia-oxidizing bacteria increased with increasing soil moisture and decreased with increasing temperature. Potential nitrification activity was altered by interactions among temperature, soil moisture, and fertilizer, with activity tending to be higher when soil moisture and temperature were increased. The increase in potential nitrification activity with increased temperature was surprising, given that the overall abundance of ammonia-oxidizing bacteria decreased significantly under these conditions. This observation suggests that (i) Nitrosospira sp. strain AF-like bacteria may respond to increased temperature with an increase in activity, despite a decrease in abundance, or (ii) that potential nitrification activity in these soils may be due to organisms other than bacteria (e.g., archaeal ammonia oxidizers), at least under conditions of increased temperature. PMID:17158615</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29367677','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29367677"><span>Interactive effects of compost and pre-planting soil moisture on plant biomass, nutrition and formation of mycorrhizas: a context dependent response.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ngo, H T T; Cavagnaro, T R</p> <p>2018-01-24</p> <p>We aimed to investigate the combined impacts of compost addition and pre-planting soil moisture conditions, on plant-available nutrients, and subsequent impacts on the biomass, nutrition and formation of AM by two important crop species. A glasshouse study was undertaken in which wheat and tomato plants were grown in compost amended or un-amended soil that was subjected to different moisture regimes prior to planting. The availability of P was strongly influenced by compost addition, but not pre-planting moisture conditions. In contrast, mineral N pools were affected by compost addition and pre-planting soil moisture conditions in complex ways. These changes in nutrient availability affected plant biomass, nutrient uptake and formation of AM. In general, plant performance was better where pre-planting soil moisture conditions were wet or dry, and worse where they involved a wet/dry cycle, and mycorrhizal colonisation was lower where compost was added to the soil. That pre-planting moisture conditions affect the biomass of subsequent crops is an important finding, the potential implications of which are considered here.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_2 --> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H53A1513S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H53A1513S"><span>Quantifying the influence of deep soil moisture on ecosystem albedo: the role of vegetation Zulia M. Sánchez-Mejía 1 and Shirley A. Papuga1 1School of Natural Resources and the Environment, University of Arizona, Tucson, AZ</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sanchez-Mejia, Z. M.; Papuga, S. A.</p> <p>2012-12-01</p> <p>Water limited ecosystems in arid and semiarid regions are characterized by sparse vegetation and a relatively large fraction of bare soil. Importantly, the land surface in these dryland regions is highly sensitive to pulses of moisture that affect the vegetation canopy in density and color, as well as the soil color. Changes in surface conditions due to these pulses have been shown to affect the surface energy fluxes and atmospheric processes in these regions. For instance, previous studies have shown that shallow soil moisture ( < 20 cm below the surface) significantly changes surface albedo (a= SWup/ SWin). Recent studies have highlighted the importance of deep soil moisture ( > 20 cm below the surface) for vegetation dynamics in these regions. We hypothesize that deep soil moisture will change vegetation canopy density and color enough that changes in albedo will be observable at the surface, therefore linking deep soil moisture and albedo. We adopt a conceptual framework to address this hypothesis, where at any point in time the soil profile falls into one of four cases: (1) dry shallow soil and dry deep soil; (2) wet shallow soil and dry deep soil; (3) wet shallow soil and wet deep soil; and (4) dry shallow soil and wet deep soil. At a creosotebush dominated ecosystem of the Santa Rita Experimental Range, southern Arizona during summers of 2011 and 2012, we took albedo measurements during these cases at multiple bare and vegetated patches within the footprint of an eddy covariance tower. We found that when the soil is completely dry (Case 1) albedo is highest in both bare and vegetated patches. Likewise, when the soil is wet in both the shallow and deep regions (Case 3), albedo is lowest in both bare and vegetated patches. Interestingly, we also found that albedo is significantly lower for vegetated patches when the deep soil is wet and shallow soil is dry (Case 4). These results imply that deep soil moisture can be important in altering ecosystem level albedo. We note that ecosystems with higher percent vegetative cover are likely to be more sensitive to deep soil moisture driven changes in albedo. To quantify the influence of percent cover on ecosystem albedo, we populate a 100 x 100 cell grid randomly with bare and vegetated cells. For each case, we assign an albedo value to each cell based on probability distribution functions (PDFs) of soil moisture and albedo created from our field campaign data. Using this technique we can identify for each soil moisture case at which point the percent vegetative cover will significantly influence ecosystem albedo. Quantitative analyses of these ecosystem interactions help identify the unique role of deep soil moisture in land surface - atmosphere interactions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940006468','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940006468"><span>Design of a global soil moisture initialization procedure for the simple biosphere model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liston, G. E.; Sud, Y. C.; Walker, G. K.</p> <p>1993-01-01</p> <p>Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H21C1423J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H21C1423J"><span>Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.</p> <p>2016-12-01</p> <p>Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010WRR....46.2516B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010WRR....46.2516B"><span>Spatial-temporal variability of soil moisture and its estimation across scales</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.</p> <p>2010-02-01</p> <p>The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA594064','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA594064"><span>Energetic Materials Effects on Essential Soil Processes: Decomposition of Orchard Grass (Dactylis glomerata) Litter in Soil Contaminated with Energetic Materials</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-02-01</p> <p>moisture level of 14% dry soil mass was maintained for the duration of the study by weekly additions of ASTM Type I water. Soil samples were collected...maintain the initial soil moisture level. One cluster of Orchard grass straw was harvested from a set of randomly selected replicate containers...decomposition is among the most integrating processes within the soil ecosystem because it involves complex interactions of soil microbial, plant , and</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H"><span>Surface Soil Moisture Memory Estimated from Models and SMAP Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.</p> <p>2017-12-01</p> <p>Soil moisture memory(SMM), which is loosely defined as the time taken by soil to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the soil moisture time series and the timescale which only considers soil moisture increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on soil moisture memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the soil moisture time series autocorrelation, deT0 based on the detrending soil moisture time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface soil moisture was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface Soil Moisture, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data Product, 2014</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70168512','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70168512"><span>Does the stress-gradient hypothesis hold water? Disentangling spatial and temporal variation in plant effects on soil moisture in dryland systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Butterfield, Bradley J.; Bradford, John B.; Armas, Cristina; Prieto, Ivan; Pugnaire, Francisco I.</p> <p>2016-01-01</p> <p>Taken together, the results of this simulation study suggest that plant effects on soil moisture are predictable based on relatively general relationships between precipitation inputs and differential evaporation and transpiration rates between plant and interspace microsites that are largely driven by temperature. In particular, this study highlights the importance of differentiating between temporal and spatial variation in weather and climate, respectively, in determining plant effects on available soil moisture. Rather than focusing on the somewhat coarse-scale predictions of the SGH, it may be more beneficial to explicitly incorporate plant effects on soil moisture into predictive models of plant-plant interaction outcomes in drylands.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..561..833S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..561..833S"><span>The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye</p> <p>2018-06-01</p> <p>The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can affect the simulated evaporation fluxes, especially under dry condition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150023611','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150023611"><span>4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.</p> <p>2015-01-01</p> <p>This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/972970-evaluating-influence-antecedent-soil-moisture-variability-north-american-monsoon-precipitation-coupled-mm5-vic-modeling-system','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/972970-evaluating-influence-antecedent-soil-moisture-variability-north-american-monsoon-precipitation-coupled-mm5-vic-modeling-system"><span>Evaluating the influence of antecedent soil moisture on variability of the North American Monsoon precipitation in the coupled MM5/VIC modeling system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Zhu, Chunmei; Leung, Lai R.; Gochis, David</p> <p>2009-11-29</p> <p>The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5-VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most ofmore » the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land-sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet premonsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. The surface temperature changes induced by differences in surface energy flux partitioning associated with pre-monsoon soil moisture anomalies changed the surface pressure and consequently the flow field in the coupled model, which in turn changed moisture convergence and, accordingly, precipitation patterns. Both the largescale circulation change and local land-atmospheric interactions in response to premonsoon soil moisture anomalies play important roles in the coupled model’s positive soil moisture monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture precipitation feedbacks.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B43F0621F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B43F0621F"><span>Study Variability of Seasonal Soil Moisture in Ensemble of CMIP5 Models Over South Asia During 1950-2005</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.</p> <p>2015-12-01</p> <p>Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H13K1568S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H13K1568S"><span>Electrical resistivity surveys to understand vegetation-water interlinkages in a northern latitude headwater catchment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Soulsby, C.; Dick, J.; Tetzlaff, D.; Bradford, J.</p> <p>2016-12-01</p> <p>The role of vegetation on the partitioning of precipitation, and the subsequent storage and release of water within the landscape is poorly understood. In particular, the relationship between vegetation and soil moisture is complex and reciprocal. The role of soil moisture as the primary source of water to plants may affect vegetation distribution. In turn, the structure of vegetation canopies may regulate water partitioning into interception, throughfall and steam flow. Such spatial differences in the inputs, together with complex patterns of water uptake from highly distributed root networks can create marked heterogeneity in soil moisture dynamics at small scales. Here, we present a study combining 3D and 2D ERT surveys with soil moisture measurements in a 3.2km upland catchment in the Scottish Highlands to understand influences of different vegetation types on spatio-temporal dynamics in soil moisture. The study focussed on one year of fortnightly ERT surveys to investigate plant-soil-water interactions within the root zone in podzolic soils. Locations were selected in both forest stands of 15m high Scots pine (Pinus sylvestris) and non-forest locations dominated by heather (Calluna vulgaris) shrubs (<0.5m high). These dominant species are typical of forest and non-forest vegetation communities in the Scottish Highlands. Results showed differences in the soil moisture dynamics under the different vegetation types, with heterogeneous patterns in the forested site mainly correlated with canopy cover and mirroring interception losses, with pronounced wetting cycles of the soil surrounding the bole of trees as a consequence of stem flow. Temporal variability in the forested site was greater, probably due to the interception, and increased evapotranspiration losses relative to the heather site, with drying typically being focussed on the areas around the trees, and reflecting the amount of water uptake. Moisture changes in the heather site were fairly heterogeneous are related to micro-topographic affects, lower interception ( 30% compared with 45%) and a smaller microclimatic effect of the canopy which serves to create greater fluctuations in soil moisture. Our results confirm the value in using geophysics to spatially elucidate subsurface plant-soil-water interactions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B13B0573Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B13B0573Z"><span>Soil Nitrification and N2O Production: the connection with N concentration and Soil Water Content</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu-Barker, X.; Horwath, W. R.</p> <p>2016-12-01</p> <p>The development of mitigation strategies to reduce nitrous oxide (N2O) emission from soils is dependent on explicating the biophysical factors affecting different N2O production pathways. Ammonia oxidation and heterotrophic denitrification are the main pathways of N2O production, depending on soil conditions such as soil moisture content, oxygen (O2) content and N substrate. Many researchers have reported that N2O production increased as substrate concentration and soil moisture content increased. However, less understood is how N fertilizer concentration and moisture content interact to affect N2O production pathways. To investigate interaction and its effect on O2 consumption, we incubated three agricultural soils (clay, sandy loam, and peat) with different concentrations of (NH4)2SO4 (0-1000 µg N g-1) under 50 %, 75%, and 100% of water holding capacity. All treatments received 15N -KNO3 to bring the concentrations of NO3-_N in soils to 50 mg kg-1 soil and the NO3- pool to an enrichment of 10 atom% 15N. In all soils, the total amount of O2 consumption and N2O production increased as soil ammonical N concentration increased. The increased soil moisture significantly promoted N2O production in sandy loam and clay loam soils, compared to the peat soil. These results indicate that N2O production increased as substrate concentration increased likely due to the onset of O2 limitation caused by ammonia oxidation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...620018R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...620018R"><span>Experimental evidence for drought induced alternative stable states of soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Robinson, David. A.; Jones, Scott B.; Lebron, Inma; Reinsch, Sabine; Domínguez, María T.; Smith, Andrew R.; Jones, Davey L.; Marshall, Miles R.; Emmett, Bridget A.</p> <p>2016-01-01</p> <p>Ecosystems may exhibit alternative stable states (ASS) in response to environmental change. Modelling and observational data broadly support the theory of ASS, however evidence from manipulation experiments supporting this theory is limited. Here, we provide long-term manipulation and observation data supporting the existence of drought induced alternative stable soil moisture states (irreversible soil wetting) in upland Atlantic heath, dominated by Calluna vulgaris (L.) Hull. Manipulated repeated moderate summer drought, and intense natural summer drought both lowered resilience resulting in shifts in soil moisture dynamics. The repeated moderate summer drought decreased winter soil moisture retention by ~10%. However, intense summer drought, superimposed on the experiment, that began in 2003 and peaked in 2005 caused an unexpected erosion of resilience and a shift to an ASS; both for the experimental drought manipulation and control plots, impairing the soil from rewetting in winter. Measurements outside plots, with vegetation removal, showed no evidence of moisture shifts. Further independent evidence supports our findings from historical soil moisture monitoring at a long-term upland hydrological observatory. The results herald the need for a new paradigm regarding our understanding of soil structure, hydraulics and climate interaction.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4726285','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4726285"><span>Experimental evidence for drought induced alternative stable states of soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Robinson, David. A.; Jones, Scott B.; Lebron, Inma; Reinsch, Sabine; Domínguez, María T.; Smith, Andrew R.; Jones, Davey L.; Marshall, Miles R.; Emmett, Bridget A.</p> <p>2016-01-01</p> <p>Ecosystems may exhibit alternative stable states (ASS) in response to environmental change. Modelling and observational data broadly support the theory of ASS, however evidence from manipulation experiments supporting this theory is limited. Here, we provide long-term manipulation and observation data supporting the existence of drought induced alternative stable soil moisture states (irreversible soil wetting) in upland Atlantic heath, dominated by Calluna vulgaris (L.) Hull. Manipulated repeated moderate summer drought, and intense natural summer drought both lowered resilience resulting in shifts in soil moisture dynamics. The repeated moderate summer drought decreased winter soil moisture retention by ~10%. However, intense summer drought, superimposed on the experiment, that began in 2003 and peaked in 2005 caused an unexpected erosion of resilience and a shift to an ASS; both for the experimental drought manipulation and control plots, impairing the soil from rewetting in winter. Measurements outside plots, with vegetation removal, showed no evidence of moisture shifts. Further independent evidence supports our findings from historical soil moisture monitoring at a long-term upland hydrological observatory. The results herald the need for a new paradigm regarding our understanding of soil structure, hydraulics and climate interaction. PMID:26804897</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H43G1553S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H43G1553S"><span>Retrieving pace in vegetation growth using precipitation and soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sohoulande Djebou, D. C.; Singh, V. P.</p> <p>2013-12-01</p> <p>The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUSM.A34B..07K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUSM.A34B..07K"><span>Impact of vegetation feedback at subseasonal & seasonal timescales on precipitation over North America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Y.; Wang, G.</p> <p>2006-05-01</p> <p>Soil moisture-vegetation-precipitation feedbacks tend to enhance soil moisture memory in some areas of the globe, which contributes to the subseasonal and seasonal climate prediction skill. In this study, the impact of vegetation on precipitation over North America is investigated using a coupled land-atmosphere model CAM3- CLM3. The coupled model has been modified to include a predictive vegetation phenology scheme and validated against the MODIS data. Vegetation phenology is modeled by updating the leaf area index (LAI) daily in response to cumulative and concurrent hydrometeorological conditions. First, driven with the climatological SST, a large group of 5-member ensembles of simulations from the late spring and summer to the end of year are generated with the different initial conditions of soil moisture. The impact of initial soil moisture anomalies on subsequent precipitation is examined with the predictive vegetation phenology scheme disabled/enabled ("SM"/"SM_Veg" ensembles). The simulated climate differences between "SM" and "SM_Veg" ensembles represent the role of vegetation in soil moisture-vegetation- precipitation feedback. Experiments in this study focus on how the response of precipitation to initial soil moisture anomalies depends on their characteristics, including the timing, magnitude, spatial coverage and vertical depth, and further how it is modified by the interactive vegetation. Our results, for example, suggest that the impact of late spring soil moisture anomalies is not evident in subsequent precipitation until early summer when local convective precipitation dominates. With the summer wet soil moisture anomalies, vegetation tends to enhance the positive feedback between soil moisture and precipitation, while vegetation tends to suppress such positive feedback with the late spring anomalies. Second, the impact of vegetation feedback is investigated by driving the model with the inter-annually varying monthly SST (1983-1994). With the predictive vegetation phenology disabled/enabled ("SM"/"SM_Veg" ensembles), the simulated climates are compared with the observation. This will present the role of an interactive or predictive vegetation phenology scheme in subseasonal and seasonal climate prediction. Specifically, the extreme climate events such as drought in 1988 and flood in 1993 over the Midwestern United States will be the focus of results analyses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6988M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6988M"><span>Groundwater influence on soil moisture memory and land-atmosphere interactions over the Iberian Peninsula</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Martinez-de la Torre, Alberto; Miguez-Macho, Gonzalo</p> <p>2017-04-01</p> <p>We investigate the memory introduced in soil moisture fields by groundwater long timescales of variation in the semi-arid regions of the Iberian Peninsula with the LEAFHYDRO soil-vegetation-hydrology model, which includes a dynamic water table fully coupled to soil moisture and river flow via 2-way fluxes. We select a 10-year period (1989-1998) with transitions from wet to dry to again wet long lasting conditions and we carry out simulations at 2.5 km spatial resolution forced by ERA-Interim and a high-resolution precipitation analysis over Spain and Portugal. The model produces a realistic water table that we validate with hundreds of water table depth observation time series (ranging from 4 to 10 years) over the Iberian Peninsula. Modeled river flow is also compared to observations. Over shallow water table regions, results highlight the groundwater buffering effect on soil moisture fields over dry spells and long-term droughts, as well as the slow recovery of pre-drought soil wetness once climatic conditions turn wetter. Groundwater sustains river flow during dry summer periods. The longer lasting wet conditions in the soil when groundwater is considered increase summer evapotranspiration, that is mostly water-limited. Our results suggest that groundwater interaction with soil moisture should be considered for climate seasonal forecasting and climate studies in general over water-limited regions where shallow water tables are significantly present and connected to land surface hydrology.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913136S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913136S"><span>Assimilating soil moisture into an Earth System Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stacke, Tobias; Hagemann, Stefan</p> <p>2017-04-01</p> <p>Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/8728','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/8728"><span>Soil bulk density and soil moisture calculated with a FORTRAN 77 program.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>G.L. Starr; J.M. Geist</p> <p>1988-01-01</p> <p>This paper presents an improved version of BDEN, an interactive computer program written in FORTRAN 77 that will calculate soil bulk density and moisture percentage by weight and volume. Calculations allow for deducting coarse fragment weight and volume. The program will also summarize the resulting data by giving the mean, standard deviation, and 95-percent confidence...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_3 --> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70173864','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70173864"><span>Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Yi, Shuhua; McGuire, A. David; Harden, Jennifer; Kasischke, Eric; Manies, Kristen L.; Hinzman, Larry; Liljedahl, Anna K.; Randerson, J.; Liu, Heping; Romanovsky, Vladimir E.; Marchenko, Sergey S.; Kim, Yongwon</p> <p>2009-01-01</p> <p>Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.8156E..02C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.8156E..02C"><span>MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent</p> <p>2011-09-01</p> <p>Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70192461','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70192461"><span>Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.; Yackulic, Charles B.; Duniway, Michael C.; Hall, Sonia A.; Jia, Gensuo; Jamiyansharav, Khishigbayar; Munson, Seth M.; Wilson, Scott D.; Tietjen, Britta</p> <p>2017-01-01</p> <p>The distribution of rainfed agriculture is expected to respond to climate change and human population growth. However, conditions that support rainfed agriculture are driven by interactions among climate, including climate extremes, and soil moisture availability that have not been well defined. In the temperate regions that support much of the world’s agriculture, these interactions are complicated by seasonal temperature fluctuations that can decouple climate and soil moisture. Here, we show that suitability to support rainfed agriculture can be effectively represented by the interactive effects of just two variables: suitability increases where warm conditions occur with wet soil, and suitability decreases with extreme high temperatures. 21st century projections based on ecohydrological modeling of downscaled climate forecasts imply geographic shifts and overall increases in the area suitable for rainfed agriculture in temperate regions, especially at high latitudes, and pronounced, albeit less widespread, declines in suitable areas in low latitude drylands, especially in Europe. These results quantify the integrative direct and indirect impact of rising temperatures on rainfed agriculture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5889175','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5889175"><span>Diel hysteresis between soil respiration and soil temperature in a biological soil crust covered desert ecosystem</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Xinrong; Zhang, Peng; Chen, Yongle</p> <p>2018-01-01</p> <p>Soil respiration induced by biological soil crusts (BSCs) is an important process in the carbon (C) cycle in arid and semi-arid ecosystems, where vascular plants are restricted by the harsh environment, particularly the limited soil moisture. However, the interaction between temperature and soil respiration remains uncertain because of the number of factors that control soil respiration, including temperature and soil moisture, especially in BSC-dominated areas. In this study, the soil respiration in moss-dominated crusts and lichen-dominated crusts was continuously measured using an automated soil respiration system over a one-year period from November 2015 to October 2016 in the Shapotou region of the Tengger Desert, northern China. The results indicated that over daily cycles, the half-hourly soil respiration rates in both types of BSC-covered areas were commonly related to the soil temperature. The observed diel hysteresis between the half-hourly soil respiration rates and soil temperature in the BSC-covered areas was limited by nonlinearity loops with semielliptical shapes, and soil temperature often peaked later than the half-hourly soil respiration rates in the BSC-covered areas. The average lag times between the half-hourly soil respiration rates and soil temperature for both types of BSC-covered areas were two hours over the diel cycles, and they were negatively and linearly related to the volumetric soil water content. Our results highlight the diel hysteresis phenomenon that occurs between soil respiration rates and soil temperatures in BSC-covered areas and the negative response of this phenomenon to soil moisture, which may influence total C budget evaluations. Therefore, the interactive effects of soil temperature and moisture on soil respiration in BSC-covered areas should be considered in global carbon cycle models of desert ecosystems. PMID:29624606</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21500076','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21500076"><span>Polynomial response of 2,4-D mineralization to temperature in soils at varying soil moisture contents, slope positions and depths.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Shymko, Janna L; Farenhorst, Annemieke; Zvomuya, Francis</p> <p>2011-01-01</p> <p>The herbicide 2,4-D [2,4-(dichlorophenoxy) acetic acid] is a widely used broadleaf control agent in cereal production systems. Although 2,4-D soil-residual activity (half-lives) are typically less than 10 days, this herbicide also has as a short-term leaching potential due to its relatively weak retention by soil constituents. Herbicide residual effects and leaching are influenced by environmental variables such as soil moisture and temperature. The objective of this study was to determine impacts of these environmental variables on the magnitude and extent of 2,4-D mineralization in a cultivated undulating Manitoba prairie landscape. Microcosm incubation experiments were utilized to assess 2,4-D half-lives and total mineralization using a 4 × 4 × 3 × 2 factorial design (with soil temperature at 4 levels: 5, 10, 20 and 40°C; soil moisture at 4 levels: 60, 85, 110, 135 % of field capacity; slope position at 3 levels: upper-, mid- and lower-slopes; and soil depth at 2 levels: 0-5 cm and 5-15 cm). Half-lives (t(½)) varied from 3 days to 51 days with the total 2,4-D mineralization (M(T)) ranging from 5.8 to 50.9 %. The four-way interaction (temperature × moisture × slope × depth) significantly (p < 0.001) influenced both t(½) and M(T). Second-order polynomial equations best described the relations of temperature with t(½) and M(T) as was expected from a biological system. However, the interaction and variability of t(½) and M(T) among different temperatures, soil moistures, slope positions, and soil depth combinations indicates that the complex nature of these interacting factors should be considered when applying 2,4-D in agricultural fields and in utilizing these parameters in pesticide fate models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010HESSD...7...67G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010HESSD...7...67G"><span>Shallow soil moisture - ground thaw interactions and controls - Part 2: Influences of water and energy fluxes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guan, X. J.; Spence, C.; Westbrook, C. J.</p> <p>2010-01-01</p> <p>The companion paper (Guan et al., 2010) demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the key control in variable soil moisture and frost table interactions among the sites was the presence of surface water. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to conductive ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010HESS...14.1387G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010HESS...14.1387G"><span>Shallow soil moisture - ground thaw interactions and controls - Part 2: Influences of water and energy fluxes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guan, X. J.; Spence, C.; Westbrook, C. J.</p> <p>2010-07-01</p> <p>The companion paper (Guan et al., 2010) demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the presence of surface water was the key control in variable soil moisture and frost table interactions among sites. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological and energy processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916428C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916428C"><span>Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue</p> <p>2017-04-01</p> <p>Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial community responds different to environmental change dependent on the soil moisture regime. These results are important to include in future modeling efforts to predict changes in soil-atmosphere exchange of CH4 under global change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5694439','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5694439"><span>Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.</p> <p>2017-01-01</p> <p>Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820011755','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820011755"><span>AgRISTARS: Yield model development/soil moisture. Interface control document</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1980-01-01</p> <p>The interactions and support functions required between the crop Yield Model Development (YMD) Project and Soil Moisture (SM) Project are defined. The requirements for YMD support of SM and vice-versa are outlined. Specific tasks in support of these interfaces are defined for development of support functions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140004260','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140004260"><span>Data Assimilation of SMAP Observations and the Impact on Weather Forecasts and Heat Stress</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zavodsky, Bradley; Case, Jonathan; Blankenship, Clay; Crosson, William; White, Khristopher</p> <p>2014-01-01</p> <p>SPoRT produces real-time LIS soil moisture products for situational awareness and local numerical weather prediction over CONUS, Mesoamerica, and East Africa ?Currently interact/collaborate with operational partners on evaluation of soil moisture products ?Drought/fire ?Extreme heat ?Convective initiation ?Flood and water borne diseases ?Initial efforts to assimilate L2 soil moisture observations from SMOS (as a precursor for SMAP) have been successful ?Active/passive blended product from SMAP will be assimilated similarly and higher spatial resolution should improve on local-scale processes</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6692U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6692U"><span>An inversion method for retrieving soil moisture information from satellite altimetry observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne</p> <p>2016-04-01</p> <p>Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H11E0817A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H11E0817A"><span>Patterns Of Moisture Storage During Canadian Prairie Drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Agboma, C. O.; Snelgrove, K. R.</p> <p>2008-12-01</p> <p>Comprehensive studies of soil moisture storage patterns during drought episodes and normal years on the Canadian Prairie are rare. These studies have become increasingly imperative and desirable for an understanding and quantification of the influences of the land surface moisture on atmospheric processes. These influences or "memory" of the soil moisture may play an important role under conditions of extreme climate such as drought and flood. The recollection of a wet or dry anomaly by the soil moisture memory is a fundamental component of any regional land-atmosphere interactions, which possess significant implications for seasonal forecasting. The 13,000km2 Upper Assiniboine River Basin in Central Saskatchewan with its outlet at Kamsack is the domain of this study; via deploying a land surface model variously known as the Variable Infiltration Capacity/Xinanjiang/ARNO model driven offline both in the water and energy balance modes, it was possible to capture the dynamics and seasonal response of the soil moisture storage up to a depth of about 1-metre. Meteorological inputs required to drive the model were retrieved respectively from Environment Canada and the North American Regional Reanalysis (NARR) dataset at daily and sub-daily time steps correspondingly. The North American Land Data Assimilation System (NLDAS) served as the repository from which the soil and vegetation parameters were obtained. The patterns in seasonal and inter-annual soil moisture storage as well as changes in the total water storage anomaly averaged over the entire basin were captured during a period of 11 years commencing 1994. The role of the observed patterns in the regional land-atmosphere interactions is being assessed to ascertain the relevance of the inherent memory in soil moisture as one of the slow drivers of the Canadian Prairie regional climate system with the key objective of attaining a better understanding of drought evolution, continuation and eventual cessation over this region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/958854-soil-moisture-surpasses-elevated-co2-temperature-control-soil-carbon-dynamics-multi-factor-climate-change-experiment','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/958854-soil-moisture-surpasses-elevated-co2-temperature-control-soil-carbon-dynamics-multi-factor-climate-change-experiment"><span>Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Garten Jr, Charles T; Classen, Aimee T; Norby, Richard J</p> <p>2009-01-01</p> <p>Some single-factor experiments suggest that elevated CO2 concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO2 x temperature x soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO2 had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO2, indicated between 14 and 19% new soil carbon under two different watering treatmentsmore » with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr-1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO2 efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO2 and temperature as a control on soil carbon dynamics.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24743980','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24743980"><span>Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören</p> <p>2014-01-01</p> <p>Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H42A..06O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H42A..06O"><span>Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ochsner, T.; Venterea, R. T.</p> <p>2009-12-01</p> <p>Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching will also be examined.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19797245','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19797245"><span>Low moisture availability inhibits the enhancing effect of increased soil temperature on net photosynthesis of white birch (Betula papyrifera) seedlings grown under ambient and elevated carbon dioxide concentrations.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ambebe, Titus F; Dang, Qing-Lai</p> <p>2009-11-01</p> <p>White birch (Betula papyrifera Marsh.) seedlings were grown under two carbon dioxide concentrations (ambient: 360 micromol mol(-1) and elevated: 720 micromol mol(-1)), three soil temperatures (5, 15 and 25 degrees C initially, increased to 7, 17 and 27 degrees C, respectively, 1 month later) and three moisture regimes (low: 30-40%; intermediate: 45-55% and high: 60-70% field water capacity) in greenhouses. In situ gas exchange and chlorophyll fluorescence were measured after 2 months of treatments. Net photosynthetic rate (A(n)) of seedlings grown under the intermediate and high moisture regimes increased from low to intermediate T(soil) and then decreased to high T(soil). There were no significant differences between the low and high T(soil), with the exception that A(n) was significantly higher under high than low T(soil) at the high moisture regime. No significant T(soil) effect on A(n) was observed at the low moisture regime. The intermediate T(soil) increased stomatal conductance (g(s)) only at intermediate and high but not at low moisture regime, whereas there were no significant differences between the low and high T(soil) treatments. Furthermore, the difference in g(s) between the intermediate and high T(soil) at high moisture regime was not statistically significant. The low moisture regime significantly reduced the internal to ambient CO2 concentration ratio at all T(soil). There were no significant individual or interactive effects of treatment on maximum carboxylation rate of Rubisco, light-saturated electron transport rate, triose phosphate utilization or potential photochemical efficiency of photosystem II. The results of this study suggest that soil moisture condition should be taken into account when predicting the responses of white birch to soil warming.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.8807S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.8807S"><span>Empirical Modeling of Planetary Boundary Layer Dynamics Under Multiple Precipitation Scenarios Using a Two-Layer Soil Moisture Approach: An Example From a Semiarid Shrubland</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A.</p> <p>2017-11-01</p> <p>In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used Santa Rita Creosote Ameriflux and Tucson Airport atmospheric sounding data to generate empirical relationships between soil moisture, albedo, and PBLh. Empirical relationships showed that ˜50% of the variation in PBLh can be explained by soil moisture and albedo with additional knowledge gained by dividing the soil profile into two layers. Therefore, we coupled these empirical relationships with soil moisture estimated using a two-layer bucket approach to model PBLh under six precipitation scenarios. Overall we observed that decreases in precipitation tend to limit the recovery of the PBL at the end of the wet season. However, increases in winter precipitation despite decreases in summer precipitation may provide opportunities for positive feedbacks that may further generate more winter precipitation. Our results highlight that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface-atmosphere applications have great potential for exploring the consequences of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003749','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003749"><span>Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo</p> <p>2016-01-01</p> <p>Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4058808','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4058808"><span>Interactive Effects of Moss-Dominated Crusts and Artemisia ordosica on Wind Erosion and Soil Moisture in Mu Us Sandland, China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yang, Yongsheng; Bu, Chongfeng; Mu, Xingmin; Shao, Hongbo; Zhang, Kankan</p> <p>2014-01-01</p> <p>To better understand the effects of biological soil crusts (BSCs) on soil moisture and wind erosion and study the necessity and feasibility of disturbance of BSCs in the Mu Us sandland, the effects of four treatments, including moss-dominated crusts alone, Artemisia ordosica alone, bare sand, and Artemisia ordosica combined with moss-dominated crusts, on rainwater infiltration, soil moisture, and annual wind erosion were observed. The major results are as follows. (1) The development of moss-dominated crusts exacerbated soil moisture consumption and had negative effects on soil moisture in the Mu Us sandland. (2) Moss-dominated crusts significantly increased soil resistance to wind erosion, and when combined with Artemisia ordosica, this effect became more significant. The contribution of moss-dominated crusts under Artemisia ordosica was significantly lower than that of moss-dominated crusts alone in sites where vegetative coverage > 50%. (3) Finally, an appropriate disturbance of moss-dominated crusts in the rainy season in sites with high vegetative coverage improved soil water environment and vegetation succession, but disturbance in sites with little or no vegetative cover should be prohibited to avoid the exacerbation of wind erosion. PMID:24982973</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24982973','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24982973"><span>Interactive effects of moss-dominated crusts and Artemisia ordosica on wind erosion and soil moisture in Mu Us sandland, China.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yang, Yongsheng; Bu, Chongfeng; Mu, Xingmin; Shao, Hongbo; Zhang, Kankan</p> <p>2014-01-01</p> <p>To better understand the effects of biological soil crusts (BSCs) on soil moisture and wind erosion and study the necessity and feasibility of disturbance of BSCs in the Mu Us sandland, the effects of four treatments, including moss-dominated crusts alone, Artemisia ordosica alone, bare sand, and Artemisia ordosica combined with moss-dominated crusts, on rainwater infiltration, soil moisture, and annual wind erosion were observed. The major results are as follows. (1) The development of moss-dominated crusts exacerbated soil moisture consumption and had negative effects on soil moisture in the Mu Us sandland. (2) Moss-dominated crusts significantly increased soil resistance to wind erosion, and when combined with Artemisia ordosica, this effect became more significant. The contribution of moss-dominated crusts under Artemisia ordosica was significantly lower than that of moss-dominated crusts alone in sites where vegetative coverage > 50%. (3) Finally, an appropriate disturbance of moss-dominated crusts in the rainy season in sites with high vegetative coverage improved soil water environment and vegetation succession, but disturbance in sites with little or no vegetative cover should be prohibited to avoid the exacerbation of wind erosion.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27600157','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27600157"><span>Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Feng, Huihui</p> <p>2016-09-07</p> <p>Climate and vegetation change are two dominating factors for soil moisture trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the soil moisture change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively affected soil moisture trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the soil moisture trends, while vegetation change acts as a regulator to drying or wetting the soil under the changing climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H33F1393K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H33F1393K"><span>Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korres, W.; Reichenau, T. G.; Schneider, K.</p> <p>2012-12-01</p> <p>Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29076022','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29076022"><span>The impact of cerium oxide nanoparticles on the physiology of soybean (Glycine max (L.) Merr.) under different soil moisture conditions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cao, Zhiming; Rossi, Lorenzo; Stowers, Cheyenne; Zhang, Weilan; Lombardini, Leonardo; Ma, Xingmao</p> <p>2018-01-01</p> <p>The ongoing global climate change raises concerns over the decreasing moisture content in agricultural soils. Our research investigated the physiological impact of two types of cerium oxide nanoparticles (CeO 2 NPs) on soybean at different moisture content levels. One CeO 2 NP was positively charged on the surface and the other negatively charged due to the polyvinylpyrrolidone (PVP) coating. The results suggest that the effect of CeO 2 NPs on plant photosynthesis and water use efficiency (WUE) was dependent upon the soil moisture content. Both types of CeO 2 NPs exhibited consistently positive impacts on plant photosynthesis at the moisture content above 70% of field capacity (θ fc ). Similar positive impact of CeO 2 NPs was not observed at 55% θ fc , suggesting that the physiological impact of CeO 2 NPs was dependent upon the soil moisture content. The results also revealed that V Cmax (maximum carboxylation rate) was affected by CeO 2 NPs, indicating that CeO 2 NPs affected the Rubisco activity which governs carbon assimilation in photosynthesis. In conclusion, CeO 2 NPs demonstrated significant impacts on the photosynthesis and WUE of soybeans and such impacts were affected by the soil moisture content. Graphical abstract Soil moisture content affects plant cerium oxide nanoparticle interactions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70162540','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70162540"><span>Soil moisture and biogeochemical factors influence the distribution of annual Bromus species</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Belnap, Jayne; Stark, John Thomas; Rau, Benjamin; Allen, Edith B.; Phillips, Sue</p> <p>2016-01-01</p> <p>Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromusoccurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan), little or noBromus is found, likely due to timing or amount of soil moisture relative to Bromus phenology. In hot, winter-rainfall-dominated deserts (parts of the Mojave Desert), Bromus rubens is widespread and correlated with high phosphorus availability. It also responds positively to additions of nitrogen alone or with phosphorus. On the Colorado Plateau, with higher soil moisture availability, factors limiting Bromus tectorum populations vary with life stage: phosphorus and water limit germination, potassium and the potassium/magnesium ratio affect winter performance, and water and potassium/magnesium affect spring performance. Controlling nutrients also change with elevation. In cooler deserts with winter precipitation (Great Basin, Columbia Plateau) and thus even greater soil moisture availability, B. tectorum populations are controlled by nitrogen, phosphorus, or potassium. Experimental nitrogen additions stimulate Bromus performance. The reason for different nutrients limiting in dissimilar climatic regions is not known, but it is likely that site conditions such as soil texture (as it affects water and nutrient availability), organic matter, and/or chemistry interact in a manner that regulates nutrient availability and limitations. Under future drier, hotter conditions,Bromus distribution is likely to change due to changes in the interaction between moisture and nutrient availability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AdWR..109..236K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AdWR..109..236K"><span>Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.</p> <p>2017-11-01</p> <p>Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land-atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales. Over the past four decades, several active and passive microwave sensors have been deployed, along with the recent launch of two fully dedicated missions (SMOS and SMAP). Signifying the four decades of microwave remote sensing of soil moisture, this Part 2 of the two-part review series aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy for retrieving soil moisture. The first part discusses the developments made in active and passive microwave soil moisture retrieval algorithms. We assess the evolution of the products of various sensors over the last four decades, in terms of daily coverage, temporal performance, and spatial performance, by comparing the products of eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product) with the International Soil Moisture Network (ISMN) in-situ stations and the Variable Infiltration Capacity (VIC) land surface model simulations over the Contiguous United States (CONUS). In the process, the regional impacts of vegetation conditions on the spatial and temporal performance of soil moisture products are investigated. We also carried out inter-satellite comparisons to study the roles of sensor design and algorithms on the retrieval accuracy. We find that substantial improvements have been made over recent years in this field in terms of daily coverage, retrieval accuracy, and temporal dynamics. We conclude that the microwave soil moisture products have significantly evolved in the last four decades and will continue to make key contributions to the progress of hydro-meteorological and climate sciences.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..12113859Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..12113859Y"><span>The intraannual variability of land-atmosphere coupling over North America in the Canadian Regional Climate Model (CRCM5)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang Kam Wing, G.; Sushama, L.; Diro, G. T.