Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2001-01-01

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Near Surface Soil Moisture Estimation Using SAR Images: A Case Study in the Mediterranean Area of Catalonia

NASA Astrophysics Data System (ADS)

Reppucci, Antonio; Moreno, Laura

2010-12-01

Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.

Soil moisture under contrasted atmospheric conditions in Eastern Spain

NASA Astrophysics Data System (ADS)

Azorin-Molina, César; Cerdà, Artemi; Vicente-Serrano, Sergio M.

2014-05-01

Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at p<0.01) with the amount of measured precipitation. In this study we analyze the role of other crucial atmospheric parameters (i.e., temperature, relative humidity, global solar radiation, and wind speed and wind direction) in the intraanual evolution of soil moisture; focussing our analyses on the soil moisture discharge episodes. Here we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, 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). Key Words: Soil Moisture Discharges, Intraannual changes, Atmospheric parameters, Eastern Spain Acknowledgements The research projects GL2008-02879/BTE, LEDDRA 243857 and RECARE FP7 project 603498 supported this research. References: Azorin-Molina, C., Connell, B.H., Baena-Calatrava, R. 2009. Sea-breeze convergence zones from AVHRR over the Iberian Mediterranean Area and the Isle of Mallorca, Spain. Journal of Applied Meteorology and Climatology 48 (10), 2069-2085. Azorin-Molina, C., Vicente-Serrano, S. M., Cerdà, A. 2013. Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming. EGU, Geophysical Research Abstracts, EGU2013-13286. Bodí, M.B., Mataix-Solera, J., Doerr, S.H. & Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 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. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments, 52, 319-337. García-Fayos, P. García-Ventoso, B. Cerdà, A. 2000. Limitations to Plant establishment on eroded slopes in Southeastern Spain. Journal of Vegetation Science, 11- 77- 86. Ghafoor, A., Murtaza, G., Rehman, M. Z., Saifullah Sabir, M. 2012. Reclamation and salt leaching efficiency for tile drained saline-sodic soil using marginal quality water for irrigating rice and wheat crops. Land Degradation & Development, 23: 1 -9. DOI 10.1002/ldr.1033 Johnston, C. R., Vance, G. F., Ganjegunte, G. K. 2013. Soil properties changes following irrigation with coalbed natural gas water: role of water treatments, soil amendments and land suitability. Land Degradation & Development, 24: 350- 362. DOI 10.1002/ldr.1132 Qadir, M., Noble, A. D., Chartres, C. 2013. Adapting to climate change by improving water productivity of soil in dry areas. Land Degradation & Development, 24: 12- 21. DOI 10.1002/ldr.1091 Ziadat, F. M., and Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

Soil moisture at local scale: Measurements and simulations

NASA Astrophysics Data System (ADS)

Romano, Nunzio

2014-08-01

Soil moisture refers to the water present in the uppermost part of a field soil and is a state variable controlling a wide array of ecological, hydrological, geotechnical, and meteorological processes. The literature on soil moisture is very extensive and is developing so rapidly that it might be considered ambitious to seek to present the state of the art concerning research into this key variable. Even when covering investigations about only one aspect of the problem, there is a risk of some inevitable omission. A specific feature of the present essay, which may make this overview if not comprehensive at least of particular interest, is that the reader is guided through the various traditional and more up-to-date methods by the central thread of techniques developed to measure soil moisture interwoven with applications of modeling tools that exploit the observed datasets. This paper restricts its analysis to the evolution of soil moisture at the local (spatial) scale. Though a somewhat loosely defined term, it is linked here to a characteristic length of the soil volume investigated by the soil moisture sensing probe. After presenting the most common concepts and definitions about the amount of water stored in a certain volume of soil close to the land surface, this paper proceeds to review ground-based methods for monitoring soil moisture and evaluates modeling tools for the analysis of the gathered information in various applications. Concluding remarks address questions of monitoring and modeling of soil moisture at scales larger than the local scale with the related issue of data aggregation. An extensive, but not exhaustive, list of references is provided, enabling the reader to gain further insights into this subject.

L-band Soil Moisture Mapping using Small UnManned Aerial Systems

NASA Astrophysics Data System (ADS)

Dai, E.

2015-12-01

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

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.

The Influence of Soil Moisture, Coastline Curvature, and Land-Breeze Circulations on Sea-Breeze Initiated Precipitation

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.

Soil CO2 evolution and root respiration in 11 year-old Loblolly Pine (Pinus taeda) Plantations as Affected by Moisture and Nutrient Availability

Treesearch

Chris A. Maier; L.W. Kress

2000-01-01

We measured soil CO2 evolution rates with (Sff) and without (Sms) the forest floor litter and root respiration monthly in 11-year-old loblolly pine (Pinus taeda L.) plantations during the fourth year of fertilization and irrigation treatments. Values of Sff...

Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.

2017-11-01

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.

The consecutive dry days to trigger rainfall over West Africa

NASA Astrophysics Data System (ADS)

Lee, J. H.

2018-01-01

In order to resolve contradictions in addressing a soil moisture-precipitation feedback mechanism over West Africa and to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, we first validated various data sets (SMOS satellite soil moisture observations, NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models) with the Analyses Multidisciplinaires de la Mousson Africaine (AMMA) field campaign data. Based on this analysis, it was suggested that biases of data sets might cause contradictions in studying mechanisms. Thus, by taking into account uncertainties in data, it was found that the approach of consecutive dry days (i.e. a relative comparison of time-series) showed consistency across various data sets, while the direct comparison approach for soil moisture state and rainfall did not. Thus, it was discussed that it may be difficult to directly relate rain with soil moisture as the absolute value, however, it may be reasonable to compare a temporal progress of the variables. Based upon the results consistently showing a positive relationship between the consecutive dry days and rainfall, this study supports a negative feedback often neglected by climate model structure. This approach is less sensitive to interpretation errors arising from systematic errors in data sets, as this measures a temporal gradient of soil moisture state.

Compact polarimetric synthetic aperture radar for monitoring soil moisture condition

NASA Astrophysics Data System (ADS)

Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.

2017-12-01

Coarse resolution soil moisture maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational soil moisture monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface soil moisture. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate soil moisture over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of soil moisture retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.

Host specificity of two pollinating seed-consuming fly species is not related to soil moisture of host plant in the high Himalayas.

PubMed

Song, Bo; Stöcklin, Jürg; Gao, Yong-Qian; Peng, De-Li; Sun, Hang

2017-01-01

Studying the drivers of host specificity can contribute to our understanding of the origin and evolution of obligate pollination mutualisms. The preference-performance hypothesis predicts that host plant choice of female insects is related mainly to the performance of their offspring. Soil moisture is thought to be particularly important for the survival of larvae and pupae that inhabit soil. In the high Himalayas, Rheum nobile and R. alexandrae differ in their distribution in terms of soil moisture; that is, R. nobile typically occurs in scree with well-drained soils, R. alexandrae in wetlands. The two plant species are pollinated by their respective mutualistic seed-consuming flies, Bradysia sp1. and Bradysia sp2. We investigated whether soil moisture is important for regulating host specificity by comparing pupation and adult emergence of the two fly species using field and laboratory experiments. Laboratory experiments revealed soil moisture did have significant effects on larval and pupal performances in both fly species, but the two fly species had similar optimal soil moisture requirements for pupation and adult emergence. Moreover, a field reciprocal transfer experiment showed that there was no significant difference in adult emergence for both fly species between their native and non-native habitats. Nevertheless, Bradysia sp1., associated with R. nobile , was more tolerant to drought stress, while Bradysia sp2., associated with R. alexandrae , was more tolerant to flooding stress. These results indicate that soil moisture is unlikely to play a determining role in regulating host specificity of the two fly species. However, their pupation and adult emergence in response to extremely wet or dry soils are habitat-specific.

SMOS and SMAP: from Lessons Learned to Future Mission Requirements

NASA Astrophysics Data System (ADS)

Kerr, Y. H.; Wigneron, J. P.; Cabot, F.; Escorihuela, M. J.; Anterrieu, E.; Rouge, B.; Rodriguez Fernandez, N.; Bindlish, R.; Khazaal, A.; Al-Bitar, A.; Mialon, A.; Lesthievent, G.

2017-12-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface, vegetation water content over land, and ocean salinity. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. TheSoil Moisture Active and Passive for over 2 years.The two data set have been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) to be merged into one product, while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years of L-Band data acquisition, it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the two mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets of L-band microwave radiometry in two specific cases, namely droughts and water budget over a large basin. Several other analyses are under way currently. Obviously, vegetation water content, but also dielectric constant, are carrying a wealth of information and some interesting perspectives will be presented. More important it is now possible to draw conclusions from the lessons learnt and, with the help of the user's community, define the requirements for future missions. And, finally, from these requirement to propose mission scenarii.

Relative Influence of Initial Surface and Atmospheric Conditions on Seasonal Water and Energy Balances

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Roads, John O.; Robertson, Franklin R.; Goodman, H. Michael (Technical Monitor)

2001-01-01

We constructed and analyzed wet and dry soil moisture composites for the mid-latitude GCIP region of the central US using long climate model simulations made with the NCAR CCM3 and reanalysis products from NCEP. Using the diagnostic composites as a guide, we have completed a series of predictability experiments in which we imposed soil water initial conditions in CCM3 for the GCIP region for June 1 from anomalously wet and dry years, with atmospheric initial conditions taken from June 1 of a year with 'near-normal' soil water, and initial soil water from the near-normal year and atmospheric initial conditions from the wet and dry years. Preliminary results indicate that the initial state of the atmosphere is more important than the initial state of soil water determining the subsequent late spring and summer evolution of sod water over the GCIP region. Surprisingly, neither the composites or the predictability experiments yielded a strong influence of soil moisture on the atmosphere. To explore this further, we have made runs with extreme dry soil moisture initial anomalies imposed over the GCIP region (the soil close to being completely dry). These runs did yield a very strong effect on the atmosphere that persisted for at least three months. We conclude that the magnitude of the initial soil moisture anomaly is crucial, at least in CCM3, and are currently investigating whether a threshold exists, below which little impact is seen. In a complementary study, we compared the impact of the initial condition of snow cover versus the initial atmospheric state over the western US (corresponding to the westward extension of the GAPP program follow-on to GCIP). In this case, the initial prescription of snow cover is far more important than the initial atmospheric state in determining the subsequent evolution of snow cover. We are currently working to understand the very different soil water and snow cover results.

Observations of soil moisture and infiltrability in contour-aligned, banded chenopod shrubland at Fowlers Gap, arid western NSW, Australia.

NASA Astrophysics Data System (ADS)

Dunkerley, D.

2009-04-01

Speculation abounds concerning the drivers of spatial patterning in dryland vegetation, and many numerical analyses have been built with little use of field evidence for parameterisation or validation. In fact, studies of soil moisture distribution, the most commonly hypothesised driver of pattern formation, are uncommon. Here, soil infiltrability and soil moisture data are presented from a banded vegetation community in arid western NSW Australia. The site had received 40 mm of rain in one day a week prior to field measurement. This is an exceptional rain event for this region, and provided the opportunity to observe resulting distributions of soil moisture within various mosaics, including contour-aligned groves and intergroves in chenopod shrubland. Results taken at 2 m intervals across many cycles of the repeating banded pattern show that near-surface (6 cm) soil moisture is relatively constant, except in lower intergroves, which were drier. Patterns of soil infiltrability by cylinder infiltrometer follow the same pattern, with lowest values at the same locations as the soil moisture minima. Locally high soil infiltrabilities occur in both grove and intergrove, but low values are restricted to intergroves. These results suggest that any runoff-runon system operating at the site is driven largely from the intergroves, where high bulk density, hydrophobic biological soil crusts, and mantles of small stones with associated vesicular horizons, limit water entry. If this is so, it suggests that attention must be paid to intergrove processes, which may be more significant that plant facilitation within groves. Model developments will thus need to address the evolution of low infiltrability in intergroves in parallel with any high infiltrability within groves.

Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

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).

A Simplified Land Model (SLM) for use in cloud-resolving models: Formulation and evaluation

NASA Astrophysics Data System (ADS)

Lee, Jungmin M.; Khairoutdinov, Marat

2015-09-01

A Simplified Land Model (SLM) that uses a minimalist set of parameters with a single-layer vegetation and multilevel soil structure has been developed distinguishing canopy and undercanopy energy budgets. The primary motivation has been to design a land model for use in the System for Atmospheric Modeling (SAM) cloud-resolving model to study land-atmosphere interactions with a sufficient level of realism. SLM uses simplified expressions for the transport of heat, moisture, momentum, and radiation in soil-vegetation system. The SLM performance has been evaluated over several land surface types using summertime tower observations of micrometeorological and biophysical data from three AmeriFlux sites, which include grassland, cropland, and deciduous-broadleaf forest. In general, the SLM captures the observed diurnal cycle of surface energy budget and soil temperature reasonably well, although reproducing the evolution of soil moisture, especially after rain events, has been challenging. The SLM coupled to SAM has been applied to the case of summertime shallow cumulus convection over land based on the Atmospheric Radiation Measurements (ARM) Southern Great Plain (SGP) observations. The simulated surface latent and sensible heat fluxes as well as the evolution of thermodynamic profiles in convective boundary layer agree well with the estimates based on the observations. Sensitivity of atmospheric boundary layer development to the soil moisture and different land cover types has been also examined.

Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Noto, L. V.; Sivandran, G.; Bras, R. L.

2013-01-01

This paper presents the development of a rainfall-triggered landslide module within a physically based spatially distributed ecohydrologic model. The model, Triangulated Irregular Networks Real-time Integrated Basin Simulator and VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics is resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the Luquillo Forest (the study area). The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards equation to better represent the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the Factor of Safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the Infinite Slope model creating a powerful tool for the assessment of landslide risk.

Moisture can be the dominant environmental parameter governing cadaver decomposition in soil.

PubMed

Carter, David O; Yellowlees, David; Tibbett, Mark

2010-07-15

Forensic taphonomy involves the use of decomposition to estimate postmortem interval (PMI) or locate clandestine graves. Yet, cadaver decomposition remains poorly understood, particularly following burial in soil. Presently, we do not know how most edaphic and environmental parameters, including soil moisture, influence the breakdown of cadavers following burial and alter the processes that are used to estimate PMI and locate clandestine graves. To address this, we buried juvenile rat (Rattus rattus) cadavers (approximately 18 g wet weight) in three contrasting soils from tropical savanna ecosystems located in Pallarenda (sand), Wambiana (medium clay), or Yabulu (loamy sand), Queensland, Australia. These soils were sieved (2mm), weighed (500 g dry weight), calibrated to a matric potential of -0.01 megapascals (MPa), -0.05 MPa, or -0.3 MPa (wettest to driest) and incubated at 22 degrees C. Measurements of cadaver decomposition included cadaver mass loss, carbon dioxide-carbon (CO(2)-C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, ninhydrin-reactive nitrogen (NRN) and soil pH. Cadaver burial resulted in a significant increase in CO(2)-C evolution, MBC, enzyme activities, NRN and soil pH. Cadaver decomposition in loamy sand and sandy soil was greater at lower matric potentials (wetter soil). However, optimal matric potential for cadaver decomposition in medium clay was exceeded, which resulted in a slower rate of cadaver decomposition in the wettest soil. Slower cadaver decomposition was also observed at high matric potential (-0.3 MPa). Furthermore, wet sandy soil was associated with greater cadaver decomposition than wet fine-textured soil. We conclude that gravesoil moisture content can modify the relationship between temperature and cadaver decomposition and that soil microorganisms can play a significant role in cadaver breakdown. We also conclude that soil NRN is a more reliable indicator of gravesoil than soil pH. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Patterns Of Moisture Storage During Canadian Prairie Drought

NASA Astrophysics Data System (ADS)

Agboma, C. O.; Snelgrove, K. R.

2008-12-01

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.

Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

2015-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

NASA Technical Reports Server (NTRS)

Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

1998-01-01

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).

Infusion of SMAP Data into Offline and Coupled Models: Evaluation, Calibration, and Assimilation

NASA Astrophysics Data System (ADS)

Lawston, P.; Santanello, J. A., Jr.; Dennis, E. J.; Kumar, S.

2017-12-01

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.

The Evolution of CO2 on Mars

NASA Technical Reports Server (NTRS)

Kahn, R.

1985-01-01

The consequences of the hypothesis that the evolution of CO2 is directly linked to the occurrence of at least transitory pockets of moisture were exposed. The current conditions preclude the existence of open bodies of liquid water and the formation of moisture in disequilibrium is not excluded by any known constraints. The water evaporation rate is inversely proportional to PCO2, and the existence of a limiting value (P*) for which liquid water can form in the Mars environment is postulated. The evolution of PCO2 is controlled largely by relatively rapid aqueous chemistry forming carbon-containing sedimentary rocks, perhaps during early history in open water, but more recently in transitory pockets of moisture in the soil. Once the total atmospheric pressure is reduced to near P*, the occurrence of transitory moisture is inhibited, and atmospheric CO2 is no longer depleted by an efficient mechanism. The role of the carbonate reservoir in the current overall carbon budget on Mars, according to this scheme, is illustrated.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

SMOS data and extreme events

NASA Astrophysics Data System (ADS)

Kerr, Yann; Wigneron, Jean-Pierre; Ferrazzoli, Paolo; Mahmoodi, Ali; Al-Yaari, Amen; Parrens, Marie; Bitar, Ahmad Al; Rodriguez-Fernandez, Nemesio; Bircher, Simone; Molero-rodenas, Beatriz; Drusch, Matthias; Mecklenburg, Susanne

2017-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3), vegetation water content over land, and ocean salinity. These geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches, and in particular in improving model forecasts. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. The whole data set has been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets of L-band microwave radiometry in two specific cases, namely droughts and water budget over a large basin. Several other analyses are under way currently. Obviously, vegetation water content, but also dielectric constant, are carrying a wealth of information and some interesting perspectives will be presented.

Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Noto, L. V.; Sivandran, G.; Bras, R. L.

2013-09-01

This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

L-band Soil Moisture Mapping using Small UnManned Aerial Systems

NASA Astrophysics Data System (ADS)

Dai, E.; Gasiewski, A. J.; Stachura, M.; Elston, J.; Venkitasubramony, A.

2016-12-01

1. IntroductionSoil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling scale studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015 and Yuma Colorado Irrigation Research Foundation (IRF) site from June to August, 2016. These tests were flown at 25-50 m altitude to obtain differing spatial resolutions. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. 2. References[1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.

Challenges in Ecohydrological Monitoring at Soil-Vegetation Interfaces: Exploiting the Potential for Fibre Optic Technologies

NASA Astrophysics Data System (ADS)

Chalari, A.; Ciocca, F.; Krause, S.; Hannah, D. M.; Blaen, P.; Coleman, T. I.; Mondanos, M.

2015-12-01

The Birmingham Institute of Forestry Research (BIFoR) is using Free-Air Carbon Enrichment (FACE) experiments to quantify the long-term impact and resilience of forests into rising atmospheric CO2 concentrations. The FACE campaign critically relies on a successful monitoring and understanding of the large variety of ecohydrological processes occurring across many interfaces, from deep soil to above the tree canopy. At the land-atmosphere interface, soil moisture and temperature are key variables to determine the heat and water exchanges, crucial to the vegetation dynamics as well as to groundwater recharge. Traditional solutions for monitoring soil moisture and temperature such as remote techniques and point sensors show limitations in fast acquisition rates and spatial coverage, respectively. Hence, spatial patterns and temporal dynamics of heat and water fluxes at this interface can only be monitored to a certain degree, limiting deeper knowledge in dynamically evolving systems (e.g. in impact of growing vegetation). Fibre optics Distributed Temperature Sensors (DTS) can measure soil temperatures at high spatiotemporal resolutions and accuracy, along kilometers of optical cable buried in the soil. Heat pulse methods applied to electrical elements embedded in the optical cable can be used to obtain the soil moisture. In July 2015 a monitoring system based on DTS has been installed in a recently forested hillslope at BIFoR in order to quantify high-resolution spatial patterns and high-frequency temporal dynamics of soil heat fluxes and soil moisture conditions. Therefore, 1500m of optical cables have been carefully deployed in three overlapped loops at 0.05m, 0.25m and 0.4m from the soil surface and an electrical system to send heat pulses along the optical cable has been developed. This paper discussed both, installation and design details along with first results of the soil moisture and temperature monitoring carried out since July 2015. Moreover, interpretations of the collected data to investigate the impact on soil moisture dynamics of i) forest evolution (long timescale), (ii) seasonality and, (iii) high-frequency forcing, are discussed.

Propagation of hydroclimatic variability through the critical zone

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Calabrese, S.; Parolari, A.

2016-12-01

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.

Evaluation of the potential of soil remediation by direct multi-channel pulsed corona discharge in soil.

PubMed

Wang, Tie Cheng; Qu, Guangzhou; Li, Jie; Liang, Dongli

2014-01-15

A novel approach, named multi-channel pulsed corona discharge in soil, was developed for remediating organic pollutants contaminated soil, with p-nitrophenol (PNP) as the model pollutant. The feasibility of PNP degradation in soil was explored by evaluating effects of pulse discharge voltage, air flow rate and soil moisture on PNP degradation. Based on roles of chemically active species and evolution of degradation intermediates, PNP degradation processes were discussed. Experimental results showed that about 89.4% of PNP was smoothly degraded within 60min of discharge treatment at pulse discharge voltage 27kV, soil moisture 5% and air flow rate 0.8Lmin(-1), and the degradation process fitted the first-order kinetic model. Increasing pulse discharge voltage was found to be favorable for PNP degradation, but not for energy yield. There existed appropriate air flow rate and soil moisture for obtaining gratifying PNP degradation efficacy. Roles of radical scavenger and measurement of active species suggested that ozone, H2O2, and OH radicals played very important roles in PNP degradation. CN bond in PNP molecule was cleaved, and the main intermediate products such as hydroquinone, benzoquinone, catechol, phenol, acetic acid, formic acid, oxalic acid, NO2(-) and NO3(-) were identified. Possible pathway of PNP degradation in soil in such a system was proposed. Copyright © 2013 Elsevier B.V. All rights reserved.

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

NASA Technical Reports Server (NTRS)

Chung, Y. C.; England, A. W.; DeRoo, R. D.; Weininger, Etai

2006-01-01

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

Microwave Brightness Of Land Surfaces From Outer Space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1991-01-01

Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

NASA Astrophysics Data System (ADS)

Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

2017-12-01

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

On the use of L-band microwave and multi-mission EO data for high resolution soil moisture

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Merlin, Olivier; Malbeteau, Yoann; Molero-Rodenas, Beatriz; Zribi, Mehrez; Sekhar, Muddu; Tomer, Sat Kumar; José Escorihuela, Maria; Stefan, Vivien; Suere, Christophe; Mialon, Arnaud; Kerr, Yann

2017-04-01

Sub-kilometric soil moisture maps have been increasingly mentioned as a need in the scientific community for many applications ranging from agronomical and hydrological (Wood et al. 2011). For example, this type of dataset will become essential to support the current evolution of the land surface and hydrologic modelling communities towards high resolution global modelling. But the ability of the different sensors to monitor soil moisture is different. The L-Band microwave EO provides, at a coarse resolution, the most sensitive information to surface soil moisture when compared to C-Band microwave, optical or C-band SAR. On the other hand the optical and radar sensors provide the spatial distribution of associated variables like surface soil moisture,surface temperature or vegetation leaf area index. This paper describes two complementary fusion approaches to obtain such data from optical or SAR in combination to microwave EO, and more precisely L-Band microwave from the SMOS mission. The first approach, called MAPSM, is based on the use of high resolution soil moisture from SAR and microwave. The two types of sensors have all weather capabilities. The approach uses the new concept of water change capacity (Tomer et al. 2015, 2016). It has been applied to the Berambadi watershed in South-India which is characterised by high cloud coverage. The second approach, called Dispatch, is based on the use of optical sensors in a physical disaggregation approach. It is a well-established approach (Merlin et al. 2012, Malbeteau et al. 2015) that has been implemented operationally in the CATDS (Centre Aval de Traitement des Données SMOS) processing centre (Molero et al. 2016). An analysis on the complementarity of the approaches is discussed. The results show the performances of the methods when compared to existing soil moisture monitoring networks in arid, sub-tropical and humid environments. They emphasis on the need for large inter-comparison studied for the qualification of such products on different climatic zones and on the need of an adaptative multisensor approach. The availability of the recent Sentinel-1 2 and 3 missions from ESA provides an exceptional environment to apply such algorithms at larger scales.