</p> <p>2016-12-01</p> <p>This study investigates the intraannual variability of soil moisture-temperature coupling over North America. To this effect, coupled and uncoupled simulations are performed with the fifth-generation Canadian Regional Climate Model (CRCM5), driven by ERA-Interim. In coupled simulations, land and atmosphere interact freely; in uncoupled simulations, the interannual variability of soil moisture is suppressed by prescribing climatological values for soil liquid and frozen water contents. The study also explores projected changes to coupling by comparing coupled and uncoupled CRCM5 simulations for current (1981-2010) and future (2071-2100) periods, driven by the Canadian Earth System Model. Coupling differs for the northern and southern parts of North America. Over the southern half, it is persistent throughout the year while for the northern half, strongly coupled regions generally follow the freezing line during the cold months. Detailed analysis of the southern Canadian Prairies reveals seasonal differences in the underlying coupling mechanism. During spring and fall, as opposed to summer, the interactive soil moisture phase impacts the snow depth and surface albedo, which further impacts the surface energy budget and thus the surface air temperature; the air temperature then influences the snow depth in a feedback loop. Projected changes to coupling are also season specific: relatively drier soil conditions strengthen coupling during summer, while changes in soil moisture phase, snow depth, and cloud cover impact coupling during colder months. Furthermore, results demonstrate that soil moisture variability amplifies the frequency of temperature extremes over regions of strong coupling in current and future climates.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/54125','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/54125"><span>Topography may mitigate drought effects on vegetation along a hillslope gradient</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Sandra Hawthorne; Chelcy Ford Miniat</p> <p>2017-01-01</p> <p>Topography may mitigate drought effects on vegetation along a hillslope gradient through redistribution of soil moisture. We examined the interaction of topography, climate, soil moisture, and transpiration in a lowâelevation, mixedâhardwood forest in the southern Appalachian Mountains. The effects of meteorological variation (wet and dry years) and topographic...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27108479','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27108479"><span>Influence of soil properties and soil moisture on the efficacy of indaziflam and flumioxazin on Kochia scoparia L.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sebastian, Derek J; Nissen, Scott J; Westra, Phil; Shaner, Dale L; Butters, Greg</p> <p>2017-02-01</p> <p>Kochia (Kochia scoparia L.) is a highly competitive, non-native weed found throughout the western United States. Flumioxazin and indaziflam are two broad-spectrum pre-emergence herbicides that can control kochia in a variety of crop and non-crop situations; however, under dry conditions, these herbicides sometimes fail to control this important weed. There is very little information describing the effect of soil properties and soil moisture on the efficacy of these herbicides. Soil organic matter (SOM) explained the highest proportion of variability in predicting the herbicide dose required for 80% kochia growth reduction (GR 80 ) for flumioxazin and indaziflam (R 2 = 0.72 and 0.79 respectively). SOM had a greater impact on flumioxazin phytotoxicity compared to indaziflam. Flumioxazin and indaziflam kochia phytotoxicity was greatly reduced at soil water potentials below -200 kPa. Kochia can germinate at soil moisture potentials below the moisture required for flumioxazin and indaziflam activation, which means that kochia control is greatly influenced by the complex interaction between soil physical properties and soil moisture. This research can be used to gain a better understanding of how and why some weeds, like kochia, are so difficult to manage even with herbicides that normally provide excellent control. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24288263','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24288263"><span>Interactive effects of λ-cyhalothrin, soil moisture, and temperature on Folsomia candida and Sinella curviseta (Collembola).</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bandow, Cornelia; Coors, Anja; Karau, Nora; Römbke, Jörg</p> <p>2014-03-01</p> <p>The authors investigated whether and how 2 environmental factors could influence the toxicity of a pyrethroid to 2 representatives of an important group of soil organisms. The impacts of different temperatures (20 °C and 26 °C) and soil moisture levels (30%, 50%, and 70% of water holding capacity) were investigated in combination with the insecticide λ-cyhalothrin on the reproduction success of Folsomia candida and Sinella curviseta in a full factorial design. Testing was based on the standard collembolan reproduction test (Organisation for Economic Co-operation and Development, guideline 232) following an effect concentration design. The results showed an effect of environmental and chemical factors on the number of juveniles of these animals. Particularly in dry soil, the reproduction of both species was reduced, while higher soil moisture levels influenced the number of juveniles positively compared with the middle soil moisture level. In general, however, higher soil moisture led to increased sensitivity to λ-cyhalothrin. In both organisms, temperature affected the toxicity of the pesticide but in different directions: high temperature led to higher toxicity in F. candida but to lower toxicity in S. curviseta. © 2013 SETAC.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017InAgr..31..339H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017InAgr..31..339H"><span>Effect of carbon and nitrogen addition on nitrous oxide and carbon dioxide fluxes from thawing forest soils</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haohao, Wu; Xingkai, Xu; Cuntao, Duan; TuanSheng, Li; Weiguo, Cheng</p> <p>2017-07-01</p> <p>Packed soil-core incubation experiments were done to study the effects of carbon (glucose, 6.4 g C m-2) and nitrogen (NH4Cl and KNO3, 4.5 g N m-2) addition on nitrous oxide (N2O) and carbon dioxide (CO2) fluxes during thawing of frozen soils under two forest stands (broadleaf and Korean pine mixed forest and white birch forest) with two moisture levels (55 and 80% water-filled pore space). With increasing soil moisture, the magnitude and longevity of the flush N2O flux from forest soils was enhanced during the early period of thawing, which was accompanied by great NO3--N consumption. Without N addition, the glucose-induced cumulative CO2 fluxes ranged from 9.61 to 13.49 g CO2-C m-2, which was larger than the dose of carbon added as glucose. The single addition of glucose increased microbial biomass carbon but slightly affected soil dissolved organic carbon pool. Thus, the extra carbon released upon addition of glucose can result from the decomposition of soil native organic carbon. The glucose-induced N2O and CO2 fluxes were both significantly correlated to the glucose-induced total N and dissolved organic carbon pools and influenced singly and interactively by soil moisture and KNO3 addition. The interactive effects of glucose and nitrogen inputs on N2O and CO2 fluxes from forest soils after frost depended on N sources, soil moisture, and vegetation types.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000PhDT........38W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000PhDT........38W"><span>Soil moisture profile variability in land-vegetation- atmosphere continuum</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Wanru</p> <p></p> <p>Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical experiments are conducted to examine the impacts of some potential controlling factors, which include atmospheric forcing (periodic and pulse) at the upper boundary, the initial soil moisture profile, the relative root abundance and the soil texture, on the variability of soil moisture profile and the corresponding evapotranspiration. Similar statistical data analyses are performed for the experimental data. Observations from the First International Satellite Land Surface Climatological Project (ISLSCP) Field Experiment (FIFE) are analyzed and used for the testing of model. The integration of the observational and modeling approaches makes it possible to better understand the mechanisms by which the soil moisture profile variability is generated with phase shift, fluctuation amplitude damping and low-pass frequency filtering with soil depth, to improve the strategies of parameterizations in land surface schemes, and furthermore, to assess its contribution to climate variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B"><span>Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.</p> <p>2017-12-01</p> <p>Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H41J..07H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H41J..07H"><span>The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.</p> <p>2011-12-01</p> <p>Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5808H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5808H"><span>A missing piece of the puzzle in climate change hotspots: Near-surface turbulent interactions controlling ET-soil moisture coupling in semiarid areas</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haghighi, Erfan; Gianotti, Daniel J.; Rigden, Angela J.; Salvucci, Guido D.; Kirchner, James W.; Entekhabi, Dara</p> <p>2017-04-01</p> <p>Being located in the transitional zone between dry and wet climate areas, semiarid ecosystems (and their associated ecohydrological processes) play a critical role in controlling climate change and global warming. Land evapotranspiration (ET), which is a central process in the climate system and a nexus of the water, energy and carbon cycles, typically accounts for up to 95% of the water budget in semiarid areas. Thus, the manner in which ET is partitioned into soil evaporation and plant transpiration in these settings is of practical importance for water and carbon cycling and their feedbacks to the climate system. ET (and its partitioning) in these regions is primarily controlled by surface soil moisture which varies episodically under stochastic precipitation inputs. Important as the ET-soil moisture relationship is, it remains empirical, and physical mechanisms governing its nature and dynamics are underexplored. Thus, the objective of this study is twofold: (1) to provide observational evidence for the influence of surface cover conditions on ET-soil moisture coupling in semiarid regions using soil moisture data from NASA's SMAP satellite mission combined with independent observationally based ET estimates, and (2) to develop a relatively simple mechanistic modeling platform improving our physical understanding of interactions between micro and macroscale processes controlling ET and its partitioning in partially vegetated areas. To this end, we invoked concepts from recent progress in mechanistic modeling of turbulent energy flux exchange in bluff-rough regions, and developed a physically based ET model that explicitly accounts for how vegetation-induced turbulence in the near-surface region influences soil drying and thus ET rates and dynamics. Model predictions revealed nonlinearities in the strength of the ET-soil moisture relationship (i.e., ∂ET/∂θ) as vegetation cover fraction increases, accounted for by the nonlinearity of surface-cover-dependent turbulent interactions. We identified a (predictable) critical vegetation cover fraction (as a function of vegetation stature and environmental conditions) that yields the strongest ET-soil moisture relationship under prescribed atmospheric conditions. Overall, the results suggest that ∂ET/ ∂θ varies more widely in regions with tall-stature woody vegetation that experience higher rates of change in turbulence intensity as the cover fraction increases. Our results facilitate a mathematically tractable description of ∂ET/ ∂θ, which is a core component of models that seek to predict hydrology-climate feedback processes in a changing climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature"><span>Soil Moisture, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo</p> <p>1999-01-01</p> <p>Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as soil moisture distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of soil moisture and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of soil moisture influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature affects the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (soil moisture and coastline curvature) are required to fully account for observed rainfall amounts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19947194','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19947194"><span>[Influence of soil moisture, nitrogen and phosphorus contents on Bauhinia faberi seedlings growth characteristics in arid valley of Minjiang River].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Song, Cheng-Jun; Ma, Ke-Ming; Fu, Bo-Jie; Qu, Lai-Ye; Liu, Yang; Zhong, Jian-Fei</p> <p>2009-08-01</p> <p>To study the influence of resources thresholds on plant growth is a major theme in restoration ecology. Based on the simulation of the natural thresholds of soil moisture, nitrogen (N), and phosphorus (P) under drought condition in the arid valley of Mingjiang River, a full factorial experiment was designed to study the dynamics of Bauhinia faberi seedlings survival rate, growth, biomass production, and resources use efficiency across one growth season. High soil moisture (40% field water capacity), high soil P (24 mg P x kg(-1)), and low N (100 mg N x kg(-1)) increased the seedlings survival rate, and promoted the seedlings growth, biomass production, and water use efficiency. There was a significant coupling effect between soil N and P, but the interactions between soil moisture and soil N and P were not obvious. High N (240 mg N x kg(-1)) restrained the seedlings growth markedly, while high P mitigated the negative effects of high N via increasing root area, root length, and root mass to promote the seedlings N and P uptake. The N and P use efficiency across one growth season kept steady, and had significant positive correlation with root/shoot mass ratio. The combination of high soil moisture, low N, and high P promoted the seedlings growth effectively, while that of low soil moisture, low P, and high N inhibited the seedlings growth markedly.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.3523S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.3523S"><span>Is soil moisture initialization important for seasonal to decadal predictions?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stacke, Tobias; Hagemann, Stefan</p> <p>2014-05-01</p> <p>The state of soil moisture can can have a significant impact on regional climate conditions for short time scales up to several months. However, focusing on seasonal to decadal time scales, it is not clear whether the predictive skill of global a Earth System Model might be enhanced by assimilating soil moisture data or improving the initial soil moisture conditions with respect to observations. As a first attempt to provide answers to this question, we set up an experiment to investigate the life time (memory) of extreme soil moisture states in the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). This experiment consists of an ensemble of 3 years simulations which are initialized with extreme wet and dry soil moisture states for different seasons and years. Instead of using common thresholds like wilting point or critical soil moisture, the extreme states were extracted from a reference simulation to ensure that they are within the range of simulated climate variability. As a prerequisite for this experiment, the soil hydrology in JSBACH was improved by replacing the bucket-type soil hydrology scheme with a multi-layer scheme. This new scheme is a more realistic representation of the soil, including percolation and diffusion fluxes between up to five separate layers, the limitation of bare soil evaporation to the uppermost soil layer and the addition of a long term water storage below the root zone in regions with deep soil. While the hydrological cycle is not strongly affected by this new scheme, it has some impact on the simulated soil moisture memory which is mostly strengthened due to the additional deep layer water storage. Ensemble statistics of the initialization experiment indicate perturbation lengths between just a few days up to several seasons for some regions. In general, the strongest effects are seen for wet initialization during northern winter over cold and humid regions, while the shortest memory is found during northern spring. For most regions, the soil moisture memory is either sensitive to wet or to dry perturbations, indicating that soil moisture anomalies interact with the respective weather pattern for a given year and might be able to enhance or dampen extreme conditions. To further investigate this effect, the simulations will be repeated using JSBACH with prescribed meteorological forcing to better disentangle the direct effects of soil moisture initialization and the atmospheric response.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930053193&hterms=watershed+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwatershed%2Banalysis','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930053193&hterms=watershed+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwatershed%2Banalysis"><span>Microwave soil moisture estimation in humid and semiarid watersheds</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>O'Neill, P. E.; Jackson, T. J.; Chauhan, N. S.; Seyfried, M. S.</p> <p>1993-01-01</p> <p>Land surface hydrologic-atmospheric interactions in humid and semi-arid watersheds were investigated. Active and passive microwave sensors were used to estimate the spatial and temporal distribution of soil moisture at the catchment scale in four areas. Results are presented and discussed. The eventual use of this information in the analysis and prediction of associated hydrologic processes is examined.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=189827&Lab=NHEERL&keyword=evapotranspiration&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=189827&Lab=NHEERL&keyword=evapotranspiration&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Seasonal and long-term effects of CO2 and O3 and their interaction with climate and soil moisture on water loss in ponderosa pine</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Evapotranspiration (ET) is driven by evaporative demand, available solar energy and soil moisture as well as by physiological plant activity which may be substantially affected by elevated CO2 and O3. A multi-year study was conducted in outdoor sun-lit controlled-environment cha...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=197105&Lab=NHEERL&keyword=evapotranspiration&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=197105&Lab=NHEERL&keyword=evapotranspiration&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Seasonal and long-term effects of CO2 and O3 on water loss in ponderosa pine and their interaction with climate and soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Evapotranspiration (ET) is driven by evaporative demand, available solar energy and soil moisture (SM) as well as by plant physiological activity which may be substantially affected by elevated CO2 and O3. A multi-year study was conducted in outdoor sunlit-controlled environment ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016HESS...20..329S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016HESS...20..329S"><span>Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.</p> <p>2016-01-01</p> <p>Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRNS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower, and runoff flumes used to close the water balance. We found a very good agreement between the CRNS method and the distributed sensor network (root mean square error (RMSE) of 0.009 and 0.013 m3 m-3 at SRER and JER, respectively) at the hourly timescale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was also obtained in soil moisture changes estimated from the CRNS and watershed water balance methods (RMSE of 0.001 and 0.082 m3 m-3 at SRER and JER, respectively), with deviations due to bypassing of the CRNS measurement depth during large rainfall events. Once validated, the CRNS soil moisture estimates were used to investigate hydrological processes at the footprint scale at each site. Through the computation of the water balance, we showed that drier-than-average conditions at SRER promoted plant water uptake from deeper soil layers, while the wetter-than-average period at JER resulted in percolation towards deeper soils. The CRNS measurements were then used to quantify the link between evapotranspiration and soil moisture at a commensurate scale, finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H13F0984I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H13F0984I"><span>Soil Moisture Processes in the Near Surface Unsaturated Zone: Experimental Investigations in Multi-scale Test Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Illangasekare, T. H.; Sakaki, T.; Smits, K. M.; Limsuwat, A.; Terrés-Nícoli, J. M.</p> <p>2008-12-01</p> <p>Understanding the dynamics of soil moisture distribution near the ground surface is of interest in various applications involving land-atmospheric interaction, evaporation from soils, CO2 leakage from carbon sequestration, vapor intrusion into buildings, and land mine detection. Natural soil heterogeneity in combination with water and energy fluxes at the soil surface creates complex spatial and temporal distributions of soil moisture. Even though considerable knowledge exists on how soil moisture conditions change in response to flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability both at high spatial and temporal resolutions. The issue of up-scaling becomes critical in all applications, as in general, field measurements are taken at sparsely distributed spatial locations that require assimilation with measurements taken using remote sensing technologies. It is our contention that the knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solution cannot be obtained easily in the field due to a number of constraints. One of these basic constraints is the inability to make measurements at very fine spatial scales at high temporal resolutions in naturally heterogeneous field systems. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and tools cannot be validated for the diversity of conditions that could be expected in the field. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this presentation, we will discuss the advantages and limitations of studies conducted in both two and three dimensional intermediate scale test systems together with instrumentation and measuring techniques. The features and capabilities of a new coupled porous media/climate wind tunnel test system that allows for the study of near surface unsaturated soil moisture conditions under climate boundary conditions will also be presented with the goal of exploring opportunities to use such a facility to study some of the multi-scale problems in the near surface unsaturated zone.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1586J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1586J"><span>Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.</p> <p>2017-12-01</p> <p>Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional-to-global land-atmosphere CO2 exchange.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.9121S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.9121S"><span>Investigation on the dominant factors controlling the spatio-temporal distribution of soil moisture in experimental grasslands</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schwichtenberg, G.; Hildebrandt, A.; Samaniego-Eguiguren, L.; Kreutziger, Y.; Attinger, S.</p> <p>2009-04-01</p> <p>The spatio-temporal distribution of soil moisture in the unsaturated zone influences the vegetation growth, governs the runoff generation processes as well as the energy balance at the interface between biosphere and the atmosphere, by influencing evapotranspiration. A better understanding of the spatio-temporal variability and dependence of soil moisture on living versus abiotic environment would lead to an improved representation of the soil-vegetation-atmosphere processes in hydrological and climate models. The Jena Experiment site (Germany) was established October 2001 in order to analyse the interaction between plant diversity and ecosystem processes. The main experiment covers 92 plots of 20 x 20 m arranged into a grid, on which a mixture of up to 60 grassland species and of one to four plant functional groups have been seeded. Each of these plots is equipped with at least one measurement tube for soil moisture. Measurements have been conducted weekly for four growing seasons (SSF). Here, we use geostatistical methods, like variograms and multivariate regressions, to investigate in how far abiotic environment and ecosystem explain the spatial and temporal variation of soil moisture at the Jena Experiment site. We test the influence of the soil environment, biodiversity, leaf area index and groundwater table. The poster will present the results of this analysis.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8445P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8445P"><span>Ecohydrology of the wetland-forestland interface: hydrophobicity in leaf litter and its potential effect on surface evaporation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Probert, Samantha; Kettridge, Nicholas; Devito, Kevin; Hurley, Alexander</p> <p>2017-04-01</p> <p>Riparian wetlands represent an important ecotone at the interface of peatlands and forests within the Western Boreal Plain of Canada. Water storage and negative feedbacks to evaporation in these systems is crucial for the conservation and redistribution of water during dry periods and providing ecosystem resilience to disturbance. Litter cover can alter the relative importance of the physical processes that drive soil evaporation. Negative feedbacks to drying are created as the hydrophysical properties of the litter and soil override atmospheric controls on evaporation in dry conditions, subsequently dampening the effects of external forcings on the wetland moisture balance. In this study, water repellency in leaf litter has been shown to significantly correlate with surface-atmosphere interactions, whereby severely hydrophobic leaf litter is linked to the highest surface resistances to evaporation, and therefore lowest instantaneous evaporation. Decreasing moisture is associated with increasing hydrophobicity, which may reduce the evaporative flux further as the dry hydrophobic litter creates a hydrological disconnect between soil moisture and the atmosphere. In contrast, hydrophilic litter layers exhibited higher litter moistures, which is associated with reduced resistances to evaporation and enhanced evaporative fluxes. Water repellency of the litter layer has a greater control on evaporation than the presence or absence of litter itself. Litter removal had no significant effect on instantaneous evaporation or surface resistance to evaporation except under the highest evaporation conditions, where litter layers produced higher resistance values than bare peat soils. However, litter removal modified the dominant physical controls on evaporation: moisture loss in plots with leaf litter was driven by leaf and soil hydrophysical properties. Contrastingly, bare peat soils following litter removal exhibited cooler, wetter surfaces and were more strongly correlated to atmospheric controls. The interaction between evaporation, hydrophobicity and moisture of the soil surface, or litter, presents a potentially significant negative feedback to drying across wetland-forestland interfaces.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12211278X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12211278X"><span>Modulation of Soil Initial State on WRF Model Performance Over China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xue, Haile; Jin, Qinjian; Yi, Bingqi; Mullendore, Gretchen L.; Zheng, Xiaohui; Jin, Hongchun</p> <p>2017-11-01</p> <p>The soil state (e.g., temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land-atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10 cm) and second (10-25 cm) soil layers compared to in situ observations in July 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated 4 times per day and run 48 h. Model results show that the corrected soil state, for example, warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JHyd..498...89K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JHyd..498...89K"><span>Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korres, W.; Reichenau, T. G.; Schneider, K.</p> <p>2013-08-01</p> <p>Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950031248&hterms=balance+general&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dbalance%2Bgeneral','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950031248&hterms=balance+general&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dbalance%2Bgeneral"><span>Climatology and natural variability of the global hydrologic cycle in the GLA atmospheric general circulation model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lau, K.-M.; Mehta, V. M.; Sud, Y. C.; Walker, G. K.</p> <p>1994-01-01</p> <p>Time average climatology and low-frequency variabilities of the global hydrologic cycle (GHC) in the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) were investigated in the present work. A 730-day experiment was conducted with the GLA GCM forced by insolation, sea surface temperature, and ice-snow undergoing climatological annual cycles. Ifluences of interactive soil moisture on time average climatology and natural variability of the GHC were also investigated by conducting 365-day experiments with and without interactive soil moisture. Insolation, sea surface temperature, and ice-snow were fixed at their July levels in the latter two experiments. Results show that the model's time average hydrologic cycle variables for July in all three experiments agree reasonably well with observations. Except in the case of precipitable water, the zonal average climates of the annual cycle experiment and the two perpetual July experiments are alike, i.e., their differences are within limits of the natural variability of the model's climate. Statistics of various components of the GHC, i.e., water vapor, evaporation, and precipitation, are significantly affected by the presence of interactive soil moisture. A long-term trend is found in the principal empirical modes of variability of ground wetness, evaporation, and sensible heat. Dominant modes of variability of these quantities over land are physically consistent with one another and with land surface energy balance requirements. The dominant mode of precipitation variability is found to be closely related to organized convection over the tropical western Pacific Ocean. The precipitation variability has timescales in the range of 2 to 3 months and can be identified with the stationary component of the Madden-Julian Oscillation. The precipitation mode is not sensitive to the presence of interactive soil moisture but is closely linked to both the rotational and divergent components of atmospheric moisture transport. The present results indicate that globally coherent natural variability of the GHC in the GLA GCM has two basic timescales in the absence of annual cycles of external forcings: a long-term trend associated with atmosphere-soil moisture interaction which affects the model atmosphere mostly over midlatitude continental regions and a large-scale 2- to 3-month variability associated with atmospheric moist processes over the western Pacific Ocean.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1454920-complex-terrain-alters-temperature-moisture-limitations-forest-soil-respiration-across-semiarid-subalpine-gradient','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1454920-complex-terrain-alters-temperature-moisture-limitations-forest-soil-respiration-across-semiarid-subalpine-gradient"><span>Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Berryman, E. M.; Barnard, H. R.; Adams, H. R.; ...</p> <p>2015-02-10</p> <p>Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1454920','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1454920"><span>Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Berryman, E. M.; Barnard, H. R.; Adams, H. R.</p> <p></p> <p>Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70147570','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70147570"><span>Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D.</p> <p>2015-01-01</p> <p>Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JHyd..387..176T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JHyd..387..176T"><span>Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tramblay, Yves; Bouvier, Christophe; Martin, Claude; Didon-Lescot, Jean-François; Todorovik, Dragana; Domergue, Jean-Marc</p> <p>2010-06-01</p> <p>Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture, modelled soil moisture through the Interaction-Sol-Biosphère-Atmosphère (ISBA) component of the SIM model (Météo-France), antecedent precipitation and base flow. A modelling approach based on the Soil Conservation Service-Curve Number method (SCS-CN) is used to simulate the flood events in a small headwater catchment in the Cevennes region (France). The model involves two parameters: one for the runoff production, S, and one for the routing component, K. The S parameter can be interpreted as the maximal water retention capacity, and acts as the initial condition of the model, depending on the antecedent moisture conditions. The model was calibrated from a 20-flood sample, and led to a median Nash value of 0.9. The local TDR measurements in the deepest layers of soil (80-140 cm) were found to be the best predictors for the S parameter. TDR measurements averaged over the whole soil profile, outputs of the SIM model, and the logarithm of base flow also proved to be good predictors, whereas antecedent precipitations were found to be less efficient. The good correlations observed between the TDR predictors and the S calibrated values indicate that monitoring soil moisture could help setting the initial conditions for simplified event-based models in small basins.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S"><span>Pathways of soil moisture controls on boundary layer dynamics</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Siqueira, M.; Katul, G.; Porporato, A.</p> <p>2007-12-01</p> <p>Soil moisture controls on precipitation are now receiving significant attention in climate systems because the memory of their variability is much slower than the memory of the fast atmospheric processes. We propose a new model that integrates soil water dynamics, plant hydraulics and stomatal responses to water availability to estimate root water uptake and available energy partitioning, as well as feedbacks to boundary layer dynamics (in terms of water vapor and heat input to the atmospheric system). Using a simplified homogenization technique, the model solves the intrinsically 3-D soil water movement equations by two 1-D coupled Richards' equations. The first resolves the radial water flow from bulk soil to soil-root interface to estimate root uptake (assuming the vertical gradients in moisture persist during the rapid lateral flow), and then it solves vertical water movement through the soil following the radial moisture adjustments. The coupling between these two equations is obtained by area averaging the soil moisture in the radial domain (i.e. homogenization) to calculate the vertical fluxes. For each vertical layer, the domain is discretized in axi-symmetrical grid with constant soil properties. This is deemed to be appropriate given the fact that the root uptake occurs on much shorter time scales closely following diurnal cycles, while the vertical water movement is more relevant to the inter-storm time scale. We show that this approach was able to explicitly simulate known features of root uptake such as diurnal hysteresis of canopy conductance, water redistribution by roots (hydraulic lift) and downward shift of root uptake during drying cycles. The model is then coupled with an atmospheric boundary layer (ABL) growth model thereby permitting us to explore low-dimensional elements of the interaction between soil moisture and ABL states commensurate with the lifting condensation level.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811852C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811852C"><span>N2O and N2 emissions from contrasting soil environments - interactive effects of soil nitrogen, hydrology and microbial communities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Christiansen, Jesper; Elberling, Bo; Ribbons, Relena; Hedo, Javier; José Fernández Alonso, Maria; Krych, Lukasz; Sandris Nielsen, Dennis; Kitzler, Barbara</p> <p>2016-04-01</p> <p>Reactive nitrogen (N) in the environment has doubled relative to the natural global N cycle with consequences for biogeochemical cycling of soil N. Also, climate change is expected to alter precipitation patterns and increase soil temperatures which in Arctic environments may accelerate permafrost thawing. The combination of changes in the soil N cycle and hydrological regimes may alter microbial transformations of soil N with unknown impacts on N2O and N2 emissions from temperate and Arctic soils. We present the first results of soil N2O and N2 emissions, chemistry and microbial communities over soil hydrological gradients (upslope, intermediate and wet) across a global N deposition gradient. The global gradient covered an N-limited high Arctic tundra (Zackenberg-ZA), a pacific temperate rain forest (Vancouver Island-VI) and an N saturated forest in Austria (Klausenleopoldsdorf-KL). The N2O and N2 emissions were measured from intact cores at field moisture in a He-atmosphere system. Extractable NH4+ and NO3-, organic and microbial C and N and potential enzyme-activities were determined on soil samples. Soil genomic DNA was subjected to MiSeq-based tag-encoded 16S rRNA and ITS gene amplicon sequencing for the bacterial and fungal community structure. Similar soil moisture levels were observed for the upslope, intermediate and wet locations at ZA, VI and KL, respectively. Extractable NO3- was highest at the N rich KL and lowest at ZA and showed no trend with soil moisture similar to NH4+. At ZA and VI soil NH4+ was higher than NO3- indicating a tighter N cycling. N2O emissions increased with soil moisture at all sites. The N2O emissions for the wet locations ranked similarly to NO3- with the largest response to soil moisture at KL. N2 emissions were remarkably similar across the sites and increased with soil wetness. Microbial C and N also increased with soil moisture and were overall lowest at the N rich KL site. The potential activity of protease enzyme was site dependent indicating different capacities for N turnover of the microbial community. These findings indicate a positive feedback between increased soil N and wetter soils that promotes N2O relative to N2. These interactions may be site specific due to differential functional diversity of the soil microbial community. Future characterization of the community structure will shed light on the link between the role of microbial groups related to soil N cycling pathways and the resultant partitioning of N2O and N2 emissions in these contrasting environments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/26471','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/26471"><span>Interactive effects of ozone and climate on water use, soil moisture content and streamflow in a southern Appalachian forest in the USA</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>S.B. McLaughlin; S.D. Wullschleger; G. Sun; M. Nosal</p> <p>2007-01-01</p> <p>Documentation of the degree and direction of effects of ozone on transpiration of canopies of mature forest trees is critically needed to model ozone effects on forest water use and growth in a warmer future climate.Patterns of sap flow in stems and soil moisture in the rooting zones of mature trees, coupled with late-season...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EnMan..52..861P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EnMan..52..861P"><span>Relationship Between Woody Plant Colonization and Typha L. Encroachment in Stormwater Detention Basins</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Plumb, Priscilla Bocskor; Day, Susan D.; Wynn-Thompson, Theresa M.; Seiler, John R.</p> <p>2013-10-01</p> <p>We studied stormwater detention basins where woody vegetation removal was suspended for 2 years in Virginia, USA to determine if woody vegetation can control Typha populations and how early woody plant succession interacts with Typha, other herbaceous vegetation, and site factors. Distribution and composition of woody vegetation, Typha and non- Typha herbaceous vegetation biomass, and site factors were assessed at 100 plots in four basins ranging in age from 7 to 17 years. A greenhouse study examined the interaction of shade and soil moisture on Typha biomass and persistence. Principal component analysis identified an environmental gradient associated with greater water table depths and decreased elevation that favored Typha but negatively influenced woody vegetation. Elevation was correlated with litter layer distribution, suggesting that initial topography influences subsequent environmental characteristics and thus plant communities. Soil organic matter at 0-10 cm ranged from 5.4 to 12.7 %. Woody plants present were native species with the exception of Ailanthus altissima and Pyrus calleryana. In the greenhouse, shade and reduced soil moisture decreased Typha biomass and rhizome length. The shade effect was strongest in flooded plants and the soil moisture effect was strongest for plants in full sun. Typha in dry soil and heavy shade had 95 % less total biomass and 83 % smaller rhizomes than Typha in flooded soil and full sun, but even moderate soil moisture reductions decreased above- and below-ground biomass by 63 and 56 %, respectively. Suspending maintenance allows restoration of woody vegetation dominated by native species and may suppress Typha invasion.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15042457','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15042457"><span>Modifying the 'pulse-reserve' paradigm for deserts of North America: precipitation pulses, soil water, and plant responses.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Reynolds, James F; Kemp, Paul R; Ogle, Kiona; Fernández, Roberto J</p> <p>2004-10-01</p> <p>The 'pulse-reserve' conceptual model--arguably one of the most-cited paradigms in aridland ecology--depicts a simple, direct relationship between rainfall, which triggers pulses of plant growth, and reserves of carbon and energy. While the heuristics of 'pulses', 'triggers' and 'reserves' are intuitive and thus appealing, the value of the paradigm is limited, both as a conceptual model of how pulsed water inputs are translated into primary production and as a framework for developing quantitative models. To overcome these limitations, we propose a revision of the pulse-reserve model that emphasizes the following: (1) what explicitly constitutes a biologically significant 'rainfall pulse', (2) how do rainfall pulses translate into usable 'soil moisture pulses', and (3) how are soil moisture pulses differentially utilized by various plant functional types (FTs) in terms of growth? We explore these questions using the patch arid lands simulation (PALS) model for sites in the Mojave, Sonoran, and Chihuahuan deserts of North America. Our analyses indicate that rainfall variability is best understood in terms of sequences of rainfall events that produce biologically-significant 'pulses' of soil moisture recharge, as opposed to individual rain events. In the desert regions investigated, biologically significant pulses of soil moisture occur in either winter (October-March) or summer (July-September), as determined by the period of activity of the plant FTs. Nevertheless, it is difficult to make generalizations regarding specific growth responses to moisture pulses, because of the strong effects of and interactions between precipitation, antecedent soil moisture, and plant FT responses, all of which vary among deserts and seasons. Our results further suggest that, in most soil types and in most seasons, there is little separation of soil water with depth. Thus, coexistence of plant FTs in a single patch as examined in this PALS study is likely to be fostered by factors that promote: (1) separation of water use over time (seasonal differences in growth), (2) relative differences in the utilization of water in the upper soil layers, or (3) separation in the responses of plant FTs as a function of preceding conditions, i.e., the physiological and morphological readiness of the plant for water-uptake and growth. Finally, the high seasonal and annual variability in soil water recharge and plant growth, which result from the complex interactions that occur as a result of rainfall variability, antecedent soil moisture conditions, nutrient availability, and plant FT composition and cover, call into question the use of simplified vegetation models in forecasting potential impacts of climate change in the arid zones in North America.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9784H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9784H"><span>Impact of realistic soil moisture initialization on the representation of extreme events in the western Mediterranean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helgert, Sebastian; Khodayar, Samiro</p> <p>2017-04-01</p> <p>In a warmer Mediterranean climate an increase in the intensity and frequency of extreme events like floods, droughts and extreme heat is expected. The ability to predict such events is still a great challenge and exhibits many uncertainties in the weather forecast and climate predictions. Thereby the missing knowledge about soil moisture-atmosphere interactions and their representation in models is identified as one of the main sources of uncertainty. In this context the soil moisture(SM) plays an important role in the partitioning of sensible and latent heat fluxes on the surface and consequently influences the boundary-layer stability and the precipitation formation. The aim of this research work is to assess the influence of soil moisture-atmosphere interactions on the initiation and development of extreme events in the western Mediterranean (WMED). In this respect the impact of realistic SM initialization on the model representation of extreme events is investigated. High-resolution simulations of different regions in the WMED, including various climate zones from moderate to arid climate, are conducted with the atmospheric COSMO (Consortium for Small-scale Modeling) model in the numerical weather prediction and climate mode. A multiscale temporal and spatial approach is used (days to years, 7km to 2.8km grid spacing). Observational data provided by the framework of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) as well as satellite data such as precipitation from CMORPH (CPC MORPHing technique), evapotranspiration from Land Surface Analysis Satellite Applications Facility (LSA-SAF) and atmospheric moisture from MODIS (Moderate Resolution Imaging Spectroradiometer) are used for process understanding and model validation. To select extreme dry and wet periods the Effective Drought Index (EDI) is calculated. In these periods sensitivity studies of extreme SM initialization scenarios are performed to prove a possible impact of soil moisture on precipitation in the WMED. For the realistic SM initialization different state-of-art high-resolution SM products (25km up to 1km grid spacing) of the Soil Moisture Ocean Salinity mission (SMOS) are examined. A CDF-matching method is applied to reduce the bias between model and SMOS-satellite observation. Moreover, techniques to estimate the initial soil moisture profile from satellite data are tested.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H33H1649M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H33H1649M"><span>Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mohanty, B.; Kathuria, D.; Katzfuss, M.</p> <p>2016-12-01</p> <p>Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B33G..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B33G..07M"><span>Soil carbon content and CO2 flux along a hydrologic gradient in a High-Arctic tundra lake basin, Northwest Greenland</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McKnight, J.; Klein, E. S.; Welker, J. M.; Schaeffer, S. M.; Franklin, M.</p> <p>2015-12-01</p> <p>High Arctic landscapes are composed of watershed basins that vary in size and ecohydrology, but typically have a plant community complex that ranges from dry tundra to moist tundra to wet sedge systems along water body shorelines. The spatial extent of these plant communities reflects mean annual soil moisture and temperature, and is vulnerable to changes in climate conditions. Soil moisture and temperature significantly influence organic matter microbial activity and decomposition, and can affect the fate of soil carbon in tundra soils. Consequently, due to the unique soil carbon differences between tundra plant communities, shifts in their spatial extent may drive future High Arctic biosphere-atmosphere interactions. Understanding this terrestrial-atmosphere trace gas feedback, however, requires quantification of the rates and patterns of CO2 exchange along soil moisture gradients and the associated soil properties. In summer of 2015, soil CO2 flux rate, soil moisture and temperature were measured along a soil moisture gradient spanning three vegetation zones (dry tundra, wet tundra, and wet grassland) in a snow melt-fed lake basin near Thule Greenland. Mean soil temperature during the 2015 growing season was greater in dry tundra than in wet tundra and wet grassland (13.0 ± 1.2, 7.8 ± 0.8, and 5.5 ± 0.9°C, respectively). Mean volumetric soil moisture differed among all three vegetation zones where the soil moisture gradient ranged from 9 % (dry tundra) to 34 % (wet tundra) to 51 % (wet grassland). Mean soil CO2 flux was significantly greater in the wet grassland (1.7 ± 0.1 μmol m-2 s-1) compared to wet tundra (0.9 ± 0.2 μmol m-2 s-1) and dry tundra (1.2 ± 0.2 μmol m-2 s-1). Soil CO2 flux increased and decreased with seasonal warming and cooling of soil temperature. Although soil temperature was an important seasonal driver of soil CO2 flux rates, differences in mean seasonal soil CO2 flux rates among vegetation zones appeared to be a function of the combined effects of soil temperature and soil moisture conditions. These results suggest that the response of vegetation distribution to shifts in precipitation and warmer climate conditions may have significant implications for release of soil carbon as CO2 in High Arctic tundra ecosystems in Northwest Greenland.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950010624&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950010624&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps"><span>Large area mapping of soil moisture using the ESTAR passive microwave radiometer</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jackson, T. J.; Levine, D. M.; Swift, C. T.; Schmugge, T. J.</p> <p>1994-01-01</p> <p>Investigations designed to study land surface hydrologic-atmospheric interactions, showing the potential of L band passive microwave radiometry for measuring surface soil moisture over large areas, are discussed. Satisfying the data needs of these investigations requires the ability to map large areas rapidly. With aircraft systems this means a need for more beam positions over a wider swath on each flightline. For satellite systems the essential problem is resolution. Both of these needs are currently being addressed through the development and verification of Electronically Scanned Thinned Array Radiometer (ESTAR) technology. The ESTAR L band radiometer was evaluated for soil moisture mapping applications in two studies. The first was conducted over the semiarid rangeland Walnut Gulch watershed located in south eastern Arizona (U.S.). The second was performed in the subhumid Little Washita watershed in south west Oklahoma (U.S.). Both tests showed that the ESTAR is capable of providing soil moisture with the same level of accuracy as existing systems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6402V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6402V"><span>Impact of groundwater capillary rises as lower boundary conditions for soil moisture in a land surface model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vergnes, Jean-Pierre; Decharme, Bertrand; Habets, Florence</p> <p>2014-05-01</p> <p>Groundwater is a key component of the global hydrological cycle. It sustains base flow in humid climate while it receives seepage in arid region. Moreover, groundwater influences soil moisture through water capillary rise into the soil and potentially affects the energy and water budget between the land surface and the atmosphere. Despite its importance, most global climate models do not account for groundwater and their possible interaction with both the surface hydrology and the overlying atmosphere. This study assesses the impact of capillary rise from shallow groundwater on the simulated water budget over France. The groundwater scheme implemented in the Total Runoff Integrated Pathways (TRIP) river routing model in a previous study is coupled with the Interaction between Soil Biosphere Atmosphere (ISBA) land surface model. In this coupling, the simulated water table depth acts as the lower boundary condition for the soil moisture diffusivity equation. An original parameterization accounting for the subgrid elevation inside each grid cell is proposed in order to compute this fully-coupled soil lower boundary condition. Simulations are performed at high (1/12°) and low (0.5°) resolutions and evaluated over the 1989-2009 period. Compared to a free-drain experiment, upward capillary fluxes at the bottom of soil increase the mean annual evapotranspiration simulated over the aquifer domain by 3.12 % and 1.54 % at fine and low resolutions respectively. This process logically induces a decrease of the simulated recharge from ISBA to the aquifers and contributes to enhance the soil moisture memory. The simulated water table depths are then lowered, which induces a slight decrease of the simulated mean annual river discharges. However, the fully-coupled simulations compare well with river discharge and water table depth observations which confirms the relevance of the coupling formalism.