Two types of flash drought over China and their connections with sub-seasonal to seasonal soil moisture drought

NASA Astrophysics Data System (ADS)

Wang, L.; Yuan, X.; Xie, Z.

2017-12-01

Flash drought has been receiving attention recently due to its rapid development and vast damage on crops in the growing season. Accompanied with heatwave and rainfall deficit, the soil moisture decreased rapidly in a short time and may lead to the failure of root water uptake and large-scale crops wither. There are two types of flash droughts according to the causes (Mo and Lettenmaier, 2016), i.e., heat wave flash drought and rainfall deficit flash drought. Here, based on pentad-mean surface air temperature and precipitation observations from over two thousand meteorological stations as well as soil moisture and ET estimations from three global reanalysis products, the characteristics and evolution of the two types of flash droughts over China are being explored. Heat wave flash drought is more likely to occur in humid and semi-humid areas, such as southern China, while rainfall deficit flash drought is more likely to occur in northern China. Unlike the traditional drought that persists for a few months to decades, the mean durations of both types of flash droughts are very short. We use monthly mean soil moisture to calculate sub-seasonal to seasonal (S2S) soil moisture drought, and compare its characteristics and preferred conditions such as the large-scale atmospheric circulation and oceanic anomaly for both types of flash droughts. The percentages of flash drought in different periods of S2S drought are also being explored to see the potential relationship between flash drought and S2S drought over different regions.

Summer moisture changes in the Lake Qinghai area on the northeastern Tibetan Plateau recorded from a meadow section over the past 8400 yrs

NASA Astrophysics Data System (ADS)

Li, Xiangzhong; Liu, Xiangjun; He, Yuxin; Liu, Weiguo; Zhou, Xin; Wang, Zheng

2018-02-01

Holocene climatic and environmental changes on the northeastern Tibetan Plateau (TP) have been widely discussed based on the climatic records from sedimentary cores. However, differences in the reconstructed climatic history from various studies in this region still exist, probably due to influence of climatic proxies from multiple factors and the chronological uncertainties in lacustrine sediments. Here we present records of terrestrial plant δ13C, soil color and total organic carbon content over the past 8400 years from a well-dated meadow section on the northeastern TP. The terrestrial plant δ13C value serves as a good summer precipitation/moisture indicator in the studied region. Soil color property and TOC content are also able to disentangle the moisture evolution history. All the data show much wet climates at 8400-7400 cal yr BP, dry climates at 7400-6000 cal yr BP and then wet conditions with fluctuation at 6000-3200 cal yr BP. Late Holocene moisture appears to be comparable with moist conditions from 6000 to 3200 cal yr BP. By further comparing the climatic variations in the Lake Qinghai area with records of the reconstructed summer temperature and the Asian Monsoon precipitation, we believe that the pattern of moisture/precipitation evolution in the Lake Qinghai area was not completely consistent with regions around Lake Qinghai, probably due to complicated interaction between the East Asian Summer Monsoon and the Indian Summer Monsoon.

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

2016-01-01

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.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

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).

Assessment of model behavior and acceptable forcing data uncertainty in the context of land surface soil moisture estimation

NASA Astrophysics Data System (ADS)

Dumedah, Gift; Walker, Jeffrey P.

2017-03-01

The sources of uncertainty in land surface models are numerous and varied, from inaccuracies in forcing data to uncertainties in model structure and parameterizations. Majority of these uncertainties are strongly tied to the overall makeup of the model, but the input forcing data set is independent with its accuracy usually defined by the monitoring or the observation system. The impact of input forcing data on model estimation accuracy has been collectively acknowledged to be significant, yet its quantification and the level of uncertainty that is acceptable in the context of the land surface model to obtain a competitive estimation remain mostly unknown. A better understanding is needed about how models respond to input forcing data and what changes in these forcing variables can be accommodated without deteriorating optimal estimation of the model. As a result, this study determines the level of forcing data uncertainty that is acceptable in the Joint UK Land Environment Simulator (JULES) to competitively estimate soil moisture in the Yanco area in south eastern Australia. The study employs hydro genomic mapping to examine the temporal evolution of model decision variables from an archive of values obtained from soil moisture data assimilation. The data assimilation (DA) was undertaken using the advanced Evolutionary Data Assimilation. Our findings show that the input forcing data have significant impact on model output, 35% in root mean square error (RMSE) for 5cm depth of soil moisture and 15% in RMSE for 15cm depth of soil moisture. This specific quantification is crucial to illustrate the significance of input forcing data spread. The acceptable uncertainty determined based on dominant pathway has been validated and shown to be reliable for all forcing variables, so as to provide optimal soil moisture. These findings are crucial for DA in order to account for uncertainties that are meaningful from the model standpoint. Moreover, our results point to a proper treatment of input forcing data in general land surface and hydrological model estimation.

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

NASA Astrophysics Data System (ADS)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

Rainfall-induced soil aggregate breakdown in field experiments at different rainfall intensities and initial soil moisture conditions

NASA Astrophysics Data System (ADS)

Shi, Pu; Thorlacius, Sigurdur; Keller, Thomas; Keller, Martin; Schulin, Rainer

2017-04-01

Soil aggregate breakdown under rainfall impact is an important process in interrill erosion, but is not represented explicitly in water erosion models. Aggregate breakdown not only reduces infiltration through surface sealing during rainfall, but also determines the size distribution of the disintegrated fragments and thus their availability for size-selective sediment transport and re-deposition. An adequate representation of the temporal evolution of fragment mass size distribution (FSD) during rainfall events and the dependence of this dynamics on factors such as rainfall intensity and soil moisture content may help improve mechanistic erosion models. Yet, little is known about the role of those factors in the dynamics of aggregate breakdown under field conditions. In this study, we conducted a series of artificial rainfall experiments on a field silt loam soil to investigate aggregate breakdown dynamics at different rainfall intensity (RI) and initial soil water content (IWC). We found that the evolution of FSD in the course of a rainfall event followed a consistent two-stage pattern in all treatments. The fragment mean weight diameter (MWD) drastically decreased in an approximately exponential way at the beginning of a rainfall event, followed by a further slow linear decrease in the second stage. We proposed an empirical model that describes this temporal pattern of MWD decrease during a rainfall event and accounts for the effects of RI and IWC on the rate parameters. The model was successfully tested using an independent dataset, showing its potential to be used in erosion models for the prediction of aggregate breakdown. The FSD at the end of the experimental rainfall events differed significantly among treatments, indicating that different aggregate breakdown mechanisms responded differently to the variation in initial soil moisture and rainfall intensity. These results provide evidence that aggregate breakdown dynamics needs to be considered in a case-specific manner in modelling sediment mobilization and transport during water erosion events.

Assessment of Multi-frequency Electromagnetic Induction for Determining Soil Moisture Patterns at the Hillslope Scale

NASA Astrophysics Data System (ADS)

Tromp-van Meerveld, I.; McDonnell, J.

2009-05-01

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.

Assimilation of Passive and Active Microwave Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.

2012-01-01

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.

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

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 rover, 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.

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

PubMed

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

2015-08-01

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.

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.

Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes

USDA-ARS?s Scientific Manuscript database

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...

Assessment of multi-frequency electromagnetic induction for determining soil moisture patterns at the hillslope scale

NASA Astrophysics Data System (ADS)

Tromp-van Meerveld, H. J.; McDonnell, J. J.

2009-04-01

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.

Divergent Egg Physiologies in Two Closely Related Grasshopper Species: Taeniopoda eques versus Romalea microptera (Orthoptera: Romaleidae)

PubMed Central

STAUFFER, TIMOTHY W.; HATLE, JOHN D.; WHITMAN, DOUGLAS W.

2013-01-01

We compared egg survivorship and egg development time at different soil moistures for two closely related grasshopper species from divergent habitats: marsh-inhabiting Romalea microptera (Beauvois) versus desert-inhabiting Taeniopoda eques (Burmeister). These two species can interbreed and produce viable offspring. In nature, both species have a similar 8–9 mo subterranean egg stage, but their soil environments differ dramatically in water content. We predicted that the eggs of the two species would exhibit differential survivorship and development times under different moisture levels. Our laboratory results show that the eggs of both species survived a wide range of soil moistures (≈ 0.5 to 90%), maintained for 3 mo. However, the eggs of the marsh grasshopper, R. microptera, better tolerated the highest soil moistures (95 and 100%), whereas the eggs of the desert species, T. eques, better tolerated the lowest soil moistures (0.0 and 0.1%). Sixty-five percent of marsh-inhabiting R. microptera eggs, but no desert T. eques eggs, survived 3 mo submersion under water. In contrast, 49% of desert T. eques eggs, but only 3.5% of R. microptera eggs, survived after being laid into oven-dried sand and then maintained with no additional water until hatch. In the laboratory at 26°C, the two species differed significantly in the mean length of the oviposition-to-hatch interval: 176 d for R. microptera versus 237 d for T. eques. These divergent traits presumably benefit these insects in their divergent habitats. Our results suggest the evolution of physiological divergence that is consistent with adaptations to local environments. PMID:22182625

Investigation of Hydrological Response of Three Identical Artificial Hillslopes at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Matos, K.; Alves Meira Neto, A.; Troch, P. A. A.; Volkmann, T.

2017-12-01

Hydrological processes at the hillslope scale are complex and heterogeneous, but monitoring hillslopes with a large number of sensors or replicate experimental designs is rarely feasible. The Landscape Evolution Observatory (LEO) at Biosphere 2 consists of three replicated, large (330 m2) artificial hillslopes (East, Center and West) packed with 1-m depth of initially homogeneous, basaltic soil. Each landscape contains a spatially dense network of sensors capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture content and water potential, as well as the hillslope-integrated water balance components. A sophisticated irrigation system allows performing controlled forcing experiments. The three hillslopes are thought to be nearly identical, however recent data showed significant differences in discharge and storage behavior. A 45-day periodic-steady-state tracer experiment was conducted in November and December of 2016, where a 3.5-day long, identical irrigation sequence was repeated 15 times. Each sequence's rainfall, runoff, and storage dynamics were recorded, and distributed moisture characteristics were derived using paired moisture content and matric potential data from 496 positions in each hillslope. In order to understand why the three hillslopes behave hydrologically different, we analyzed soil water retention characteristics at various scales ranging from individually paired moisture and matric potential to whole-hillslope soil water retention characteristics. The results confirm the distinct hydrological behavior between the three hillslopes. The East and West hillslopes behave more similar with respect to the release of water. In contrast, the East and Center hillslopes are more similar with respect to their storage behavior. The differences in hillslope behavior arising from three identically built hillslopes are a surprising and beneficial opportunity to explore how differences in small-scale heterogeneity can impact hydrological dynamics at the hillslope scale.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

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.

2011-01-01

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.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

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.

Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China

NASA Astrophysics Data System (ADS)

Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru

2012-12-01

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.

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.;

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies

NASA Astrophysics Data System (ADS)

Tootle, G.; Anderson, S.; Grissino-Mayer, H.

2012-12-01

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.

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

NASA Astrophysics Data System (ADS)

Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

2017-04-01

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.

Combining SAR with LANDSAT for Change Detection of Riparian Buffer Zone in a Semi-arid River Basin

NASA Astrophysics Data System (ADS)

Chang, N.

2006-12-01

A combination of RADARSAT-1 and Landsat 5 TM satellite images linking the soil moisture variation with Normalized Difference Vegetation Index (NDVI) measurements were used to accomplish remotely sensed change detection of riparian buffer zone in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The CCRW was selected as the study area contributing to the reservoir, which is mostly agricultural and range land in a semi-arid coastal environment. This makes the study significant due to the interception capability of non-point source impact within the riparian buffer zone and the maintenance of ecosystem integrity region wide. First of all, an estimation of soil moisture using RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery was conducted. With its all-weather capability, the RADARSAT-1 is a promising tool for measuring the surface soil moisture over seasons. The time constraint is almost negligible since the RADARSAT-1 is able to capture surface soil moisture over a large area in a matter of seconds, if the area is within its swath. RADARSAT-1 images presented at here were captured in two acquisitions, including April and September 2004. With the aid of five corner reflectors deployed by Alaska Satellite Facility (ASF), essential radiometric and geometric calibrations were performed to improve the accuracy of the SAR imagery. The horizontal errors were reduced from initially 560 meter down to less than 5 meter at the best try. Then two Landsat 5 TM satellite images were summarized based on its NDVI. The combination of and NDVI and SAR data obviously show that soil moisture and vegetation biomass wholly varies in space and time in the CCRW leading to identify the riparian buffer zone evolution over seasons. It is found that the seasonal soil moisture variation is highly tied with the NDVI values and the change detection of buffer zone is technically feasible. It will contribute to develop more effective management strategies for non-point source pollution control, bird habitat monitoring, and grazing and live stock handlings in the future. Future research focuses on comparison of soil moisture variability within RADARSAT-1 footprints and NDVI variations against interferometric SAR for studying riparian ecosystem functioning on a seasonal basis.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

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.

Four-dimensional soil moisture response during an extreme rainfall event at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Troch, Peter A.; Niu, Guo-Yue; Gevaert, Anouk; Teuling, Adriaan; Uijlenhoet, Remko; Pasetto, Damiano; Paniconi, Claudio; Putti, Mario

2014-05-01

The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. We observed the spatial and temporal evolution of the soil moisture content at 496 5-TM Decagon sensors distributed over 5 different depths during a low-intensity long-duration rainfall experiment in February 2013. This presentation will focus on our modeling efforts to reveal subsurface hydraulic heterogeneity required to explain observed rainfall-runoff dynamics at the hillslope scale.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

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.

High resolution change estimation of soil moisture and its assimilation into a land surface model

NASA Astrophysics Data System (ADS)

Narayan, Ujjwal

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.

Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar

NASA Astrophysics Data System (ADS)

Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani

2017-07-01

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.

Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products

USDA-ARS?s Scientific Manuscript database

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...

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

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.

Evaluation of the validated soil moisture product from the SMAP radiometer

USDA-ARS?s Scientific Manuscript database

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...

NASA Soil Moisture Data Products and Their Incorporation in DREAM

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

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.

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.

2011-01-01

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.

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

NASA Technical Reports Server (NTRS)

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.

2017-01-01

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.

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

NASA Astrophysics Data System (ADS)

Drusch, M.

2007-02-01

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.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

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.

Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

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.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

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.

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

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.

Low-field NMR logging sensor for measuring hydraulic parameters of model soils

NASA Astrophysics Data System (ADS)

Sucre, Oscar; Pohlmeier, Andreas; Minière, Adrien; Blümich, Bernhard

2011-08-01

SummaryKnowing the exact hydraulic parameters of soils is very important for improving water management in agriculture and for the refinement of climate models. Up to now, however, the investigation of such parameters has required applying two techniques simultaneously which is time-consuming and invasive. Thus, the objective of this current study is to present only one technique, i.e., a new non-invasive method to measure hydraulic parameters of model soils by using low-field nuclear magnetic resonance (NMR). Hereby, two model clay or sandy soils were respectively filled in a 2 m-long acetate column having an integrated PVC tube. After the soils were completely saturated with water, a low-field NMR sensor was moved up and down in the PVC tube to quantitatively measure along the whole column the initial water content of each soil sample. Thereafter, both columns were allowed to drain. Meanwhile, the NMR sensor was set at a certain depth to measure the water content of that soil slice. Once the hydraulic equilibrium was reached in each of the two columns, a final moisture profile was taken along the whole column. Three curves were subsequently generated accordingly: (1) the initial moisture profile, (2) the evolution curve of the moisture depletion at that particular depth, and (3) the final moisture profile. All three curves were then inverse analyzed using a MATLAB code over numerical data produced with the van Genuchten-Mualem model. Hereby, a set of values ( α, n, θr and θs) was found for the hydraulic parameters for the soils under research. Additionally, the complete decaying NMR signal could be analyzed through Inverse Laplace Transformation and averaged on the 1/ T2 space. Through measurement of the decay in pure water, the effect on the relaxation caused by the sample could be estimated from the obtained spectra. The migration of the sample-related average <1/ T2, Sample> with decreasing saturation speaks for a enhancement of the surface relaxation as the soil dries, in concordance with results found by other authors. In conclusion, this low-field mobile NMR technique has proven itself to be a fast and a non-invasive mean to investigate the hydraulic behavior of soils and to explore microscopical aspect of the water retained in them. In the future, the sensor should allow easy soil moisture measurements on-field.

Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands

NASA Astrophysics Data System (ADS)

Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.

2017-12-01

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.

A microwave systems approach to measuring root zone soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W.; Paris, J. F.; Clark, B. V.

1983-01-01

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.

The international soil moisture network: A data hosting facility for global in situ soil moisture measurements

USDA-ARS?s Scientific Manuscript database

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...

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.

Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

NASA Astrophysics Data System (ADS)

Henneberg, Olga; Ament, Felix; Grützun, Verena

2018-05-01

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.

Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.

DOT National Transportation Integrated Search

2016-09-01

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...

A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2012-12-01

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.

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

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.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

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.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

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

Linking the soil moisture distribution pattern to dynamic processes along slope transects in the Loess Plateau, China.

PubMed

Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo

2015-12-01

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.

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Sure, A.; Dikshit, O.

2017-12-01

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.

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

2015-01-01

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.

Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin

NASA Astrophysics Data System (ADS)

Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.

2017-12-01

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.

Response of spectral vegetation indices to soil moisture in grasslands and shrublands

USGS Publications Warehouse

Zhang, Li; Ji, Lei; Wylie, Bruce K.

2011-01-01

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.

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.

The Temporal Dynamics of Spatial Patterns of Observed Soil Moisture Interpreted Using the Hydrus 1-D Model

NASA Astrophysics Data System (ADS)

Chen, M.; Willgoose, G. R.; Saco, P. M.

2009-12-01

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.

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

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.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

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.

Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan

2017-07-01

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.

The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*

NASA Astrophysics Data System (ADS)

Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.

2012-04-01

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.

A multiyear study of soil moisture patterns across agricultural and forested landscapes

NASA Astrophysics Data System (ADS)

Georgakakos, C. B.; Hofmeister, K.; O'Connor, C.; Buchanan, B.; Walter, T.

2017-12-01

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.

A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products

USDA-ARS?s Scientific Manuscript database

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...

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

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.

Empirical Soil Moisture Estimation with Spaceborne L-band Polarimetric Radars: Aquarius, SMAP, and PALSAR-2

NASA Astrophysics Data System (ADS)

Burgin, M. S.; van Zyl, J. J.

2017-12-01

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.

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...

SMAP Radiometer Captures Views of Global Soil Moisture

NASA Image and Video Library

2015-05-06

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.

Drought evolution: greater and faster impacts on blue water than on green water

NASA Astrophysics Data System (ADS)

Destouni, G.; Orth, R.

2017-12-01

Drought propagates through the terrestrial water cycle, affecting different interlinked geospheres which have so far been mostly investigated separately and without direct comparison. By use of comprehensive multi-decadal data from >400 near-natural catchments along a steep climate gradient across Europe we here analyze drought propagation from precipitation (deficits) through soil moisture to runoff (blue water) and evapotranspiration (green water). We show that soil-moisture droughts reduce runoff stronger and faster than evapotranspiration. While runoff responds within weeks, evapotranspiration can be unaffected for months, or even entirely as in central and northern Europe. Understanding these different drought pathways towards blue and green water resources contributes to improve food and water security and offers early warning potential to mitigate (future) drought impacts on society and ecosystems.

Investigating local controls on soil moisture temporal stability using an inverse modeling approach

NASA Astrophysics Data System (ADS)

Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

2013-04-01

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).

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

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.

Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission

NASA Technical Reports Server (NTRS)

Arya, L. M.; Phinney, D. E. (Principal Investigator)

1980-01-01

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.

Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank

2005-01-01

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.

Effects of soil moisture on dust emission from 2011 to 2015 observed over the Horqin Sandy Land area, China

NASA Astrophysics Data System (ADS)

Ju, Tingting; Li, Xiaolan; Zhang, Hongsheng; Cai, Xuhui; Song, Yu

2018-06-01

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.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

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.

Hydrologic downscaling of soil moisture using global data without site-specific calibration

USDA-ARS?s Scientific Manuscript database

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...

New Physical Algorithms for Downscaling SMAP Soil Moisture

NASA Astrophysics Data System (ADS)

Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.

2017-12-01

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.

Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

NASA Astrophysics Data System (ADS)

Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

2017-05-01

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.

Methods of measuring soil moisture in the field

USGS Publications Warehouse

Johnson, A.I.

1962-01-01

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.

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

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.

Soil Moisture under Different Vegetation cover in response to Precipitation

NASA Astrophysics Data System (ADS)

Liang, Z.; Zhang, J.; Guo, B.; Ma, J.; Wu, Y.

2016-12-01

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

Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites

USDA-ARS?s Scientific Manuscript database

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 ...

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

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.

Drive by Soil Moisture Measurement: A Citizen Science Project

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

2017-12-01

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.

Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products

NASA Astrophysics Data System (ADS)

Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.

2016-12-01

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.

Global land moisture trends: drier in dry and wetter in wet over land.

PubMed

Feng, Huihui; Zhang, Mingyang

2015-12-11

The "dry gets drier, wet gets wetter" (DGDWGW) paradigm is widely accepted in global moisture change. However, Greve et al. have declared that this paradigm has been overestimated. This controversy leaves a large gap in the understanding of the evolution of water-related processes. Here, we examine the global moisture trends using satellite soil moisture for the past 35 years (1979-2013). Our results support those of Greve et al., although there are quantitative differences. Generally, approximately 30% of global land has experienced robust moisture trends (22.16% have become drier, and 7.14% have become wetter). Only 15.12% of the land areas have followed the DGDWGW paradigm, whereas 7.77% have experienced the opposite trend. A new finding is that there is a significant "drier in dry, wetter in wet" (DIDWIW) trend paradigm; 52.69% of the drying trend occurred in arid regions, and 48.34% of the wetter trend occurred in the humid regions. Overall, 51.63% of the trends followed the DIDWIW paradigm, and 26.93% followed the opposite trend. We also identified the DGDWGW and DIDWIW paradigms in low precipitation-induced arid regions in which the dry soil led to an increasing sensible heat flux and temperature and subsequently potential evapotranspiration.

Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF)

NASA Astrophysics Data System (ADS)

Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin

2005-11-01

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.

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981

NASA Technical Reports Server (NTRS)

Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.

1982-01-01

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.

Diagnosing the Sensitivity of Local Land-Atmosphere Coupling via the Soil Moisture-Boundary Layer Interaction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.

2011-01-01

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.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

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.

An Efficient Approach to Modeling the Topographic Control of Surface Hydrology for Regional and Global Climate Modeling.