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70148032','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70148032"><span>Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.</p> <p>2015-01-01</p> <p>The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917873G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917873G"><span>Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María</p> <p>2017-04-01</p> <p>This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFMIN43B1184L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFMIN43B1184L"><span>Soil Moisture Estimation Using Hyperspectral SWIR Imagery</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lewis, D.</p> <p>2007-12-01</p> <p>The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations generated by using radiometer data collected over calibration tarps. Regions of Interest (ROI) were drawn over the image data set corresponding with the location of the soil moisture meters. Scripts written in ENVI's Interactive Data Language (IDL) were developed to extract the spectra from each of the processed hyperspectral image data over each soil moisture meter from its corresponding ROI. The informatics relationship between soil moisture and SWIR spectra was identified by using the resulting data set.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810004904','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810004904"><span>The joint measuring campaign 1979 in Ruthe (West Germany) description and preliminary data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vanderploeg, R. R.; Tassone, G.; Vonhoyningen-Huene, J. (Principal Investigator)</p> <p>1979-01-01</p> <p>The measurements and observations performed as part of the TELLUS project on soil moisture and heat budget evaluations of selected areas in the vecinity of Ruthe, West Germany are presented and discussed. The main lines of investigation include evapotranspiration and moisture content in bare soils covered by vegetation, interactions between natural phenomena and mesoscale heat budget, and man made changes and their impact on regional heat budget.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1169520','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1169520"><span>Exploratory Research - Using Volatile Organic Compounds to Separate Heterotrophic and Autotrophic Forest Soil Respiration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Roberts, Scott D</p> <p>2015-02-09</p> <p>The initial focus of this project was to develop a method to partition soil respiration into its components (autotrophic, heterotrophic etc.) using the fingerprint of volatile organic compounds (VOCs) from soils. We were able to identify 63 different VOCs in our study; however, due to technical difficulties we were unable to take reliable measurements in order to test our hypotheses and develop this method. In the end, we changed the objectives of the project. Our new objectives were to characterize the effects of species and soil moisture regime on the composition of soil organic matter. We utilized the soils frommore » the greenhouse experiment we had established for the soil VOC study and determined the lignin biomarker profiles of each of the treatments. We found that moisture had a significant effect on the carbon content of the soils with the low moisture treatments having higher carbon content than the high moisture treatments. We found that the relative yield of syringyl phenols (SP), ligin (Lig), and substituted fatty acids (SFA) were elevated in deciduous planted pots and reduced in conifer planted pots relative to plant-free treatments. Our results suggest nuttall oak preserved lignin and SFA, while loblolly pine lost lignin and SFA similarly to the plant free treatments. Since we did not find that the carbon concentrations of the soils were different between the species, nuttall oak probably replaced more native soil carbon than loblolly pine. This suggests that relative to loblolly pine, nuttall oak is a priming species. Since priming may impact soil carbon pools more than temperature or moisture, determining which species are priming species may facilitate an understanding of the interaction that land use and climate change may have on soil carbon pools.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1911934S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1911934S"><span>Monitoring water cycle elements using GNSS geodetic receivers at the field research station Marquardt, Germany</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Simeonov, Tzvetan; Vey, Sibylle; Alshawaf, Fadwa; Dick, Galina; Guerova, Guergana; Güntner, Andreas; Hohmann, Christian; Kunwar, Ajeet; Trost, Benjamin; Wickert, Jens</p> <p>2017-04-01</p> <p>Water storage variations in the atmosphere and in soils are among the most dynamic within the Earth's water cycle. The continuous measurement of water storage in these media with a high spatial and temporal resolution is a challenging task, not yet completely solved by various observation techniques. With the development of the Global Navigation Satellite Systems (GNSS) a new approach for atmospheric water vapor estimation in the atmosphere and in parallel of soil moisture in the vicinity of GNSS ground stations was established in the recent years with several key advantages compared to traditional techniques. Regional and global GNSS networks are nowadays operationally used to provide the Integrated Water Vapor (IWV) information with high temporal resolution above the individual stations. Corresponding data products are used to improve the day-by-day weather prediction of leading forecast centers. Selected stations from these networks can be used to additionally derive the soil moisture in the vicinity of the receivers. Such parallel measurement of IWV and soil moisture using a single measuring device provides a unique possibility to analyze water fluxes between the atmosphere and the land surface. We installed an advanced experimental GNSS setup for hydrology at the field research station of the Leibniz Institute for Agricultural Engineering and Bioeconomy in Marquardt, around 30km West of Berlin, Germany. The setup includes several GNSS receivers, various Time Domain Reflectometry (TDR) sensors at different depths for soil moisture measurement and an meteorological station. The setup was mainly installed to develop and improve GNSS based techniques for soil moisture determination and to analyze GNSS IWV and SM in parallel on a long-term perspective. We introduce initial results from more than two years of measurements. The comparison in station Marquardt shows good agreement (correlation 0.79) between the GNSS derived soil moisture and the TDR measurements. A detailed study for several periods with different GNSS settings, vegetation and soil conditions in the vicinity of the station is presented with emphasis on the behavior of GNSS derived soil moisture, compared to TDR. Case studies of intense rainfall events and lasting dry periods show the interaction between the IWV and soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170003709&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170003709&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsoil"><span>Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping</p> <p>2016-01-01</p> <p>Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29624051','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29624051"><span>Soil Bacterial Diversity Is Associated with Human Population Density in Urban Greenspaces.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Haitao; Cheng, Minying; Dsouza, Melissa; Weisenhorn, Pamela; Zheng, Tianling; Gilbert, Jack A</p> <p>2018-05-01</p> <p>Urban greenspaces provide extensive ecosystem services, including pollutant remediation, water management, carbon maintenance, and nutrient cycling. However, while the urban soil microbiota underpin these services, we still have limited understanding of the factors that influence their distribution. We characterized soil bacterial communities from turf-grasses associated with urban parks, streets, and residential sites across a major urban environment, including a gradient of human population density. Bacterial diversity was significantly positively correlated with the population density; and species diversity was greater in park and street soils, compared to residential soils. Population density and greenspace type also led to significant differences in the microbial community composition that was also significantly correlated with soil pH, moisture, and texture. Co-occurrence network analysis revealed that microbial guilds in urban soils were well correlated. Abundant soil microbes in high density population areas had fewer interactions, while abundant bacteria in high moisture soils had more interactions. These results indicate the significant influence of changes in urban demographics and land-use on soil microbial communities. As urbanization is rapidly growing across the planet, it is important to improve our understanding of the consequences of urban zoning on the soil microbiota.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812133C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812133C"><span>Improving Soil Moisture and Temperature Profile and Surface Turbulent Fluxes Estimations in Irrigated Field by Assimilating Multi-source Data into Land Surface Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen</p> <p>2016-04-01</p> <p>The optimal estimation of hydrothermal conditions in irrigation field is restricted by the deficiency of accurate irrigation information (when and how much to irrigate). However, the accurate estimation of soil moisture and temperature profile and surface turbulent fluxes are crucial to agriculture and water management in irrigated field. In the framework of land surface model, soil temperature is a function of soil moisture - subsurface moisture influences the heat conductivity at the interface of layers and the heat storage in different layers. In addition, soil temperature determines the phase of soil water content with the transformation between frozen and unfrozen. Furthermore, surface temperature affects the partitioning of incoming radiant energy into ground (sensible and latent heat flux), as a consequence changes the delivery of soil moisture and temperature. Given the internal positive interaction lying in these variables, we attempt to retrieve the accurate estimation of soil moisture and temperature profile via assimilating the observations from the surface under unknown irrigation. To resolve the input uncertainty of imprecise irrigation quantity, original EnKS is implemented with inflation and localization (referred to as ESIL) aiming at solving the underestimation of the background error matrix and the extension of observation information from the top soil to the bottom. EnKS applied in this study includes the states in different time points which tightly connect with adjacent ones. However, this kind of relationship gradually vanishes along with the increase of time interval. Thus, the localization is also employed to readjust temporal scale impact between states and filter out redundant or invalid correlation. Considering the parameter uncertainty which easily causes the systematic deviation of model states, two parallel filters are designed to recursively estimate both states and parameters. The study area consists of irrigated farmland and is located in an artificial oasis in the semi-arid region of northwestern China. Land surface temperature (LST) and soil volumetric water content (SVW) at first layer measured at Daman station are taken as observations in the framework of data assimilation. The study demonstrates the feasibility of ESIL in improving the soil moisture and temperature profile under unknown irrigation. ESIL promotes the coefficient correlation with in-situ measurements for soil moisture and temperature at first layer from 0.3421 and 0.7027 (ensemble simulation) to 0.8767 and 0.8304 meanwhile all the RMSE of soil moisture and temperature in deeper layers dramatically decrease more than 40 percent in different degree. To verify the reliability of ESIL in practical application, thereby promoting the utilization of satellite data, we test ESIL with varying observation internal interval and standard deviation. As a consequence, ESIL shows stabilized and promising effectiveness in soil moisture and soil temperature estimation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11I1989H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11I1989H"><span>Conceptualizing the self organization of cloud cells, cold pools and soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Henneberg, O.; Härter, J. O. M.</p> <p>2017-12-01</p> <p>Convective-type cloud is the cause of extreme, short-duration precipitation, challenging weather forecasting and climate modeling. Such extremes are ultimately tied to the uneven redistribution of water in the course of convective self organization and possibly the interaction between clouds [1]. Over land, moisture is organized through: cloud cells, cold pools, and the land surface. Each of these generally capture and release moisture at different rates, e.g. cold pools form quickly but dissipate slowly. Such distinct timescales have implications for the emergent dynamics.Incorporating such distinct time scales, we here present a conceptual model for the spatio-temporal self organization within the diurnal cycle of convection and describe the possible role of soil moisture memory in serving as a predisposition for extremes.We bolster our findings by high resolution, large eddy simulations: Sensible and latent heat fluxes, which are determined by the soil moisture content, can influence the stability of the atmosphere. The onset of initial precipitation is affected by such heat release, which in turn is modified by previous precipitation. Starting from static heat sources, we quantify how their spatial distribution affects the self organization and thus onset, duration and strength of precipitation events in an idealized model setup. Furthermore, an extended model setup with inhomogeneous, self organized distributions of latent and sensible heat fluxes is used to contrast how emergent soil moisture patterns impact on the selforganization structure of convection. Our findings may have implications for the role of land use changes regarding the development of extreme convective precipitation.Reference[1] Moseley et al. (2016) "Intensification of convective extremes driven by cloud-cloud interaction", Nature Geosc. , 9, 748-752</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24687903','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24687903"><span>Interactive biotic and abiotic regulators of soil carbon cycling: evidence from controlled climate experiments on peatland and boreal soils.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Briones, María Jesús I; McNamara, Niall P; Poskitt, Jan; Crow, Susan E; Ostle, Nicholas J</p> <p>2014-09-01</p> <p>Partially decomposed plant and animal remains have been accumulating in organic soils (i.e. >40% C content) for millennia, making them the largest terrestrial carbon store. There is growing concern that, in a warming world, soil biotic processing will accelerate and release greenhouse gases that further exacerbate climate change. However, the magnitude of this response remains uncertain as the constraints are abiotic, biotic and interactive. Here, we examined the influence of resource quality and biological activity on the temperature sensitivity of soil respiration under different soil moisture regimes. Organic soils were sampled from 13 boreal and peatland ecosystems located in the United Kingdom, Ireland, Spain, Finland and Sweden, representing a natural resource quality range of C, N and P. They were incubated at four temperatures (4, 10, 15 and 20 °C) at either 60% or 100% water holding capacity (WHC). Our results showed that chemical and biological properties play an important role in determining soil respiration responses to temperature and moisture changes. High soil C : P and C : N ratios were symptomatic of slow C turnover and long-term C accumulation. In boreal soils, low bacterial to fungal ratios were related to greater temperature sensitivity of respiration, which was amplified in drier conditions. This contrasted with peatland soils which were dominated by bacterial communities and enchytraeid grazing, resulting in a more rapid C turnover under warmer and wetter conditions. The unexpected acceleration of C mineralization under high moisture contents was possibly linked to the primarily role of fermented organic matter, instead of oxygen, in mediating microbial decomposition. We conclude that to improve C model simulations of soil respiration, a better resolution of the interactions occurring between climate, resource quality and the decomposer community will be required. © 2014 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3690Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3690Z"><span>Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo</p> <p>2017-04-01</p> <p>Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUSM.B42A..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUSM.B42A..02S"><span>Investigating Soil Moisture Feedbacks on Precipitation With Tests of Granger Causality</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Salvucci, G. D.; Saleem, J. A.; Kaufmann, R.</p> <p>2002-05-01</p> <p>Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture (S) feedback on precipitation (P) using data from Illinois. In this framework S is said to Granger cause P if F(Pt;At-dt)does not equal F(P;(A-S)t-dt) where F denotes the conditional distribution of P at time t, At-dt represents the set of all knowledge available at time t-dt, and (A-S)t-dt represents all knowledge available at t-dt except S. Critical for land-atmosphere interaction research is that At-dt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected (p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNH51B1932V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNH51B1932V"><span>Drought causes substantial reductions in non-isothermal soil strength</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vahedifard, F.; Robinson, J. D.; Love, C. A.; AghaKouchak, A.</p> <p>2016-12-01</p> <p>The stability and settlement of natural slopes and engineering structures are governed primarily by the shear strength of foundation soil. Understanding soil-atmosphere interactions and their impacts on shear strength is imperative to evaluating drought impacts on the resilience of our infrastructure. This understanding is also important for assessing a variety of emerging science and engineering problems in a changing climate including analyzing existing and new infrastructures, landslides, soil carbon sequestration, land management, and managing traction and tillage in agriculture. While progress has been made in understanding shear strength response to soil moisture changes, the impacts of concurrent soil moisture and temperature changes on shear strength remain uncertain from a regional-scale perspective. Here we present a methodological framework based on various soil types, temperatures, and moistures, and surface fluxes, to quantify a non-isothermal soil shear strength. We employ a non-isothermal soil strength analysis (NISSA) to explore the extent to which elevated soil temperatures and low moistures, along with abnormal surface fluxes, during California's record-setting 2012 - 2015 drought reduced the soil's shear strength. Our results suggest that the prolonged California drought reduced the shear strength of fine-grained soil as much as 95%. In contrast, the NISSA suggests that drought impacts on coarse-grained soil were not as significant. These opposing behaviors are attributed to the existence and absence of intermolecular physico-chemical forces in fine- and coarse-grained soils, respectively. The outlined framework offers a unique avenue to explore how soil shear strength is likely to behave under extreme drought conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B13N0076H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B13N0076H"><span>The role of tree species and soil moisture in soil organic matter stabilization and destabilization</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hatten, J. A.; Dewey, J.; Roberts, S.; McNeal, K.; Shaman, A.</p> <p>2014-12-01</p> <p>Inputs of labile organic substrates to soils are commonly associated with elevated soil organic carbon mineralization rates; this process is known as the priming effect. Plant presence and soil conditions (i.e. water regime, nutrient status) are known to be interacting factors governing priming. In this study, we examine the role of differing species, loblolly pine (Pinus taeda L.) and nuttall oak (Quercus texana B.), and moisture regimes (low and high) upon the soil priming effect in a fine textured soil. We explore whether there is depletion of original soil carbon and concurrent replacement through addition of fresh organic matter from the planted tree species. By employing a series of planted and plant-free pots in a greenhouse mesocosm study, we were able to characterize the composition of soil organic matter and its carbon with the use of CuO oxidation products (e.g. lignin, cutin/suberin biomarkers). Carbon was elevated on the low moisture samples relative to all other treatments, and the C:N ratio suggests that newly produced plant carbon replaced original soil carbon. The soil lignin content of the planted treatments was lower than the plant-free treatments suggesting that lignin present in the original soil may have been preferentially degraded by priming and not replaced. We will discuss the utility of CuO oxidation products to explore soil organic carbon dynamics and the implications of understanding the role of species and soil moisture in predicting the response of soil carbon to land use and climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H12G..06L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H12G..06L"><span>Infusion of SMAP Data into Offline and Coupled Models: Evaluation, Calibration, and Assimilation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lawston, P.; Santanello, J. A., Jr.; Dennis, E. J.; Kumar, S.</p> <p>2017-12-01</p> <p>The impact of the land surface on the water and energy cycle is modulated by its coupling to the planetary boundary layer (PBL), and begins at the local scale. A core component of the local land-atmosphere coupling (LoCo) effort requires understanding the `links in the chain' between soil moisture and precipitation, most notably through surface heat fluxes and PBL evolution. To date, broader (i.e. global) application of LoCo diagnostics has been limited by observational data requirements of the coupled system (and in particular, soil moisture) that are typically only met during localized, short-term field campaigns. SMAP offers, for the first time, the ability to map high quality, near-surface soil moisture globally every few days at a spatial resolution comparable to current modeling efforts. As a result, there are numerous potential avenues for SMAP model-data fusion that can be explored in the context of improving understanding of L-A interaction and NWP. In this study, we assess multiple points of intersection of SMAP products with offline and coupled models and evaluate impacts using process-level diagnostics. Results will inform upon the importance of high-resolution soil moisture mapping for improved coupled prediction and model development, as well as reconciling differences in modeled, retrieved, and measured soil moisture. Specifically, NASA model (LIS, NU-WRF) and observation (SMAP, NLDAS-2) products are combined with in-situ standard and IOP measurements (soil moisture, flux, and radiosonde) over the ARM-SGP. An array of land surface model spinups (via LIS-Noah) are performed with varying atmospheric forcing, greenness fraction, and soil layering permutations. Calibration of LIS-Noah soil hydraulic parameters is then performed using an array of in-situ soil moisture and flux and SMAP products. In addition, SMAP assimilation is performed in LIS-Noah both at the scale of the observation (36 and 9km) and the model grid (1km). The focus is on the consistency in calibrated parameters, impact of soil drydown dynamics and soil layers, and terrestrial (soil moisture-flux) coupling. The impacts of these various spinup runs and initialization of NU-WRF coupled forecasts then follows with a focus on weather (ambient, PBL, and precipitation) using LoCo metrics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.H11C..02T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.H11C..02T"><span>Assessment of Multi-frequency Electromagnetic Induction for Determining Soil Moisture Patterns at the Hillslope Scale</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tromp-van Meerveld, I.; McDonnell, J.</p> <p>2009-05-01</p> <p>We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for soil moisture measurements in areas with shallow soils?; (2) Can EM represent the temporal and spatial patterns of soil moisture throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of soil moisture? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to soil moisture measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition, the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua-pro soil moisture measurements.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013591','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013591"><span>Assimilation of Passive and Active Microwave Soil Moisture Retrievals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.</p> <p>2012-01-01</p> <p>Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.2007Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.2007Y"><span>Impact of elevated precipitation, nitrogen deposition and warming on soil respiration in a temperate desert</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yue, Ping; Cui, Xiaoqing; Gong, Yanming; Li, Kaihui; Goulding, Keith; Liu, Xuejun</p> <p>2018-04-01</p> <p>Soil respiration (Rs) is the most important source of carbon dioxide emissions from soil to atmosphere. However, it is unclear what the interactive response of Rs would be to environmental changes such as elevated precipitation, nitrogen (N) deposition and warming, especially in unique temperate desert ecosystems. To investigate this an in situ field experiment was conducted in the Gurbantunggut Desert, northwest China, from September 2014 to October 2016. The results showed that precipitation and N deposition significantly increased Rs, but warming decreased Rs, except in extreme precipitation events, which was mainly through its impact on the variation of soil moisture at 5 cm depth. In addition, the interactive response of Rs to combinations of the factors was much less than that of any single-factor, and the main response was a positive effect, except for the response from the interaction of increased precipitation and high N deposition (60 kg N ha-1 yr-1). Although Rs was found to show a unimodal change pattern with the variation of soil moisture, soil temperature and soil NH4+-N content, and it was significantly positively correlated to soil dissolved organic carbon (DOC) and pH, a structural equation model found that soil temperature was the most important controlling factor. Those results indicated that Rs was mainly interactively controlled by the soil multi-environmental factors and soil nutrients, and was very sensitive to elevated precipitation, N deposition and warming. However, the interactions of multiple factors largely reduced between-year variation of Rs more than any single-factor, suggesting that the carbon cycle in temperate deserts could be profoundly influenced by positive carbon-climate feedback.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017HESS...21.6049M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017HESS...21.6049M"><span>Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross</p> <p>2017-12-01</p> <p>Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the <q>rover</q>, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1414537-shifts-pore-connectivity-from-precipitation-versus-groundwater-rewetting-increases-soil-carbon-loss-after-drought','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1414537-shifts-pore-connectivity-from-precipitation-versus-groundwater-rewetting-increases-soil-carbon-loss-after-drought"><span>Shifts in pore connectivity from precipitation versus groundwater rewetting increases soil carbon loss after drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Smith, A. Peyton; Bond-Lamberty, Ben; Benscoter, Brian W.</p> <p></p> <p>Droughts and other extreme precipitation events are predicted to increase in intensity, duration and extent, with uncertain implications for terrestrial carbon (C) sequestration. Soil wetting from above (precipitation) results in a characteristically different pattern of pore-filling than wetting from below (groundwater), with larger, well-connected pores filling before finer pore spaces, unlike groundwater rise in which capillary forces saturate the finest pores first. Here we demonstrate that pore-scale wetting patterns interact with antecedent soil moisture conditions to alter pore-, core- and field-scale C dynamics. Drought legacy and wetting direction are perhaps more important determinants of short-term C mineralization than current soilmore » moisture content in these soils. Our results highlight that microbial access to C is not solely limited by physical protection, but also by drought or wetting-induced shifts in hydrologic connectivity. We argue that models should treat soil moisture within a three-dimensional framework emphasizing hydrologic conduits for C and resource diffusion.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26672277','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26672277"><span>[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua</p> <p>2015-08-01</p> <p>Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018OPhy...16...14X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018OPhy...16...14X"><span>Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Fei; Zhang, Yaning; Jin, Guangri; Li, Bingxi; Kim, Yong-Song; Xie, Gongnan; Fu, Zhongbin</p> <p>2018-04-01</p> <p>A three-phase model capable of predicting the heat transfer and moisture migration for soil freezing process was developed based on the Shen-Chen model and the mechanisms of heat and mass transfer in unsaturated soil freezing. The pre-melted film was taken into consideration, and the relationship between film thickness and soil temperature was used to calculate the liquid water fraction in both frozen zone and freezing fringe. The force that causes the moisture migration was calculated by the sum of several interactive forces and the suction in the pre-melted film was regarded as an interactive force between ice and water. Two kinds of resistance were regarded as a kind of body force related to the water films between the ice grains and soil grains, and a block force instead of gravity was introduced to keep balance with gravity before soil freezing. Lattice Boltzmann method was used in the simulation, and the input variables for the simulation included the size of computational domain, obstacle fraction, liquid water fraction, air fraction and soil porosity. The model is capable of predicting the water content distribution along soil depth and variations in water content and temperature during soil freezing process.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160006707&hterms=walker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D50%26Ntt%3Dwalker','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160006707&hterms=walker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D50%26Ntt%3Dwalker"><span>Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, R. D.; Walker, G. K.</p> <p>2015-01-01</p> <p>The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007JGRD..11210125F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007JGRD..11210125F"><span>Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fan, Ying; Miguez-Macho, Gonzalo; Weaver, Christopher P.; Walko, Robert; Robock, Alan</p> <p>2007-05-01</p> <p>Soil moisture is a key participant in land-atmosphere interactions and an important determinant of terrestrial climate. In regions where the water table is shallow, soil moisture is coupled to the water table. This paper is the first of a two-part study to quantify this coupling and explore its implications in the context of climate modeling. We examine the observed water table depth in the lower 48 states of the United States in search of salient spatial and temporal features that are relevant to climate dynamics. As a means to interpolate and synthesize the scattered observations, we use a simple two-dimensional groundwater flow model to construct an equilibrium water table as a result of long-term climatic and geologic forcing. Model simulations suggest that the water table depth exhibits spatial organization at watershed, regional, and continental scales, which may have implications for the spatial organization of soil moisture at similar scales. The observations suggest that water table depth varies at diurnal, event, seasonal, and interannual scales, which may have implications for soil moisture memory at these scales.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017HESS...21.4767Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017HESS...21.4767Z"><span>Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Sibo; Roussel, Nicolas; Boniface, Karen; Ha, Minh Cuong; Frappart, Frédéric; Darrozes, José; Baup, Frédéric; Calvet, Jean-Christophe</p> <p>2017-09-01</p> <p>This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2 = 0.74, RMSE = 0.009 m3 m-3) when the wheat is smaller than one wavelength (˜ 19 cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2 = 0.98, RMSE = 6.2 cm). The latter correlates with modeled above-ground dry biomass of the wheat from stem elongation to ripening. It is found that the vegetation height retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in situ observations, and to modeled above-ground dry biomass.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=280017','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=280017"><span>Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41L..01A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41L..01A"><span>The Effect of Vegetation on Soil Water Infiltration and Retention Capacity by Improving Soil Physiochemical Property in Semi-arid Grassland</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>A, Y.; Wang, G.</p> <p>2017-12-01</p> <p>Water shortage is the main limiting factor for semi-arid grassland development. However, the grassland are gradually degraded represented by species conversion, biomass decrease and ecosystem structure simplification under the influence of human activity. Soil water characteristics such as moisture, infiltration and conductivity are critical variables affecting the interactions between soil parameters and vegetation. In this study, Cover, Height, Shannon-Wiener diversity index, Pielou evenness index and Richness index are served as indexes of vegetation productivity and community structure. And saturated hydraulic conductivity (Ks) and soil moisture content are served as indexes of soil water characters. The interaction between vegetation and soil water is investigated through other soil parameters, such as soil organic matter content at different vertical depths and in different degradation area (e.g., initial, transition and degraded plots). The results show that Ks significantly controlled by soil texture other than soil organic matter content. So the influence of vegetation on Ks through increasing soil organic content (SOM) might be slight. However, soil moisture content (SMC) appeared significantly positive relationship with SOM and silt content and negative relationship with sand content at all depth, significantly. This indicated that capacity of soil water storage was influenced both by soil texture and organic matter. In addition, the highest correlation coefficient of SMC was with SOM at the sub-surficial soil layer (20 40 cm). At the depth of 20 40 cm, the soil water content was relatively steady which slightly influenced by precipitation and evaporation. But it significantly influenced by soil organic matter content which related to vegetation. The correlation coefficient between SOM and SMC at topsoil layer (0 20 cm) was lowest (R2=0.36, p<0.01), which indicated the influence of vegetation on soil water content not only by soil organic matter content but also the other influential factors, such as the root water uptake, precipitation and evaporation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JHyd..368...56T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JHyd..368...56T"><span>Assessment of multi-frequency electromagnetic induction for determining soil moisture patterns at the hillslope scale</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tromp-van Meerveld, H. J.; McDonnell, J. J.</p> <p>2009-04-01</p> <p>SummaryHillslopes are fundamental landscape units, yet represent a difficult scale for measurements as they are well-beyond our traditional point-scale techniques. Here we present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the hillslope scale. We test the new multi-frequency GEM-300 for spatially distributed soil moisture measurements at the well-instrumented Panola hillslope. EM-based apparent conductivity measurements were linearly related to soil moisture measured with the Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7.290, 9.090, 11.250, and 14.010 kHz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the soil moisture measurements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21M..03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21M..03L"><span>Impact of hydraulic redistribution on multispecies vegetation water use in a semi-arid ecosystem: An experimental and modeling synthesis</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, E.; Kumar, P.; Barron-Gafford, G.; Scott, R. L.; Hendryx, S. M.; Sanchez-Canete, E. P.; Minor, R. L.; Colella, A.</p> <p>2017-12-01</p> <p>A key challenge in critical zone science is to understand and predict the interaction between aboveground and belowground ecohydrologic processes. One of the links that facilitates the interaction is hydraulic redistribution (HR), a phenomenon by which roots serve as preferential pathways for water movement from wet to dry soil layers. We use a multi-layer canopy model in conjunction with experimental data to examine the influence of HR on eco-hydrologic processes, such as transpiration, soil evaporation, and soil moisture, which characterize the competitive and facilitative dynamics between velvet mesquite and understory bunchgrass. Both measured and simulated results show that hydraulic descent (HD) dominates sap flux during the wet monsoon season, whereas hydraulic lift (HL) occurs between precipitation events. About 17% of precipitation is absorbed as soil-moisture, with the rest of the precipitation returning to the atmosphere as evapotranspiration. In the wet season, 13% of precipitation is transferred to deep soil (>2m) through mesquite roots, and in the dry season, 9% of this redistributed water is transported back to shallow soil depth (<0.5m). Assuming water supplied through HR is well-mixed with moisture transported directly through the soil matrix and supports vegetation evapotranspiration, HR supports about 47% of mesquite transpiration and 9% of understory transpiration. Through modeling and experimental synthesis, this study demonstrates that in the dry land ecosystem of southwestern U.S., Mesquite exhibits competitive advantage over understory bunchgrass through HR.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51E1317N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51E1317N"><span>Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nair, A. S.; Indu, J.</p> <p>2017-12-01</p> <p>Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008257','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008257"><span>Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.</p> <p>2011-01-01</p> <p>The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5810Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5810Y"><span>Soil Moisture and Temperature Measuring Networks in the Tibetan Plateau and Their Hydrological Applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Kun; Chen, Yingying; Qin, Jun; Lu, Hui</p> <p>2017-04-01</p> <p>Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data Assimilation System (GLDAS). 2. Development of New Products. We developed a dual-pass land data assimilation system. The essential idea of the system is to calibrate a land data assimilation system before a normal data assimilation. The calibration is based on satellite data rather than in situ data. Through this way, we may alleviate the impact of uncertainties in determining the error covariance of both observation operator and model operation, as it is always tough to determine the covariance. The performance of the data assimilation system is presented through comparison against the Tibetan Plateau soil moisture measuring networks. And the results are encouraging. 3. Estimation of Soil Parameter Values in a Land Surface Model. We explored the possibility to estimate soil parameter values by assimilating AMSR-E brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.7967N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.7967N"><span>Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun</p> <p>2015-04-01</p> <p>Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.3406R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.3406R"><span>Climate change hampers endangered species through intensified moisture-related plant stresses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>(Ruud) Bartholomeus, R. P.; (Flip) Witte, J. P. M.; (Peter) van Bodegom, P. M.; (Jos) van Dam, J. C.; (Rien) Aerts, R.</p> <p>2010-05-01</p> <p>With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. The first physiological process inhibited at high soil moisture contents is plant root respiration, i.e. oxygen consumption in the roots, which responds to increased temperatures. High soil moisture contents hamper oxygen transport from the atmosphere, through the soil - where part of the oxygen additionally disappears by soil microbial oxygen consumption - and to the root cells. Reduced respiration negatively affects the energy supply to plant metabolism. Plant transpiration, which responds to increased temperatures and atmospheric CO2-concentrations, is the first physiological process that will be inhibited by low soil moisture contents, negatively affecting both photosynthesis and cooling. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060037627&hterms=biome&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dbiome','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060037627&hterms=biome&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dbiome"><span>Estimation of Moisture Content of Forest Canopy and Floor from SAR Data Part I: Volume Scattering Case</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moghaddam, M.; Saatchi, S.</p> <p>1996-01-01</p> <p>To understand and predict the functioning of forest biomes, their interaction with the atmosphere, and their growth rates, the knowledge of moisture content of their canopy and the floor soil is essential. The synthetic aperture radar on airborne and spaceborne platforms has proven to be a flexible tool for measuring electromagnetic back- scattering properties of vegetation related to their moisture content.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC41C1106C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC41C1106C"><span>Forecasting the forest and the trees: consequences of drought in competitive forests</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clark, J. S.</p> <p>2015-12-01</p> <p>Models that translate individual tree responses to distribution and abundance of competing populations are needed to understand forest vulnerability to drought. Currently, biodiversity predictions rely on one scale or the other, but do not combine them. Synthesis is accomplished here by modeling data together, each with their respective scale-dependent connections to the scale needed for prediction—landscape to regional biodiversity. The approach we summarize integrates three scales, i) individual growth, reproduction, and survival, ii) size-species structure of stands, and iii) regional forest biomass. Data include 24,347 USDA Forest Inventory and Analysis (FIA) plots and 135 Long-term Forest Demography plots. Climate, soil moisture, and competitive interactions are predictors. We infer and predict the four-dimensional size/species/space/time (SSST) structure of forests, where all demographic rates respond to winter temperature, growing season length, moisture deficits, local moisture status, and competition. Responses to soil moisture are highly non-linear and not strongly related to responses to climatic moisture deficits over time. In the Southeast the species that are most sensitive to drought on dry sites are not the same as those that are most sensitive on moist sites. Those that respond most to spatial moisture gradients are not the same as those that respond most to regional moisture deficits. There is little evidence of simple tradeoffs in responses. Direct responses to climate constrain the ranges of few tree species, north or south; there is little evidence that range limits are defined by fecundity or survival responses to climate. By contrast, recruitment and the interactions between competition and drought that affect growth and survival are predicted to limit ranges of many species. Taken together, results suggest a rich interaction involving demographic responses at all size classes to neighbors, landscape variation in moisture, and regional climate change.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H31C1516D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H31C1516D"><span>Stochastic Analysis and Probabilistic Downscaling of Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.</p> <p>2017-12-01</p> <p>Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JHyd..475..111Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JHyd..475..111Y"><span>Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru</p> <p>2012-12-01</p> <p>SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T"><span>Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tootle, G.; Anderson, S.; Grissino-Mayer, H.</p> <p>2012-12-01</p> <p>Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41G1539O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41G1539O"><span>Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.</p> <p>2017-12-01</p> <p>Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000073234&hterms=How+soil+form&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHow%2Bsoil%2Bform','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000073234&hterms=How+soil+form&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHow%2Bsoil%2Bform"><span>Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.</p> <p>2000-01-01</p> <p>Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H32E..04T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H32E..04T"><span>Validation of SMAP Radar Vegetation Data Cubes from Agricultural Field Measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tsang, L.; Xu, X.; Liao, T.; Kim, S.; Njoku, E. G.</p> <p>2012-12-01</p> <p>The NASA Soil Moisture Active/Passive (SMAP) Mission will be launched in October 2014. The objective of the SMAP mission is to provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. In the active algorithm, the retrieval is performed based on the backscattering data cube, which are characterized by two surface parameters, which are soil moisture and soil surface rms height, and one vegetation parameter, the vegetation water content. We have developed a physical-based forward scattering model to generate the data cube for agricultural fields. To represent the agricultural crops, we include a layer of cylinders and disks on top of the rough surface. The scattering cross section of the vegetation layer and its interaction with the underground soil surface were calculated by the distorted Born approximation, which give explicitly three scattering mechanisms. A) The direct volume scattering B) The double bounce effect as, and C) The double bouncing effects. The direct volume scattering is calculated by using the Body of Revolution code. The double bounce effects, exhibited by the interaction of rough surface with the vegetation layer is considered by modifying the rough surface reflectivity using the coherent wave as computed by Numerical solution of Maxwell equations of 3 Dimensional simulations (NMM3D) of bare soil scattering. The rough surface scattering of the soil was calculated by NMM3D. We have compared the physical scattering models with field measurements. In the field campaign, the measurements were made on soil moisture, rough surface rms heights and vegetation water content as well as geometric parameters of vegetation. The three main crops lands are grassland, cornfield and soybean fields. The corresponding data cubes are validated using SGP99, SMEX02 and SMEX 08 field experiments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22720037','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22720037"><span>Soil moisture and fungi affect seed survival in California grassland annual plants.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mordecai, Erin A</p> <p>2012-01-01</p> <p>Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1911086P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1911086P"><span>Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung</p> <p>2017-04-01</p> <p>Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..553..678T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..553..678T"><span>Preferential flows and soil moistures on a Benggang slope: Determined by the water and temperature co-monitoring</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tao, Yu; He, Yangbo; Duan, Xiaoqian; Zou, Ziqiang; Lin, Lirong; Chen, Jiazhou</p> <p>2017-10-01</p> <p>Soil preferential flow (PF) has important effects on rainfall infiltration, moisture distribution, and hydrological and ecological process; but it is very difficult to monitor and characterize on a slope. In this paper, soil water and soil temperature at 20, 40, 60, 80 cm depths in six positions were simultaneously monitored at high frequency to confirm the occurrence of PF at a typical Benggang slope underlain granite residual deposits, and to determine the interaction of soil moisture distribution and Benggang erosion. In the presence of PF, the soil temperature was first (half to one hour) governed by the rainwater temperature, then (more than one hour) governed by the upper soil temperature; in the absence of PF (only matrix flow, MF), the soil temperature was initially governed by the upper soil temperature, then by the rainwater temperature. The results confirmed the water replacement phenomenon in MF, thus it can be distinguished from PF by additional temperature monitoring. It indicates that high frequency moisture and temperature monitoring can determine the occurrence of PF and reveal the soil water movement. The distribution of soil water content and PF on the different positions of the slope showed that a higher frequency of PF resulted in a higher variation of average of water content. The frequency of PF at the lower position can be three times as that of the upper position, therefore, the variation coefficient of soil water content increased from 4.67% to 12.68% at the upper position to 8.18%-33.12% at the lower position, where the Benggang erosion (soil collapse) was more possible. The results suggest strong relationships between PF, soil water variation, and collapse activation near the Benggang wall.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=245162','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=245162"><span>Soil Moisture Dynamics Under Corn, Soybean, and Perennial Kura Clover</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting th...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1595M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1595M"><span>A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.</p> <p>2017-12-01</p> <p>Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1598S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1598S"><span>Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.