NASA Astrophysics Data System (ADS)

Stieglitz, Marc; Rind, David; Famiglietti, James; Rosenzweig, Cynthia

1997-01-01

The current generation of land-surface models used in GCMs view the soil column as the fundamental hydrologic unit. While this may be effective in simulating such processes as the evolution of ground temperatures and the growth/ablation of a snowpack at the soil plot scale, it effectively ignores the role topography plays in the development of soil moisture heterogeneity and the subsequent impacts of this soil moisture heterogeneity on watershed evapotranspiration and the partitioning of surface fluxes. This view also ignores the role topography plays in the timing of discharge and the partitioning of discharge into surface runoff and baseflow. In this paper an approach to land-surface modeling is presented that allows us to view the watershed as the fundamental hydrologic unit. The analytic form of TOPMODEL equations are incorporated into the soil column framework and the resulting model is used to predict the saturated fraction of the watershed and baseflow in a consistent fashion. Soil moisture heterogeneity represented by saturated lowlands subsequently impacts the partitioning of surface fluxes, including evapotranspiration and runoff. The approach is computationally efficient, allows for a greatly improved simulation of the hydrologic cycle, and is easily coupled into the existing framework of the current generation of single column land-surface models. Because this approach uses the statistics of the topography rather than the details of the topography, it is compatible with the large spatial scales of today's regional and global climate models. Five years of meteorological and hydrological data from the Sleepers River watershed located in the northeastern United States where winter snow cover is significant were used to drive the new model. Site validation data were sufficient to evaluate model performance with regard to various aspects of the watershed water balance, including snowpack growth/ablation, the spring snowmelt hydrograph, storm hydrographs, and the seasonal development of watershed evapotranspiration and soil moisture.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

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

Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

NASA Technical Reports Server (NTRS)

Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.

1997-01-01

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.

Method for evaluating moisture tensions of soils using spectral data

NASA Technical Reports Server (NTRS)

Peterson, John B. (Inventor)

1982-01-01

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.

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

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.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

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.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

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.

Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller

NASA Astrophysics Data System (ADS)

Gines, G. A.; Bea, J. G.; Palaoag, T. D.

2018-03-01

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.

Soil Moisture Memory in Climate Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

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.

Soil moisture and vegetation patterns in northern California forests

Treesearch

James R. Griffin

1967-01-01

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...

Effect of land-use practice on soil moisture variability for soils covered with dense forest vegetation of Puerto Rico

NASA Technical Reports Server (NTRS)

Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.

1998-01-01

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.

A comparison of soil-moisture loss from forested and clearcut areas in West Virginia

Treesearch

Charles A. Troendle

1970-01-01

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.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

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.

Impact of Diverse Hydrologic Pathways, 3D Failure Geometries, and Unsaturated Soil Suctions on Shallow Landsliding

NASA Astrophysics Data System (ADS)

Reid, M. E.; Iverson, R. M.; Brien, D. L.; Iverson, N. R.; Lahusen, R. G.; Logan, M.

2016-12-01

Shallow landslides and ensuing debris flows can be triggered by diverse hydrologic phenomena such as groundwater inflow, prolonged moderate-intensity precipitation, or bursts of high-intensity precipitation. However, hazard assessments typically rely on simplistic hydrologic models that disregard this diversity. We used the USGS debris-flow flume to conduct controlled, field-scale slope failure experiments designed to investigate the effects of diverse hydrologic pathways, as well as the effects of 3D landslide geometries and suction stresses in unsaturated soil. Using overhead sprinklers or groundwater injectors on the flume bed, we induced failures in 6 m3 (0.65-m thick and 2-m wide) prisms of loamy sand on a 31º slope. We used 50 sensors to monitor soil deformation, variably saturated pore pressures, and moisture changes. We also determined shear strength, hydraulic conductivity, and unsaturated moisture retention characteristics from ancillary tests. The three hydrologic scenarios noted above led to different behaviors. Groundwater injection and prolonged infiltration created differing soil moisture patterns. Intense sprinkling bursts caused rapid failure without development of widespread positive pore pressures. We simulated these observed differences numerically by coupling 2D variably saturated groundwater flow modeling and 3D limit-equilibrium analysis. We also simulated the time evolution of changes in factors of safety, and quantified the mechanical effects of 3D geometry and unsaturated soil suction on stability. When much of the soil became relatively wet, effects of 3D geometry and soil suction produced slight increases ( 10-20%) in factors of safety. Suction effects were more pronounced with drier soils. Our results indicate that simplistic models cannot consistently predict the timing of slope failure, and that high frequency monitoring (with sampling periods < 60 s) is needed to measure and interpret the effects of rapid hydrologic triggers.

Examining diel patterns of soil and xylem moisture using electrical resistivity imaging

NASA Astrophysics Data System (ADS)

Mares, Rachel; Barnard, Holly R.; Mao, Deqiang; Revil, André; Singha, Kamini

2016-05-01

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.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

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.

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

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.

Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective

NASA Astrophysics Data System (ADS)

Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.

2017-12-01

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.

Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun

2018-07-01

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.

Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

2017-12-01

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.

Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

NASA Astrophysics Data System (ADS)

Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

2018-03-01

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.

Improving the Non-Hydrostatic Numerical Dust Model by Integrating Soil Moisture and Greenness Vegetation Fraction Data with Different Spatiotemporal Resolutions.

PubMed

Yu, Manzhu; Yang, Chaowei

2016-01-01

Dust storms are devastating natural disasters that cost billions of dollars and many human lives every year. Using the Non-Hydrostatic Mesoscale Dust Model (NMM-dust), this research studies how different spatiotemporal resolutions of two input parameters (soil moisture and greenness vegetation fraction) impact the sensitivity and accuracy of a dust model. Experiments are conducted by simulating dust concentration during July 1-7, 2014, for the target area covering part of Arizona and California (31, 37, -118, -112), with a resolution of ~ 3 km. Using ground-based and satellite observations, this research validates the temporal evolution and spatial distribution of dust storm output from the NMM-dust, and quantifies model error using measurements of four evaluation metrics (mean bias error, root mean square error, correlation coefficient and fractional gross error). Results showed that the default configuration of NMM-dust (with a low spatiotemporal resolution of both input parameters) generates an overestimation of Aerosol Optical Depth (AOD). Although it is able to qualitatively reproduce the temporal trend of the dust event, the default configuration of NMM-dust cannot fully capture its actual spatial distribution. Adjusting the spatiotemporal resolution of soil moisture and vegetation cover datasets showed that the model is sensitive to both parameters. Increasing the spatiotemporal resolution of soil moisture effectively reduces model's overestimation of AOD, while increasing the spatiotemporal resolution of vegetation cover changes the spatial distribution of reproduced dust storm. The adjustment of both parameters enables NMM-dust to capture the spatial distribution of dust storms, as well as reproducing more accurate dust concentration.

Variation in microbial activity in histosols and its relationship to soil moisture.

PubMed

Tate, R L; Terry, R E

1980-08-01

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.

Variation in Microbial Activity in Histosols and Its Relationship to Soil Moisture †

PubMed Central

Tate, Robert L.; Terry, Richard E.

1980-01-01

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

Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach

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.

Climate Prediction Center - United States Drought Information

Science.gov Websites

• Crop Moisture Indices • Soil Moisture Percentiles (based on NLDAS) • Standardized Runoff Index (based /Minimum • Mean Surface Hydrology (based on NLDAS) • Total Soil Moisture • Total SM Change • MOSAIC Soil Moisture Profile • NOAH Soil Moisture Profile • NOAH Soil T Profile • Evaporation • E-P Â

An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

NASA Technical Reports Server (NTRS)

Wang, J. R.

1992-01-01

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.

Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin

2016-03-01

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.

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.

2016-12-01

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

Downscaled soil moisture from SMAP evaluated using high density observations

USDA-ARS?s Scientific Manuscript database

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 ...

Data assimilation to extract soil moisture information from SMAP observations

USDA-ARS?s Scientific Manuscript database

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...

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

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.

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.

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

2012-01-01

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 (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.

Microwave remote sensing and its application to soil moisture detection

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator)

1977-01-01

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.

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

NASA Technical Reports Server (NTRS)

Whiting, Michael L.; Li, Lin; Ustin, Susan L.

2004-01-01

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.

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

2015-01-01

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.

Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.

2005-12-01

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.

Data documentation for the bare soil experiment at the University of Arkansas

NASA Technical Reports Server (NTRS)

Waite, W. P.; Scott, H. D. (Principal Investigator); Hancock, G. D.

1980-01-01

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.

Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA

Treesearch

James Reardon; Gary Curcio; Roberta Bartlette

2009-01-01

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...

The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission

USDA-ARS?s Scientific Manuscript database

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 ...

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

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.

Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions

PubMed Central

Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto

2007-01-01

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

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

NASA Technical Reports Server (NTRS)

Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

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.

Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)

1982-01-01

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.

Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.

PubMed

Luster-Teasley, S; Ubaka-Blackmoore, N; Masten, S J

2009-08-15

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.

Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization

PubMed Central

Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie

2015-01-01

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

Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

2016-06-01

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.

Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Cao, W.; Sheng, Y.

2017-12-01

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.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

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.

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

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.

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

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.

Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J. F.; Mecikalski, J. R.

2015-12-01

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.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

2017-09-01

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.

National Centers for Environmental Prediction

Science.gov Websites

) soilm1 0-10cm soil moisture soilm2 10-40cm soil moisture soilm3 40-100cm soil moisture soilm4 100-200cm soil moisture soilt1 0-10cm soil temperature soilt2 10-40cm soil temperature soilt3 40-100cm soil temperature soilt4 100-200cm soil temperature thick700.ptype 850-700mb thickness precipitation type thick850

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

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.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

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.

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

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.

SMERGE: A multi-decadal root-zone soil moisture product for CONUS

NASA Astrophysics Data System (ADS)

Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.

2017-12-01

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.

Global response of the growing season to soil moisture and topography

NASA Astrophysics Data System (ADS)

Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.

2017-12-01

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.

Soil Moisture and the Persistence of North American Drought.

NASA Astrophysics Data System (ADS)

Oglesby, Robert J.; Erickson, David J., III

1989-11-01

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.

Holocene moisture variations over the arid central Asia revealed by a comprehensive sand-dune record from the central Tian Shan, NW China

NASA Astrophysics Data System (ADS)

Long, Hao; Shen, Ji; Chen, Jianhui; Tsukamoto, Sumiko; Yang, Linhai; Cheng, Hongyi; Frechen, Manfred

2017-10-01

Arid central Asia (ACA) is one of the largest arid (desert) areas in the world, and its climate is dominated by the westerlies. In this study, we examined sand dune evolution from the Bayanbulak Basin in the Tian Shan (Xinjiang, NW China), aiming to infer the Holocene moisture history of the ACA. Combined with stratigraphic observation and environmental proxies analysis (grain size, magnetic susceptibility and total organic content), large numbers of luminescence ages from multiple sites (eight sections, 79 samples) were applied to reconstruct the evolution of the sand dune accumulation in the study basin. The overall results imply very dry conditions characterized by sand dune accumulation at ∼12-6.5 ka, a wet interval between ∼6.5 and 0.8 ka when soil formation occurred, and decreased moisture during the last 0.8 ka. This moisture variation pattern is generally consistent with that inferred from many lacustrine records in the core zone of ACA, suggesting a widespread dry period in the early-to-middle Holocene and relatively wet middle-to-late Holocene. Thus, the moisture history derived from the current sand dune system contrasts with that in Asian monsoon areas, which are characterized by a strong monsoon (high precipitation) in the early and mid-Holocene and a weak monsoon (low precipitation and dry climate) during the late Holocene. Our results strongly suggest that the winter solar insolation and the external boundary conditions such as atmospheric CO2 concentration, ice sheets, and meltwater fluxes, have been major influential factors triggering the Holocene moisture evolution in the core zone of ACA.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

2011-02-01

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; http://www.ipf.tuwien.ac.at/insitu) 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.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

NASA Astrophysics Data System (ADS)

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.

2011-05-01

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; http://www.ipf.tuwien.ac.at/insitu) 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.

Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products

USDA-ARS?s Scientific Manuscript database

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...

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

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...

Evaluation of SMOS soil moisture products over the CanEx-SM10 area

USDA-ARS?s Scientific Manuscript database

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...

SMOS soil moisture validation with U.S. in situ newworks

USDA-ARS?s Scientific Manuscript database

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...

Potential of bias correction for downscaling passive microwave and soil moisture data

USDA-ARS?s Scientific Manuscript database

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...

Validation of SMAP surface soil moisture products with core validation sites

USDA-ARS?s Scientific Manuscript database

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...

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets

USDA-ARS?s Scientific Manuscript database

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...

Estimating error cross-correlations in soil moisture data sets using extended collocation analysis

USDA-ARS?s Scientific Manuscript database

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...