</p> <p>2017-12-01</p> <p>Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AdWR...25.1305S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AdWR...25.1305S"><span>Investigating soil moisture feedbacks on precipitation with tests of Granger causality</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Salvucci, Guido D.; Saleem, Jennifer A.; Kaufmann, Robert</p> <p></p> <p>Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture ( S) feedback on precipitation ( P) using data from Illinois. In this framework S is said to Granger cause P if F(P t|Ω t- Δt )≠F(P t|Ω t- Δt -S t- Δt ) where F denotes the conditional distribution of P, Ω t- Δt represents the set of all knowledge available at time t-Δ t, and Ω t- Δt -S t- Δt represents all knowledge except S. Critical for land-atmosphere interaction research is that Ω t- Δt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed changes in storm probability to Monte-Carlo simulated differences generated with unconditional occurrence probabilities. The null hypothesis is not rejected ( p>0.5) suggesting that contrary to recently published results, insufficient evidence exists to support an influence of soil moisture on precipitation in Illinois.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27241203','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27241203"><span>Soil moisture controls on phenology and productivity in a semi-arid critical zone.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cleverly, James; Eamus, Derek; Restrepo Coupe, Natalia; Chen, Chao; Maes, Wouter; Li, Longhui; Faux, Ralph; Santini, Nadia S; Rumman, Rizwana; Yu, Qiang; Huete, Alfredo</p> <p>2016-10-15</p> <p>The Earth's Critical Zone, where physical, chemical and biological systems interact, extends from the top of the canopy to the underlying bedrock. In this study, we investigated soil moisture controls on phenology and productivity of an Acacia woodland in semi-arid central Australia. Situated on an extensive sand plain with negligible runoff and drainage, the carry-over of soil moisture content (θ) in the rhizosphere enabled the delay of phenology and productivity across seasons, until conditions were favourable for transpiration of that water to prevent overheating in the canopy. Storage of soil moisture near the surface (in the top few metres) was promoted by a siliceous hardpan. Pulsed recharge of θ above the hardpan was rapid and depended upon precipitation amount: 150mm storm(-1) resulted in saturation of θ above the hardpan (i.e., formation of a temporary, discontinuous perched aquifer above the hardpan in unconsolidated soil) and immediate carbon uptake by the vegetation. During dry and inter-storm periods, we inferred the presence of hydraulic lift from soil storage above the hardpan to the surface due to (i) regular daily drawdown of θ in the reservoir that accumulates above the hardpan in the absence of drainage and evapotranspiration; (ii) the dimorphic root distribution wherein most roots were found in dry soil near the surface, but with significant root just above the hardpan; and (iii) synchronisation of phenology amongst trees and grasses in the dry season. We propose that hydraulic redistribution provides a small amount of moisture that maintains functioning of the shallow roots during long periods when the surface soil layer was dry, thereby enabling Mulga to maintain physiological activity without diminishing phenological and physiological responses to precipitation when conditions were favourable to promote canopy cooling. Copyright © 2016 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1712494P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1712494P"><span>Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio</p> <p>2015-04-01</p> <p>Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170004545','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170004545"><span>VHF SoOp (Signal of Opportunity) Technology Demonstration for Soil Moisture Measurement Using Microwave Hydraulic Boom Truck Platform</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Joseph, A. T.; Deshpande, M.; O'Neill, P. E.; Miles, L.</p> <p>2017-01-01</p> <p>A goal of this research is to test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a global direct surface soil moisture (SM) and RZSM measurement system over a variety of land covers. Knowledge of RZSM up to a depth of 1 meter and surface SM up to a depth of 0.05 meter on a global scale, at a spatial resolution of 1-10 km through moderate-to-heavy vegetation, is critical to understanding global water resources and the vertical moisture gradient in the Earths surface layer which controls moisture interactions between the soil, vegetation, and atmosphere. Current observations of surface SM from space by L-band radiometers (1.4 GHz) and radars (1.26 GHz) are limited to measurements of surface SM up to a depth of 0.05 meter through moderate amounts of vegetation. This limitation is mainly due to the inability of L-band signals to penetrate through dense vegetation and deep into the soil column. Satellite observations of the surface moisture conditions are coupled to sophisticated models which extrapolate the surface SM into the root zone, thus providing an indirect estimate rather than a direct measurement of RZSM. To overcome this limitation, low-frequency airborne radars operating at 435 MHz and 118 MHz have been investigated, since these lower frequencies should penetrate denser vegetation and respond to conditions deeper in the soil.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........51N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........51N"><span>High resolution change estimation of soil moisture and its assimilation into a land surface model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Narayan, Ujjwal</p> <p></p> <p>Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.129..305S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.129..305S"><span>Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani</p> <p>2017-07-01</p> <p>Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT.......140D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT.......140D"><span>Precipitation recycling as a mechanism for ecoclimatological stability through local and non-local interactions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dominguez, Francina</p> <p></p> <p>This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=266165','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=266165"><span>Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.9660B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.9660B"><span>A conceptual framework for regional feedbacks in a changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Batlle Bayer, L.; van den Hurk, B. J. J. M.; Strengers, B.</p> <p>2012-04-01</p> <p>Terrestrial ecosystems and climate influence each other through biogeochemical (e.g. carbon cycle) and biogeophysical (e.g. albedo, water fluxes) processes. These interactions might be disturbed when a climate human-induced forcing takes place (e.g. deforestation); and the ecosystem responses to the climate system might amplify (positive feedback) or dampen (negative feedback) the initial forcing. Research on feedbacks has been mainly based on the carbon cycle at the global scale. However, biogeophysical feedbacks might have a great impact at the local or regional scale, which is the main focus of this article. A conceptual framework, with the major interactions and processes between terrestrial ecosystems and climate, is presented to further explore feedbacks at the regional level. Four hot spots with potential changes in land use/management and climate are selected: sub-Saharan Africa (SSA), Europe, the Amazon Basin and South and Southeast Asia. For each region, diverse climate human-induced forcings and feedbacks were identified based on relevant published literature. For Europe, the positive soil moisture-evapotranspiration (ET) is important for natural vegetation during a heat wave event, while the positive soil moisture-precipitation feedback plays a more important role for droughts in the Amazon region. Agricultural expansion in SSA will depend on the impacts of the changing climate on crop yields and the adopted agro-technologies. The adoption of irrigation in the commonly rainfed systems might turn the positive soil moisture- ET feedback into a negative one. In contrast, South and Southeast Asia might face water shortage in the future, and thus turning the soil moisture-ET feedback into a positive one. Further research is needed for the major processes that affect the ultimate sign of the feedbacks, as well as for the interactions, which effect remains uncertain, such as ET-precipitation interaction. In addition, socio-economic feedbacks need to be added in the ecosystems-climate system since they play an essential role in human decisions on land use and land cover change (LULCC).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D"><span>On the assimilation of satellite derived soil moisture in numerical weather prediction models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drusch, M.</p> <p>2006-12-01</p> <p>Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23H1773S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23H1773S"><span>Quantifying the role of vegetation in controlling the time-variant age of evapotranspiration, soil water and stream flow</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smith, A.; Tetzlaff, D.; Soulsby, C.</p> <p>2017-12-01</p> <p>Identifying the sources of water which sustain plant water uptake is an essential prerequisite to understanding the interactions of vegetation and water within the critical zone. Estimating the sources of root-water uptake is complicated by ecohydrological separation, or the notion of "two-water worlds" which distinguishes more mobile and immobile water sources which respectively sustain streamflow and evapotranspiration. Water mobility within the soil determines both the transit time/residence time of water through/in soils and the subsequent age of root-uptake and xylem water. We used time-variant StorAge Selection (SAS) functions to conceptualise the transit/residence times in the critical zone using a dual-storage soil column differentiating gravity (mobile) and tension dependent (immobile) water, calibrated to measured stable isotope signatures of soil water. Storage-discharge relationships [Brutsaert and Nieber, 1977] were used to identify gravity and tension dependent storages. A temporally variable distribution for root water uptake was identified using simulated stable isotopes in xylem and soil water. Composition of δ2H and δ18O was measured in soil water at 4 depths (5, 10, 15, and 20 cm) on 10 occasions, and 5 times for xylem water within the dominant heather (Calluna sp. and Erica sp.) vegetation in a Scottish Highland catchment over a two-year period. Within a 50 cm soil column, we found that more than 53% of the total stored water was water that was present before the start of the simulation. Mean residence times of the mobile water in the upper 20 cm of the soil were 16, 25, 36, and 44 days, respectively. Mean evaporation transit time varied between 9 and 40 days, driven by seasonal changes and precipitation events. Lastly, mean transit times of xylem water ranged between 95-205 days, driven by changes in soil moisture. During low soil moisture (i.e. lower than mean soil moisture), root-uptake was from lower depths, while higher than mean soil moisture showed preferential uptake of near surface water. In our humid, low energy environment, we found that xylem water is comprised of both mobile and immobile water. The division of soil storage into two storages, gravity and tension dependent, has shown potential to identify the sources of plant water and vegetation and soil water interactions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=325197','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=325197"><span>Evaluation of the validated soil moisture product from the SMAP radiometer</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050238481','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050238481"><span>NASA Soil Moisture Data Products and Their Incorporation in DREAM</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette</p> <p>2005-01-01</p> <p>NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011762','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011762"><span>Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.</p> <p>2011-01-01</p> <p>The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.1931Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.1931Z"><span>Deriving surface soil moisture from reflected GNSS signal observations from a grassland site in southwestern France</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Sibo; Calvet, Jean-Christophe; Darrozes, José; Roussel, Nicolas; Frappart, Frédéric; Bouhours, Gilles</p> <p>2018-03-01</p> <p>This work assesses the estimation of surface volumetric soil moisture (VSM) using the global navigation satellite system interferometric reflectometry (GNSS-IR) technique. Year-round observations were acquired from a grassland site in southwestern France using an antenna consecutively placed at two contrasting heights above the ground surface (3.3 and 29.4 m). The VSM retrievals are compared with two independent reference datasets: in situ observations of soil moisture, and numerical simulations of soil moisture and vegetation biomass from the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model. Scaled VSM estimates can be retrieved throughout the year removing vegetation effects by the separation of growth and senescence periods and by the filtering of the GNSS-IR observations that are most affected by vegetation. Antenna height has no significant impact on the quality of VSM estimates. Comparisons between the VSM GNSS-IR retrievals and the in situ VSM observations at a depth of 5 cm show good agreement (R2 = 0.86 and RMSE = 0.04 m3 m-3). It is shown that the signal is sensitive to the grass litter water content and that this effect triggers differences between VSM retrievals and in situ VSM observations at depths of 1 and 5 cm, especially during light rainfall events.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170007429&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170007429&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil"><span>Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.</p> <p>2017-01-01</p> <p>The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007JGRD..112.3102D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007JGRD..112.3102D"><span>Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drusch, M.</p> <p>2007-02-01</p> <p>Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z"><span>Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.</p> <p>2012-04-01</p> <p>Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9877E..2BS','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9877E..2BS"><span>Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.</p> <p>2016-05-01</p> <p>Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B41E0251G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B41E0251G"><span>Modeling soil moisture memory in savanna ecosystems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gou, S.; Miller, G. R.</p> <p>2011-12-01</p> <p>Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20120009941&hterms=soil+layers&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%2Blayers','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20120009941&hterms=soil+layers&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%2Blayers"><span>Diagnosing the Sensitivity of Local Land-Atmosphere Coupling via the Soil Moisture-Boundary Layer Interaction</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.</p> <p>2011-01-01</p> <p>The inherent coupled nature of earth s energy and water cycles places significant importance on the proper representation and diagnosis of land atmosphere (LA) interactions in hydrometeorological prediction models. However, the precise nature of the soil moisture precipitation relationship at the local scale is largely determined by a series of nonlinear processes and feedbacks that are difficult to quantify. To quantify the strength of the local LA coupling (LoCo), this process chain must be considered both in full and as individual components through their relationships and sensitivities. To address this, recent modeling and diagnostic studies have been extended to 1) quantify the processes governing LoCo utilizing the thermodynamic properties of mixing diagrams, and 2) diagnose the sensitivity of coupled systems, including clouds and moist processes, to perturbations in soil moisture. This work employs NASA s Land Information System (LIS) coupled to the Weather Research and Forecasting (WRF) mesoscale model and simulations performed over the U.S. Southern Great Plains. The behavior of different planetary boundary layers (PBL) and land surface scheme couplings in LIS WRF are examined in the context of the evolution of thermodynamic quantities that link the surface soil moisture condition to the PBL regime, clouds, and precipitation. Specifically, the tendency toward saturation in the PBL is quantified by the lifting condensation level (LCL) deficit and addressed as a function of time and space. The sensitivity of the LCL deficit to the soil moisture condition is indicative of the strength of LoCo, where both positive and negative feedbacks can be identified. Overall, this methodology can be applied to any model or observations and is a crucial step toward improved evaluation and quantification of LoCo within models, particularly given the advent of next-generation satellite measurements of PBL and land surface properties along with advances in data assimilation schemes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913930C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913930C"><span>Using satellite image data to estimate soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chuang, Chi-Hung; Yu, Hwa-Lung</p> <p>2017-04-01</p> <p>Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D"><span>Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.</p> <p>2017-12-01</p> <p>Tropical peatlands in Equatorial Asia have become more vulnerable to fire due to deforestation and peatland drainage over the last 30 years. In these regions, water table depth has been shown to play an important role in mediating fire risk as it serves as a proxy for peat moisture content. However, water table depth observations are sparse and expensive. Soil moisture could provide a more direct indicator of fire risk than water table depth. In this study, we use new soil moisture retrievals from the Soil Moisture Active Passive (SMAP) satellite to demonstrate that - contrary to popular wisdom - remotely sensed soil moisture observations are possible over most Southeast Asian peatlands. Soil moisture estimation in this region was previously thought to be impossible over tropical peatlands because of dense vegetation cover. We show that vegetation density is sufficiently low across most Equatorial Asian peatlands to allow soil moisture estimation, and hypothesize that deforestation and other anthropogenic changes in land cover have combined to reduce overall vegetation density sufficient to allow soil moisture estimation. We further combine burned area estimates from the Global Fire Emissions Database and SMAP soil moisture retrievals to show that soil moisture provides a strong signal for fire risk in peatlands, with fires occurring at a much greater rate over drier soils. We will also develop an explicit fire risk model incorporating soil moisture with additional climatic, land cover, and anthropogenic predictor variables.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840014939','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840014939"><span>A microwave systems approach to measuring root zone soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Newton, R. W.; Paris, J. F.; Clark, B. V.</p> <p>1983-01-01</p> <p>Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=264667','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=264667"><span>The international soil moisture network: A data hosting facility for global in situ soil moisture measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1588H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1588H"><span>An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hunt, E. D.; Otkin, J.; Zhong, Y.</p> <p>2017-12-01</p> <p>Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5339292','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5339292"><span>Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nishar, Abdul; Bader, Martin K.-F.; O’Gorman, Eoin J.; Deng, Jieyu; Breen, Barbara; Leuzinger, Sebastian</p> <p>2017-01-01</p> <p>Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming. PMID:28326088</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28326088','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28326088"><span>Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nishar, Abdul; Bader, Martin K-F; O'Gorman, Eoin J; Deng, Jieyu; Breen, Barbara; Leuzinger, Sebastian</p> <p>2017-01-01</p> <p>Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3524093','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3524093"><span>Aspen Increase Soil Moisture, Nutrients, Organic Matter and Respiration in Rocky Mountain Forest Communities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Buck, Joshua R.; St. Clair, Samuel B.</p> <p>2012-01-01</p> <p>Development and change in forest communities are strongly influenced by plant-soil interactions. The primary objective of this paper was to identify how forest soil characteristics vary along gradients of forest community composition in aspen-conifer forests to better understand the relationship between forest vegetation characteristics and soil processes. The study was conducted on the Fishlake National Forest, Utah, USA. Soil measurements were collected in adjacent forest stands that were characterized as aspen dominated, mixed, conifer dominated or open meadow, which includes the range of vegetation conditions that exist in seral aspen forests. Soil chemistry, moisture content, respiration, and temperature were measured. There was a consistent trend in which aspen stands demonstrated higher mean soil nutrient concentrations than mixed and conifer dominated stands and meadows. Specifically, total N, NO3 and NH4 were nearly two-fold higher in soil underneath aspen dominated stands. Soil moisture was significantly higher in aspen stands and meadows in early summer but converged to similar levels as those found in mixed and conifer dominated stands in late summer. Soil respiration was significantly higher in aspen stands than conifer stands or meadows throughout the summer. These results suggest that changes in disturbance regimes or climate scenarios that favor conifer expansion or loss of aspen will decrease soil resource availability, which is likely to have important feedbacks on plant community development. PMID:23285012</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080044842','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080044842"><span>Estimation of Soil Moisture with L-band Multi-polarization Radar</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shi, J.; Chen, K. S.; Kim, Chung-Li Y.; Van Zyl, J. J.; Njoku, E.; Sun, G.; O'Neill, P.; Jackson, T.; Entekhabi, D.</p> <p>2004-01-01</p> <p>Through analyses of the model simulated data-base, we developed a technique to estimate surface soil moisture under HYDROS radar sensor (L-band multi-polarizations and 40deg incidence) configuration. This technique includes two steps. First, it decomposes the total backscattering signals into two components - the surface scattering components (the bare surface backscattering signals attenuated by the overlaying vegetation layer) and the sum of the direct volume scattering components and surface-volume interaction components at different polarizations. From the model simulated data-base, our decomposition technique works quit well in estimation of the surface scattering components with RMSEs of 0.12,0.25, and 0.55 dB for VV, HH, and VH polarizations, respectively. Then, we use the decomposed surface backscattering signals to estimate the soil moisture and the combined surface roughness and vegetation attenuation correction factors with all three polarizations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.6413H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.6413H"><span>Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Henneberg, Olga; Ament, Felix; Grützun, Verena</p> <p>2018-05-01</p> <p>Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale. We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil moisture with realistic fields from different days has an insignificant influence on precipitation. The findings of this study underline the need for uncertainty estimates in soil moisture studies based on convection-resolving models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/31968','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/31968"><span>Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a></p> <p></p> <p>2016-09-01</p> <p>Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during c...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H41O..02I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H41O..02I"><span>Soil Moisture Dynamics in the Shallow Subsurface Near the Land/Atmospheric Interface- Challenges and New Research Approaches (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Illangasekare, T. H.; Smits, K. M.; Trautz, A.; Rice, A. K.; Cihan, A.; Davarzani, H.</p> <p>2013-12-01</p> <p>SSoil moisture processes in the subsurface/near-land-surface, play a crucial role in the hydrologic cycle and global water budget. This zone is subject to both natural and human induced disturbances, resulting in continually changing soil structure and hydraulic, thermal, and mechanical properties. Understanding of the dynamics of soil moisture distribution in this zone is of interest in various applications in hydrology such as land-atmospheric interaction, soil evaporation and evapotranspiration, as well as emerging problems on assessing the risk of leakage of sequestrated CO2 from deep geologic formations to the shallow subsurface, and potential leakage of methane to the atmosphere in shale gas development that contributes to global warming. Shallow subsurface soil moisture is highly influenced by diurnal temperature variations, evaporation/condensation, precipitation and liquid water and water vapor flow, all of which are strongly coupled. Modeling studies, have shown that soil moisture in this zone is highly sensitive to the heat and mass flux boundary conditions at the land surface. Hence, approximation of these boundary conditions without properly incorporating complex feedback between the land and the atmospheric boundary layer are expected to result in significant errors. Even though considerable knowledge exists on how soil moisture changes in response to the flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability at higher spatial and temporal resolutions than what is needed in traditional applications in soil physics and vadose zone hydrology. These factors lead to many modeling challenges, primarily of which is the issue of up-scaling. It is our contention that knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solutions cannot be obtained using only field data. Basic to this limitation is the inability to make field measurements at very fine scales at high temporal resolutions. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and models cannot be validated for a diversity of conditions that could be expected. As an alternative, we propose an innovative testing approach that couples a low velocity boundary layer climate wind tunnel to intermediate scale porous media tanks. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this talk, we will present examples of studies we have conducted in a hierarchy of test systems, including the intermediate scale. The advantages and limitations of testing at this scale are discussed using these examples. The features and capabilities of newly developed test systems are presented with the goal of exploring opportunities to use them to study some of the challenging multi-scale problems in the near surface unsaturated zone.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H11N..02T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H11N..02T"><span>A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tuttle, S. E.; Salvucci, G.</p> <p>2012-12-01</p> <p>Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1372969-variations-annual-water-energy-balance-correlations-vegetation-soil-moisture-dynamics-case-study-wei-river-basin-china','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1372969-variations-annual-water-energy-balance-correlations-vegetation-soil-moisture-dynamics-case-study-wei-river-basin-china"><span>Variations in annual water-energy balance and their correlations with vegetation and soil moisture dynamics: A case study in the Wei River Basin, China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Huang, Shengzhi; Huang, Qiang; Leng, Guoyong</p> <p></p> <p>It is of importance to investigate watershed water-energy balance variations and to explore their correlations with vegetation and soil moisture dynamics, which helps better understand the interplays between underlying surface dynamics and the terrestrial water cycle. The heuristic segmentation method was adopted to identify change points in the parameter to series in Fu's equation belonging to the Budyko framework in the Wei River Basin (WRB) and its sub-basins aiming to examine the validity of stationary assumptions. Additionally, the cross wavelet analysis was applied to explore the correlations between vegetation and soil moisture dynamics and to variations. Results indicated that (1)more » the omega variations in the WRB are significant, with some change points identified except for the sub-basin above Zhangjiashan, implying that the stationarity of omega series in the WRB is invalid except for the sub-basin above Zhangjiashan; (2) the correlations between soil moisture series and to series are weaker than those between Normalized Difference Vegetation Index (NDVI) series and omega series; (3) vegetation dynamics show significantly negative correlations with omega variations in 1983-2003 with a 4-8 year signal in the whole WRB, and both vegetation and soil moisture dynamics exert strong impacts on the parameter omega changes. This study helps understanding the interactions between underlying land surface dynamics and watershed water-energy balance. (C) 2017 Elsevier B.V. All rights reserved.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AdWR...86..155J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AdWR...86..155J"><span>Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ji, Xinye; Shen, Chaopeng; Riley, William J.</p> <p>2015-12-01</p> <p>Soil moisture statistical fractal is an important tool for downscaling remotely-sensed observations and has the potential to play a key role in multi-scale hydrologic modeling. The fractal was first introduced two decades ago, but relatively little is known regarding how its scaling exponents evolve in time in response to climatic forcings. Previous studies have neglected the process of moisture re-distribution due to regional groundwater flow. In this study we used a physically-based surface-subsurface processes model and numerical experiments to elucidate the patterns and controls of fractal temporal evolution in two U.S. Midwest basins. Groundwater flow was found to introduce large-scale spatial structure, thereby reducing the scaling exponents (τ), which has implications for the transferability of calibrated parameters to predict τ. However, the groundwater effects depend on complex interactions with other physical controls such as soil texture and land use. The fractal scaling exponents, while in general showing a seasonal mode that correlates with mean moisture content, display hysteresis after storm events that can be divided into three phases, consistent with literature findings: (a) wetting, (b) re-organizing, and (c) dry-down. Modeling experiments clearly show that the hysteresis is attributed to soil texture, whose "patchiness" is the primary contributing factor. We generalized phenomenological rules for the impacts of rainfall, soil texture, groundwater flow, and land use on τ evolution. Grid resolution has a mild influence on the results and there is a strong correlation between predictions of τ from different resolutions. Overall, our results suggest that groundwater flow should be given more consideration in studies of the soil moisture statistical fractal, especially in regions with a shallow water table.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21Q..06B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21Q..06B"><span>Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.</p> <p>2017-12-01</p> <p>Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H31M..06W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H31M..06W"><span>A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.</p> <p>2013-12-01</p> <p>In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27764203','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27764203"><span>The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K</p> <p>2016-01-01</p> <p>Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5072646','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5072646"><span>The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.</p> <p>2016-01-01</p> <p>Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26620951','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26620951"><span>Linking the soil moisture distribution pattern to dynamic processes along slope transects in the Loess Plateau, China.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo</p> <p>2015-12-01</p> <p>Soil moisture pulses are a prerequisite for other land surface pulses at various spatiotemporal scales in arid and semi-arid areas. The temporal dynamics and profile variability of soil moisture in relation to land cover combinations were studied along five slopes transect on the Loess Plateau during the rainy season of 2011. Within the 3 months of the growing season coupled with the rainy season, all of the soil moisture was replenished in the area, proving that a type stability exists between different land cover soil moisture levels. Land cover combinations disturbed the trend determined by topography and increased soil moisture variability in space and time. The stability of soil moisture resulting from the dynamic processes could produce stable patterns on the slopes. The relationships between the mean soil moisture and vertical standard deviation (SD) and coefficient of variation (CV) were more complex, largely due to the fact that different land cover types had distinctive vertical patterns of soil moisture. The spatial SD of each layer had a positive correlation and the spatial CV exhibited a negative correlation with the increase in mean soil moisture. The soil moisture stability implies that sampling comparisons in this area can be conducted at different times to accurately compare different land use types.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43Q..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43Q..08S"><span>Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sure, A.; Dikshit, O.</p> <p>2017-12-01</p> <p>Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000713','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000713"><span>Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy</p> <p>2015-01-01</p> <p>Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53D0923D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53D0923D"><span>Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.</p> <p>2017-12-01</p> <p>Soil moisture and soil temperature are critical to plant community distribution and soil carbon cycle processes in High Arctic tundra. As environmental drivers of soil biochemical processes, the predictability of soil moisture and soil temperature by vegetation zone in High Arctic landscapes has significant implications for the use of satellite imagery and vegetation distribution maps to estimate of soil gas flux rates. During the 2017 growing season, we monitored soil moisture and soil temperature weekly at 48 sites in dry tundra, moist tundra, and wet grassland vegetation zones in a High Arctic lake basin. Soil temperature in all three communities reflected fluctuations in air temperature throughout the season. Mean soil temperature was highest in the dry tundra community at 10.5±0.6ºC, however, did not differ between moist tundra and wet grassland communities (2.7±0.6 and 3.1±0.5ºC, respectively). Mean volumetric soil moisture differed significantly among all three plant communities with the lowest and highest soil moisture measured in the dry tundra and wet grassland (30±1.2 and 65±2.7%), respectively. For all three communities, soil moisture was highest during the early season snow melt. Soil moisture in wet grassland remained high with no significant change throughout the season, while significant drying occurred in dry tundra. The most significant change in soil moisture was measured in moist tundra, ranging from 61 to 35%. Our results show different gradients in soil moisture variability within each plant community where: 1) soil moisture was lowest in dry tundra with little change, 2) highest in wet grassland with negligible change, and 3) variable in moist tundra which slowly dried but remained moist. Consistently high soil moisture in wet grassland restricts this plant community to areas with no significant drying during summer. The moist tundra occupies the intermediary areas between wet grassland and dry tundra and experiences the widest range of soil moisture variability. As climate projections predict wetter summers in the High Arctic, expansion of areas with seasonally inundated soils and increased soil moisture variability could result in an expansion of wet grassland and moist tundra communities with a commensurate decrease in dry tundra area.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034418','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034418"><span>Response of spectral vegetation indices to soil moisture in grasslands and shrublands</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Zhang, Li; Ji, Lei; Wylie, Bruce K.</p> <p>2011-01-01</p> <p>The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H33A0855C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H33A0855C"><span>The Temporal Dynamics of Spatial Patterns of Observed Soil Moisture Interpreted Using the Hydrus 1-D Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, M.; Willgoose, G. R.; Saco, P. M.</p> <p>2009-12-01</p> <p>This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC52A..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC52A..04S"><span>Temperature extremes in a changing climate: Drivers and feedbacks (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seneviratne, S. I.; Davin, E. L.; Hirschi, M.; Mueller, B.; Orlowsky, B.; Orth, R.; Wilhelm, M.</p> <p>2013-12-01</p> <p>Global warming increases the occurrence probability of hot extremes, and improving the predictability of such events is thus becoming of critical importance (e.g. Seneviratne et al. 2012). This presentation provides an overview of past and projected changes in hot extremes on the global and regional scale, and of the respective drivers and feedbacks responsible for their occurrence. In particular, soil moisture-temperature feedbacks have been identified as major drivers for hot extremes (e.g. Seneviratne et al. 2006, 2010; Hirschi et al. 2011). Recently, a global study (Mueller and Seneviratne 2012) has shown that wide areas of the world display a strong relationship between the number of hot days in the regions' hottest month and preceding precipitation deficits. These findings suggest that effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed, with for instance large hot spots of soil moisture-temperature coupling in the Southern Hemisphere. Further results indicate that this relationship could be better used in the context of seasonal forecasting, allowing an early warning of impending hot summers (Mueller and Seneviratne 2012, Orth and Seneviratne 2013). In addition, the role of soil moisture-climate feedbacks for climate projections will also be discussed (e.g. Orlowsky and Seneviratne 2012; Seneviratne et al., 2013). Finally, we will address the relevance of the identified feedbacks in the context of urban climate, as well as potential relevant impacts of other land-climate interactions (e.g. from modifications in surface albedo). References: Hirschi, M., et al., 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nature Geosci., 4, 17-21, doi:10.1038/ngeo1032. Mueller, B., and S.I. Seneviratne, 2012: Hot days induced by precipitation deficits at the global scale. Proc. Natl Acad. Sci., 109 (31), 12398-12403, doi: 10.1073/pnas.1204330109. Orth, R. and S.I. Seneviratne 2013: Using soil moisture forecasts for sub-seasonal temperature predictions in Europe. Submitted to Clim. Dyn.. Seneviratne, S.I., et al., 2006: Land-atmosphere coupling and climate change in Europe. Nature, 443, 205-209. Seneviratne, S.I., et al., 2010: Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Science Reviews, 99, 3-4, 125-161, doi:10.1016/j.earscirev.2010.02.004. Seneviratne, S.I., N. Nicholls, et al., 2012: Changes in climate extremes and their impacts on the natural physical environment. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., et al. (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, pp. 109-230. Seneviratne, S.I., et al., 2013: Impact of soil moisture-climate feedbacks on CMIP5 projections: First results from the GLACE-CMIP5 experiment. Submitted to Geophys. Res. Lett.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdWR...92...73K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdWR...92...73K"><span>On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Jongho; Dwelle, M. Chase; Kampf, Stephanie K.; Fatichi, Simone; Ivanov, Valeriy Y.</p> <p>2016-06-01</p> <p>This study advances mechanistic interpretation of predictability challenges in hydro-geomorphology related to the role of soil moisture spatial variability. Using model formulations describing the physics of overland flow, variably saturated subsurface flow, and erosion and sediment transport, this study explores (1) why a basin with the same mean soil moisture can exhibit distinctly different spatial moisture distributions, (2) whether these varying distributions lead to non-unique hydro-geomorphic responses, and (3) what controls non-uniqueness in relation to the response type. Two sets of numerical experiments are carried out with two physically-based models, HYDRUS and tRIBS+VEGGIE+FEaST, and their outputs are analyzed with respect to pre-storm moisture state. The results demonstrate that distinct spatial moisture distributions for the same mean wetness arise because near-surface soil moisture dynamics exhibit different degrees of coupling with deeper-soil moisture and the process of subsurface drainage. The consequences of such variations are different depending on the type of hydrological response. Specifically, if the predominant runoff response is of infiltration excess type, the degree of non-uniqueness is related to the spatial distribution of near-surface moisture. If runoff is governed by subsurface stormflow, the extent of deep moisture contributing area and its "readiness to drain" determine the response characteristics. Because the processes of erosion and sediment transport superimpose additional controls over factors governing runoff generation and overland flow, non-uniqueness of the geomorphic response can be highly dampened or enhanced. The explanation is sediment composed by multi-size particles can alternate states of mobilization or surface shielding and the transient behavior is inherently intertwined with the availability of mobile particles. We conclude that complex nonlinear dynamics of hydro-geomorphic processes are inherent expressions of physical interactions. As complete knowledge of watershed properties, states, or forcings will always present the ultimate, if ever resolvable, challenge, deterministic predictability will remain handicapped. Coupling of uncertainty quantification methods and space-time physics-based approaches will need to evolve to facilitate mechanistic interpretations and informed practical applications.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H41C0908B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H41C0908B"><span>Generation of a Realistic Soil Moisture Initialization System and its Potential Impact on Short-to-Seasonal Forecasting of Near Surface Variables</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boisserie, M.; Cocke, S.; O'Brien, J. J.</p> <p>2009-12-01</p> <p>Although the amount of water contained in the soil seems insignificant when compared to the total amount of water on a global-scale, soil moisture is widely recognized as a crucial variable for climate studies. It plays a key role in regulating the interaction between the atmosphere and the land-surface by controlling the repartition between the surface latent and sensible heat fluxes. In addition, the persistence of soil moisture anomalies provides one of the most important components of memory for the climate system. Several studies have shown that, during the boreal summer in mid-latitudes, the soil moisture role in controlling the continental precipitation variability may be more important than that of the sea surface temperature (Koster et al. 2000, Hong and Kalnay 2000, Koster et al. 2000, Kumar and Hoerling 1995, Trenberth et al. 1998, Shukla 1998). Although all of the above studies have demonstrated the strong sensitivity of seasonal forecasts to the soil moisture initial conditions, they relied on extreme or idealized soil moisture levels. The question of whether realistic soil moisture initial conditions lead to improved seasonal predictions has not been adequately addressed. Progress in addressing this question has been hampered by the lack of long-term reliable observation-based global soil moisture data sets. Since precipitation strongly affects the soil moisture characteristics at the surface and in depth, an alternative to this issue is to assimilate precipitation. Because precipitation is a diagnostic variable, most of the current reanalyses do not directly assimilate it into their models (M. Bosilovitch, 2008). In this study, an effective technique that directly assimilates the precipitation is used. We examine two experiments. In the first experiment, the model is initialized by directly assimilating a global, 3-hourly, 1.0° precipitation dataset, provided by Sheffield et al. (2006), in a continuous assimilation period of a couple of months. For this, we use a technique named the Precipitation Assimilation Reanalysis (PAR) described in Nunes and Cocke (2004). This technique consists of modifying the vertical profile of humidity as a function of the observed and predicted model rain rates. In the second experiment, the model is initialized without precipitation assimilation. For each experiment, ten sets of seasonal forecasts of the coupled land-atmosphere Florida State University/Center for Ocean and Atmosphere Predictions Studies (FSU/COAPS) model were generated, starting from the boreal summer of each year between 1986 and 1995. For each forecast, ten ensembles are produced by starting the forecast from the 1st and the 15th of each month from April to August. The results of these experiments show, first, that the PAR technique greatly improves the temporal and spatial variability of out model soil moisture estimate. Second, using these realistic soil moisture initial conditions, we found a significant increase in the air temperature seasonal forecasting skills. However, not significant increase has been found in the precipitation seasonal forecasting skills. The results of this study are involved in the GLACE-2 international multi-model experiment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870007870&hterms=discrimination&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddiscrimination','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870007870&hterms=discrimination&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddiscrimination"><span>Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vandegriend, A. A.; Oneill, P. E.</p> <p>1986-01-01</p> <p>Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120016510','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120016510"><span>Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bolten, John; Crow, Wade</p> <p>2012-01-01</p> <p>The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..550..466Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..550..466Y"><span>Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan</p> <p>2017-07-01</p> <p>Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/50775','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/50775"><span>Fine and coarse root parameters from mature black spruce displaying genetic x soil moisture interaction in growth</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>John E. Major; Kurt H. Johnsen; Debby C. Barsi; Moira Campbell</p> <p>2012-01-01</p> <p>Fine and coarse root biomass, C, and N mass parameters were assessed by root size and soil depths from soil cores in plots of 32-year-old black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) from four full-sib families studied previously for drought tolerance and differential productivity on a dry and wet...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.9394U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.9394U"><span>The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.</p> <p>2012-04-01</p> <p>Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016cosp...41E.369C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016cosp...41E.369C"><span>SURFEX modeling of soil moisture fields over the Valencia Anchor Station and their comparison to different SMOS products and in situ measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coll Pajaron, M. Amparo; Lopez-Baeza, Ernesto; Fernandez-Moran, Roberto; Samiro Khodayar-Pardo, D.</p> <p>2016-07-01</p> <p>Soil moisture is a difficult variable to obtain proper representation because of its high temporal and spatial variability. It is a significant parameter in agriculture, hydrology, meteorology and related disciplines. {it SVAT (Soil-Vegetation-Atmosphere-Transfer)} models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the {bf SURFEX (Surface Externalisée)} model developed at the {it Centre National de Recherches Météorologiques (CNRM)} at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the {bf Valencia Anchor Station}. SURFEX integrates the {bf ISBA (Interaction Sol-Biosphère-Atmosphère}; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) that have been adapted to describe the land covers of our study area. The Valencia Anchor Station was chosen as a core validation site for the {it SMOS (Soil Moisture and Ocean Salinity)} mission and as one of the hydrometeorological sites for the {it HyMeX (HYdrological cycle in Mediterranean EXperiment)} programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few small scattered industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields over the Valencia Anchor Station to be compared with SMOS level-2 (resolution 15 km) and level-3 (resolution 25 km) soil moisture maps and high resolution SMOS pixel-disaggregated soil moisture products, obtained by combining SMOS level-2 with MODIS NDVI and LST data (resolution 1 km) (Piles et al., 2011). In situ measurements from the Valencia Anchor Station network of soil moisture stations are also available as reference covering a reduced number of different vegetation cover and soil types, as well as estimations from the ESA ELBARA-II L-band radiometer installed over a vineyard crop to monitor SMOS validation conditions. Different interpolation methods have been applied to all significant atmospheric forcing parameters from the two met stations available in the area (pressure, temperature, relative humidity and precipitation) in order to obtain a good representation of soil conditions. The period of investigation covers the complete year 2012 of which we will particularly focus on selected periods.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41C1453G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41C1453G"><span>A multiyear study of soil moisture patterns across agricultural and forested landscapes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Georgakakos, C. B.; Hofmeister, K.; O'Connor, C.; Buchanan, B.; Walter, T.</p> <p>2017-12-01</p> <p>This work compares varying spatial and temporal soil moisture patterns in wet and dry years between forested and agricultural landscapes. This data set spans 6 years (2012-2017) of snow-free soil moisture measurements across multiple watersheds and land covers in New York State's Finger Lakes region. Due to the relatively long sampling period, we have captured fluctuations in soil moisture dynamics across wetter, dryer, and average precipitation years. We can therefore analyze response of land cover types to precipitation under varying climatic and hydrologic conditions. Across the study period, mean soil moisture in forest soils was significantly drier than in agricultural soils, and exhibited a smaller range of moisture conditions. In the drought year of 2016, soil moisture at all sites was significantly drier compared to the other years. When comparing the effects of land cover and year on soil moisture, we found that land cover had a more significant influence. Understanding the difference in landscape soil moisture dynamics between forested and agricultural land will help predict watershed responses to changing precipitation patterns in the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=332939','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=332939"><span>A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H43H1638S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H43H1638S"><span>Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Singh, G.; Panda, R. K.; Mohanty, B.</p> <p>2015-12-01</p> <p>Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51R..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51R..04B"><span>Empirical Soil Moisture Estimation with Spaceborne L-band Polarimetric Radars: Aquarius, SMAP, and PALSAR-2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Burgin, M. S.; van Zyl, J. J.</p> <p>2017-12-01</p> <p>Traditionally, substantial ancillary data is needed to parametrize complex electromagnetic models to estimate soil moisture from polarimetric radar data. The Soil Moisture Active Passive (SMAP) baseline radar soil moisture retrieval algorithm uses a data cube approach, where a cube of radar backscatter values is calculated using sophisticated models. In this work, we utilize the empirical approach by Kim and van Zyl (2009) which is an optional SMAP radar soil moisture retrieval algorithm; it expresses radar backscatter of a vegetated scene as a linear function of soil moisture, hence eliminating the need for ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine two coefficients of a linear model function on a global scale. These coefficients are used to estimate soil moisture with 2.5 months of L-band SMAP and L-band PALSAR-2 data. The estimated soil moisture is compared with the SMAP Level 2 radiometer-only soil moisture product; the global unbiased RMSE of the SMAP derived soil moisture corresponds to 0.06-0.07 cm3/cm3. In this study, we leverage the three diverse L-band radar data sets to investigate the impact of pixel size and pixel heterogeneity on soil moisture estimation performance. Pixel sizes range from 100 km for Aquarius, over 3, 9, 36 km for SMAP, to 10m for PALSAR-2. Furthermore, we observe seasonal variation in the radar sensitivity to soil moisture which allows the identification and quantification of seasonally changing vegetation. Utilizing this information, we further improve the estimation performance. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2017. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA17798.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA17798.html"><span>SMAP Radiometer Captures Views of Global Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-05-06</p> <p>These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.7936B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.7936B"><span>Investigating local controls on soil moisture temporal stability using an inverse modeling approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry</p> <p>2013-04-01</p> <p>A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B53E0237D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B53E0237D"><span>Barrier island community change: What controls it?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dows, B.; Young, D.; Zinnert, J.</p> <p>2014-12-01</p> <p>Conversion from grassland to woody dominated communities has been observed globally. In recent decades, this pattern has been observed in coastal communities along the mid-Atlantic U.S. In coastal environments, a suite of biotic and abiotic factors interact as filters to determine plant community structure and distribution. Microclimatic conditions: soil and air temperature, soil moisture and salinity, and light attenuation under grass cover were measured across a grassland-woody encroachment gradient on a Virginia barrier island; to identify the primary factors that mediate this change. Woody establishment was associated with moderately dense (2200 shoots/m2) grass cover, but reduced at high (> 6200 shoots/ m2) and low (< 1250 shoots/ m2) densities. Moderately dense grass cover reduced light attenuation (82.50 % reduction) to sufficiently reduce soil temperature thereby limiting soil moisture evaporation. However, high grass density reduced light attenuation (98.7 % reduction) enough to inhibit establishment of woody species; whereas low grass density attenuated much less light (48.7 % reduction) which allowed for greater soil moisture evaporation. Soil salinity was dynamic as rainfall, tidal inundation, and sea spray produce spatiotemporal variation throughout the barrier island landscape. The importance of light and temperature were compounded as they also indirectly affect soil salinity via their affects on soil moisture. Determining how these biotic and abiotic factors relate to sea level rise and climate change will improve understanding coastal community response as global changes proceed. Understanding how community shifts affect ecosystem function and their potential to affect adjacent systems will also improve predictive ability of coastal ecosystem responses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27760156','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27760156"><span>Moss Mediates the Influence of Shrub Species on Soil Properties and Processes in Alpine Tundra.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bueno, C Guillermo; Williamson, Scott N; Barrio, Isabel C; Helgadóttir, Ágústa; HiK, David S</p> <p>2016-01-01</p> <p>In tundra ecosystems, bryophytes influence soil processes directly and indirectly through interactions with overstory shrub species. We experimentally manipulated moss cover and measured seasonal soil properties and processes under two species of deciduous shrubs with contrasting canopy structures, Salix planifolia pulchra and Betula glandulosa-nana complex. Soil properties (seasonal temperature, moisture and C:N ratios) and processes (seasonal litter decomposition and soil respiration) were measured over twelve months. Shrub species identity had the largest influence on summer soil temperatures and soil respiration rates, which were higher under Salix canopies. Mosses were associated with lower soil moisture irrespective of shrub identity, but modulated the effects of shrubs on winter soil temperatures and soil C:N ratios so that moss cover reduced differences in soil winter temperatures between shrub species and reduced C:N ratios under Betula but not under Salix canopies. Our results suggest a central role of mosses in mediating soil properties and processes, with their influence depending on shrub species identity. Such species-dependent effects need to be accounted for when forecasting vegetation dynamics under ongoing environmental changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5070840','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5070840"><span>Moss Mediates the Influence of Shrub Species on Soil Properties and Processes in Alpine Tundra</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Williamson, Scott N.; Barrio, Isabel C.; Helgadóttir, Ágústa; HiK, David S.</p> <p>2016-01-01</p> <p>In tundra ecosystems, bryophytes influence soil processes directly and indirectly through interactions with overstory shrub species. We experimentally manipulated moss cover and measured seasonal soil properties and processes under two species of deciduous shrubs with contrasting canopy structures, Salix planifolia pulchra and Betula glandulosa-nana complex. Soil properties (seasonal temperature, moisture and C:N ratios) and processes (seasonal litter decomposition and soil respiration) were measured over twelve months. Shrub species identity had the largest influence on summer soil temperatures and soil respiration rates, which were higher under Salix canopies. Mosses were associated with lower soil moisture irrespective of shrub identity, but modulated the effects of shrubs on winter soil temperatures and soil C:N ratios so that moss cover reduced differences in soil winter temperatures between shrub species and reduced C:N ratios under Betula but not under Salix canopies. Our results suggest a central role of mosses in mediating soil properties and processes, with their influence depending on shrub species identity. Such species-dependent effects need to be accounted for when forecasting vegetation dynamics under ongoing environmental changes. PMID:27760156</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28247272','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28247272"><span>Biostimulation and rainfall infiltration: influence on retention of biodiesel in residual clayey soil.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Thomé, Antônio; Cecchin, Iziquiel; Reginatto, Cleomar; Colla, Luciane M; Reddy, Krishna R</p> <p>2017-04-01</p> <p>This study investigates the retention of biodiesel in residual clayey soil during biostimulation by nutrients (nitrogen, phosphorus, and potassium) under conditions of rainfall infiltration. Several column tests were conducted in a laboratory under different void ratios (1.14, 1.24, and 1.34), varying moisture contents (15, 25, and 35%), and in both the presence and absence of biostimulation. The volume of biodiesel (which was equivalent to the volume of voids in the soil) was placed atop the soil and allowed to percolate for a period of 15 days. The soil was subjected to different rainfall infiltration conditions (0.30 or 60 mm). The greatest reductions in residual contaminants occurred after 60 mm of rain simulation, at values of up to 74% less than in samples with the same conditions but no precipitation. However, the residual contamination decay rate was greater with 0-30 mm (0.29 g/mm) of precipitation than with 30-60 mm (0.075 g/mm). Statistical assessment revealed that increased moisture and the presence of nutrients were the factors with the most powerful effect on contaminant retention in the soil. The residual contaminant level was 21 g/kg at a moisture content of 15% and no precipitation, decreasing to 12 g/kg at 35% moisture and no precipitation. Accordingly, it is possible to conclude that biostimulation and rainfall infiltration conditions can decrease the retention of contaminants in soil and allow a greater leaching or spreading of the contamination. All of these phenomena are worthy of careful examination for the in situ bioremediation of organic contamination. • The higher moisture in the soil, due to a high initial moisture content and/or infiltration of rainfall, can reduce contaminant retention, • The use of biostimulation through the addition of nutrients to accelerate the biodegradation of toxic organic contaminants may induce inadvertent undesirable interactions between the soil and the contaminant. • When adopting biostimulation for bioremediation, the effects of rainfall should be addressed; ideally, it should be prevented from entering the affected site, in order to avoid increased contaminant leaching and potential spreading.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9762M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9762M"><span>Value of Available Global Soil Moisture Products for Agricultural Monitoring</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard</p> <p>2016-04-01</p> <p>The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS) versus C-/X-band (AMSR2) observations. The soil moisture products analyzed here were derived using the Land Parameter Retrieval Model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810020956','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810020956"><span>Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Arya, L. M.; Phinney, D. E. (Principal Investigator)</p> <p>1980-01-01</p> <p>Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050181940&hterms=soil+layers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil%2Blayers','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050181940&hterms=soil+layers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil%2Blayers"><span>Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank</p> <p>2005-01-01</p> <p>We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AeoRe..32...14J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AeoRe..32...14J"><span>Effects of soil moisture on dust emission from 2011 to 2015 observed over the Horqin Sandy Land area, China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ju, Tingting; Li, Xiaolan; Zhang, Hongsheng; Cai, Xuhui; Song, Yu</p> <p>2018-06-01</p> <p>Using the observational data of dust concentrations and meteorological parameters from 2011 to 2015, the effects of soil moisture and air humidity on dust emission were studied at long (monthly) and short (several days or hours) time scales over the Horqin Sandy Land area, Inner Mongolia of China. The results show that the monthly mean dust concentrations and dust fluxes within the near-surface layer had no obvious relationship with the monthly mean soil moisture content but had a slightly negative correlation with monthly mean air relative humidity from 2011 to 2015. The daily mean soil moisture exhibited a significantly negative correlation with the daily mean dust concentrations and dust fluxes, as soil moisture changed obviously. However, such negative correlation between soil moisture and dust emission disappeared on dust blowing days. Additionally, the effect of soil moisture on an important parameter for dust emission, the threshold friction velocity (u∗t), was investigated during several saltation-bombardment and/or aggregation-disintegration dust emission (SADE) events. Under dry soil conditions, the values of u∗t were not influenced by soil moisture content; however, when the soil moisture content was high, the values of u∗t increased with increasing soil moisture content.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PApGe.175.1187V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PApGe.175.1187V"><span>Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Varikoden, Hamza; Revadekar, J. V.</p> <p>2018-03-01</p> <p>Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186"><span>Hydrologic downscaling of soil moisture using global data without site-specific calibration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Numerous applications require fine-resolution (10-30 m) soil moisture patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9-60 km) soil moisture estimates. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales soil moistu...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1596S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1596S"><span>New Physical Algorithms for Downscaling SMAP Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.</p> <p>2017-12-01</p> <p>The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.4152W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.4152W"><span>Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip</p> <p>2017-05-01</p> <p>This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/wsp/1619u/report.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/wsp/1619u/report.pdf"><span>Methods of measuring soil moisture in the field</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Johnson, A.I.</p> <p>1962-01-01</p> <p>For centuries, the amount of moisture in the soil has been of interest in agriculture. The subject of soil moisture is also of great importance to the hydrologist, forester, and soils engineer. Much equipment and many methods have been developed to measure soil moisture under field conditions. This report discusses and evaluates the various methods for measurement of soil moisture and describes the equipment needed for each method. The advantages and disadvantages of each method are discussed and an extensive list of references is provided for those desiring to study the subject in more detail. The gravimetric method is concluded to be the most satisfactory method for most problems requiring onetime moisture-content data. The radioactive method is normally best for obtaining repeated measurements of soil moisture in place. It is concluded that all methods have some limitations and that the ideal method for measurement of soil moisture under field conditions has yet to be perfected.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912968W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912968W"><span>Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Mousong; Sholze, Marko</p> <p>2017-04-01</p> <p>We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H31G1467L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H31G1467L"><span>Soil Moisture under Different Vegetation cover in response to Precipitation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liang, Z.; Zhang, J.; Guo, B.; Ma, J.; Wu, Y.</p> <p>2016-12-01</p> <p>The response study of soil moisture to different precipitation and landcover is significant in the field of Hydropedology. The influence of precipitation to soil moisture is obvious in addition to individual stable aquifer. With data of Hillsborough County, Florida, USA, the alluvial wetland forest and ungrazed Bahia grass that under wet and dry periods were chosen as the research objects, respectively. HYDRUS-3D numerical simulation method was used to simulate soil moisture dynamics in the root zone (10-50 cm) of those vegetation. The soil moisture response to precipitation was analyzed. The results showed that the simulation results of alluvial wetland forest by HYDRUS-3D were better than that of the Bahia grass, and for the same vegetation, the simulation results of soil moisture under dry period were better. Precipitation was more in June, 2003, the soil moisture change of alluvial wetland forest in 10-30 cm soil layer and Bahia grass in 10 cm soil layer were consistent with the precipitation change conspicuously. The alluvial wetland forest soil moisture declined faster than Bahia grass under dry period, which demonstrated that Bahia grass had strong ability to hold water. Key words: alluvial wetland forest; Bahia grass; soil moisture; HYDRUS-3D; precipitation</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6462G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6462G"><span>Round Robin evaluation of soil moisture retrieval models for the MetOp-A ASCAT Instrument</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gruber, Alexander; Paloscia, Simonetta; Santi, Emanuele; Notarnicola, Claudia; Pasolli, Luca; Smolander, Tuomo; Pulliainen, Jouni; Mittelbach, Heidi; Dorigo, Wouter; Wagner, Wolfgang</p> <p>2014-05-01</p> <p>Global soil moisture observations are crucial to understand hydrologic processes, earth-atmosphere interactions and climate variability. ESA's Climate Change Initiative (CCI) project aims to create a global consistent long-term soil moisture data set based on the merging of the best available active and passive satellite-based microwave sensors and retrieval algorithms. Within the CCI, a Round Robin evaluation of existing retrieval algorithms for both active and passive instruments was carried out. In this study we present the comparison of five different retrieval algorithms covering three different modelling principles applied to active MetOp-A ASCAT L1 backscatter data. These models include statistical models (Bayesian Regression and Support Vector Regression, provided by the Institute for Applied Remote Sensing, Eurac Research Viale Druso, Italy, and an Artificial Neural Network, provided by the Institute of Applied Physics, CNR-IFAC, Italy), a semi-empirical model (provided by the Finnish Meteorological Institute), and a change detection model (provided by the Vienna University of Technology). The algorithms were applied on L1 backscatter data within the period of 2007-2011, resampled to a 12.5 km grid. The evaluation was performed over 75 globally distributed, quality controlled in situ stations drawn from the International Soil Moisture Network (ISMN) using surface soil moisture data from the Global Land Data Assimilation System (GLDAS-) Noah land surface model as second independent reference. The temporal correlation between the data sets was analyzed and random errors of the the different algorithms were estimated using the triple collocation method. Absolute soil moisture values as well as soil moisture anomalies were considered including both long-term anomalies from the mean seasonal cycle and short-term anomalies from a five weeks moving average window. Results show a very high agreement between all five algorithms for most stations. A slight vegetation dependency of the errors and a spatial decorrelation of the performance patterns of the different algorithms was found. We conclude that future research should focus on understanding, combining and exploiting the advantages of all available modelling approaches rather than trying to optimize one approach to fit every possible condition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330382','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330382"><span>Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..559..684D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..559..684D"><span>Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris</p> <p>2018-04-01</p> <p>As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN43B0078S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN43B0078S"><span>Drive by Soil Moisture Measurement: A Citizen Science Project</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.</p> <p>2017-12-01</p> <p>Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H51A1175S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H51A1175S"><span>Modeling vegetation rooting strategies on a hillslope</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sivandran, G.; Bras, R. L.</p> <p>2011-12-01</p> <p>The manner in which water and energy is partitioned and redistributed along a hillslope is the result of complex coupled ecohydrological interactions between the climatic, soils, topography and vegetation operating over a wide range of spatiotemporal scales. Distributed process based modeling creates a framework through which the interaction of vegetation with the subtle differences in the spatial and temporal dynamics of soil moisture that arise under localized abiotic conditions along a hillslope can be simulated and examined. One deficiency in the current dynamic vegetation models is the one sided manner in which vegetation responds to soil moisture dynamics. Above ground, vegetation is given the freedom to dynamically evolve through alterations in fractional vegetation cover and/or canopy height and density; however below ground rooting profiles are simplistically represented and often held constant in time and space. The need to better represent the belowground role of vegetation through dynamic rooting strategies is fundamental in capturing the magnitude and timing of water and energy fluxes between the atmosphere and land surface. In order to allow vegetation to adapt to gradients in soil moisture a dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically based distributed ecohydrological model). The dynamic rooting scheme allows vegetation the freedom to adapt their rooting depth and distribution in response abiotic conditions in a way that more closely mimics observed plant behavior. The incorporation of this belowground plasticity results in vegetation employing a suite of rooting strategies based on soil texture, climatic conditions and location on the hillslope.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H51H1601B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H51H1601B"><span>Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.</p> <p>2016-12-01</p> <p>The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5827620','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5827620"><span>Leaf endophytic fungus interacts with precipitation to alter belowground microbial communities in primary successional dunes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bell-Dereske, Lukas; Takacs-Vesbach, Cristina; Kivlin, Stephanie N.; Emery, Sarah M.; Rudgers, Jennifer A.</p> <p>2017-01-01</p> <p>Abstract Understanding interactions between above- and belowground components of ecosystems is an important next step in community ecology. These interactions may be fundamental to predicting ecological responses to global change because indirect effects occurring through altered species interactions can outweigh or interact with the direct effects of environmental drivers. In a multiyear field experiment (2010–2015), we tested how experimental addition of a mutualistic leaf endophyte (Epichloë amarillans) associated with American beachgrass (Ammophila breviligulata) interacted with an altered precipitation regime (±30%) to affect the belowground microbial community. Epichloë addition increased host root biomass at the plot scale, but reduced the length of extraradical arbuscular mycorrhizal (AM) fungal hyphae in the soil. Under ambient precipitation alone, the addition of Epichloë increased root biomass per aboveground tiller and reduced the diversity of AM fungi in A. breviligulata roots. Furthermore, with Epichloë added, the diversity of root-associated bacteria declined with higher soil moisture, whereas in its absence, bacterial diversity increased with higher soil moisture. Thus, the aboveground fungal mutualist not only altered the abundance and composition of belowground microbial communities but also affected how belowground communities responded to climate, suggesting that aboveground microbes have potential for cascading influences on community dynamics and ecosystem processes that occur belowground. PMID:28334408</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AdAtS..22..936Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AdAtS..22..936Z"><span>Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin</p> <p>2005-11-01</p> <p>The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840011893','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840011893"><span>Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.</p> <p>1982-01-01</p> <p>The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18..845M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18..845M"><span>Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen</p> <p>2016-04-01</p> <p>Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H54D..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H54D..04D"><span>Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.</p> <p>2015-12-01</p> <p>Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H13B1104B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H13B1104B"><span>Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.</p> <p>2014-12-01</p> <p>The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41D1464Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41D1464Y"><span>Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.</p> <p>2017-12-01</p> <p>In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038138&hterms=modeling+hydrological+basins&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dmodeling%2Bhydrological%2Bbasins','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038138&hterms=modeling+hydrological+basins&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dmodeling%2Bhydrological%2Bbasins"><span>Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.</p> <p>1997-01-01</p> <p>A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H21C1073E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H21C1073E"><span>Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Engda, T. A.; Kelleners, T. J.; Paige, G. B.</p> <p>2013-12-01</p> <p>Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H43F1514P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H43F1514P"><span>Application of time-lapse ERT to characterize soil-water-disease interactions of young citrus trees</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peddinti, S. R.; Kbvn, D. P.; Ranjan, S.; R M, P. G.</p> <p>2016-12-01</p> <p>Vidarbha region in Maharashtra, India is witnessing a continuous decrease in orange crop due to the propagation of `Phytopthora root rot', a water mold disease. Under favorable conditions, the disease causing bacteria can attack the plant root system and propagates to the surface (where first visual impression is made), making difficult to regain the plant health. This research aims at co-relating eco-hydrological fluxes with disease sensing parameters of orange trees. Two experimental plots around a healthy-young and declined-young orange trees were selected for our analysis. A 3-dimentional electrical resistivity tomography (ERT) (Figure) was carried at each plot to quantify the soil moisture distribution at a vadose zone. Pedo-electric relations were obtained considering modified Archie's law parameters. ERT derived moisture data was validated with time domain reflectometry (TDR) point observations. Soil moisture profiles derived from ERT were observed to be differ marginally between the two plots. Disease quantification was done by estimating the density of Phytopthora spp. inoculum in soils sampled along the root zone. Identification of Phytopthora spp. was done in the laboratory using taxonomic and morphologic criteria of the colonies. Spatio-temporal profiles of soil moisture and inoculum density were then co-related to comment on the eco-hydrological fluxes contributing to the health propagation of root rot in orange tree for implementing effective water management practices.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080004233','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080004233"><span>Method for evaluating moisture tensions of soils using spectral data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Peterson, John B. (Inventor)</p> <p>1982-01-01</p> <p>A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H13K1738P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H13K1738P"><span>A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pradhan, N. R.</p> <p>2015-12-01</p> <p>Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JHyd..357..405G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JHyd..357..405G"><span>Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig</p> <p>2008-08-01</p> <p>SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70000240','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70000240"><span>Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig</p> <p>2008-01-01</p> <p>This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018MS%26E..325a2019G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018MS%26E..325a2019G"><span>Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gines, G. A.; Bea, J. G.; Palaoag, T. D.</p> <p>2018-03-01</p> <p>Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010027896','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010027896"><span>Soil Moisture Memory in Climate Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2000-01-01</p> <p>Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920052381&hterms=Hydrology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DHydrology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920052381&hterms=Hydrology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DHydrology"><span>MACHYDRO-90 - The microwave aircraft experiment for hydrology</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Engman, Edwin T.</p> <p>1991-01-01</p> <p>MACHYDRO-90 is a multisensor aircraft campaign (MAC) that was held in central Pennsylvania over an eleven day period in July 1990. The emphasis of the campaign was on the microwave measurements of soil moisture, although other aspects of hydrology and microwave-target interactions were also studied. A description is given of the experiment, its organization, and the meteorological conditions during the eleven days. Preliminary results are also presented from PBMR (Push-Broom Microwave Radiometer) and SAR (synthetic aperture radar) measurements of soil moisture. These results are portrayed in the context of the hydrology, which, during this experiment, exhibited dry and wet extremes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/28625','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/28625"><span>Soil moisture and vegetation patterns in northern California forests</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>James R. Griffin</p> <p>1967-01-01</p> <p>Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000032232&hterms=pH+effects+soil&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DpH%2Beffects%2Bsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000032232&hterms=pH+effects+soil&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DpH%2Beffects%2Bsoil"><span>Effect of land-use practice on soil moisture variability for soils covered with dense forest vegetation of Puerto Rico</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.</p> <p>1998-01-01</p> <p>Little is known about the landuse management effect on soil moisture and soil pH distribution on a landscape covered with dense tropical forest vegetation. This study was conducted at three locations where the history of the landuse management is different. Soil moisture was measured using a 6-cm three-rod Time Domain Reflectometery (TDR) probe. Disturbed soil samples were taken from the top 5-cm at the up, mid, and foothill landscape position from the same spots where soil moisture was measured. The results showed that soil moisture varies with landscape position and depth at all three locations. Soil pH and moisture variability were found to be affected by the change in landuse management and landscape position. Soil moisture distribution usually expected to be relatively higher in the foothill (P3) area of these forests than the uphill (P1) position. However, our results indicated that in the Luquillo and Guanica site the surface soil moisture was significantly higher for P1 than P3 position. These suggest that the surface and subsurface drainage in these two sites may have been poor due to the nature of soil formation and type.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JAMES...7..335S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JAMES...7..335S"><span>Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sierra, Carlos A.; Trumbore, Susan E.; Davidson, Eric A.; Vicca, Sara; Janssens, I.</p> <p>2015-03-01</p> <p>The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUSM.B32A..11Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUSM.B32A..11Y"><span>Assimilation of Satellite-Derived Precipitation into the Regional Atmospheric Model System (RAMS): Its Impacts on the Weather and Hydrology in the Southwest United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yi, H.; Gao, X.; Sorooshian, S.</p> <p>2002-05-01</p> <p>As one aspect of the study of interactions between the atmosphere, vegetation, soil, and hydrology, there has been on going efforts to assimilate soil moisture data using coupled and uncoupled land surface-atmosphere hydrology models. The assimilation of soil moisture is expected to have influence due to its vital function in regulating runoff, partitioning latent and sensible heat, and through determining groundwater recharge. Soil moisture can provides long-term memory or persistence of the surface boundary condition, influencing large-scale atmospheric circulation over subsequent intervals. Now that the application of satellite remote sensing has become obvious to provide input parameters associated with land surface processes to the numerical models, this study utilizes remotely sensed precipitation data, PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) to assimilate soil moisture and other soil surface characteristics. Compared to the other earlier modeling experiments of seasonal or interannual temporal scale in continental or global spatial scale, this study investigates short term predictability in regional scale with the southwest United States as a study area, which has unique metrological and geographical features that provide special difficulties for mesoscale modeling. Research objectives are to assimilate the PERSIANN precipitation data into the mesoscale model for model initialization, examine the influence and memory of model precipitation errors on the land surface and atmospheric processes, and thereby study the short term predictability of meteorology and hydrology in the Southwest United States.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/19797','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/19797"><span>A comparison of soil-moisture loss from forested and clearcut areas in West Virginia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Charles A. Troendle</p> <p>1970-01-01</p> <p>Soil-moisture losses from forested and clearcut areas were compared on the Fernow Experimental Forest. As expected, hardwood forest soils lost most moisture while revegetated clearcuttings, clearcuttings, and barren areas lost less, in that order. Soil-moisture losses from forested soils also correlated well with evapotranspiration and streamflow.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..536..327M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..536..327M"><span>Examining diel patterns of soil and xylem moisture using electrical resistivity imaging</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mares, Rachel; Barnard, Holly R.; Mao, Deqiang; Revil, André; Singha, Kamini</p> <p>2016-05-01</p> <p>The feedbacks among forest transpiration, soil moisture, and subsurface flowpaths are poorly understood. We investigate how soil moisture is affected by daily transpiration using time-lapse electrical resistivity imaging (ERI) on a highly instrumented ponderosa pine and the surrounding soil throughout the growing season. By comparing sap flow measurements to the ERI data, we find that periods of high sap flow within the diel cycle are aligned with decreases in ground electrical conductivity and soil moisture due to drying of the soil during moisture uptake. As sap flow decreases during the night, the ground conductivity increases as the soil moisture is replenished. The mean and variance of the ground conductivity decreases into the summer dry season, indicating drier soil and smaller diel fluctuations in soil moisture as the summer progresses. Sap flow did not significantly decrease through the summer suggesting use of a water source deeper than 60 cm to maintain transpiration during times of shallow soil moisture depletion. ERI captured spatiotemporal variability of soil moisture on daily and seasonal timescales. ERI data on the tree showed a diel cycle of conductivity, interpreted as changes in water content due to transpiration, but changes in sap flow throughout the season could not be interpreted from ERI inversions alone due to daily temperature changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H34D..03C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H34D..03C"><span>Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crow, W. T.; Bolten, J. D.</p> <p>2014-12-01</p> <p>Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008055','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008055"><span>The Contribution of Soil Moisture Information to Forecast Skill: Two Studies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, Randal</p> <p>2010-01-01</p> <p>This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H13I1520H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H13I1520H"><span>Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.</p> <p>2017-12-01</p> <p>Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GPC...166...48Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GPC...166...48Z"><span>Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun</p> <p>2018-07-01</p> <p>Soil moisture plays crucial roles in the hydrological cycle and is also a critical link between land surface and atmosphere. The Pearl River basin (PRb) is climatically subtropical and tropical and is highly sensitive to climate changes. In this study, seasonal soil moisture changes across the PRb were analyzed using the Variable Infiltration Capacity (VIC) model forced by the gridded 0.5° × 0.5° climatic observations. Seasonal changes of soil moisture in both space and time were investigated using the Mann-Kendall trend test method. Potential influencing factors behind seasonal soil moisture changes such as precipitation and temperature were identified using the Maximum Covariance Analysis (MCA) technique. The results indicated that: (1) VIC model performs well in describing changing properties of soil moisture across the PRb; (2) Distinctly different seasonal features of soil moisture can be observed. Soil moisture in spring decreased from east to west parts of the PRb. In summer however, soil moisture was higher in east and west parts but was lower in central parts of the PRb; (3) A significant drying trend was identified over the PRb in autumn, while no significant drying trends can be detected in other seasons; (4) The increase/decrease in precipitation can generally explain the wetting/drying tendency of soil moisture. However, warming temperature contributed significantly to the drying trends and these drying trends were particularly evident during autumn and winter; (5) Significant decreasing precipitation and increasing temperature combined to trigger substantially decreasing soil moisture in autumn. In winter, warming temperature is the major reason behind decreased soil moisture although precipitation is in slightly decreasing tendency. Season variations of soil moisture and related implications for hydro-meteorological processes in the subtropical and tropical river basins over the globe should arouse considerable human concerns.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41A1427A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41A1427A"><span>Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.</p> <p>2017-12-01</p> <p>Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018WRR....54.1476A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018WRR....54.1476A"><span>Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara</p> <p>2018-03-01</p> <p>The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..559..327C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..559..327C"><span>Regional variation of flow duration curves in the eastern United States: Process-based analyses of the interaction between climate and landscape properties</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chouaib, Wafa; Caldwell, Peter V.; Alila, Younes</p> <p>2018-04-01</p> <p>This paper advances the physical understanding of the flow duration curve (FDC) regional variation. It provides a process-based analysis of the interaction between climate and landscape properties to explain disparities in FDC shapes. We used (i) long term measured flow and precipitation data over 73 catchments from the eastern US. (ii) We calibrated the Sacramento model (SAC-SMA) to simulate soil moisture and flow components FDCs. The catchments classification based on storm characteristics pointed to the effect of catchments landscape properties on the precipitation variability and consequently on the FDC shapes. The landscape properties effect was pronounce such that low value of the slope of FDC (SFDC)-hinting at limited flow variability-were present in regions of high precipitation variability. Whereas, in regions with low precipitation variability the SFDCs were of larger values. The topographic index distribution, at the catchment scale, indicated that saturation excess overland flow mitigated the flow variability under conditions of low elevations with large soil moisture storage capacity and high infiltration rates. The SFDCs increased due to the predominant subsurface stormflow in catchments at high elevations with limited soil moisture storage capacity and low infiltration rates. Our analyses also highlighted the major role of soil infiltration rates on the FDC despite the impact of the predominant runoff generation mechanism and catchment elevation. In conditions of slow infiltration rates in soils of large moisture storage capacity (at low elevations) and predominant saturation excess, the SFDCs were of larger values. On the other hand, the SFDCs decreased in catchments of prevalent subsurface stormflow and poorly drained soils of small soil moisture storage capacity. The analysis of the flow components FDCs demonstrated that the interflow contribution to the response was the higher in catchments with large value of slope of the FDC. The surface flow FDC was the most affected by the precipitation as it tracked the precipitation duration curve (PDC). In catchments with low SFDCs, this became less applicable as surface flow FDC diverged from PDC at the upper tail (> 40% of the flow percentile). The interflow and baseflow FDCs illustrated most the filtering effect on the precipitation. The process understanding we achieved in this study is key for flow simulation and assessment in addition to future works focusing on process-based FDC predictions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16345610','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16345610"><span>Variation in microbial activity in histosols and its relationship to soil moisture.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tate, R L; Terry, R E</p> <p>1980-08-01</p> <p>Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=291573','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=291573"><span>Variation in Microbial Activity in Histosols and Its Relationship to Soil Moisture †</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tate, Robert L.; Terry, Richard E.</p> <p>1980-01-01</p> <p>Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in soil cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped soil, whereas biomass ranged from equivalence in the two soils to a threefold stimulation in the cropped soil. Biomass in soil cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane soil were nearly equivalent to those of the fallow soil. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with soil moisture levels. These data indicate that within the moisture ranges detected in the surface soils, increased moisture stimulated microbial activity, whereas within the soil profile where moisture ranges reached saturation, increased moisture inhibited aerobic activities and stimulated anaerobic processes. PMID:16345610</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.cpc.ncep.noaa.gov/products/Drought','SCIGOVWS'); return false;" href="http://www.cpc.ncep.noaa.gov/products/Drought"><span>Climate Prediction Center - United States Drought Information</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p> Crop Moisture Indices  <em>Soil</em> Moisture Percentiles (based on NLDAS)  Standardized Runoff Index (based /Minimum  Mean Surface Hydrology (based on NLDAS)  Total <em>Soil</em> Moisture  Total SM Change  MOSAIC <em>Soil</em> Moisture Profile  NOAH <em>Soil</em> Moisture Profile  NOAH <em>Soil</em> T Profile  Evaporation  E-P Â</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930036630&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930036630&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation"><span>An overview of the measurements of soil moisture and modeling of moisture flux in FIFE</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, J. R.</p> <p>1992-01-01</p> <p>Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70169003','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70169003"><span>Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tucker, Colin; Reed, Sasha C.</p> <p>2016-01-01</p> <p>Arid and semiarid ecosystems (drylands) may dominate the trajectory of biosphere-to-atmosphere carbon (C) flux over the coming century. Accordingly, understanding dryland CO2 efflux controls is important for understanding C cycling at the global-scale: key unknowns regarding how temperature and moisture interact to regulate dryland C cycling remain. Further, the patchiness of dryland vegetation can create ‘islands of fertility’, with spatially heterogeneous rates of soil respiration (Rs). At our study site in southeastern Utah, USA we added or removed litter (0 to 650% of control) in paired plots that were either associated with a shrub or with interspaces between vascular plants. We measured Rs, soil temperature, and water content (θ) on eight sampling dates between October 2013 and November 2014. Rs was highest following monsoon rains in late summer when soil temperature was ~30°C. During mid-summer, Rs was low, associated with high soil temperatures (>40°C), resulting in an apparent negative temperature sensitivity of Rs at high temperatures, and positive temperature sensitivity at low-moderate temperatures. We used Bayesian statistical methods to compare multiple competing models capturing a wide range of hypothesized relationships between temperature, moisture, and Rs. The best fit model indicates apparent negative temperature sensitivity of soil respiration at high temperatures reflects the control of soil moisture – not high temperatures – in limiting Rs. The modeled Q10 ranged from 2.7 at 5°C to 1.4 at 45°C. Litter addition had no effect on temperature sensitivity or reference respiration (Rref = Rs at 20°C and optimum moisture) beneath shrubs, and little effect on Rref in interspaces, yet Rref was 1.5 times higher beneath shrubs than in interspaces. Together, these results suggest reduced Rs often observed at high temperatures in drylands is dominated by the control of moisture, and that variable litter inputs – at least over the short-term – exert minimal control over Rs.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=320683','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=320683"><span>The effect of western corn rootworm (Coleoptera: Chrysomelidae) and water deficit on maize performance under controlled conditions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>A series of greenhouse experiments using three infestation levels of the western corn rootworm, Diabrotica virgifera virgifera LeConte, under well-watered, moderately dry, and very dry soil moisture levels were conducted to quantify the interaction of western corn rootworm and soil water deficit on ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20809408','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20809408"><span>Inter- and under-canopy soil water, leaf-level and whole-plant gas exchange dynamics of a semi-arid perennial C4 grass.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hamerlynck, Erik P; Scott, Russell L; Susan Moran, M; Schwander, Andrea M; Connor, Erin; Huxman, Travis E</p> <p>2011-01-01</p> <p>It is not clear if tree canopies in savanna ecosystems exert positive or negative effects on soil moisture, and how these might affect understory plant carbon balance. To address this, we quantified rooting-zone volumetric soil moisture (θ(25 cm)), plant size, leaf-level and whole-plant gas exchange of the bunchgrass, bush muhly (Muhlenbergia porteri), growing under and between mesquite (Prosopis velutina) in a southwestern US savanna. Across two contrasting monsoon seasons, bare soil θ(25 cm) was 1.0-2.5% lower in understory than in the intercanopy, and was consistently higher than in soils under grasses, where θ(25 cm) was similar between locations. Understory plants had smaller canopy areas and volumes with larger basal diameters than intercanopy plants. During an above-average monsoon, intercanopy and understory plants had similar seasonal light-saturated leaf-level photosynthesis (A(net-sat)), stomatal conductance (g(s-sat)), and whole-plant aboveground respiration (R(auto)), but with higher whole-plant photosynthesis (GEP(plant)) and transpiration (T(plant)) in intercanopy plants. During a below-average monsoon, intercanopy plants had higher diurnally integrated GEP(plant), R(auto), and T(plant). These findings showed little evidence of strong, direct positive canopy effects to soil moisture and attendant plant performance. Rather, it seems understory conditions foster competitive dominance by drought-tolerant species, and that positive and negative canopy effects on soil moisture and community and ecosystem processes depends on a suite of interacting biotic and abiotic factors.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..45..187W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..45..187W"><span>Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin</p> <p>2016-03-01</p> <p>High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN). The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 soil moisture products for different ecoregions. Although AMSR2 soil moisture retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC21H1187C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC21H1187C"><span>Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.</p> <p>2016-12-01</p> <p>Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau Yaokui Cui, Di Long, Yang Hong, Chao Zeng, and Zhongying Han State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China Abstract: Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the world's third pole. Large-scale consistent and continuous soil moisture datasets are of importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is one of relatively new passive microwave products. The FY-3B/MWRI soil moisture product is reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo using different gap-filling methods. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and the NDVI, LST, and albedo, but also the relationship between the soil moisture and the four-dimensional variation using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 larger than 0.63, and RMSE less than 0.1 cm3 cm-3 and bias less than 0.07 cm3 cm-3 for both frozen and unfrozen periods, compared with in-situ measurements in the central TP. The reconstruction method is subsequently applied to generate spatially consistent and temporally continuous surface soil moisture over the TP. The reconstructed FY-3B/MWRI soil moisture product could be valuable in studying meteorology, hydrology, and agriculture over the TP. Keywords: FY-3B/MWRI; Soil moisture; Reconstruction; Tibetan Plateau</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331905','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331905"><span>Downscaled soil moisture from SMAP evaluated using high density observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347544','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347544"><span>Data assimilation to extract soil moisture information from SMAP observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.8006E..1FX','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.8006E..1FX"><span>Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang</p> <p>2011-12-01</p> <p>Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009280','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009280"><span>NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-Comparing Soil Moisture Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih</p> <p>2012-01-01</p> <p>There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data (e.g., precipitation). An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. The latter relationships are particularly important for applications users, for whom the continuity of soil moisture data, from whatever source, is critical. A recent example was provided by the sudden demise of EOS Aqua AMSR-E and the end of its soil moisture data production, as well as the end of other soil moisture products that had used the AMSR-E brightness temperature data. The purpose of the current effort is to create an environment, as part of the NASA Giovanni family of portals, that facilitates inter-comparisons of soil moisture algorithms and their derived data products.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780009499','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780009499"><span>Microwave remote sensing and its application to soil moisture detection</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Newton, R. W. (Principal Investigator)</p> <p>1977-01-01</p> <p>The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B51B0392H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B51B0392H"><span>Prediction of Gross Primary Production during the Drought and Normal Years over the US Using Solar-Induced Chlorophyll Fluorescence</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Halubok, M.; Yang, Z. L.</p> <p>2016-12-01</p> <p>This study investigates how gross primary production (GPP) estimates can be improved with the use of solar-induced chlorophyll fluorescence (SIF) and presents an effort to produce GPP predictions based on the interdependence between SIF, precipitation, soil moisture and GPP using Global Ozone Monitoring Experiment-2 (GOME-2), Tropical Rainfall Measuring Mission (TRMM), European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) datasets and FLUXNET observations. We found that considering the relationships between SIF, precipitation and soil moisture, isolating SIF-GPP relationships for different plant functional types (PFTs), and using precipitation and soil moisture conditions pertinent to the continental US provides the most accurate GPP estimates over the Great Plains and Texas. We found that there exists a lag between a precipitation event and corresponding fluorescence levels, ranging from about 2 weeks for grasses to a month for crops. Using these lead-lag relationships, we estimate GPP using SIF, precipitation and soil moisture data for two different PFTs (C3 non-arctic grass and crop) over the US applying the multiple linear regression technique. GPP values estimated from our lead-lag based SIF show the closest possible match with the observational data from the FLUXNET stations. During the drought 2011 year over Texas, our GPP values show a decrease by 100 gC/m2/month as compared to the reference year of 2007. In 2012 (drought year over the Great Plains), we observe significant decrease in GPP, especially in the area of high production (>500 gC/m2/month) that is reduced in July and August 2012. Hence, estimating GPP using specific SIF-GPP relationships, considering the differences in biomes and their interactions with precipitation and soil moisture pertinent to a certain region can detect the drought trends and produce reasonable GPP estimates. Thus, this simple and computationally efficient method based on derived linear equations can be used to obtain GPP predictions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050192452','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050192452"><span>Estimating Surface Soil Moisture in Simulated AVIRIS Spectra</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Whiting, Michael L.; Li, Lin; Ustin, Susan L.</p> <p>2004-01-01</p> <p>Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B"><span>Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.</p> <p>2005-12-01</p> <p>The Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the AMSR-E provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated AMSR-E channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the AMSR-E soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of AMSR-E derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European Centre for Medium-Range Weather Forecasts. The results of this research will contribute to a better characterization of the low biases and discrepancies currently observed in the AMSR-E soil moisture product.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830025012','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830025012"><span>Data documentation for the bare soil experiment at the University of Arkansas</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Waite, W. P.; Scott, H. D. (Principal Investigator); Hancock, G. D.</p> <p>1980-01-01</p> <p>The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/33766','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/33766"><span>Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>James Reardon; Gary Curcio; Roberta Bartlette</p> <p>2009-01-01</p> <p>Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=288987','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=288987"><span>The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812705V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812705V"><span>Biophysical interactions between plant and soil: theory and practice</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>van der Ploeg, Martine</p> <p>2016-04-01</p> <p>Vegetation plays an essential role in the hydrological cycle, as it regulates the water flux to the atmosphere through evapotranspiration, while it is dependent on adequate water supply. Vegetation shapes the land surface by changing infiltration characteristics as a result of root growth, and controls soil moisture storage, which in turn affect runoff characteristics and groundwater recharge. Vegetation and the underlying geology are in constant interaction, wherein water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. Models are a useful tool to explore interaction and feedbacks between vegetation, soil and landscape. Plants respond biochemically to their environment, while the models used for hydrology are often based on physical interactions. Gene-expression and genotype adaptation may complicate our modelling efforts in for example climate change impacts. Combination of new techniques to assess soil and plant properties facilitates assessment of biophysical interactions. This poster will review these techniques and compare the obtained insights of soil-plant relationships with the current modeling approaches.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018WRR....54.2199D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018WRR....54.2199D"><span>Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, Jingnuo; Ochsner, Tyson E.</p> <p>2018-03-01</p> <p>Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2802917','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2802917"><span>Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto</p> <p>2007-01-01</p> <p>Background and Aims It has been hypothesized that soil moisture conditions could affect the dormancy status of buried weed seeds, and, consequently, their sensitivity to light stimuli. In this study, an investigation is made of the effect of different soil moisture conditions during cold-induced dormancy loss on changes in the sensitivity of Polygonum aviculare seeds to light. Methods Seeds buried in pots were stored under different constant and fluctuating soil moisture environments at dormancy-releasing temperatures. Seeds were exhumed at regular intervals during storage and were exposed to different light treatments. Changes in the germination response of seeds to light treatments during storage under the different moisture environments were compared in order to determine the effect of soil moisture on the sensitivity to light of P. aviculare seeds. Key Results Seed acquisition of low-fluence responses during dormancy release was not affected by either soil moisture fluctuations or different constant soil moisture contents. On the contrary, different soil moisture environments affected seed acquisition of very low fluence responses and the capacity of seeds to germinate in the dark. Conclusions The results indicate that under field conditions, the sensitivity to light of buried weed seeds could be affected by the soil moisture environment experienced during the dormancy release season, and this could affect their emergence pattern. PMID:17430979</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013012','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013012"><span>Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.</p> <p>2013-01-01</p> <p>Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820018884','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820018884"><span>Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)</p> <p>1982-01-01</p> <p>Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19223120','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19223120"><span>Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Luster-Teasley, S; Ubaka-Blackmoore, N; Masten, S J</p> <p>2009-08-15</p> <p>In this study, pyrene spiked soil (300 ppm) was ozonated at pH levels of 2, 6, and 8 and three moisture contents. It was found that soil pH and moisture content impacted the effectiveness of PAH oxidation in unsaturated soils. In air-dried soils, as pH increased, removal increased, such that pyrene removal efficiencies at pH 6 and pH 8 reached 95-97% at a dose of 2.22 mg O(3)/mg pyrene. Ozonation at 16.2+/-0.45 mg O(3)/ppm pyrene in soil resulted in 81-98% removal of pyrene at all pH levels tested. Saturated soils were tested at dry, 5% or 10% moisture conditions. The removal of pyrene was slower in moisturized soils, with the efficiency decreasing as the moisture content increased. Increasing the pH of the soil having a moisture content of 5% resulted in improved pyrene removals. On the contrary, in the soil having a moisture content of 10%, as the pH increased, pyrene removal decreased. Contaminated PAH soils were stored for 6 months to compare the efficiency of PAH removal in freshly contaminated soil and aged soils. PAH adsorption to soil was found to increase with longer exposure times; thus requiring much higher doses of ozone to effectively oxidize pyrene.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4607364','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4607364"><span>Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie</p> <p>2015-01-01</p> <p>Robust models for predicting soil salinity that use visible and near-infrared (vis–NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis–NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future. PMID:26468645</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..48..146M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..48..146M"><span>Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.</p> <p>2016-06-01</p> <p>Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53D0922C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53D0922C"><span>Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cao, W.; Sheng, Y.</p> <p>2017-12-01</p> <p>The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005PhDT.......214B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005PhDT.......214B"><span>Soil moisture observations using L-, C-, and X-band microwave radiometers</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bolten, John Dennis</p> <p></p> <p>The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70033698','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70033698"><span>Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Waldrop, M.P.; Harden, J.W.</p> <p>2008-01-01</p> <p>Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or community structure induced by fire might also affect these processes. We particularly wanted to understand whether postfire reductions in microbial biomass could affect rates of decomposition. Additionally, we compared the short-term effects of wildfire to the long-term effects of climate warming and permafrost decline. We compared soil microbial communities between control and recently burned soils that were located in areas with and without permafrost near Delta Junction, AK. In addition to soil physical variables, we quantified changes in microbial biomass, fungal biomass, fungal community composition, and C cycling processes (phenol oxidase enzyme activity, lignin decomposition, and microbial respiration). Five years following fire, organic surface horizons had lower microbial biomass, fungal biomass, and dissolved organic carbon (DOC) concentrations compared with control soils. Reductions in soil fungi were associated with reductions in phenol oxidase activity and lignin decomposition. Effects of wildfire on microbial biomass and activity in the mineral soil were minor. Microbial community composition was affected by wildfire, but the effect was greater in nonpermafrost soils. Although the presence of permafrost increased soil moisture contents, effects on microbial biomass and activity were limited to mineral soils that showed lower fungal biomass but higher activity compared with soils without permafrost. Fungal abundance and moisture were strong predictors of phenol oxidase enzyme activity in soil. Phenol oxidase enzyme activity, in turn, was linearly related to both 13C lignin decomposition and microbial respiration in incubation studies. Taken together, these results indicate that reductions in fungal biomass in postfire soils and lower soil moisture in nonpermafrost soils reduced the potential of soil heterotrophs to decompose soil carbon. Although in the field increased rates of microbial respiration can be observed in postfire soils due to warmer soil conditions, reductions in fungal biomass and activity may limit rates of decomposition. ?? 2008 The Authors Journal compilation ?? 2008 Blackwell Publishing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H34C..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H34C..08M"><span>Antecedent moisture content and soil texture effects on infiltration and erosion</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mamedov, A. I.; Huang, C.; Levy, G. J.</p> <p>2006-12-01</p> <p>Water infiltration, seal formation, runoff and erosion depend on the soil's inherent properties and surface conditions. Most erosion models consider only soil inherent properties (mainly texture) in assessing infiltration and erosion without consideration of spatial and temporary variation in the surface condition, particularly the antecedent moisture content. We studied the interaction of two different surface conditions, i.e. antecedent moisture content (AMC) and aging (timing after wetting) on infiltration (IR), seal formation (runoff generation) and erosion in four soils varying from loam to clay. Soil samples were packed in erosion box and wetted with different amounts of water (0, 1, 2, 3, 4, 6, 8, or 16 mm) to obtain a wide moisture range (i.e., pF 0-6.2, or from air dry to full saturation). The boxes were put in plastic bags and allowed to age for 0.01, 1, 3, or 7 days. Then the soil in the erosion box exposed to 60 mm of rain. At no aging final IR of soils did not change significantly, but runoff volume (a measure for seal development) and soil loss increased with an increase in AMC mainly because of aggregate breakdown. For any given aging, the highest IR and smallest runoff volume and soil loss were obtained at the intermediate AMC levels (pF 2.4-4.2, between wilting point and field capacity). For instance, in the clay soil to which 3 mm of water (pF~2.7) was added, as aging increased from one to seven days, final IR increased from 5.3 to 7.9 mm h-1, while runoff and soil loss decreased from 34 mm to 22 mm, and from 630 to 360 g m2 respectively. At this AMC range, increasing aging time resulted in up to 40% increase in IR and decrease in runoff or soil loss. This tendency significantly more pronounced for clay soils because water-filled pores in the clay fabric were considered active in the stabilization process and the development of cohesive bonds between and within particles during the aging period. The results of this study are important for soil erosion modeling. In order to improve the prediction capabilities of erosion models, temporal and spatial variation of soil moisture content (AMC, wetting and aging) prior to erosive rainstorms should be considered and or incorporated. In addition, management practices could be adapted to diminish the severe soil moisture variation, where ever possible, (minimum till or no-till with known residue) to maintain the soil surface at a desired AMC level prior to expected rainstorms in order to decrease soil susceptibility to seal formation, runoff and soil loss.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3.1739W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3.1739W"><span>Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.</p> <p>2018-04-01</p> <p>Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51H1487M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51H1487M"><span>Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mishra, V.; Cruise, J. F.; Mecikalski, J. R.</p> <p>2015-12-01</p> <p>Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..552..620M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..552..620M"><span>Drought monitoring with soil moisture active passive (SMAP) measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara</p> <p>2017-09-01</p> <p>Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.emc.ncep.noaa.gov/NEMS/launcher.php','SCIGOVWS'); return false;" href="http://www.emc.ncep.noaa.gov/NEMS/launcher.php"><span>National Centers for Environmental Prediction</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>) soilm1 0-10cm <em>soil</em> moisture soilm2 10-40cm <em>soil</em> moisture soilm3 40-100cm <em>soil</em> moisture soilm4 100-200cm <em>soil</em> moisture soilt1 0-10cm <em>soil</em> temperature soilt2 10-40cm <em>soil</em> temperature soilt3 40-100cm <em>soil</em> temperature soilt4 100-200cm <em>soil</em> temperature thick700.ptype 850-700mb thickness precipitation type thick850</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..546..393B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..546..393B"><span>Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.</p> <p>2017-03-01</p> <p>Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.2967L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.2967L"><span>Toward improving the representation of the water cycle at High Northern Latitudes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke</p> <p>2016-04-01</p> <p>The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1602X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1602X"><span>Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Y.; Wang, L.</p> <p>2017-12-01</p> <p>Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H13I1516C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H13I1516C"><span>SMERGE: A multi-decadal root-zone soil moisture product for CONUS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.</p> <p>2017-12-01</p> <p>Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B34C..06G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B34C..06G"><span>Global response of the growing season to soil moisture and topography</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.</p> <p>2017-12-01</p> <p>Soil moisture has a direct influence in plant productivity. Plant productivity and its greenness can be inferred by remote sensing with higher spatial detail than soil moisture. The objective was to improve the coarse scale of currently available satellite soil moisture estimates and identify areas of strong coupling between the interannual variability soil moisture and the maximum greenness vegetation fraction (MGVF) at the global scale. We modeled, cross-validated and downscaled remotely sensed soil moisture using machine learning and digital terrain analysis across 23 years (1991-2013) of available data. Improving the accuracy (0.69-0.87 % of cross-validated explained variance) and the spatial detail (from 27 to 15km) of satellite soil moisture, we filled temporal gaps of information across vegetated areas where satellite soil moisture does not work properly. We found that 7.57% of global vegetated area shows strong correlation with our downscaled product (R2>0.5, Fig. 1). We found a dominant positive response of vegetation greenness to topography-based soil moisture across water limited environments, however, the tropics and temperate environments of higher latitudes showed a sparse negative response. We conclude that topography can be used to effectively improve the spatial detail of globally available remotely sensed soil moisture, which is convenient to generate unbiased comparisons with global vegetation dynamics, and better inform land and crop modeling efforts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1989JCli....2.1362O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1989JCli....2.1362O"><span>Soil Moisture and the Persistence of North American Drought.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oglesby, Robert J.; Erickson, David J., III</p> <p>1989-11-01</p> <p>We describe numerical sensitivity experiments exploring the effects of soil moisture on North American summertime climate using the NCAR CCMI, a 12-layer global atmospheric general circulation model. In particular. the hypothesis that reduced soil moisture may help induce and amplify warm, dry summers over midlatitude continental interiors is examined. Equilibrium climate statistics are computed for the perpetual July model response to imposed soil moisture anomalies over North America between 36° and 49°N. In addition, the persistence of imposed soil moisture anomalies is examined through use of the seasonal cycle mode of operation with use of various initial atmospheric states both equilibrated and nonequilibrated to the initial soil moisture anomaly.The climate statistics generated by thew model simulations resemble in a general way those of the summer of 1988, when extensive heat and drought occurred over much of North America. A reduction in soil moisture in the model leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. Low-level moisture advection from the Gulf of Mexico is important in determining where persistent soil moisture deficits can be maintained. In seasonal cycle simulations, it lock longer for an initially unequilibrated atmosphere to respond to the imposed soil moisture anomaly, via moisture transport from the Gulf of Mexico, than when initially the atmosphere was in equilibrium with the imposed anomaly., i.e., the initial state was obtained from the appropriate perpetual July simulation. The results demonstrate the important role of soil moisture in prolonging and/or amplifying North American summertime drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70035945','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70035945"><span>Interactive effects of fire, soil climate, and moss on CO2 fluxes in black spruce ecosystems of interior Alaska</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>O'Donnell, J. A.; Turetsky, M.R.; Harden, J.W.; Manies, K.L.; Pruett, L.E.; Shetler, G.; Neff, J.C.</p> <p>2009-01-01</p> <p>Fire is an important control on the carbon (C) balance of the boreal forest region. Here, we present findings from two complementary studies that examine how fire modifies soil organic matter properties, and how these modifications influence rates of decomposition and C exchange in black spruce (Picea mariana) ecosystems of interior Alaska. First, we used laboratory incubations to explore soil temperature, moisture, and vegetation effects on CO2 and DOC production rates in burned and unburned soils from three study regions in interior Alaska. Second, at one of the study regions used in the incubation experiments, we conducted intensive field measurements of net ecosystem exchange (NEE) and ecosystem respiration (ER) across an unreplicated factorial design of burning (2 year post-fire versus unburned sites) and drainage class (upland forest versus peatland sites). Our laboratory study showed that burning reduced the sensitivity of decomposition to increased temperature, most likely by inducing moisture or substrate quality limitations on decomposition rates. Burning also reduced the decomposability of Sphagnum-derived organic matter, increased the hydrophobicity of feather moss-derived organic matter, and increased the ratio of dissolved organic carbon (DOC) to total dissolved nitrogen (TDN) in both the upland and peatland sites. At the ecosystem scale, our field measurements indicate that the surface organic soil was generally wetter in burned than in unburned sites, whereas soil temperature was not different between the burned and unburned sites. Analysis of variance results showed that ER varied with soil drainage class but not by burn status, averaging 0.9 ?? 0.1 and 1.4 ?? 0.1 g C m-2d-1 in the upland and peatland sites, respectively. However, a more complex general linear model showed that ER was controlled by an interaction between soil temperature, moisture, and burn status, and in general was less variable over time in the burned than in the unburned sites. Together, findings from these studies across different spatial scales suggest that although fire can create some soil climate conditions more conducive to rapid decomposition, rates of C release from soils may be constrained following fire by changes in moisture and/or substrate quality that impede rates of decomposition. ?? 2008 Springer Science+Business Media, LLC.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70032787','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70032787"><span>Interactive effects of fire, soil climate, and moss on CO2 fluxes in black spruce ecosystems of interior Alaska</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>O'Donnell, Jonathan A.; Turetsky, Merritt R.; Harden, Jennifer W.; Manies, Kristen L.; Pruett, L.E.; Shetler, Gordon; Neff, Jason C.</p> <p>2009-01-01</p> <p>Fire is an important control on the carbon (C) balance of the boreal forest region. Here, we present findings from two complementary studies that examine how fire modifies soil organic matter properties, and how these modifications influence rates of decomposition and C exchange in black spruce (Picea mariana) ecosystems of interior Alaska. First, we used laboratory incubations to explore soil temperature, moisture, and vegetation effects on CO2 and DOC production rates in burned and unburned soils from three study regions in interior Alaska. Second, at one of the study regions used in the incubation experiments, we conducted intensive field measurements of net ecosystem exchange (NEE) and ecosystem respiration (ER) across an unreplicated factorial design of burning (2 year post-fire versus unburned sites) and drainage class (upland forest versus peatland sites). Our laboratory study showed that burning reduced the sensitivity of decomposition to increased temperature, most likely by inducing moisture or substrate quality limitations on decomposition rates. Burning also reduced the decomposability of Sphagnum-derived organic matter, increased the hydrophobicity of feather moss-derived organic matter, and increased the ratio of dissolved organic carbon (DOC) to total dissolved nitrogen (TDN) in both the upland and peatland sites. At the ecosystem scale, our field measurements indicate that the surface organic soil was generally wetter in burned than in unburned sites, whereas soil temperature was not different between the burned and unburned sites. Analysis of variance results showed that ER varied with soil drainage class but not by burn status, averaging 0.9 ± 0.1 and 1.4 ± 0.1 g C m−2 d−1 in the upland and peatland sites, respectively. However, a more complex general linear model showed that ER was controlled by an interaction between soil temperature, moisture, and burn status, and in general was less variable over time in the burned than in the unburned sites. Together, findings from these studies across different spatial scales suggest that although fire can create some soil climate conditions more conducive to rapid decomposition, rates of C release from soils may be constrained following fire by changes in moisture and/or substrate quality that impede rates of decomposition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000032323&hterms=sars&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsars','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000032323&hterms=sars&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsars"><span>A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John</p> <p>1998-01-01</p> <p>Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...8.1609D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...8.1609D"><span>The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.</p> <p>2011-02-01</p> <p>In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; <a href="http://www.ipf.tuwien.ac.at/insitu" target="_blank">http://www.ipf.tuwien.ac.at/insitu</a>) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESS...15.1675D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESS...15.1675D"><span>The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.</p> <p>2011-05-01</p> <p>In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; <a href="http://www.ipf.tuwien.ac.at/insitu" target="_blank">http://www.ipf.tuwien.ac.at/insitu</a>) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B31F2052K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B31F2052K"><span>A numerical study of the effect of irrigation on land-atmosphere interactions in a spring wheat cropland in India using a coupled atmosphere-crop growth dynamics model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kumari, S.; Sharma, P.; Srivastava, A.; Rastogi, D.; Sehgal, V. K.; Dhakar, R.; Roy, S. B.</p> <p>2017-12-01</p> <p>Vegetation dynamics and surface meteorology are tightly coupled through the exchange of momentum, moisture and heat between the land surface and the atmosphere. In this study, we use a recently developed coupled atmosphere-crop growth dynamics model to study these exchanges and their effects in a spring wheat cropland in northern India. In particular, we investigate the role of irrigation in controlling crop growth rates, surface meteorology, and sensible and latent heat fluxes. The model is developed by implementing a crop growth module based on the Simple and Universal Crop growth Simulator (SUCROS) model in the Weather Research Forecasting (WRF) mesoscale atmospheric model. The crop module calculates photosynthesis rates, carbon assimilation, and biomass partitioning as a function of environmental factors and crop development stage. The leaf area index (LAI) and root depth calculated by the crop module is then fed to the Noah-MP land module of WRF to calculate land-atmosphere fluxes. The crop model is calibrated using data from an experimental spring wheat crop site in the Indian Agriculture Research Institute. The coupled model is capable of simulating the observed spring wheat phenology. Irrigation is simulated by changing the soil moisture levels from 50% - 100% of field capacity. Results show that the yield first increases with increasing soil moisture and then starts decreasing as we further increase the soil moisture. Yield attains its maximum value with soil moisture at the level of 60% water of FC. At this level, high LAI values lead to a decrease in the Bowen Ratio because more energy is transferred to the atmosphere as latent heat rather than sensible heat resulting in a cooling effect on near-surface air temperatures. Apart from improving simulation of land-atmosphere interactions, this coupled modeling approach can form the basis for the seamless crop yield and seasonal scale weather outlook prediction system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24028021','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24028021"><span>[Accumulation of S, Fe and Cd in rhizosphere of rice and their uptake in rice with different water managements].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhang, Xue-Xia; Zhang, Xiao-Xia; Zheng, Yu-Ji; Wang, Rong-Ping; Chen, Neng-Chang; Lu, Pu-Xiang</p> <p>2013-07-01</p> <p>The interactions between the concentrations of sulfur, iron and cadmium in the rhizosphere and their uptakes in rice (Oryza sativa L. ) were studied using paddy soil which was contaminated by acid mine drainage under five water-management treatments of 60%, 80%, 100% field moisture capacity (FMC), flooded throughout the entire rice growth period and flooded followed by keeping 80% FMC after heading-flowering period. The water managements had no significant influence on the Fe and Cd concentrations in rhizosphere soil in maturity stage, although the concentration of Cd slightly increased with the increase of soil moisture in the tillering stage. However, the uptake of Fe and Cd in rice was obviously related to water managements. The increase of soil moisture enhanced the uptake of Fe, but decreased the uptake of Cd in different organs of rice (roots, stems and leaves, grains) except for Cd uptake of the root in the 60% FMC treatment. However, aerobic treatment after heading-flowering period enhanced Cd uptake in rice in all treatments, but did not influence the uptake of Fe in rice. On the other hand, the increase of soil moisture reduced the concentrations of total sulfur and available sulfur in the rhizosphere soil except for the 60% FMC treatment, which corresponded with the reduction of Cd uptake in rice. And the aerobic treatment promoted Cd uptake in rice, which was also positively related to the increase of total sulfur and available sulfur in rhizosphere soil. Therefore, it was concluded that the uptake and speciation of sulfur in rhizosphere soil other than the change of Fe concentration induced by water management could play an important role in Cd uptake of rice.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.U53A..05P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.U53A..05P"><span>Propagation of hydroclimatic variability through the critical zone</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Porporato, A. M.; Calabrese, S.; Parolari, A.</p> <p>2016-12-01</p> <p>The interaction between soil moisture dynamics and mineral-weathering reactions (e.g., ion exchange, precipitation-dissolution) affects the availability of nutrients to plants, composition of soils, soil acidification, as well as CO2 sequestration. Across the critical zone (CZ), this interaction is responsible for propagating hydroclimatic fluctuations to deeper soil layers, controlling weathering rates via leaching events which intermittently alter the alkalinity levels. In this contribution, we analyze these dynamics using a stochastic modeling approach based on spatially lumped description of soil hydrology and chemical weathering reactions forced by multi-scale temporal hydrologic variability. We quantify the role of soil moisture dynamics in filtering the rainfall fluctuations through its impacts on soil water chemistry, described by a system of ordinary differential equations (and algebraic equations, for the equilibrium reactions), driving the evolution of alkalinity, pH, the chemical species of the soil solution, and the mineral-weathering rate. A probabilistic description of the evolution of the critical zone is thus obtained, allowing us to describe the CZ response to long-term climate fluctuations, ecosystem and land-use conditions, in terms of key variables groups. The model is applied to the weathering rate of albite in the Calhoun CZ observatory and then extended to explore similarities and differences across other CZs. Typical time scales of response and degrees of sensitivities of CZ to hydroclimatic fluctuations and human forcing are also explored.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090008689','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090008689"><span>Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Joseph, A.T.; Lang, R.; O'Neill, P.E.; van der Velde, R.; Gish, T.</p> <p>2008-01-01</p> <p>A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=272272','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=272272"><span>Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions suc...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275"><span>Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=304546','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=304546"><span>Evaluation of SMOS soil moisture products over the CanEx-SM10 area</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658"><span>SMOS soil moisture validation with U.S. in situ newworks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=318185','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=318185"><span>Potential of bias correction for downscaling passive microwave and soil moisture data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813"><span>Validation of SMAP surface soil moisture products with core validation sites</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well-calibrated in situ soil moisture measurements within SMAP product grid pixels for diver...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=335031','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=335031"><span>Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=320076','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=320076"><span>Estimating error cross-correlations in soil moisture data sets using extended collocation analysis</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373"><span>Precipitation estimation using L-Band and C-Band soil moisture retrievals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=265877','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=265877"><span>Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1513286A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1513286A"><span>Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Azorin-Molina, Cesar; Vicente-Serrano, Sergio M.; Cerdà, Artemi</p> <p>2013-04-01</p> <p>Within the Soil Erosion and Degradation Research Group Experimental Stations, soil moisture is being researched as a key factor of the soil hydrology and soil erosion (Cerdà, 1995; Cerda, 1997; Cerdà 1998). This because under semiarid conditions soil moisture content plays a crucial role for agriculture, forest, groundwater recharge and soil chemistry and scientific improvement is of great interest in agriculture, hydrology and soil sciences. Soil moisture has been seeing as the key factor for plant photosynthesis, respiration and transpiration in orchards (Schneider and Childers, 1941) and plant growth (Veihmeyer and Hendrickson, 1950). Moreover, soil moisture determine the root growth and distribution (Levin et al., 1979) and the soil respiration ( Velerie and Orchard, 1983). Water content is expressed as a ratio, ranging from 0 (dry) to the value of soil porosity at saturation (wet). In this study we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, Eastern Spain: one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). The EC-5 soil moisture smart sensor S-SMC-M005 integrated with the field-proven ECH2O™ Sensor and a 12-bit A/D has been choosen for measuring soil water content providing ±3% accuracy in typical soil conditions. Soil moisture measurements were carried out at 5-minute intervals from January till December 2012. In addition, soil moisture was measured at two depths in each landscape: 2 and 20 cm depth - in order to retrieve a representative vertical cross-section of soil moisture. Readings are provided directly from 0 (dry) to 0.450 m3/m3 (wet) volumetric water content. The soil moisture smart sensor is conected to a HOBO U30 Station - GSM-TCP which also stored 5-minute temperature, relative humidity, dew point, global solar radiation, precipitation, wind speed and wind direction data. These complementary atmospheric measurements will serve to explain the intraannual and vertical variations observed in the soil moisture content in both experimental landscapes. This kind of study is aimed to understand the soil moisture content in two different environments such as irrigated rainfed orchards in a semi-arid region. For instance, these measurements have a direct impact on water availability for crops, plant transpiration and could have practical applications to schedule irrigation. Additionally, soil water content has also implications for erosion processes. Key Words: Water, Agriculture, Irrigation, Eastern Spain, Citrus. Acknowledgements The research projects GL2008-02879/BTE and LEDDRA 243857 supported this research. References Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1997. Seasonal Changes of the Infiltration Rates in a Typical Mediterranean Scrubland on Limestone in Southeast Spain. Journal of Hydrology, 198 (1-4) 198-209 Cerdà, A. 1998. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Levin, I., Assaf, R., and Bravdo, B. 1979. Soil moisture and root distribution in an apple orchard irrigated by tricklers. Plant and Soil, 52, 31-40. Schneider, G. W. And Childers, N.F. 1941. Influence of soil moisture on photosynthesis, respiration and transpiration of apples leaves. Plant Physiol., 16, 565-583. Valerie, A. and Orchard, F.J. Cook. 1983. Relationship between soil respiration and soil moisture. Soil Biology and Biochemistry, 15, 447-453. Veihmeyer, F. J. and Hendrickson, A. H. 1950. Soil Moisture in Relation to Plant Growth. Annual Review of Plant Physiology, 1, 285-304.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.nco.ncep.noaa.gov/pmb/products/gfs/gfs_upgrade/gfs.t06z.sfluxgrbf00.grib2.shtml','SCIGOVWS'); return false;" href="http://www.nco.ncep.noaa.gov/pmb/products/gfs/gfs_upgrade/gfs.t06z.sfluxgrbf00.grib2.shtml"><span>Inventory of File gfs.t06z.sfluxgrbf00.grib2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>Volumetric <em>Soil</em> Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric <em>Soil</em> Volumetric <em>Soil</em> Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric <em>Soil</em> Moisture analysis Temperature [K] 071 0-0.1 m below ground SOILL analysis Liquid Volumetric <em>Soil</em> Moisture (non</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010291','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010291"><span>Assessment of Soil Moisture Data Requirements by the Potential SMAP Data User Community: Review of SMAP Mission User Community</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Brown, Molly E.; Escobar, Vanessa M.</p> <p>2013-01-01</p> <p>NASA's Soil Moisture Active and Passive (SMAP) mission is planned for launch in October 2014 and will provide global measurements of soil moisture and freeze thaw state. The project is driven by both basic research and applied science goals. Understanding how application driven end-users will apply SMAP data, prior to the satellite's launch, is an important goal of NASA's applied science program and SMAP mission success. Because SMAP data are unique, there are no direct proxy data sets that can be used in research and operational studies to determine how the data will interact with existing processes. The objective of this study is to solicit data requirements, accuracy needs, and current understanding of the SMAP mission from the potential user community. This study showed that the data to be provided by the SMAP mission did substantially meet the user community needs. Although there was a broad distribution of requirements stated, the SMAP mission fit within these requirements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JHyd..512...27B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JHyd..512...27B"><span>Towards soil property retrieval from space: Proof of concept using in situ observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph</p> <p>2014-05-01</p> <p>Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913775Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913775Z"><span>Soil water dynamics during precipitation in genetic horizons of Retisol</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zaleski, Tomasz; Klimek, Mariusz; Kajdas, Bartłomiej</p> <p>2017-04-01</p> <p>Retisols derived from silty deposits dominate in the soil cover of the Carpathian Foothills. The hydrophysical properties of these are determined by the grain-size distribution of the parent material and the soil's "primary" properties shaped in the deposition process. The other contributing factors are the soil-forming processes, such as lessivage (leaching of clay particles), and the morphogenetic processes that presently shape the relief. These factors are responsible for the "secondary" differentiation of hydrophysical properties across the soil profile. Both the primary and secondary hydrophysical properties of soils (the rates of water retention, filtration and infiltration, and the moisture distribution over the soil profile) determine their ability to take in rainfall, the amount of rainwater taken in, and the ways of its redistribution. The aims of the study, carried out during 2015, were to investigate the dynamics of soil moisture in genetic horizons of Retisol derived from silty deposits and to recognize how fast and how deep water from precipitation gets into soil horizons. Data of soil moisture were measured using 5TM moisture and temperature sensor and collected by logger Em50 (Decagon Devices USA). Data were captured every 10 minutes from 6 sensors at depths: - 10 cm, 20 cm, 40 cm, 60 cm and 80 cm. Precipitation data come from meteorological station situated 50 m away from the soil profile. Two zones differing in the type of water regime were distinguished in Retisol: an upper zone comprising humic and eluvial horizons, and a lower zone consisting of illuvial and parent material horizons. The upper zone shows smaller retention of water available for plants, and relatively wide fluctuations in moisture content, compared to the lower zone. The lower zone has stable moisture content during the vegetation season, with values around the water field capacity. Large changes in soil moisture were observed while rainfall. These changes depend on the volume of the precipitation and soil moisture before the precipitation. The following changes of moisture in the soil profile during precipitation were distinguished: if soil moisture in upper zone horizons oscillates around field capacity (higher than 0.30 m3ṡm-3) there is an evident increase in soil moisture also in the lower zone horizons. If soil moisture in the upper zone horizons is much lower than the field capacity (less than 0.20 m3ṡm-3), the soil moisture in the lower zone has very little fluctuations. The range of wetting front in the soil profile depends on the volume of the precipitation and soil moisture. The heavier precipitation, the wetting front in soil profile reaches deeper horizons. The wetter the soil is, the faster soil moisture in the deeper genetic horizons increase. This Research was financed by the Ministry of Science and Higher Education of the Republic of Poland, DS No. 3138/KGiOG/2016.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4884879','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4884879"><span>Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Arvela, H.; Holmgren, O.; Hänninen, P.</p> <p>2016-01-01</p> <p>The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038126&hterms=watershed&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwatershed','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038126&hterms=watershed&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwatershed"><span>The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.</p> <p>1997-01-01</p> <p>The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.7800U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.7800U"><span>Spatial and temporal variability of soil moisture on the field with and without plants*</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Usowicz, B.; Marczewski, W.; Usowicz, J. B.</p> <p>2012-04-01</p> <p>Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010000376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010000376"><span>Ultrasound Algorithm Derivation for Soil Moisture Content Estimation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.</p> <p>1997-01-01</p> <p>Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19637591','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19637591"><span>[Soil moisture dynamics of artificial Caragana microphylla shrubs at different topographical sites in Horqin sandy land].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui</p> <p>2009-03-01</p> <p>Based on the investigation data of vegetation and soil moisture regime of Caragana microphylla shrubs widely distributed in Horqin sandy land, the spatiotemporal variations of soil moisture regime and soil water storage of artificial sand-fixing C. microphylla shrubs at different topographical sites in the sandy land were studied, and the evapotranspiration was measured by water balance method. The results showed that the soil moisture content of the shrubs was the highest in the lowland of dunes, followed by in the middle, and in the crest of the dunes, and increased with increasing depth. No water stress occurred during the growth season of the shrubs. Soil moisture content of the shrubs was highly related to precipitation event, and the relationship of soil moisture content with precipitation was higher in deep soil layer (50-180 cm) than in shallow soil layer (0-50 cm). The variation coefficient of soil moisture content was also higher in deep layer than in shallow layer. Soil water storage was increasing in the whole growth season of the shrubs, which meant that the accumulation of soil water occurred in this area. The evapotranspiriation of the shrubs occupied above 64% of the precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090027817','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090027817"><span>An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bolten, John D.; Lakshmi, Venkat</p> <p>2009-01-01</p> <p>The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612163C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612163C"><span>Validation of SURFEX Simulated Soil Moisture over the Valencia Anchor Station using SMOS products and in situ measurements.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coll, M. Amparo; Khodayar, Samiro; Lopez-Baeza, Ernesto</p> <p>2014-05-01</p> <p>Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the SURFEX (Surface Externalisée) model developed at the Centre National de Recherches Météorologiques (CNRM) at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the Valencia Anchor Station. SURFEX integrates the ISBA (Interaction Sol-Biosphère-Atmosphère; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) and we introduced the ECOCLIMAP for the description of land covers. The Valencia Anchor Station was chosen as a validation site for the SMOS (Soil Moisture and Ocean Salinity) mission and as one of the hydrometeorological sites for the HyMeX (HYdrological cycle in Mediterranean EXperiment) programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few number of small industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry-sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields to be compared with level-2 and level-3 soil moisture maps generated from SMOS over the Valencia Anchor Station, as a continuation to the previous work carried out around SMOS launch and commissioning phase (Juglea et al., 2010). In situ measurements are also available as reference from a network of stations covering the reduced number of different vegetation cover and soil types. An L-band radiometer from ESA (European Space Agency), ELBARA-II, is installed in the area to monitor SMOS validation conditions over a vineyard crop. Different interpolation methods will be applied to all significant atmospheric forcing parameters from the two met stations available in the area (pressure, temperature, relative humidity and precipitation) in order to obtain a good representation of soil conditions to be compared to level-2 and -3 SMOS soil moisture products. The period of investigation covers the complete 2012 period and we will particularly focus on selected periods from September to November 2012 where there were extreme rain events in our study area.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330724','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330724"><span>Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=326220','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=326220"><span>Application of triple collocation in ground-based validation of soil moisture active/passive (SMAP) level 2 data products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The validation of the soil moisture retrievals from the recently-launched NASA Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/35309','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/35309"><span>Soil-moisture constants and their variation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Walter M. Broadfoot; Hubert D. Burke</p> <p>1958-01-01</p> <p>"Constants" like field capacity, liquid limit, moisture equivalent, and wilting point are used by most students and workers in soil moisture. These constants may be equilibrium points or other values that describe soil moisture. Their values under specific soil and cover conditions have been discussed at length in the literature, but few general analyses and...