Precipitation estimation using L-Band and C-Band soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

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...

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

USDA-ARS?s Scientific Manuscript database

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...

Evaluation of an operational real-time irrigation scheduling scheme for drip irrigated citrus fields in Picassent, Spain

NASA Astrophysics Data System (ADS)

Li, Dazhi; Hendricks-Franssen, Harrie-Jan; Han, Xujun; Jiménez Bello, Miguel Angel; Martínez Alzamora, Fernando; Vereecken, Harry

2017-04-01

Irrigated agriculture accounts worldwide for 40% of food production and 70% of fresh water withdrawals. Irrigation scheduling aims to minimize water use while maintaining the agricultural production. In this study we were concerned with the real-time automatic control of irrigation, which calculates daily water allocation by combining information from soil moisture sensors and a land surface model. The combination of soil moisture measurements and predictions by the Community Land Model (CLM) using sequential data assimilation (DA) is a promising alternative to improve the estimate of soil and plant water status. The LETKF (Local Ensemble Transform Kalman Filter) was chosen to assimilate soil water content measured by FDR (Frequency Domain Reflectometry) into CLM and improve the initial (soil moisture) conditions for the next model run. In addition, predictions by the GFS (Global Forecast System) atmospheric simulation model were used as atmospheric input data for CLM to predict an ensemble of possible soil moisture evolutions for the next days. The difference between predicted and target soil water content is defined as the water deficit, and the irrigation amount was calculated by the integrated water deficit over the root zone. The corresponding irrigation time to apply the required water was introduced in SCADA (supervisory control and data acquisition system) for each citrus field. In total 6 fields were irrigated according our optimization approach including data assimilation (CLM-DA) and there were also 2 fields following the FAO (Food and Agriculture Organization) water balance method and 4 fields controlled by farmers as reference. During the real-time irrigation campaign in Valencia from July to October in 2015 and June to October in 2016, the applied irrigation amount, stem water potential and soil moisture content were recorded. The data indicated that 5% 20% less irrigation water was needed for the CLM-DA scheduled fields than for the other fields following the FAO or farmers' method. Stem water potential data indicated that the CLM-DA fields were not suffering from water stress during most of the irrigation period. Even though the CLM-DA fields received the least irrigation water, the orange production was not suppressed either. Our results show the water saving potential of the CLM-DA method compared to other traditional irrigation methods.

Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming

NASA Astrophysics Data System (ADS)

Azorin-Molina, Cesar; Vicente-Serrano, Sergio M.; Cerdà, Artemi

2013-04-01

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.

Inventory of File gfs.t06z.sfluxgrbf00.grib2

Science.gov Websites

Volumetric Soil Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric Soil Volumetric Soil Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric Soil Moisture analysis Temperature [K] 071 0-0.1 m below ground SOILL analysis Liquid Volumetric Soil Moisture (non

Airborne Active and Passive L-Band Observations in Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12)

NASA Astrophysics Data System (ADS)

Colliander, A.; Yueh, S. H.; Chazanoff, S.; Jackson, T. J.; McNairn, H.; Bullock, P.; Wiseman, G.; Berg, A. A.; Magagi, R.; Njoku, E. G.

2012-12-01

NASA's (National Aeronautics and Space Administration) Soil Moisture Active Passive (SMAP) Mission is scheduled for launch in October 2014. The objective of the mission is global mapping of soil moisture and freeze/thaw state. Merging of active and passive L-band observations of the mission will enable unprecedented combination of accuracy, resolution, coverage and revisit-time for soil moisture and freeze/thaw state retrieval. For pre-launch algorithm development and validation the SMAP project and NASA coordinated a field campaign named as SMAPVEX12 (Soil Moisture Active Passive Validation Experiment 2012) together with Agriculture and Agri-Food Canada in the vicinity of Winnipeg, Canada in June-July, 2012. The main objective of SMAPVEX12 was acquisition of data record that features long-time series with varying soil moisture and vegetation conditions (for testing the application of time-series approach) over aerial domain of multiple parallel lines (for spatial disaggregation studies). The coincident active and passive L-band data were acquired using the Passive Active L-band System (PALS), which is an airborne radiometer and radar developed for testing L-band retrieval algorithms. For SMAPVEX12 PALS was installed on a Twin Otter aircraft. The flight plan included flights at two altitudes. The higher altitude was used to map the whole experiment domain and the lower altitude was used to obtain measurements over a specific set of field sites. The spatial resolution (and swath) of the radar and radiometer from low altitude was about 600 m and from high altitude about 1500 m. The PALS acquisitions were complemented with high resolution (~10 m) L-band SAR measurements carried out by UAVSAR instrument on-board G-III aircraft. The campaign ran from June 7 until July 19. The PALS instrument conducted 17 brightness temperature and backscatter measurement flights and the UAVSAR conducted 14 backscatter measurement flights. The airborne data acquisition was supported by extensive ground truth collection. In situ soil moisture and vegetation biomass and structure of the mixed cropland, pasture and forest landscape of the experiment domain was gathered synchronously with the airborne acquisitions. The conditions included wide range in both soil moisture and vegetation density. This paper presents an overview of the SMAPVEX12 campaign and an evaluation of the quality of the PALS measurements. The calibration methodology based on the internal calibration, lake over-flights and specific calibration maneuvers were utilized before and after each day's science flights to guarantee accuracy and consistency of the measurements over the campaign duration. As a consequence the correspondence of the airborne acquisitions with the spatial and temporal evolution of the geophysical variables over the experiment domain meets the requirement set by the objectives of the campaign. Acknowledgement: This work was carried out in Jet Propulsion Laboratory, California Institute of Technology under contract with National Aeronautics and Space Administration. USDA is an equal opportunity provider and employer.

Soil water dynamics during precipitation in genetic horizons of Retisol

NASA Astrophysics Data System (ADS)

Zaleski, Tomasz; Klimek, Mariusz; Kajdas, Bartłomiej

2017-04-01

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.

Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses

PubMed Central

Arvela, H.; Holmgren, O.; Hänninen, P.

2016-01-01

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

The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

NASA Technical Reports Server (NTRS)

ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

1997-01-01

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.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

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).

The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

NASA Astrophysics Data System (ADS)

Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye

2018-06-01

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.

Spatial and temporal variability of soil moisture on the field with and without plants*

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Usowicz, J. B.

2012-04-01

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.

Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

NASA Technical Reports Server (NTRS)

Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.

1997-01-01

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.

[Soil moisture dynamics of artificial Caragana microphylla shrubs at different topographical sites in Horqin sandy land].

PubMed

Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui

2009-03-01

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.

An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02

NASA Technical Reports Server (NTRS)

Bolten, John D.; Lakshmi, Venkat

2009-01-01

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.

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

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...

Application of triple collocation in ground-based validation of soil moisture active/passive (SMAP) level 2 data products

USDA-ARS?s Scientific Manuscript database

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 ...

Soil-moisture constants and their variation

Treesearch

Walter M. Broadfoot; Hubert D. Burke

1958-01-01

"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...

Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

USDA-ARS?s Scientific Manuscript database

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...

Soil moisture depletion patterns around scattered trees

Treesearch

Robert R. Ziemer

1968-01-01

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...

Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area

USDA-ARS?s Scientific Manuscript database

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 ...

Calibration and validation of the COSMOS rover for surface soil moisture

USDA-ARS?s Scientific Manuscript database

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...

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

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.

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).

PubMed

Simelane, David O

2007-06-01

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.

Effect of soil moisture on the sorption of trichloroethene vapor to vadose-zone soil at picatinny arsenal, New Jersey

USGS Publications Warehouse

Smith, J.A.; Chiou, C.T.; Kammer, J.A.; Kile, D.E.

1990-01-01

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.

Assessment of Version 4 of the SMAP Passive Soil Moisture Standard Product

NASA Technical Reports Server (NTRS)

O'neill, P. O.; Chan, S.; Bindlish, R.; Jackson, T.; Colliander, A.; Dunbar, R.; Chen, F.; Piepmeier, Jeffrey R.; Yueh, S.; Entekhabi, D.;

The global distribution and dynamics of surface soil moisture

NASA Astrophysics Data System (ADS)

McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

2017-01-01

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.

Observations of a two-layer soil moisture influence on surface energy dynamics and planetary boundary layer characteristics in a semiarid shrubland

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.

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

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.

2017-04-01

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.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

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.

Where did my wifi go? Measuring soil moisture using wifi signal strength

NASA Astrophysics Data System (ADS)

Hut, Rolf; de Jeu, Richard

2015-04-01

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.

Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.

2017-12-01

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.

High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent

NASA Astrophysics Data System (ADS)

Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.

2016-12-01

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.

Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

NASA Astrophysics Data System (ADS)

Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

2017-12-01

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.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

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.

Study Variability of Seasonal Soil Moisture in Ensemble of CMIP5 Models Over South Asia During 1950-2005

NASA Astrophysics Data System (ADS)

Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.

2015-12-01

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.

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

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).

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

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).

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

NASA Astrophysics Data System (ADS)

Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.

2018-04-01

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.

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

NASA Technical Reports Server (NTRS)

Labgaa, Rachid R.; Gautier, Catherine

1992-01-01

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.

What is the philosophy of modelling soil moisture movement?

NASA Astrophysics Data System (ADS)

Chen, J.; Wu, Y.

2009-12-01

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.

Exploring the Role of Soil Moisture Conditions for Rainfall Triggered Landslides on Catchment Scale: the case of the Ialomita Sub Carpathians, Romania

NASA Astrophysics Data System (ADS)

Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru

2014-05-01

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.

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

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

Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships

NASA Astrophysics Data System (ADS)

Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott

2018-02-01

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.

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.

Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei

2016-12-01

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.

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc

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

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE PAGES

Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc; ...

2017-12-14

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

Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grossiord, Charlotte; Sevanto, Sanna; Limousin, Jean-Marc

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

A Citizen Science Soil Moisture Sensor to Support SMAP Calibration/Validation

NASA Astrophysics Data System (ADS)

Podest, E.; Das, N. N.

2016-12-01

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.

Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils

NASA Astrophysics Data System (ADS)

Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue

2017-04-01

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.

Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi

2016-04-01

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.

The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

1985-01-01

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.

Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

1981-01-01

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.

SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann

2011-01-01

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.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers

PubMed Central

Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-01-01

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

Disaggregation Of Passive Microwave Soil Moisture For Use In Watershed Hydrology Applications

NASA Astrophysics Data System (ADS)

Fang, Bin

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.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers.

PubMed

Gao, Zhenran; Zhu, Yan; Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-05-21

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.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

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.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

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.

Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)

USDA-ARS?s Scientific Manuscript database

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 ...

Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

USDA-ARS?s Scientific Manuscript database

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...

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

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 ...

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model

USDA-ARS?s Scientific Manuscript database

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...

Understanding Soil Moisture

USDA-ARS?s Scientific Manuscript database

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...

Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study

NASA Astrophysics Data System (ADS)

Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.

2015-12-01

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.

Effect of soil moisture on the temperature sensitivity of Northern soils

NASA Astrophysics Data System (ADS)

Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.

2017-12-01

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.

Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

NASA Astrophysics Data System (ADS)

Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

2015-12-01

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.

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.

Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals

NASA Astrophysics Data System (ADS)

Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.

2009-04-01

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

Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography

NASA Astrophysics Data System (ADS)

Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.

2016-12-01

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.

Assimilating soil moisture into an Earth System Model

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2017-04-01

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.

Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara

2012-08-01

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.

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

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.

Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)

PubMed Central

Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François

2007-01-01

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

Concerning the relationship between evapotranspiration and soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1987-01-01

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.

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

1983-01-01

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.