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=251966','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=251966"><span>Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/31692','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/31692"><span>Soil moisture depletion patterns around scattered trees</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Robert R. Ziemer</p> <p>1968-01-01</p> <p>Soil moisture was measured around an isolated mature sugar pine tree (Pinus lambertiana Dougl.) in the mixed conifer forest type of the north central Sierra Nevada, California, from November 1965 to October 1966. From a sequence of measurements, horizontal and vertical soil moisture profiles were developed. Estimated soil moisture depletion from the 61-foot radius plot...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=228413','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=228413"><span>Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013"><span>Calibration and validation of the COSMOS rover for surface soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000032337&hterms=Hydrology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DHydrology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000032337&hterms=Hydrology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DHydrology"><span>Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi</p> <p>1998-01-01</p> <p>Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17540058','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17540058"><span>Influence of soil texture, moisture, and surface cracks on the performance of a root-feeding flea beetle, Longitarsus bethae (Coleoptera: Chrysomelidae), a biological control agent for Lantana camara (Verbenaceae).</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Simelane, David O</p> <p>2007-06-01</p> <p>Laboratory studies were conducted to determine the influence of soil texture, moisture and surface cracks on adult preference and survival of the root-feeding flea beetle, Longitarsus bethae Savini and Escalona (Coleoptera: Chrysomelidae), a natural enemy of the weed, Lantana camara L. (Verbenaceae). Adult feeding, oviposition preference, and survival of the immature stages of L. bethae were examined at four soil textures (clayey, silty loam, sandy loam, and sandy soil), three soil moisture levels (low, moderate, and high), and two soil surface conditions (with or without surface cracks). Both soil texture and moisture had no influence on leaf feeding and colonization by adult L. bethae. Soil texture had a significant influence on oviposition, with adults preferring to lay on clayey and sandy soils to silty or sandy loam soils. However, survival to adulthood was significantly higher in clayey soils than in other soil textures. There was a tendency for females to deposit more eggs at greater depth in both clayey and sandy soils than in other soil textures. Although oviposition preference and depth of oviposition were not influenced by soil moisture, survival in moderately moist soils was significantly higher than in other moisture levels. Development of immature stages in high soil moisture levels was significantly slower than in other soil moisture levels. There were no variations in the body size of beetles that emerged from different soil textures and moisture levels. Females laid almost three times more eggs on cracked than on noncracked soils. It is predicted that clayey and moderately moist soils will favor the survival of L. bethae, and under these conditions, damage to the roots is likely to be high. This information will aid in the selection of suitable release sites where L. bethae would be most likely to become established.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1168909-sensitivity-global-terrestrial-gross-primary-production-hydrologic-states-simulated-community-land-model-using-two-runoff-parameterizations','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1168909-sensitivity-global-terrestrial-gross-primary-production-hydrologic-states-simulated-community-land-model-using-two-runoff-parameterizations"><span>Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.</p> <p>2014-09-01</p> <p>The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically,more » differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AcO....60...49B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AcO....60...49B"><span>Climate change triggers effects of fungal pathogens and insect herbivores on litter decomposition</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Butenschoen, Olaf; Scheu, Stefan</p> <p>2014-10-01</p> <p>Increasing infestation by insect herbivores and pathogenic fungi in response to climate change will inevitably impact the amount and quality of leaf litter inputs into the soil. However, little is known on the interactive effect of infestation severity and climate change on litter decomposition, and no such study has been published for deciduous forests in Central Europe. We assessed changes in initial chemical quality of beech (Fagus sylvatica L.) and maple litter (Acer platanoides L.) in response to infestation by the gall midge Mikiola fagi Hart. and the pathogenic fungus Sawadaea tulasnei Fuckel, respectively, and investigated interactive effects of infestation severity, changes in temperature and soil moisture on carbon mineralization in a short-term laboratory study. We found that infestation by the gall midge M. fagi and the pathogenic fungus S. tulasnei significantly changed the chemical quality of beech and maple litter. Changes in element concentrations were generally positive and more pronounced, and if negative less pronounced for maple than beech litter most likely due to high quality fungal tissue remaining on litter after abscission. More importantly, alterations in litter chemical quality did not translate to distinct patterns of carbon mineralization at ambient conditions, but even low amounts of infested litter accelerated carbon mineralization at moderately increased soil moisture and in particular at higher temperature. Our results indicate that insect herbivores and fungal pathogens can markedly alter initial litter chemical quality, but that afterlife effects on carbon mineralization depend on soil moisture and temperature, suggesting that increased infestation severity under projected climate change potentially increases soil carbon release in deciduous forests in Central Europe.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70015963','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70015963"><span>Effect of soil moisture on the sorption of trichloroethene vapor to vadose-zone soil at picatinny arsenal, New Jersey</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Smith, J.A.; Chiou, C.T.; Kammer, J.A.; Kile, D.E.</p> <p>1990-01-01</p> <p>This report presents data on the sorption of trichloroethene (TCE) vapor to vadose-zone soil above a contaminated water-table aquifer at Picatinny Arsenal in Morris County, NJ. To assess the impact of moisture on TCE sorption, batch experiments on the sorption of TCE vapor by the field soil were carried out as a function of relative humidity. The TCE sorption decreases as soil moisture content increases from zero to saturation soil moisture content (the soil moisture content in equilibrium with 100% relative humidity). The moisture content of soil samples collected from the vadose zone was found to be greater than the saturation soil-moisture content, suggesting that adsorption of TCE by the mineral fraction of the vadose-zone soil should be minimal relative to the partition uptake by soil organic matter. Analyses of soil and soil-gas samples collected from the field indicate that the ratio of the concentration of TCE on the vadose-zone soil to its concentration in the soil gas is 1-3 orders of magnitude greater than the ratio predicted by using an assumption of equilibrium conditions. This apparent disequilibrium presumably results from the slow desorption of TCE from the organic matter of the vadose-zone soil relative to the dissipation of TCE vapor from the soil gas.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27846728','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27846728"><span>The MICE facility - a new tool to study plant-soil C cycling with a holistic approach.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Studer, Mirjam S; Künzli, Roland; Maier, Reto; Schmidt, Michael W I; Siegwolf, Rolf T W; Woodhatch, Ivan; Abiven, Samuel</p> <p>2017-06-01</p> <p>Plant-soil interactions are recognized to play a crucial role in the ecosystem response to climate change. We developed a facility to disentangle the complex interactions behind the plant-soil C feedback mechanisms. The MICE ('Multi-Isotope labelling in a Controlled Environment') facility consists of two climate chambers with independent control of the atmospheric conditions (light, CO 2 , temperature, humidity) and the soil environment (temperature, moisture). Each chamber holds 15 plant-soil systems with hermetical separation of the shared above ground (shoots) from the individual belowground compartments (roots, rhizosphere, soil). Stable isotopes (e.g. 13 C, 15 N, 2 H, 18 O) can be added to either compartment and traced within the whole system. The soil CO 2 efflux rate is monitored, and plant material, leached soil water and gas samples are taken frequently. The facility is a powerful tool to improve our mechanistic understanding of plant-soil interactions that drive the C cycle feedback to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007421','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007421"><span>Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>O'neill, P. O.; Chan, S.; Bindlish, R.; Jackson, T.; Colliander, A.; Dunbar, R.; Chen, F.; Piepmeier, Jeffrey R.; Yueh, S.; Entekhabi, D.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170007421'); toggleEditAbsImage('author_20170007421_show'); toggleEditAbsImage('author_20170007421_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170007421_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170007421_hide"></p> <p>2017-01-01</p> <p>NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatGe..10..100M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatGe..10..100M"><span>The global distribution and dynamics of surface soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara</p> <p>2017-01-01</p> <p>Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.5354B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.5354B"><span>Anticipating on amplifying water stress: Optimal crop production supported by anticipatory water management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bartholomeus, Ruud; van den Eertwegh, Gé; Simons, Gijs</p> <p>2015-04-01</p> <p>Agricultural crop yields depend largely on the soil moisture conditions in the root zone. Drought but especially an excess of water in the root zone and herewith limited availability of soil oxygen reduces crop yield. With ongoing climate change, more prolonged dry periods alternate with more intensive rainfall events, which changes soil moisture dynamics. With unaltered water management practices, reduced crop yield due to both drought stress and waterlogging will increase. Therefore, both farmers and water management authorities need to be provided with opportunities to reduce risks of decreasing crop yields. In The Netherlands, agricultural production of crops represents a market exceeding 2 billion euros annually. Given the increased variability in meteorological conditions and the resulting larger variations in soil moisture contents, it is of large economic importance to provide farmers and water management authorities with tools to mitigate risks of reduced crop yield by anticipatory water management, both at field and at regional scale. We provide the development and the field application of a decision support system (DSS), which allows to optimize crop yield by timely anticipation on drought and waterlogging situations. By using this DSS, we will minimize plant water stress through automated drainage and irrigation management. In order to optimize soil moisture conditions for crop growth, the interacting processes in the soil-plant-atmosphere system need to be considered explicitly. Our study comprises both the set-up and application of the DSS on a pilot plot in The Netherlands, in order to evaluate its implementation into daily agricultural practice. The DSS focusses on anticipatory water management at the field scale, i.e. the unit scale of interest to a farmer. We combine parallel field measurements ('observe'), process-based model simulations ('predict'), and the novel Climate Adaptive Drainage (CAD) system ('adjust') to optimize soil moisture conditions. CAD is used both for controlled drainage practices and for sub-irrigation. The DSS has a core of the plot-scale SWAP model (soil-water-atmosphere-plant), extended with a process-based module for the simulation of oxygen stress for plant roots. This module involves macro-scale and micro-scale gas diffusion, as well as the plant physiological demand of oxygen, to simulate transpiration reduction due to limited oxygen availability. Continuous measurements of soil moisture content, groundwater level, and drainage level are used to calibrate the SWAP model each day. This leads to an optimal reproduction of the actual soil moisture conditions by data assimilation in the first step in the DSS process. During the next step, near-future (+10 days) soil moisture conditions and drought and oxygen stress are predicted using weather forecasts. Finally, optimal drainage levels to minimize stress are simulated, which can be established by CAD. Linkage to a grid-based hydrological simulation model (SPHY) facilitates studying the spatial dynamics of soil moisture and associated implications for management at the regional scale. Thus, by using local-scale measurements, process-based models and weather forecasts to anticipate on near-future conditions, not only field-scale water management but also regional surface water management can be optimized both in space and time.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913342B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913342B"><span>Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.</p> <p>2017-04-01</p> <p>From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29726183','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29726183"><span>[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi</p> <p>2016-03-01</p> <p>The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.8426H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.8426H"><span>Where did my wifi go? Measuring soil moisture using wifi signal strength</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hut, Rolf; de Jeu, Richard</p> <p>2015-04-01</p> <p>Soil moisture is tricky to measure. Currently soil moisture is measured at small footprints using probes and other field devices, or at large footprints using satellites. Promising developments in measuring soil moisture are using fiber optic cables for measurements along a line, or using cosmos rays for field scale measurements. In this demonstration we present a low cost alternative to measure soil moisture at footprints of a few square meters. We use a wifi hotspot and a wifi dongle, both mounted in a cantenna for beam forming. We aim the hotspot on a piece of soil and put the dongle in the path of the reflection. By logging the signal strength of the wifi netwerk, we have a proxy for soil moisture. A first proof of concept is presented.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B51G1897R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B51G1897R"><span>Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.</p> <p>2017-12-01</p> <p>A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H31G1478S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H31G1478S"><span>High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.</p> <p>2016-12-01</p> <p>Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H44D..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H44D..04H"><span>Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.</p> <p>2017-12-01</p> <p>Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014WRR....50.6874W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014WRR....50.6874W"><span>The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.</p> <p>2014-08-01</p> <p>Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H11A1317P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H11A1317P"><span>Application of time-lapse ERT to Characterize Soil-Water-Disease Interactions of Citrus Orchard - Case Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peddinti, S. R.; Kbvn, D. P.; Ranjan, S.; Suradhaniwar, S.; J, P. A.; R M, G.</p> <p>2015-12-01</p> <p>Vidarbha region in Maharashtra, India (home for mandarin Orange) experience severe climatic uncertainties resulting in crop failure. Phytopthora are the soil-borne fungal species that accumulate in the presence of moisture, and attack the root / trunk system of Orange trees at any stage. A scientific understanding of soil-moisture-disease relations within the active root zone under different climatic, irrigation, and crop cycle conditions can help in practicing management activities for improved crop yield. In this study, we developed a protocol for performing 3-D time-lapse electrical resistivity tomography (ERT) at micro scale resolution to monitor the changes in resistivity distribution within the root zone of Orange trees. A total of 40 electrodes, forming a grid of 3.5 m x 2 m around each Orange tree were used in ERT survey with gradient and Wenner configurations. A laboratory test on un-disturbed soil samples of the region was performed to plot the variation of electrical conductivity with saturation. Curve fitting techniques were applied to get the modified Archie's model parameters. The calibrated model was further applied to generate the 3-D soil moisture profiles of the study area. The point estimates of soil moisture were validated using TDR probe measurements at 3 different depths (10, 20, and 40 cm) near to the root zone. In order to understand the effect of soil-water relations on plant-disease relations, we performed ERT analysis at two locations, one at healthy and other at Phytopthora affected Orange tree during the crop cycle, under dry and irrigated conditions. The degree to which an Orange tree is affected by Phytopthora under each condition is evaluated using 'grading scale' approach following visual inspection of the canopy features. Spatial-temporal distribution of moisture profiles is co-related with grading scales to comment on the effect of climatic and irrigation scenarios on the degree and intensity of crop disease caused by Phytopthora.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/35234','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/35234"><span>Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Mark P. Waldrop; Jennifer W. Harden</p> <p>2008-01-01</p> <p>Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/7695','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/7695"><span>BDEN: A timesaving computer program for calculating soil bulk density and water content.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Lynn G. Starr; Michael J. Geist</p> <p>1983-01-01</p> <p>This paper presents an interactive computer program written in BASIC language that will calculate soil bulk density and moisture percentage by weight and volume. Coarse fragment weights are required. The program will also summarize the resulting data giving mean, standard deviation, and 95-percent confidence interval on one or more groupings of data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/1955','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/1955"><span>Interaction of Soil Moisture and Seedling Shelters on Water Relations of Baldcypress Seedlings</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Ty Swirin; Hans Williams; Bob Keeland</p> <p>1999-01-01</p> <p>Stomata1 conductance, transpiration, and leaf water potential were measured during the 1996 growing season on baldcypress (Taxodium disfichum (L.) Rich.) seedlings. Seedlings were hand-planted from 1-O bareroot stock in mesic and permanently Rooded soil conditions. One-half of all seedlings were fitted with 122-cm tall polyethylene tree...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740011869','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740011869"><span>Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blanchard, M. B.; Greeley, R.; Goettelman, R.</p> <p>1974-01-01</p> <p>Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19750033072&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DSoil%2Buse','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19750033072&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DSoil%2Buse"><span>Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blanchard, M. B.; Greeley, R.; Goettelman, R.</p> <p>1974-01-01</p> <p>Two methods are used to estimate soil moisture remotely using the 0.4- to 14.0-micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.2255C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.2255C"><span>Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.</p> <p>2018-04-01</p> <p>Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008PhDT.......151H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008PhDT.......151H"><span>Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hong, Seungbum</p> <p></p> <p>Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..548..484W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..548..484W"><span>Towards robust quantification and reduction of uncertainty in hydrologic predictions: Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, S.; Huang, G. H.; Baetz, B. W.; Ancell, B. C.</p> <p>2017-05-01</p> <p>The particle filtering techniques have been receiving increasing attention from the hydrologic community due to its ability to properly estimate model parameters and states of nonlinear and non-Gaussian systems. To facilitate a robust quantification of uncertainty in hydrologic predictions, it is necessary to explicitly examine the forward propagation and evolution of parameter uncertainties and their interactions that affect the predictive performance. This paper presents a unified probabilistic framework that merges the strengths of particle Markov chain Monte Carlo (PMCMC) and factorial polynomial chaos expansion (FPCE) algorithms to robustly quantify and reduce uncertainties in hydrologic predictions. A Gaussian anamorphosis technique is used to establish a seamless bridge between the data assimilation using the PMCMC and the uncertainty propagation using the FPCE through a straightforward transformation of posterior distributions of model parameters. The unified probabilistic framework is applied to the Xiangxi River watershed of the Three Gorges Reservoir (TGR) region in China to demonstrate its validity and applicability. Results reveal that the degree of spatial variability of soil moisture capacity is the most identifiable model parameter with the fastest convergence through the streamflow assimilation process. The potential interaction between the spatial variability in soil moisture conditions and the maximum soil moisture capacity has the most significant effect on the performance of streamflow predictions. In addition, parameter sensitivities and interactions vary in magnitude and direction over time due to temporal and spatial dynamics of hydrologic processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33C1080Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33C1080Z"><span>The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Y.; Estes, L. D.; Vergopolan, N.</p> <p>2017-12-01</p> <p>Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860006235','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860006235"><span>Biochemical processes in sagebrush ecosystems: Interactions with terrain</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Matson, P. (Principal Investigator); Reiners, W.; Strong, L.</p> <p>1985-01-01</p> <p>The objectives of a biogeochemical study of sagebrush ecosystems in Wyoming and their interactions with terrain are as follows: to describe the vegetational pattern on the landscape and elucidate controlling variables, to measure the soil properties and chemical cycling properties associated with the vegetation units, to associate soil properties with vegetation properties as measured on the ground, to develop remote sensing capabilities for vegetation and surface characteristics of the sagebrush landscape, to develop a system of sensing snow cover and indexing seasonal soil to moisture; and to develop relationships between temporal Thematic Mapper (TM) data and vegetation phenological state.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940030883','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940030883"><span>A model of the CO2 exchanges between biosphere and atmosphere in the tundra</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Labgaa, Rachid R.; Gautier, Catherine</p> <p>1992-01-01</p> <p>A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H41C0899C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H41C0899C"><span>What is the philosophy of modelling soil moisture movement?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, J.; Wu, Y.</p> <p>2009-12-01</p> <p>In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9693C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9693C"><span>Exploring the Role of Soil Moisture Conditions for Rainfall Triggered Landslides on Catchment Scale: the case of the Ialomita Sub Carpathians, Romania</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru</p> <p>2014-05-01</p> <p>Like in many parts of the world, landslides represent in Romania recurrent phenomena that produce numerous damages to the infrastructure every few years. The high frequency of landslide events over the world has resulted to the development of many early warning systems that are based on the definition of rainfall thresholds triggering landslides. In Romania in particular, recent studies exploring the temporal occurrence of landslides have revealed that rainfall represents the most important triggering factor for landslides. The presence of low permeability soils and gentle slope degrees in the Ialomita Subcarpathians of Romania makes that cumulated precipitation over variable time interval and the hydraulic response of the soil plays a key role in landslides triggering. In order to identify the slope responses to rainfall events in this particular area we investigate the variability of soil moisture and its relationship to landslide events in three Subcarpathians catchments (Cricovul Dulce, Bizididel and Vulcana) by combining in situ measurements, satellite-based radiometry and hydrological modelling. For the current study, hourly soil moisture measurements from six soil moisture monitoring stations that are fitted with volumetric soil moisture sensors, temperature soil sensors and rain gauges sensors are used. Pedotransfer functions will be applied in order to infer hydraulic soil properties from soil texture sampled from 50 soil profiles. The information about spatial and temporal variability of soil moisture content will be completed with the Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. A time series analysis of soil moisture is planned to be integrated to landslide and rainfall time series in order to determine a preliminary rainfall threshold triggering landslides in Ialomita Subcarpathians.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3927501','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3927501"><span>Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander</p> <p>2008-01-01</p> <p>The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdWR..112..124B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdWR..112..124B"><span>Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott</p> <p>2018-02-01</p> <p>Many forested mountain watersheds worldwide evolved with frequent fire, which Twentieth Century fire suppression activities eliminated, resulting in unnaturally dense forests with high water demand. Restoration of pre-suppression forest composition and structure through a variety of management activities could improve forest resilience and water yields. This study explores the potential for "managed wildfire", whereby naturally ignited fires are allowed to burn, to alter the water balance. Interest in this type of managed wildfire is increasing, yet its long-term effects on water balance are uncertain. We use soil moisture as a spatially-distributed hydrologic indicator to assess the influence of vegetation, fire history and landscape position on water availability in the Illilouette Creek Basin in Yosemite National Park. Over 6000 manual surface soil moisture measurements were made over a period of three years, and supplemented with continuous soil moisture measurements over the top 1m of soil in three sites. Random forest and linear mixed effects models showed a dominant effect of vegetation type and history of vegetation change on measured soil moisture. Contemporary and historical vegetation maps were used to upscale the soil moisture observations to the basin and infer soil moisture under fire-suppressed conditions. Little change in basin-averaged soil moisture was inferred due to managed wildfire, but the results indicated that large localized increases in soil moisture had occurred, which could have important impacts on local ecology or downstream flows.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..543..242C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..543..242C"><span>Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei</p> <p>2016-12-01</p> <p>Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the Earth's 'third pole'. Large-scale spatially consistent and temporally continuous soil moisture datasets are of great importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is a relatively new passive microwave product, with the satellite being launched on November 5, 2010. This study validates and reconstructs FY-3B/MWRI soil moisture across the TP. First, the validation is performed using in situ measurements within two in situ soil moisture measurement networks (1° × 1° and 0.25° × 0.25°), and also compared with the Essential Climate Variable (ECV) soil moisture product from multiple active and passive satellite soil moisture products using new merging procedures. Results show that the ascending FY-3B/MWRI product outperforms the descending product. The ascending FY-3B/MWRI product has almost the same correlation as the ECV product with the in situ measurements. The ascending FY-3B/MWRI product has better performance than the ECV product in the frozen season and under the lower NDVI condition. When the NDVI is higher in the unfrozen season, uncertainty in the ascending FY-3B/MWRI product increases with increasing NDVI, but it could still capture the variability in soil moisture. Second, the FY-3B/MWRI soil moisture product is subsequently reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and NDVI, LST, and albedo, but also the relationship between the soil moisture and four-dimensional variations using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 higher than 0.56, RMSE less than 0.1 cm3 cm-3, and Bias less than 0.07 cm3 cm-3 for both frozen and unfrozen seasons, compared with the in situ measurements at the two networks. Third, the reconstruction method is applied to generate surface soil moisture over the TP. Both original and reconstructed FY-3B/MWRI soil moisture products could be valuable in studying meteorology, hydrology, and ecosystems over the TP.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use"><span>Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc</p> <p></p> <p>Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use"><span>Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc; ...</p> <p>2017-12-14</p> <p>Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1457599-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1457599-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use"><span>Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Grossiord, Charlotte; Sevanto, Sanna; Limousin, Jean-Marc</p> <p></p> <p>Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit (VPD) and soil moisture variations, and the generality of these effects across forest types and environments using fourmore » manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water (REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Overall, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN21A1724P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN21A1724P"><span>A Citizen Science Soil Moisture Sensor to Support SMAP Calibration/Validation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Podest, E.; Das, N. N.</p> <p>2016-12-01</p> <p>The Soil Moisture Active Passive (SMAP) satellite mission was launched in Jan. 2015 and is currently acquiring global measurements of soil moisture in the top 5 cm of the soil every 3 days. SMAP has partnered with the GLOBE program to engage students from around the world to collect in situ soil moisture and help validate SMAP measurements. The current GLOBE SMAP soil moisture protocol consists in collecting a soil sample, weighing, drying and weighing it again in order to determine the amount of water in the soil. Preparation and soil sample collection can take up to 20 minutes and drying can take up to 3 days. We have hence developed a soil moisture measurement device based on Arduino-like microcontrollers along with off-the-shelf and homemade sensors that are accurate, robust, inexpensive and quick and easy to use so that they can be implemented by the GLOBE community and citizen scientists alike. This talk will discuss building, calibration and validation of the soil moisture measuring device and assessing the quality of the measurements collected. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171139','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171139"><span>"Hot Spots" of Land Atmosphere Coupling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, Randal D.; Dirmeyer, Paul A.; Guo, Zhi-Chang; Bonan, Gordan; Chan, Edmond; Cox, Peter; Gordon, T. C.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David</p> <p>2004-01-01</p> <p>Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a severe paucity of relevant observational data and by the model-dependence of the various computational estimates. To counter this limitation, a dozen climate modeling groups have recently performed the same highly-controlled numerical experiment as part of a coordinated intercomparison project. This allows, for the first time ever, a superior multi-model approach to the estimation of the regions on the globe where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Such estimation has many potential benefits; it can contribute, for example, to seasonal rainfall prediction efforts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1816968T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1816968T"><span>Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi</p> <p>2016-04-01</p> <p>Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.H51J..03K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.H51J..03K"><span>Modeling Water and Nutrient Transport through the Soil-Root-Canopy Continuum: Explicitly Linking the Below- and Above-Ground Processes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kumar, P.; Quijano, J. C.; Drewry, D.</p> <p>2010-12-01</p> <p>Vegetation roots provide a fundamental link between the below ground water and nutrient dynamics and above ground canopy processes such as photosynthesis, evapotranspiration and energy balance. The “hydraulic architecture” of roots, consisting of the structural organization of the root system and the flow properties of the conduits (xylem) as well as interfaces with the soil and the above ground canopy, affect stomatal conductance thereby directly linking them to the transpiration. Roots serve as preferential pathways for the movement of moisture from wet to dry soil layers during the night, both from upper soil layer to deeper layers during the wet season (‘hydraulic descent’) and vice-versa (‘hydraulic lift’) as determined by the moisture gradients. The conductivities of transport through the root system are significantly, often orders of magnitude, larger than that of the surrounding soil resulting in movement of soil-moisture at rates that are substantially larger than that through the soil. This phenomenon is called hydraulic redistribution (HR). The ability of the deep-rooted vegetation to “bank” the water through hydraulic descent during wet periods for utilization during dry periods provides them with a competitive advantage. However, during periods of hydraulic lift these deep-rooted trees may facilitate the growth of understory vegetation where the understory scavenges the hydraulically lifted soil water. In other words, understory vegetation with relatively shallow root systems have access to the banked deep-water reservoir. These inter-dependent root systems have a significant influence on water cycle and ecosystem productivity. HR induced available moisture may support rhizosphere microbial and mycorrhizal fungi activities and enable utilization of heterogeneously distributed water and nutrient resources To capture this complex inter-dependent nutrient and water transport through the soil-root-canopy continuum we present modeling results using coupled partial differential equations of transport in soils and roots along with that for nutrient dynamics. We study the feedbkack of HR on the dynamics of water and nitrogen cycling in the soil and how these dynamics influence root water and nitrogen uptake and consequently carbon assimilation by the canopy. The forcing data is obtained from the Ameriflux Tower located in Blodgett Forest, Sierra Nevada, California. We consider single-species (Ponderosa Pine) and multi-species (overstory Ponderosa Pine and understory shrubs) interaction. When single species is considered, the near surface soil-moisture available from HR during dry summer season is an important source of evaporation and contributes significantly to the total ET flux. However, when multi-species interactions are taken into account, the soil-water from the HR becomes an important source of transpiration from the understory. The results also show that passive plant nitrogen uptake is higher when HR is present and it is critical for sustaining expected rates of carbon assimilation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860030863&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DSoil%2Buse','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860030863&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DSoil%2Buse"><span>The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.</p> <p>1985-01-01</p> <p>Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28311647','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28311647"><span>Interaction of vascular plants and vesicular-arbuscular mycorrhizal fungi across a soil moisture-nutrient gradient.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Anderson, R C; Liberta, A E; Dickman, L A</p> <p>1984-09-01</p> <p>Abundance and distribution of vascular plants and vesicular-arbuscular mycorrhizal (VAM) fungi across a soil moisture-nutrient gradient were studied at a single site. Vegetation on the site varied from a dry mesic paririe dominated by little bluestem (Schizachyrium scoparium) to emergent aquatic vegetation dominated by cattail (Typha latifolia) and water smartweed (Polygonum hydropiperoides). Plant cover, VAM spore abundance, plant species richness, and number of VAM fungi represented as spores, had significant positive correlations with each other and with percent organic matter. The plant and VAM spore variables had significant negative correlations with soil pH and available Ca, Mg, P and gravimetric soil moisture. Using stepwise multiple regression, Ca was found to be the best predictor of spore abundance. Test for association between plant species and VAM fungal spores indicated that the spores of Glomus caledonium are associated with plants from dry, nutrient poor sites and spores of gigaspora gigantea are positively associated with plants occurring on the wet, relatively nutrient rich sites. Glomus fasciculatum was the most abundant and widely distributed VAM fungus and it had more positive associations with endophyte hosts than the other VAM fungi. We found no relationship between beta niche breadth of plant species and the presence or absence of mycorrhizal infection. However, our data suggest that some plant species may vary with respect to their infection status depending upon soil moisture conditions that may fluctuate seasonally or annually to favor or hinder VAM associations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820016726','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820016726"><span>Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)</p> <p>1981-01-01</p> <p>Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013309','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013309"><span>SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann</p> <p>2011-01-01</p> <p>Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356"><span>Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun</p> <p>2018-01-01</p> <p>To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy. PMID:29883420</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PhDT........24F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PhDT........24F"><span>Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fang, Bin</p> <p></p> <p>In recent years the passive microwave remote sensing has been providing soil moisture products using instruments on board satellite/airborne platforms. Spatial resolution has been restricted by the diameter of antenna which is inversely proportional to resolution. As a result, typical products have a spatial resolution of tens of kilometers, which is not compatible for some hydrological research applications. For this reason, the dissertation explores three disaggregation algorithms that estimate L-band passive microwave soil moisture at the subpixel level by using high spatial resolution remote sensing products from other optical and radar instruments were proposed and implemented in this investigation. The first technique utilized a thermal inertia theory to establish a relationship between daily temperature change and average soil moisture modulated by the vegetation condition was developed by using NLDAS, AVHRR, SPOT and MODIS data were applied to disaggregate the 25 km AMSR-E soil moisture to 1 km in Oklahoma. The second algorithm was built on semi empirical physical models (NP89 and LP92) derived from numerical experiments between soil evaporation efficiency and soil moisture over the surface skin sensing depth (a few millimeters) by using simulated soil temperature derived from MODIS and NLDAS as well as AMSR-E soil moisture at 25 km to disaggregate the coarse resolution soil moisture to 1 km in Oklahoma. The third algorithm modeled the relationship between the change in co-polarized radar backscatter and the remotely sensed microwave change in soil moisture retrievals and assumed that change in soil moisture was a function of only the canopy opacity. The change detection algorithm was implemented using aircraft based the remote sensing data from PALS and UAVSAR that were collected in SMPAVEX12 in southern Manitoba, Canada. The PALS L-band h-polarization radiometer soil moisture retrievals were disaggregated by combining them with the PALS and UAVSAR L-band hh-polarization radar spatial resolutions of 1500 m and 5 m/800 m, respectively. All three algorithms were validated using ground measurements from network in situ stations or handheld hydra probes. The validation results demonstrate the practicability on coarse resolution passive microwave soil moisture products.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29883420','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29883420"><span>Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gao, Zhenran; Zhu, Yan; Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun</p> <p>2018-05-21</p> <p>To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0⁻100 cm. According to the calibration results, the degree of fitting ( R ²) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0⁻1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R ² of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R ² between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R ² between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918200F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918200F"><span>On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fois, Laura; Montaldo, Nicola</p> <p>2017-04-01</p> <p>Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9637E..1FG','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9637E..1FG"><span>Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.</p> <p>2015-10-01</p> <p>The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011920','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011920"><span>Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20110011920'); toggleEditAbsImage('author_20110011920_show'); toggleEditAbsImage('author_20110011920_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20110011920_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20110011920_hide"></p> <p>2011-01-01</p> <p>The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780"><span>Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The diversity of in situ soil moisture network protocols and instrumentation led to the development of a testbed for comparing in situ soil moisture sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each station ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459"><span>Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098"><span>On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=338364','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=338364"><span>Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70036305','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70036305"><span>Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>O'Donnell, J. A.; Harden, J.W.; McGuire, A.D.; Romanovsky, V.E.</p> <p>2011-01-01</p> <p>In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil moisture, and snow depth) and fire severity. We also conducted sensitivity analyses to explore the combined effects of fire-soil moisture interactions and snow seasonality on OC storage. OC losses were calculated as the difference in OC stocks after three fire cycles (???500 yr) following a prescribed step-change in climate and/or fire. Across single-factor scenarios, our findings indicate that warmer air temperatures resulted in the largest relative soil OC losses (???5.3 kg C mg-2), whereas dry soil conditions alone (in the absence of wildfire) resulted in the smallest carbon losses (???0.1 kg C mg-2). Increased fire severity resulted in carbon loss of ???3.3 kg C mg-2, whereas changes in snow depth resulted in smaller OC losses (2.1-2.2 kg C mg-2). Across multiple climate factors, we observed larger OC losses than for single-factor scenarios. For instance, high fire severity regime associated with warmer and drier conditions resulted in OC losses of ???6.1 kg C mg-2, whereas a low fire severity regime associated with warmer and wetter conditions resulted in OC losses of ???5.6 kg C mg-2. A longer snow-free season associated with future warming resulted in OC losses of ???5.4 kg C mg-2. Soil climate was the dominant control on soil OC loss, governing the sensitivity of microbial decomposers to fluctuations in temperature and soil moisture; this control, in turn, is governed by interannual changes in active layer depth. Transitional responses of the active layer depth to fire regimes also contributed to OC losses, primarily by determining the proportion of OC into frozen and unfrozen soil layers. ?? 2011 Author(s).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20180002841','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20180002841"><span>Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lawston, Patricia M.; Santanello, Joseph A.; Rodell, Matthew; Franz, Trenton E.</p> <p>2017-01-01</p> <p>Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H21G1493S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H21G1493S"><span>Multivariate Drought Characterization in India for Monitoring and Prediction</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sreekumaran Unnithan, P.; Mondal, A.</p> <p>2016-12-01</p> <p>Droughts are one of the most important natural hazards that affect the society significantly in terms of mortality and productivity. The metric that is most widely used by the India Meteorological Department (IMD) to monitor and predict the occurrence, spread, intensification and termination of drought is based on the univariate Standardized Precipitation Index (SPI). However, droughts may be caused by the influence and interaction of many variables (such as precipitation, soil moisture, runoff, etc.), emphasizing the need for a multivariate approach for drought characterization. This study advocates and illustrates use of the recently proposed multivariate standardized drought index (MSDI) in monitoring and prediction of drought and assessing its concerned risk in the Indian region. MSDI combines information from multiple sources: precipitation and soil moisture, and has been deemed to be a more reliable drought index. All-India monthly rainfall and soil moisture data sets are analysed for the period 1980 to 2014 to characterize historical droughts using both the univariate indices, the precipitation-based SPI and the standardized soil moisture index (SSI), as well as the multivariate MSDI using parametric and non-parametric approaches. We confirm that MSDI can capture droughts of 1986 and 1990 that aren't detected by using SPI alone. Moreover, in 1987, MSDI indicated a higher severity of drought when a deficiency in both soil moisture and precipitation was encountered. Further, this study also explores the use of MSDI for drought forecasts and assesses its performance vis-à-vis existing predictions from the IMD. Future research efforts will be directed towards formulating a more robust standardized drought indicator that can take into account socio-economic aspects that also play a key role for water-stressed regions such as India.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020081274','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020081274"><span>On Simulating the Mid-western-us Drought of 1988 with a GCM</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sud, Y. C.; Mocko, D. M.; Lau, William K.-M.; Atlas, R.</p> <p>2002-01-01</p> <p>The primary cause of the midwestern North American drought in the summer of 1988 has been identified to be the La Nina SST anomalies. Yet with the SST anomalies prescribed, this drought has not been simulated satisfactorily by any general circulation model. Seven simulation-experiments, each containing an ensemble of 4-sets of simulations, were conducted with the GEOS GCM for both 1987 and 1988. All simulations started from January 1 and continued through the end of August. In the first baseline case, Case 1, only the SST anomalies and some vegetation parameters were prescribed, while everything else (such as soil moisture, snow-cover, and clouds) was interactive. The GCM did produce some of the circulation features of a drought over North America, but they could only be identified on the planetary scales. The 1988 minus 1987 precipitation differences show that the GCM was successful in simulating reduced precipitation in the mid-west, but the accompanying circulation anomalies were not well simulated, leading one to infer that the GCM has simulated the drought for the wrong reason. To isolate the causes for this unremarkable circulation, analyzed winds and soil moisture were prescribed in Case 2 and Case 3 as continuous updates by direct replacement of the GCM-predicted fields. These cases show that a large number of simulation biases emanate from wind biases that are carried into the North American region from surroundings regions. Inclusion of soil moisture also helps to ameliorate the strong feedback, perhaps even stronger than that of the real atmosphere, between soil moisture and precipitation. Case 2 simulated one type of surface temperature anomaly pattern, whereas Case 3 with the prescribed soil moisture produced another.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70031549','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70031549"><span>Effects of rainfall seasonality and soil moisture capacity on mean annual water balance for Australian catchments</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Potter, N.J.; Zhang, L.; Milly, P.C.D.; McMahon, T.A.; Jakeman, A.J.</p> <p>2005-01-01</p> <p>An important factor controlling catchment‐scale water balance is the seasonal variation of climate. The aim of this study is to investigate the effect of the seasonal distributions of water and energy, and their interactions with the soil moisture store, on mean annual water balance in Australia at catchment scales using a stochastic model of soil moisture balance with seasonally varying forcing. The rainfall regime at 262 catchments around Australia was modeled as a Poisson process with the mean storm arrival rate and the mean storm depth varying throughout the year as cosine curves with annual periods. The soil moisture dynamics were represented by use of a single, finite water store having infinite infiltration capacity, and the potential evapotranspiration rate was modeled as an annual cosine curve. The mean annual water budget was calculated numerically using a Monte Carlo simulation. The model predicted that for a given level of climatic aridity the ratio of mean annual evapotranspiration to rainfall was larger where the potential evapotranspiration and rainfall were in phase, that is, in summer‐dominant rainfall catchments, than where they were out of phase. The observed mean annual evapotranspiration ratios have opposite results. As a result, estimates of mean annual evapotranspiration from the model compared poorly with observational data. Because the inclusion of seasonally varying forcing alone was not sufficient to explain variability in the mean annual water balance, other catchment properties may play a role. Further analysis showed that the water balance was highly sensitive to the catchment‐scale soil moisture capacity. Calibrations of this parameter indicated that infiltration‐excess runoff might be an important process, especially for the summer‐dominant rainfall catchments; most similar studies have shown that modeling of infiltration‐excess runoff is not required at the mean annual timescale.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313269','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313269"><span>Understanding Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Understanding soil moisture is critical for landscape irrigation management. This landscaep irrigation seminar will compare volumetric and matric potential soil-moisture sensors, discuss the relationship between their readings and demonstrate how to use these data. Soil water sensors attempt to sens...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMEP31A0990P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMEP31A0990P"><span>Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.</p> <p>2015-12-01</p> <p>The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B41I2077M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B41I2077M"><span>Effect of soil moisture on the temperature sensitivity of Northern soils</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.</p> <p>2017-12-01</p> <p>Arctic and boreal ecosystems are vast reservoirs of carbon and are particularly sensitive to climate warming. Changes in the temperature and precipitation regimes of these regions could significantly alter soil respiration rates, impacting atmospheric concentrations and affecting climate change feedbacks. Many incubation studies have shown that both temperature and soil moisture are important environmental drivers of soil respiration; this relationship, however, has rarely been demonstrated with in situ data. Here we present the results of a study at six field sites in Alaska from 2016 to 2017. Low-power automated soil gas systems were used to measure soil surface CO2 flux from three forced diffusion chambers and soil profile concentrations from three soil depth chambers at hourly intervals at each site. HOBO Onset dataloggers were used to monitor soil moisture and temperature profiles. Temperature sensitivity (Q10) was determined at each site using inversion analysis applied over different time periods. With highly resolved data sets, we were able to observe the changes in soil respiration in response to changes in temperature and soil moisture. Through regression analysis we confirmed that temperature is the primary driver in soil respiration, but soil moisture becomes dominant beyond a certain threshold, suppressing CO2 flux in soils with high moisture content. This field study supports the conclusions made from previous soil incubation studies and provides valuable insights into the impact of both temperature and soil moisture changes on soil respiration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51I1508E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51I1508E"><span>Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.</p> <p>2015-12-01</p> <p>The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.7170B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.7170B"><span>Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.</p> <p>2009-04-01</p> <p>Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012WRR....48.8509F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012WRR....48.8509F"><span>Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara</p> <p>2012-08-01</p> <p>Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..557...97N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..557...97N"><span>Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio</p> <p>2018-02-01</p> <p>Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3864533','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3864533"><span>Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François</p> <p>2007-01-01</p> <p>Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870052970&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Devapotranspiration','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870052970&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Devapotranspiration"><span>Concerning the relationship between evapotranspiration and soil moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wetzel, Peter J.; Chang, Jy-Tai</p> <p>1987-01-01</p> <p>The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916217M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916217M"><span>A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu</p> <p>2017-04-01</p> <p>Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.8017E..10H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.8017E..10H"><span>High-resolution soil moisture mapping in Afghanistan</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry</p> <p>2011-06-01</p> <p>Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100031160','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100031160"><span>Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt</p> <p>2010-01-01</p> <p>Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1210783B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1210783B"><span>Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry</p> <p>2010-05-01</p> <p>Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22127183','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22127183"><span>Pupal development of Ceratitis capitata (Diptera: Tephritidae) and Diachasmimorpha longicaudata (Hymenoptera: Braconidae) at different moisture values in four soil types.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bento, F de M M; Marques, R N; Costa, M L Z; Walder, J M M; Silva, A P; Parra, J R P</p> <p>2010-08-01</p> <p>This study aimed to evaluate adult emergence and duration of the pupal stage of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), and emergence of the fruit fly parasitoid, Diachasmimorpha longicaudata (Ashmead), under different moisture conditions in four soil types, using soil water matric potential. Pupal stage duration in C. capitata was influenced differently for males and females. In females, only soil type affected pupal stage duration, which was longer in a clay soil. In males, pupal stage duration was individually influenced by moisture and soil type, with a reduction in pupal stage duration in a heavy clay soil and in a sandy clay, with longer duration in the clay soil. As matric potential decreased, duration of the pupal stage of C. capitata males increased, regardless of soil type. C. capitata emergence was affected by moisture, regardless of soil type, and was higher in drier soils. The emergence of D. longicaudata adults was individually influenced by soil type and moisture factors, and the number of emerged D. longicaudata adults was three times higher in sandy loam and lower in a heavy clay soil. Always, the number of emerged adults was higher at higher moisture conditions. C. capitata and D. longicaudata pupal development was affected by moisture and soil type, which may facilitate pest sampling and allow release areas for the parasitoid to be defined under field conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015872','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015872"><span>Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ballard, Jerrell R., Jr.; Howington, Stacy E.; Cinnella, Pasquale; Smith, James A.</p> <p>2011-01-01</p> <p>The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26470371','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26470371"><span>Indirect Effects of Field Management on Pollination Service and Seed Set in Hybrid Onion Seed Production.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gillespie, Sandra; Long, Rachael; Williams, Neal</p> <p>2015-12-01</p> <p>Pollination in crops, as in native ecosystems, is a stepwise process that can be disrupted at any stage. Healthy pollinator populations are critical for adequate visitation, but pollination still might fail if crop management interferes with the attraction and retention of pollinators. Farmers must balance the direct benefits of applying insecticide and managing irrigation rates against their potential to indirectly interfere with the pollination process. We investigated these issues in hybrid onion seed production, where previous research has shown that high insecticide use reduces pollinator attraction. We conducted field surveys of soil moisture, nectar production, pollinator visitation, pollen-stigma interactions, and seed set at multiple commercial fields across 2 yr. We then examined how management actions, such as irrigation rate (approximated by soil moisture), or insecticide use could affect the pollination process. Onions produced maximum nectar at intermediate soil moisture, and high nectar production attracted more pollinators. Insecticide use weakly affected pollinator visitation, but when applied close to bloom reduced pollen germination and pollen tube growth. Ultimately, neither soil moisture nor insecticide use directly affected seed set, but the high correlation between pollinator visitation and seed set suggests that crop management will ultimately affect yields via indirect effects on the pollination process. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007420','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007420"><span>Development and Validation of The SMAP Enhanced Passive Soil Moisture Product</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chan, S.; Bindlish, R.; O'Neill, P.; Jackson, T.; Chaubell, J.; Piepmeier, J.; Dunbar, S.; Colliander, A.; Chen, F.; Entekhabi, D.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170007420'); toggleEditAbsImage('author_20170007420_show'); toggleEditAbsImage('author_20170007420_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170007420_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170007420_hide"></p> <p>2017-01-01</p> <p>Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8087G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8087G"><span>Soil moisture retrival from Sentinel-1 and Modis synergy</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas</p> <p>2017-04-01</p> <p>This study presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). In the two methodologies using change detection techniques, preprocessed radar data are combined with normalized difference vegetation index (NDVI) auxiliary data to estimate the mean soil moisture with a resolution of 1km. By modeling the relationship between the backscatter difference and NDVI, the soil moisture at a specific NDVI value is retrieved. The first algorithm is already developed on West Africa(Zribi et al., 2014) from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The proposed methodologies have been validated with the ground measurement in two demonstrative fields with RMS error about 0.05 (in volumetric moisture), and the coherence between soil moisture variations and rainfall events is observed. Soil moisture maps at 1km resolution are generated for the study area. The results demonstrate the potential of Sentinel-1 data for the retrieval of soil moisture at 1km or even better resolution.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29599664','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29599664"><span>Evaluating ESA CCI soil moisture in East Africa.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P</p> <p>2016-06-01</p> <p>To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R>0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=345204','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=345204"><span>Irrigation scheduling using soil moisture sensors</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Soil moisture sensors were evaluated and used for irrigation scheduling in humid region. Soil moisture sensors were installed in soil at depths of 15cm, 30cm, and 61cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop g...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdWR..111..224Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdWR..111..224Z"><span>Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Hongjuan; Kurtz, Wolfgang; Kollet, Stefan; Vereecken, Harry; Franssen, Harrie-Jan Hendricks</p> <p>2018-01-01</p> <p>The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810020962','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810020962"><span>Soil moisture inferences from thermal infrared measurements of vegetation temperatures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jackson, R. D. (Principal Investigator)</p> <p>1981-01-01</p> <p>Thermal infrared measurements of wheat (Triticum durum) canopy temperatures were used in a crop water stress index to infer root zone soil moisture. Results indicated that one time plant temperature measurement cannot produce precise estimates of root zone soil moisture due to complicating plant factors. Plant temperature measurements do yield useful qualitative information concerning soil moisture and plant condition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780015703','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780015703"><span>Soil moisture modeling review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hildreth, W. W.</p> <p>1978-01-01</p> <p>A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015E%26ES...25a2014B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015E%26ES...25a2014B"><span>Soil moisture monitoring for crop management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boyd, Dale</p> <p>2015-07-01</p> <p>The 'Risk management through soil moisture monitoring' project has demonstrated the capability of current technology to remotely monitor and communicate real time soil moisture data. The project investigated whether capacitance probes would assist making informed pre- and in-crop decisions. Crop potential and cropping inputs are increasingly being subject to greater instability and uncertainty due to seasonal variability. In a targeted survey of those who received regular correspondence from the Department of Primary Industries it was found that i) 50% of the audience found the information generated relevant for them and less than 10% indicted with was not relevant; ii) 85% have improved their knowledge/ability to assess soil moisture compared to prior to the project, with the most used indicator of soil moisture still being rain fall records; and iii) 100% have indicated they will continue to use some form of the technology to monitor soil moisture levels in the future. It is hoped that continued access to this information will assist informed input decisions. This will minimise inputs in low decile years with a low soil moisture base and maximise yield potential in more favourable conditions based on soil moisture and positive seasonal forecasts</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023466','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023466"><span>A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.</p> <p>2011-01-01</p> <p>Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034255','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034255"><span>Remote sensing of soil moisture using airborne hyperspectral data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.</p> <p>2011-01-01</p> <p>Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159491','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159491"><span>Remote sensing of soil moisture using airborne hyperspectral data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.</p> <p>2011-01-01</p> <p>Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70032687','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70032687"><span>Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.</p> <p>2008-01-01</p> <p>The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JESS..127...24M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JESS..127...24M"><span>Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moradizadeh, Mina; Saradjian, Mohammad R.</p> <p>2018-03-01</p> <p>Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3697171','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3697171"><span>On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco</p> <p>2008-01-01</p> <p>Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. PMID:27879932</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19940015982&hterms=neural+net&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dneural%2Bnet','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19940015982&hterms=neural+net&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dneural%2Bnet"><span>Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.</p> <p>1993-01-01</p> <p>This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdWR..113...23L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdWR..113...23L"><span>The impact of fog on soil moisture dynamics in the Namib Desert</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.</p> <p>2018-03-01</p> <p>Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001376"><span>Assimilation of SMOS Retrieved Soil Moisture into the Land Information System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary</p> <p>2014-01-01</p> <p>Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830020554','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830020554"><span>A study of the influence of soil moisture on future precipitation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fennessy, M. J.; Sud, Y. C.</p> <p>1983-01-01</p> <p>Forty years of precipitation and surface temperature data observed over 261 Local Climatic Data (LCD) stations in the Continental United States was utilized in a ground hydrology model to yield soil moisture time series at each station. A month-by-month soil moisture dataset was constructed for each year. The monthly precipitation was correlated with antecedent monthly precipitation, soil moisture and vapotranspiration separately. The maximum positive correlation is found to be in the drought prone western Great Plains region during the latter part of summer. There is also some negative correlation in coastal regions. The correlations between soil moisture and precipitation particularly in the latter part of summer, suggest that large scale droughts over extended periods may be partially maintained by the feedback influence of soil moisture on rainfall. In many other regions the lack of positive correlation shows that there is no simple answer such as higher land-surface evapotranspiration leads to more precipitation, and points out the complexity of the influence of soil moisture on the ensuring precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817485W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817485W"><span>The role of topographic structure and soil macrofauna presence at spoil heaps during spontaneous succession.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Walmsley, Alena; Vachová, Pavla; Vach, Marek</p> <p>2016-04-01</p> <p>This research was investigating whether topographic features, which determine soil nutrient and moisture distribution, in combination with soil fauna (wireworm and earthworm) presence, affect plant community composition at a spontaneously revegetated post mining area with an undulating surface. Two sites of different age with 3 types of topographic features were selected, soil moisture and nutrient content were measured, plant community composition and soil macrofauna community was sampled at each position. Wireworms were present at all positions and were most abundant at bottoms of waves at the younger site; their presence was correlated with several plant species, but the direction of the interaction isn't clear. Earthworms were only present at the older site and had highest abundance at flat sections. Earthworm presence affected the amount of nitrogen in soil - the most nitrogen content was at the site with highest earthworm density and was followed by higher diversity of plant community. The plant community composition was generally correlated with plant available nutrient content - especially P and N. We infer that topographic features affect nutrient and soil fauna distribution, which consequently influences plant community composition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..535..637Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..535..637Z"><span>Misrepresentation and amendment of soil moisture in conceptual hydrological modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhuo, Lu; Han, Dawei</p> <p>2016-04-01</p> <p>Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9299E..0JW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9299E..0JW"><span>An integrated GIS application system for soil moisture data assimilation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang</p> <p>2014-11-01</p> <p>The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MeScT..28b4002E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MeScT..28b4002E"><span>On-irrigator pasture soil moisture sensor</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian</p> <p>2017-02-01</p> <p>In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900028789&hterms=drought+california&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought%2Bcalifornia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900028789&hterms=drought+california&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought%2Bcalifornia"><span>Soil moisture and the persistence of North American drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oglesby, Robert J.; Erickson, David J., III</p> <p>1989-01-01</p> <p>Numerical sensitivity experiments on the effects of soil moisture on North American summertime climate are performed using a 12-layer global atmospheric general circulation model. Consideration is given to the hypothesis that reduced soil moisture may induce and amplify warm, dry summers of midlatitude continental interiors. The simulations resemble the conditions of the summer of 1988, including an extensive drought over much of North America. It is found that a reduction in soil moisture leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. It is shown that low-level moisture advection from the Gulf of Mexico is important in the maintenance of persistent soil moisture deficits.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313267','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313267"><span>Soil-moisture sensors and irrigation management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>This agricultural irrigation seminar will cover the major classes of soil-moisture sensors; their advantages and disadvantages; installing and reading soil-moisture sensors; and using their data for irrigation management. The soil water sensor classes include the resistance sensors (gypsum blocks, g...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23554915','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23554915"><span>Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M</p> <p>2013-01-01</p> <p>Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007422','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007422"><span>Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Colliander, Andreas; Jackson, Thomas J.; Cosh, Mike; Misra, Sidharth; Bindlish, Rajat; Powers, Jarrett; McNairn, Heather; Bullock, P.; Berg, A.; Magagi, A.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170007422'); toggleEditAbsImage('author_20170007422_show'); toggleEditAbsImage('author_20170007422_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170007422_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170007422_hide"></p> <p>2017-01-01</p> <p>NASA's SMAP (Soil Moisture Active Passive) calibration and validation program revealed that the soil moisture products are experiencing difficulties in meeting the mission requirements in certain agricultural areas. Therefore, the mission organized airborne field experiments at two core validation sites to investigate these anomalies. The SMAP Validation Experiment 2016 included airborne observations with the PALS (Passive Active L-band Sensor) instrument and intensive ground sampling. The goal of the PALS measurements are to investigate the soil moisture retrieval algorithm formulation and parameterization under the varying (spatially and temporally) conditions of the agricultural domains and to obtain high resolution soil moisture maps within the SMAP pixels. In this paper the soil moisture retrieval using the PALS brightness temperature observations in SMAPVEX16 is presented.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H23G1651H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H23G1651H"><span>Measuring Soil Moisture using the Signal Strength of Buried Bluetooth Devices.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hut, R.; Campbell, C. S.</p> <p>2015-12-01</p> <p>A low power bluetooth Low Energy (BLE) device is burried 20cm into the soil and a smartphone is placed on top of the soil to test if bluetooth signal strength can be related to soil moisture. The smartphone continuesly records and stores bluetooth signal strength of the device. The soil is artifcially wetted and drained. Results show a relation between BLE signal strength and soil moisture that could be used to measure soil moisture using these off-the-shelf consumer electronics. This opens the possibily to develop sensors that can be buried into the soil, possibly below the plow-line. These sensors can measure local parameters such as electric conductivity, ph, pressure, etc. Readings would be uploaded to a device on the surface using BLE. The signal strength of this BLE would be an (additional) measurement of soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19790010347','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19790010347"><span>An empirical model for the complex dielectric permittivity of soils as a function of water content</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, J. R.; Chmugge, T. J.</p> <p>1978-01-01</p> <p>The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.5660A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.5660A"><span>Surface soil moisture retrieval over a Mediterranean semi-arid region using X-band TerraSAR-X SAR data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Azza, Gorrab; Zribi, Mehrez; Baghdadi, Nicolas; Mougenot, Bernard; Boulet, Gilles; Lili-Chabaane, Zohra</p> <p>2015-04-01</p> <p>Mapping surface soil moisture with meter-scale spatial resolution is appropriate for multi- domains particularly hydrology and agronomy. It allows water resources and irrigation management decisions, drought monitoring and validation of multi-hydrological water balance models. In the last years, various studies have demonstrated the large potential of radar remote sensing data, mainly from C frequency band, to retrieve soil moisture. However, the accuracy of the soil moisture estimation, by inversing backscattering radar coefficients (σ°), is affected by the influence of surface roughness and vegetation biomass contributions. In recent years, different empirical, semi empirical and physical approaches are developed for bare soil conditions, to estimate accurately spatial soil moisture variability. In this study, we propose an approach based on the change detection method for the retrieval of surface soil moisture at a higher spatial resolution. The proposal algorithm combines multi-temporal X-band SAR images (TerraSAR-X) with different continuous thetaprobe measurements. Seven thetaprobe stations are installed at different depths over the central semi arid region of Tunisia (9°23' - 10°17' E, 35° 1'-35°55' N). They cover approximately the entire of our study site and provide regional scale information. Ground data were collected over agricultural bare soil fields simultaneously to various TerraSAR-X data acquired during 2013-2014 and 2014-2015. More than fourteen test fields were selected for each spatial acquisition campaign, with variations in soil texture and in surface soil roughness. For each date, we considered the volumetric water content with thetaprobe instrument and gravimetric sampling; we measured also the roughness parameters with pin profilor. To retrieve soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our analyses are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of the measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: On the first one, we applied the change detection approach between successive radar images (∆σ°) assuming unchanged soil roughness effects. Our soil moisture retrieval algorithm was validated on the basis of comparisons between estimated and in situ soil moisture measurements over test fields. Using this option, results have shown an accuracy (RMSE) of about 4.8 %. Secondly, we corrected the sensitivity of the radar backscatter images to the surface roughness variability. Results have shown a reduction of the difference between the retrieved soil moisture and ground measurements with an RMSE about 3.7%.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMEP43E..03C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMEP43E..03C"><span>Analysis of in situ resources for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cosh, M. H.; Jackson, T. J.; Colliander, A.; Bindlish, R.; McKee, L.; Goodrich, D. C.; Prueger, J. H.; Hornbuckle, B. K.; Coopersmith, E. J.; Holifield Collins, C.; Smith, J.</p> <p>2016-12-01</p> <p>With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliable. Therefore, in order to demonstrate the accuracy of the soil moisture product, NASA enacted an extensive calibration and validation program with many in situ soil moisture networks contributing data across a variety of landscape regimes. However, not all questions can be answered by these networks. As a result, two intensive field experiments were executed to provide more detailed reference points for calibration and validation. Multi-week field campaigns were conducted in Arizona and Iowa at the USDA Agricultural Research Service Walnut Gulch and South Fork Experimental Watersheds, respectively. Aircraft observations were made to provide a high resolution data product. Soil moisture, soil roughness and vegetation data were collected at high resolution to provide a downscaled dataset to compare against aircraft and satellite estimates.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790008163&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790008163&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation"><span>Soil moisture estimation using reflected solar and emitted thermal infrared radiation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.</p> <p>1978-01-01</p> <p>Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000004216&hterms=Soil+sampling+radiation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSoil%2Bsampling%2Bradiation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000004216&hterms=Soil+sampling+radiation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSoil%2Bsampling%2Bradiation"><span>Passive Microwave Remote Sensing of Soil Moisture</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Njoku, Eni G.; Entekhabi, Dara</p> <p>1996-01-01</p> <p>Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830019265','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830019265"><span>The sensitivity of numerically simulated climates to land-surface boundary conditions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mintz, Y.</p> <p>1982-01-01</p> <p>Eleven sensitivity experiments that were made with general circulation models to see how land-surface boundary conditions can influence the rainfall, temperature, and motion fields of the atmosphere are discussed. In one group of experiments, different soil moistures or albedos are prescribed as time-invariant boundary conditions. In a second group, different soil moistures or different albedos are initially prescribed, and the soil moisture (but not the albedo) is allowed to change with time according to the governing equations for soil moisture. In a third group, the results of constant versus time-dependent soil moistures are compared.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950027395','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950027395"><span>Application of IEM model on soil moisture and surface roughness estimation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.</p> <p>1995-01-01</p> <p>Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910031252&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910031252&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dsoil%2Bmaps"><span>Remotely sensed soil moisture input to a hydrologic model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Engman, E. T.; Kustas, W. P.; Wang, J. R.</p> <p>1989-01-01</p> <p>The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.H33H..06B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.H33H..06B"><span>Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.</p> <p>2010-12-01</p> <p>With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/931353-direct-indirect-effects-atmospheric-conditions-soil-moisture-surface-energy-partitioning-revealed-prolonged-drought-temperate-forest-site','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/931353-direct-indirect-effects-atmospheric-conditions-soil-moisture-surface-energy-partitioning-revealed-prolonged-drought-temperate-forest-site"><span>Direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning revealed by a prolonged drought at a temperate forest site</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Gu, Lianhong; Meyers, T. P.; Pallardy, Stephen G.</p> <p>2006-01-01</p> <p>The purpose of this paper is to examine the mechanism that controls the variation of surface energy partitioning between latent and sensible heat fluxes at a temperate deciduous forest site in central Missouri, USA. Taking advantage of multiple micrometeorological and ecophysiological measurements and a prolonged drought in the middle of the 2005 growing season at this site, we studied how soil moisture, atmospheric vapor pressure deficit (VPD), and net radiation affected surface energy partitioning. We stratified these factors to minimize potential confounding effects of correlation among them. We found that all three factors had direct effects on surface energy partitioning,more » but more important, all three factors also had crucial indirect effects. The direct effect of soil moisture was characterized by a rapid decrease in Bowen ratio with increasing soil moisture when the soil was dry and by insensitivity of Bowen ratio to variations in soil moisture when the soil was wet. However, the rate of decrease in Bowen ratio when the soil was dry and the level of soil moisture above which Bowen ratio became insensitive to changes in soil moisture depended on atmospheric conditions. The direct effect of increased net radiation was to increase Bowen ratio. The direct effect of VPD was very nonlinear: Increased VPD decreased Bowen ratio at low VPD but increased Bowen ratio at high VPD. The indirect effects were much more complicated. Reduced soil moisture weakened the influence of VPD but enhanced the influence of net adiation on surface energy partitioning. Soil moisture also controlled how net radiation influenced the relationship between surface energy partitioning and VPD and how VPD affected the relationship between surface energy partitioning and net radiation. Furthermore, both increased VPD and increased net radiation enhanced the sensitivity of Bowen ratio to changes in soil moisture and the effect of drought on surface energy partitioning. The direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning identified in this paper provide a target for testing atmospheric general circulation models in their representation of land-atmosphere coupling.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22303673','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22303673"><span>[Simulation of cropland soil moisture based on an ensemble Kalman filter].</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping</p> <p>2011-11-01</p> <p>By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.4869C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.4869C"><span>Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.</p> <p>2018-05-01</p> <p>Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H42B..02K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H42B..02K"><span>Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.</p> <p>2017-12-01</p> <p>We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70185708','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70185708"><span>Divergent surface and total soil moisture projections under global warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.</p> <p>2017-01-01</p> <p>Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.132....1L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.132....1L"><span>Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Legates, David R.; Junghenn, Katherine T.</p> <p>2018-04-01</p> <p>Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53D0921Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53D0921Z"><span>Dynamics and characteristics of soil temperature and moisture of active layer in central Tibetan Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, L.; Hu, G.; Wu, X.; Tian, L.</p> <p>2017-12-01</p> <p>Research on the hydrothermal properties of active layer during the thawing and freezing processes was considered as a key question to revealing the heat and moisture exchanges between permafrost and atmosphere. The characteristics of freezing and thawing processes at Tanggula (TGL) site in permafrost regions on the Tibetan Plateau, the results revealed that the depth of daily soil temperature transmission was about 40 cm shallower during thawing period than that during the freezing period. Soil warming process at the depth above 140 cm was slower than the cooling process, whereas they were close below 140 cm depth. Moreover, the hydro-thermal properties differed significantly among different stages. Precipitation caused an obviously increase in soil moisture at 0-20 cm depth. The vertical distribution of soil moisture could be divided into two main zones: less than 12% in the freeze state and greater than 12% in the thaw state. In addition, coupling of moisture and heat during the freezing and thawing processes also showed that soil temperature decreased faster than soil moisture during the freezing process. At the freezing stage, soil moisture exhibited an exponential relationship with the absolute soil temperature. Energy consumed for water-ice conversion during the freezing process was 149.83 MJ/m2 and 141.22 MJ/m2 in 2011 and 2012, respectively, which was estimated by the soil moisture variation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24459432','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24459432"><span>Responses of ecosystem CO 2 fluxes to short-term experimental warming and nitrogen enrichment in an Alpine meadow, northern Tibet Plateau.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zong, Ning; Shi, Peili; Jiang, Jing; Song, Minghua; Xiong, Dingpeng; Ma, Weiling; Fu, Gang; Zhang, Xianzhou; Shen, Zhenxi</p> <p>2013-01-01</p> <p>Over the past decades, the Tibetan Plateau has experienced pronounced warming, yet the extent to which warming will affect alpine ecosystems depends on how warming interacts with other influential global change factors, such as nitrogen (N) deposition. A long-term warming and N manipulation experiment was established to investigate the interactive effects of warming and N deposition on alpine meadow. Open-top chambers were used to simulate warming. N addition, warming, N addition × warming, and a control were set up. In OTCs, daytime air and soil temperature were warmed by 2.0°C and 1.6°C above ambient conditions, but soil moisture was decreased by 4.95 m(3) m(-3). N addition enhanced ecosystem respiration (Reco); nevertheless, warming significantly decreased Reco. The decline of Reco resulting from warming was cancelled out by N addition in late growing season. Our results suggested that N addition enhanced Reco by increasing soil N availability and plant production, whereas warming decreased Reco through lowering soil moisture, soil N supply potential, and suppression of plant activity. Furthermore, season-specific responses of Reco indicated that warming and N deposition caused by future global change may have complicated influence on carbon cycles in alpine ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3891229','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3891229"><span>Responses of Ecosystem CO2 Fluxes to Short-Term Experimental Warming and Nitrogen Enrichment in an Alpine Meadow, Northern Tibet Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Shi, Peili; Jiang, Jing; Song, Minghua; Xiong, Dingpeng; Ma, Weiling; Fu, Gang; Zhang, Xianzhou; Shen, Zhenxi</p> <p>2013-01-01</p> <p>Over the past decades, the Tibetan Plateau has experienced pronounced warming, yet the extent to which warming will affect alpine ecosystems depends on how warming interacts with other influential global change factors, such as nitrogen (N) deposition. A long-term warming and N manipulation experiment was established to investigate the interactive effects of warming and N deposition on alpine meadow. Open-top chambers were used to simulate warming. N addition, warming, N addition × warming, and a control were set up. In OTCs, daytime air and soil temperature were warmed by 2.0°C and 1.6°C above ambient conditions, but soil moisture was decreased by 4.95 m3 m−3. N addition enhanced ecosystem respiration (Reco); nevertheless, warming significantly decreased Reco. The decline of Reco resulting from warming was cancelled out by N addition in late growing season. Our results suggested that N addition enhanced Reco by increasing soil N availability and plant production, whereas warming decreased Reco through lowering soil moisture, soil N supply potential, and suppression of plant activity. Furthermore, season-specific responses of Reco indicated that warming and N deposition caused by future global change may have complicated influence on carbon cycles in alpine ecosystems. PMID:24459432</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100003022&hterms=space+missions+archive&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dspace%2Bmissions%2Barchive','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100003022&hterms=space+missions+archive&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dspace%2Bmissions%2Barchive"><span>Advances in Land Data Assimilation at the NASA Goddard Space Flight Center</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reichle, Rolf</p> <p>2009-01-01</p> <p>Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034514','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034514"><span>Responses of ecosystem carbon cycling to climate change treatments along an elevation gradient</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Wu, Zhuoting; Koch, George W.; Dijkstra, Paul; Bowker, Matthew A.; Hungate, Bruce A.</p> <p>2011-01-01</p> <p>Global temperature increases and precipitation changes are both expected to alter ecosystem carbon (C) cycling. We tested responses of ecosystem C cycling to simulated climate change using field manipulations of temperature and precipitation across a range of grass-dominated ecosystems along an elevation gradient in northern Arizona. In 2002, we transplanted intact plant–soil mesocosms to simulate warming and used passive interceptors and collectors to manipulate precipitation. We measured daytime ecosystem respiration (ER) and net ecosystem C exchange throughout the growing season in 2008 and 2009. Warming generally stimulated ER and photosynthesis, but had variable effects on daytime net C exchange. Increased precipitation stimulated ecosystem C cycling only in the driest ecosystem at the lowest elevation, whereas decreased precipitation showed no effects on ecosystem C cycling across all ecosystems. No significant interaction between temperature and precipitation treatments was observed. Structural equation modeling revealed that in the wetter-than-average year of 2008, changes in ecosystem C cycling were more strongly affected by warming-induced reduction in soil moisture than by altered precipitation. In contrast, during the drier year of 2009, warming induced increase in soil temperature rather than changes in soil moisture determined ecosystem C cycling. Our findings suggest that warming exerted the strongest influence on ecosystem C cycling in both years, by modulating soil moisture in the wet year and soil temperature in the dry year.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=309870','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=309870"><span>Generating large-scale estimates from sparse, in-situ networks: multi-scale soil moisture modeling at ARS watersheds for NASA’s soil moisture active passive (SMAP) calibration/validation mission</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.nco.ncep.noaa.gov/pmb/products/gfs/gfs_upgrade/gdas1.t06z.sfluxgrbf00.grib2.shtml','SCIGOVWS'); return false;" href="http://www.nco.ncep.noaa.gov/pmb/products/gfs/gfs_upgrade/gdas1.t06z.sfluxgrbf00.grib2.shtml"><span>Inventory of File gdas1.t06z.sfluxgrbf00.grib2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>analysis Volumetric <em>Soil</em> Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric <em>Soil</em> Moisture Content [Fraction] 008 0-0.1 m below ground TMP analysis Temperature [K] 009 0.1-0.4 m Volumetric <em>Soil</em> Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric <em>Soil</em> Moisture</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331936','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331936"><span>Analysis of in situ resources of for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliableas its acc...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330164','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330164"><span>SMAP soil moisture drying more rapid than observed in situ following rainfall events</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>We examine soil drying rates by comparing observations from the NASA Soil Moisture Active Passive (SMAP) mission to surface soil moisture from in situ probes during drydown periods at SMAP validation sites. SMAP and in situ probes record different soil drying dynamics after rainfall. We modeled this...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M"><span>A Round Robin evaluation of AMSR-E soil moisture retrievals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.</p> <p>2014-05-01</p> <p>Large-scale and long-term soil moisture observations based on remote sensing are promising data sets to investigate and understand various processes of the climate system including the water and biochemical cycles. Currently, the ESA Climate Change Initiative for soil moisture develops and evaluates a consistent global long-term soil moisture data set, which is based on merging passive and active remotely sensed soil moisture. Within this project an inter-comparison of algorithms for AMSR-E and ASCAT Level 2 products was conducted separately to assess the performance of different retrieval algorithms. Here we present the inter-comparison of AMSR-E Level 2 soil moisture products. These include the public data sets from University of Montana (UMT), Japan Aerospace and Space Exploration Agency (JAXA), VU University of Amsterdam (VUA; two algorithms) and National Aeronautics and Space Administration (NASA). All participating algorithms are applied to the same AMSR-E Level 1 data set. Ascending and descending paths of scaled surface soil moisture are considered and evaluated separately in daily and monthly resolution over the 2007-2011 time period. Absolute values of soil moisture as well as their long-term anomalies (i.e. removing the mean seasonal cycle) and short-term anomalies (i.e. removing a five weeks moving average) are evaluated. The evaluation is based on conventional measures like correlation and unbiased root-mean-square differences as well as on the application of the triple collocation method. As reference data set, surface soil moisture of 75 quality controlled soil moisture sites from the International Soil Moisture Network (ISMN) are used, which cover a wide range of vegetation density and climate conditions. For the application of the triple collocation method, surface soil moisture estimates from the Global Land Data Assimilation System are used as third independent data set. We find that the participating algorithms generally display a better performance for the descending compared to the ascending paths. A first classification of the sites defined by geographical locations show that the algorithms have a very similar average performance. Further classifications of the sites by land cover types and climate regions will be conducted which might result in a more diverse performance of the algorithms.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005PhDT........80G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005PhDT........80G"><span>Land surface dynamics monitoring using microwave passive satellite sensors</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guijarro, Lizbeth Noemi</p> <p></p> <p>Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps"><span>Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.</p> <p>1997-01-01</p> <p>This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface soil moisture. Validation of results using field measured values and soil texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1828R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1828R"><span>Experimental evidence and modelling of drought induced alternative stable soil moisture states</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget</p> <p>2017-04-01</p> <p>The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/36158','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/36158"><span>Soil moisture mediated interaction between Polygonatum biflorum and leaf spot disease</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Robert J. II Warren; Erin Mordecai</p> <p>2010-01-01</p> <p>Fungal pathogens can regulate the abundance and distribution of natural plant populations by inhibiting the growth, survival, and reproduction of their hosts. The abiotic environment is a crucial component in hostâpathogen interactions in natural plant populations as favorable conditions drive pathogen development, reproduction, and persistence. Foliar plant pathogens...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820018867','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820018867"><span>Interactive initialization of heat flux parameters for numerical models using satellite temperature measurements</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Carlson, T. N. (Principal Investigator)</p> <p>1982-01-01</p> <p>Progress made in HCMM research, including testing the interactive minicomputer system and preparation of a paper on the analysis of regional scale soil moisture patterns, is summarized. An exhibit on remote sensing including a videotape display of HCMM images, most of them of the State College area, was prepared.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28559315','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28559315"><span>Historical climate controls soil respiration responses to current soil moisture.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hawkes, Christine V; Waring, Bonnie G; Rocca, Jennifer D; Kivlin, Stephanie N</p> <p>2017-06-13</p> <p>Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40-70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration-moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H33B1647B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H33B1647B"><span>Land surface-precipitation feedback and ramifications on storm dynamics.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baisya, H.; PV, R.; Pattnaik, S.</p> <p>2017-12-01</p> <p>A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760008444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760008444"><span>Electrical methods of determining soil moisture content</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Silva, L. F.; Schultz, F. V.; Zalusky, J. T.</p> <p>1975-01-01</p> <p>The electrical permittivity of soils is a useful indicator of soil moisture content. Two methods of determining the permittivity profile in soils are examined. A method due to Becher is found to be inapplicable to this situation. A method of Slichter, however, appears to be feasible. The results of Slichter's method are extended to the proposal of an instrument design that could measure available soil moisture profile (percent available soil moisture as a function of depth) from a surface measurement to an expected resolution of 10 to 20 cm.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090041757','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090041757"><span>Stream Flow Prediction by Remote Sensing and Genetic Programming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, Ni-Bin</p> <p>2009-01-01</p> <p>A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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