Soil and Atmospheric Controls on the Land Surface Energy Balance: A Generalized Framework for Distinguishing Moisture-Limited and Energy-Limited Evaporation Regimes

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Short Gianotti, Daniel J.; Akbar, Ruzbeh; Salvucci, Guido D.; Entekhabi, Dara

2018-03-01

The relationship between evaporative fraction (EF) and soil moisture (SM) has traditionally been used in atmospheric and land-surface modeling communities to determine the coupling strength between land surfaces and the atmosphere in the context of the dominant evaporation regime (energy or moisture limited). However, observation-based analyses suggest that EF-SM relationship in a given region can shift subject to other environmental factors, potentially influencing the determination of the dominant evaporation regime. This implies more complex dependencies embedded in the conventional EF-SM relationship and that in fact it is a multidimensional function. In this study, we develop a generalized EF framework that explicitly accounts for dependencies on other environmental conditions. We show that large scatter in observed EF-SM relationships is primarily due to the projection of variations in other dimensions and propose a normalization of the EF-SM relationship accounting for the dimensions and dependencies not included in the conventional relationship. In this first study, we focus on bare soil conditions in order to establish the basic theoretical framework. The new generalized EF framework provides new insights into the origin of transition between energy-limited and moisture-limited evaporation regimes (marked by a critical SM), linked to soil type and meteorological input data (primarily wind speed and air temperature, but not solar radiation) dominating the evolution of land surface temperature and thus the relative efficiency of surface energy balance components during surface drying. Our results offer new opportunities to advance predictive capabilities quantifying land-atmosphere coupling for a wide range of present and projected meteorological input data.

SOIL moisture data intercomparison

NASA Astrophysics Data System (ADS)

Kerr, Yann; Rodriguez-Frenandez, Nemesio; Al-Yaari, Amen; Parens, Marie; Molero, Beatriz; Mahmoodi, Ali; Mialon, Arnaud; Richaume, Philippe; Bindlish, Rajat; Mecklenburg, Susanne; Wigneron, Jean-Pierre

2016-04-01

The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. Subsequently, the satellite has been in operation for over 6 years while the retrieval algorithms from Level 1 to Level 2 underwent significant evolutions as knowledge improved. Other approaches for retrieval at Level 2 over land were also investigated while Level 3 and 4 were initiated. In this présentation these improvements are assessed by inter-comparisons of the current Level 2 (V620) against the previous version (V551) and new products either using neural networks or Level 3. In addition a global evaluation of different SMOS soil moisture (SM) products is performed comparing products with those of model simulations and other satellites (AMSR E/ AMSR2 and ASCAT). Finally, all products were evaluated against in situ measurements of soil moisture (SM). The study demonstrated that the V620 shows a significant improvement (including those at level1 improving level2)) with respect to the earlier version V551. Results also show that neural network based approaches can yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved while RFI sources in several areas of the world are significantly reduced. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.

A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

2017-04-01

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.

High-resolution soil moisture mapping in Afghanistan

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry

2011-06-01

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.

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

2010-01-01

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.

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

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.

Pupal development of Ceratitis capitata (Diptera: Tephritidae) and Diachasmimorpha longicaudata (Hymenoptera: Braconidae) at different moisture values in four soil types.

PubMed

Bento, F de M M; Marques, R N; Costa, M L Z; Walder, J M M; Silva, A P; Parra, J R P

2010-08-01

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.

Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

NASA Technical Reports Server (NTRS)

Chan, S.; Bindlish, R.; O'Neill, P.; Jackson, T.; Chaubell, J.; Piepmeier, J.; Dunbar, S.; Colliander, A.; Chen, F.; Entekhabi, D.;

Soil moisture retrival from Sentinel-1 and Modis synergy

NASA Astrophysics Data System (ADS)

Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

2017-04-01

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.

Evaluating ESA CCI soil moisture in East Africa.

PubMed

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P

2016-06-01

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.

Irrigation scheduling using soil moisture sensors

USDA-ARS?s Scientific Manuscript database

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...

Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model

NASA Astrophysics Data System (ADS)

Zhang, Hongjuan; Kurtz, Wolfgang; Kollet, Stefan; Vereecken, Harry; Franssen, Harrie-Jan Hendricks

2018-01-01

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.

Soil moisture inferences from thermal infrared measurements of vegetation temperatures

NASA Technical Reports Server (NTRS)

Jackson, R. D. (Principal Investigator)

1981-01-01

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.

Soil moisture modeling review

NASA Technical Reports Server (NTRS)

Hildreth, W. W.

1978-01-01

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.

Soil moisture monitoring for crop management

NASA Astrophysics Data System (ADS)

Boyd, Dale

2015-07-01

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

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

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.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

2011-01-01

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.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

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.

2011-01-01

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.

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

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.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

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.

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar

PubMed Central

Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco

2008-01-01

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

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

NASA Technical Reports Server (NTRS)

Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.

1993-01-01

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.

The impact of fog on soil moisture dynamics in the Namib Desert

NASA Astrophysics Data System (ADS)

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.

2018-03-01

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.

Evaluating the influence of antecedent soil moisture on variability of the North American Monsoon precipitation in the coupled MM5/VIC modeling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Chunmei; Leung, Lai R.; Gochis, David

2009-11-29

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

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

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.

A study of the influence of soil moisture on future precipitation

NASA Technical Reports Server (NTRS)

Fennessy, M. J.; Sud, Y. C.

1983-01-01

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.

Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

NASA Astrophysics Data System (ADS)

Zhuo, Lu; Han, Dawei

2016-04-01

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).

An integrated GIS application system for soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

2014-11-01

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.

On-irrigator pasture soil moisture sensor

NASA Astrophysics Data System (ADS)

Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian

2017-02-01

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.

Soil moisture and the persistence of North American drought

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Erickson, David J., III

1989-01-01

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.

Soil-moisture sensors and irrigation management

USDA-ARS?s Scientific Manuscript database

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...

Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16

NASA Technical Reports Server (NTRS)

Colliander, Andreas; Jackson, Thomas J.; Cosh, Mike; Misra, Sidharth; Bindlish, Rajat; Powers, Jarrett; McNairn, Heather; Bullock, P.; Berg, A.; Magagi, A.;

Measuring Soil Moisture using the Signal Strength of Buried Bluetooth Devices.

NASA Astrophysics Data System (ADS)

Hut, R.; Campbell, C. S.

2015-12-01

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.

An empirical model for the complex dielectric permittivity of soils as a function of water content

NASA Technical Reports Server (NTRS)

Wang, J. R.; Chmugge, T. J.

1978-01-01

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.

Surface soil moisture retrieval over a Mediterranean semi-arid region using X-band TerraSAR-X SAR data

NASA Astrophysics Data System (ADS)

Azza, Gorrab; Zribi, Mehrez; Baghdadi, Nicolas; Mougenot, Bernard; Boulet, Gilles; Lili-Chabaane, Zohra

2015-04-01

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%.

A Texas Flood from Land to Ocean Observed by SMAP

NASA Astrophysics Data System (ADS)

Fournier, S.; Reager, J. T., II; Lee, T.; Vazquez, J.; David, C. H.; Gierach, M. M.

2016-12-01

Floods are natural hazards that can have damaging impacts not only on affected land areas but also on the adjacent coastal waters. NASA's Soil Moisture Active Passive (SMAP) mission provides measurements of both surface soil moisture and sea surface salinity (SSS), offering the opportunity to study the effects of flooding events on both terrestrial and marine environments. Here, we present analysis of a severe flood that occurred in May 2015 in Texas using SMAP observations and ancillary satellite and in situ data that describe the precipitation intensity, the evolving saturation state of the land surface, the flood discharge peak, and the resulting freshwater plume in the Gulf of Mexico. We describe the spatiotemporal evolution of the different variables, their relationships, and the associated physical processes. Specifically, we identify a freshwater plume in the north-central Gulf, being distinct from the typical Mississippi River plume, that is attributable to the Texas flood.

A semiempirical model for interpreting microwave emission from semiarid land surfaces as seen from space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1990-01-01

A radiative-transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, and polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure, and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7.

Analysis of in situ resources for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

NASA Astrophysics Data System (ADS)

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.

2016-12-01

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.

Soil moisture estimation using reflected solar and emitted thermal infrared radiation

NASA Technical Reports Server (NTRS)

Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.

1978-01-01

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.

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

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.

The sensitivity of numerically simulated climates to land-surface boundary conditions

NASA Technical Reports Server (NTRS)

Mintz, Y.

1982-01-01

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.

Application of IEM model on soil moisture and surface roughness estimation

NASA Technical Reports Server (NTRS)

Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

1995-01-01

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.

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

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.

Direct and indirect effects of atmospheric conditions and soil moisture on surface energy partitioning revealed by a prolonged drought at a temperate forest site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Lianhong; Meyers, T. P.; Pallardy, Stephen G.

2006-01-01

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

Soil water balance as affected by throughfall in gorse ( Ulex europaeus, L.) shrubland after burning

NASA Astrophysics Data System (ADS)

Soto, Benedicto; Diaz-Fierros, Francisco

1997-08-01

The role of fire in the hydrological behaviour of gorse shrub is studied from the point of view of its effects on vegetation cover and throughfall. In the first year after fire, throughfall represents about 88% of gross rainfall, whereas in unburnt areas it is 58%. Four years after fire, the throughfall coefficients are similar in burnt and unburnt plots (about 6096). The throughfall is not linearly related to vegetation cover because an increase in cover does not involve a proportional reduction in throughfall. The throughfall predicted by the two-parameter exponential model of Calder (1986, J. Hydrol., 88: 201-211) provides a good fit with the observed throughfall and the y value of the model reflects the evolution of throughfall rate. The soil moisture distribution is modified by fire owing to the increase of evaporation in the surface soil and the decrease of transpiration from deep soil layers. Nevertheless, the use of the old root system by sprouting vegetation leads to a soil water profile in which 20 months after the fire the soil water is similar in burnt and unburnt areas. Overall, soil moisture is higher in burnt plots than in unburnt plots. Surface runoff increases after a fire but does not entirely account for the increase in throughfall. Therefore the removal of vegetation cover in gorse scrub by fire mainly affects the subsurface water flows.

[Simulation of cropland soil moisture based on an ensemble Kalman filter].

PubMed

Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping

2011-11-01

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.

Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

2018-05-01

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.

Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

NASA Astrophysics Data System (ADS)

Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

2017-12-01

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.

Divergent surface and total soil moisture projections under global warming

USGS Publications Warehouse

Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

2017-01-01

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.

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

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.

Dynamics and characteristics of soil temperature and moisture of active layer in central Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhao, L.; Hu, G.; Wu, X.; Tian, L.

2017-12-01

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.

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

USDA-ARS?s Scientific Manuscript database

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...

Inventory of File gdas1.t06z.sfluxgrbf00.grib2

Science.gov Websites

analysis Volumetric Soil Moisture Content [Fraction] 007 0.1-0.4 m below ground SOILW analysis Volumetric Soil Moisture Content [Fraction] 008 0-0.1 m below ground TMP analysis Temperature [K] 009 0.1-0.4 m Volumetric Soil Moisture Content [Fraction] 068 1-2 m below ground SOILW analysis Volumetric Soil Moisture

Analysis of in situ resources of for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

USDA-ARS?s Scientific Manuscript database

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...

SMAP soil moisture drying more rapid than observed in situ following rainfall events

USDA-ARS?s Scientific Manuscript database

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...

A Round Robin evaluation of AMSR-E soil moisture retrievals

NASA Astrophysics Data System (ADS)

Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.

2014-05-01

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.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

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.

Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties

NASA Technical Reports Server (NTRS)

Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.

1997-01-01

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.

Experimental evidence and modelling of drought induced alternative stable soil moisture states

NASA Astrophysics Data System (ADS)

Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget

2017-04-01

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?

Soil moisture profile variability in land-vegetation- atmosphere continuum

NASA Astrophysics Data System (ADS)

Wu, Wanru

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.

Historical climate controls soil respiration responses to current soil moisture.

PubMed

Hawkes, Christine V; Waring, Bonnie G; Rocca, Jennifer D; Kivlin, Stephanie N

2017-06-13

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.

Land surface-precipitation feedback and ramifications on storm dynamics.

NASA Astrophysics Data System (ADS)

Baisya, H.; PV, R.; Pattnaik, S.

2017-12-01

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.

Electrical methods of determining soil moisture content

NASA Technical Reports Server (NTRS)

Silva, L. F.; Schultz, F. V.; Zalusky, J. T.

1975-01-01

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.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

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.

Soil moisture ground truth, Lafayette, Indiana, site; St. Charles Missouri, site; Centralia, Missouri, site

NASA Technical Reports Server (NTRS)

Jones, E. B.

1975-01-01

The soil moisture ground-truth measurements and ground-cover descriptions taken at three soil moisture survey sites located near Lafayette, Indiana; St. Charles, Missouri; and Centralia, Missouri are given. The data were taken on November 10, 1975, in connection with airborne remote sensing missions being flown by the Environmental Research Institute of Michigan under the auspices of the National Aeronautics and Space Administration. Emphasis was placed on the soil moisture in bare fields. Soil moisture was sampled in the top 0 to 1 in. and 0 to 6 in. by means of a soil sampling push tube. These samples were then placed in plastic bags and awaited gravimetric analysis.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-09-01

The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2010-06-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

[Sap flow characteristics of Quercus liaotungensis in response to sapwood area and soil moisture in the loess hilly region, China].

PubMed

Lyu, Jin Lin; He, Qiu Yue; Yan, Mei Jie; Li, Guo Qing; Du, Sheng

2018-03-01

To examine the characteristics of sap flow in Quercus liaotungensis and their response to environmental factors under different soil moisture conditions, Granier-type thermal dissipation probes were used to measure xylem sap flow of trees with different sapwood area in a natural Q. liaotungensis forest in the loess hilly region. Solar radiation, air temperature, relative air humidity, precipitation, and soil moisture were monitored during the study period. The results showed that sap flux of Q. liaotungensis reached daily peaks earlier than solar radiation and vapor pressure deficit. The diurnal dynamics of sap flux showed a similar pattern to those of the environmental factors. Trees had larger sap flux during the period with higher soil moisture. Under the same soil moisture conditions, trees with larger diameter and sapwood areas had significantly higher sap flux than those with smaller diameter and sapwood areas. Sap flux could be fitted with vapor pressure deficit, solar radiation, and the integrated index of the two factors using exponential saturation function. Differences in the fitted curves and parameters suggested that sap flux tended to reach saturation faster under higher soil moisture. Furthermore, trees in the smaller diameter class were more sensitive to the changes of soil moisture. The ratio of daily sap flux per unit vapor pressure deficit under lower soil moisture condition to that under higher soil moisture condition was linearly correlated to sapwood area. The regressive slope in smaller diameter class was larger than that in bigger diameter class, which further indicated the higher sensitivity of trees with smaller diameter class to soil moisture. These results indicated that wider sapwood of larger diameter class provided a buffer against drought stress.

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

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.

A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

NASA Astrophysics Data System (ADS)

Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

2017-09-01

Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.

Ecosystem-scale plant hydraulic strategies inferred from remotely-sensed soil moisture

NASA Astrophysics Data System (ADS)

Bassiouni, M.; Good, S. P.; Higgins, C. W.

2017-12-01

Characterizing plant hydraulic strategies at the ecosystem scale is important to improve estimates of evapotranspiration and to understand ecosystem productivity and resilience. However, quantifying plant hydraulic traits beyond the species level is a challenge. The probability density function of soil moisture observations provides key information about the soil moisture states at which evapotranspiration is reduced by water stress. Here, an inverse Bayesian approach is applied to a standard bucket model of soil column hydrology forced with stochastic precipitation inputs. Through this approach, we are able to determine the soil moisture thresholds at which stomata are open or closed that are most consistent with observed soil moisture probability density functions. This research utilizes remotely-sensed soil moisture data to explore global patterns of ecosystem-scale plant hydraulic strategies. Results are complementary to literature values of measured hydraulic traits of various species in different climates and previous estimates of ecosystem-scale plant isohydricity. The presented approach provides a novel relation between plant physiological behavior and soil-water dynamics.

Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

NASA Astrophysics Data System (ADS)

Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

2013-01-01

Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

PubMed

Wang, Min Zheng; Zhou, Guang Sheng

2016-06-01

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R 2 =0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

A method for soil moisture probes calibration and validation of satellite estimates.

PubMed

Holzman, Mauro; Rivas, Raúl; Carmona, Facundo; Niclòs, Raquel

2017-01-01

Optimization of field techniques is crucial to ensure high quality soil moisture data. The aim of the work is to present a sampling method for undisturbed soil and soil water content to calibrated soil moisture probes, in a context of the SMOS (Soil Moisture and Ocean Salinity) mission MIRAS Level 2 soil moisture product validation in Pampean Region of Argentina. The method avoids soil alteration and is recommended to calibrated probes based on soil type under a freely drying process at ambient temperature. A detailed explanation of field and laboratory procedures to obtain reference soil moisture is shown. The calibration results reflected accurate operation for the Delta-T thetaProbe ML2x probes in most of analyzed cases (RMSE and bias ≤ 0.05 m 3 /m 3 ). Post-calibration results indicated that the accuracy improves significantly applying the adjustments of the calibration based on soil types (RMSE ≤ 0.022 m 3 /m 3 , bias ≤ -0.010 m 3 /m 3 ). •A sampling method that provides high quality data of soil water content for calibration of probes is described.•Importance of calibration based on soil types.•A calibration process for similar soil types could be suitable in practical terms, depending on the required accuracy level.

Hillslope-scale experiment demonstrates role of convergence during two-step saturation

USGS Publications Warehouse

Gevaert, A. I.; Teuling, A. J.; Uijlenhoet, R.; DeLong, Stephen B.; Huxman, T. E.; Pangle, L. A.; Breshears, David D.; Chorover, J.; Pelletier, John D.; Saleska, S. R.; Zeng, X.; Troch, Peter A.

2014-01-01

Subsurface flow and storage dynamics at hillslope scale are difficult to ascertain, often in part due to a lack of sufficient high-resolution measurements and an incomplete understanding of boundary conditions, soil properties, and other environmental aspects. A continuous and extreme rainfall experiment on an artificial hillslope at Biosphere 2's Landscape Evolution Observatory (LEO) resulted in saturation excess overland flow and gully erosion in the convergent hillslope area. An array of 496 soil moisture sensors revealed a two-step saturation process. First, the downward movement of the wetting front brought soils to a relatively constant but still unsaturated moisture content. Second, soils were brought to saturated conditions from below in response to rising water tables. Convergent areas responded faster than upslope areas, due to contributions from lateral subsurface flow driven by the topography of the bottom boundary, which is comparable to impermeable bedrock in natural environments. This led to the formation of a groundwater ridge in the convergent area, triggering saturation excess runoff generation. This unique experiment demonstrates, at very high spatial and temporal resolution, the role of convergence on subsurface storage and flow dynamics. The results bring into question the representation of saturation excess overland flow in conceptual rainfall-runoff models and land-surface models, since flow is gravity-driven in many of these models and upper layers cannot become saturated from below. The results also provide a baseline to study the role of the co-evolution of ecological and hydrological processes in determining landscape water dynamics during future experiments in LEO.

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

Evaluation of the cosmic-ray neutron method for measuring integral soil moisture dynamics of a forested head water catchment

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.

2011-12-01

Measurements of low-energy secondary neutron intensity above the soil surface by cosmic-ray soil moisture probes (CRP) can be used to estimate soil moisture content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the soil. The conversion of neutron intensity to soil moisture content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that soil moisture content derived from CRP measurements agrees well with average moisture content from gravimetric soil samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are affected by the soil moisture distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless soil moisture sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 soil moisture sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique soil moisture data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to soil moisture variation in both the horizontal and vertical direction. Furthermore, the influence of forest biomass and shallow groundwater table fluctuations on the attenuation of cosmic-ray neutrons will be considered.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

NASA Technical Reports Server (NTRS)

Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

1995-01-01

Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.

Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas

NASA Astrophysics Data System (ADS)

Willgoose, G. R.

2006-12-01

In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically stable with time. In the second part of this presentation we will explore aspects of the calibration using data from the SASMAS site using the multiscale spatial resolution data (100m to 10km) provided by permanently installed reflectometry instruments, and how this single site measurement technique may complement satellite data.

Ground truth report 1975 Phoenix microwave experiment. [Joint Soil Moisture Experiment

NASA Technical Reports Server (NTRS)

Blanchard, B. J.

1975-01-01

Direct measurements of soil moisture obtained in conjunction with aircraft data flights near Phoenix, Arizona in March, 1975 are summarized. The data were collected for the Joint Soil Moisture Experiment.

A review of spatial downscaling of satellite remotely sensed soil moisture

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Merlin, Olivier; Verhoest, Niko E. C.

2017-06-01

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.

Evaluating ESA CCI Soil Moisture in East Africa

NASA Technical Reports Server (NTRS)

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.

2016-01-01

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 NASAs 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 greater than 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.

The Value of SMAP Soil Moisture Observations For Agricultural Applications

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.

2017-12-01

Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).

MoisturEC: an R application for geostatistical estimation of moisture content from electrical conductivity data

NASA Astrophysics Data System (ADS)

Terry, N.; Day-Lewis, F. D.; Werkema, D. D.; Lane, J. W., Jr.

2017-12-01

Soil moisture is a critical parameter for agriculture, water supply, and management of landfills. Whereas direct data (as from TDR or soil moisture probes) provide localized point scale information, it is often more desirable to produce 2D and/or 3D estimates of soil moisture from noninvasive measurements. To this end, geophysical methods for indirectly assessing soil moisture have great potential, yet are limited in terms of quantitative interpretation due to uncertainty in petrophysical transformations and inherent limitations in resolution. Simple tools to produce soil moisture estimates from geophysical data are lacking. We present a new standalone program, MoisturEC, for estimating moisture content distributions from electrical conductivity data. The program uses an indicator kriging method within a geostatistical framework to incorporate hard data (as from moisture probes) and soft data (as from electrical resistivity imaging or electromagnetic induction) to produce estimates of moisture content and uncertainty. The program features data visualization and output options as well as a module for calibrating electrical conductivity with moisture content to improve estimates. The user-friendly program is written in R - a widely used, cross-platform, open source programming language that lends itself to further development and customization. We demonstrate use of the program with a numerical experiment as well as a controlled field irrigation experiment. Results produced from the combined geostatistical framework of MoisturEC show improved estimates of moisture content compared to those generated from individual datasets. This application provides a convenient and efficient means for integrating various data types and has broad utility to soil moisture monitoring in landfills, agriculture, and other problems.

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

NASA Astrophysics Data System (ADS)

Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

2014-07-01

Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Root Water Uptake and Soil Moisture Pattern Dynamics - Capturing Connections, Controls and Causalities

NASA Astrophysics Data System (ADS)

Blume, T.; Heidbuechel, I.; Hassler, S. K.; Simard, S.; Guntner, A.; Stewart, R. D.; Weiler, M.

2015-12-01

We hypothesize that there is a shift in controls on landscape scale soil moisture patterns when plants become active during the growing season. Especially during the summer soil moisture patterns are not only controlled by soils, topography and related abiotic site characteristics but also by root water uptake. Root water uptake influences soil moisture patterns both in the lateral and vertical direction. Plant water uptake from different soil depths is estimated based on diurnal fluctuations in soil moisture content and was investigated with a unique setup of 46 field sites in Luxemburg and 15 field sites in Germany. These sites cover a range of geologies, soils, topographic positions and types of vegetation. Vegetation types include pasture, pine forest (young and old) and different deciduous forest stands. Available data at all sites includes information at high temporal resolution from 3-5 soil moisture and soil temperature profiles, matrix potential, piezometers and sapflow sensors as well as standard climate data. At sites with access to a stream, discharge or water level is also recorded. The analysis of soil moisture patterns over time indicates a shift in regime depending on season. Depth profiles of root water uptake show strong differences between different forest stands, with maximum depths ranging between 50 and 200 cm. Temporal dynamics of signal strength within the profile furthermore suggest a locally shifting spatial distribution of root water uptake depending on water availability. We will investigate temporal thresholds (under which conditions spatial patterns of root water uptake become most distinct) as well as landscape controls on soil moisture and root water uptake dynamics.

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

An Overview of Production and Validation of the SMAP Passive Soil Moisture Product

NASA Technical Reports Server (NTRS)

Chan, S.; O'Neill, P.; Njoku, E.; Jackson, T.; Bindlish, R.

2015-01-01

The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.

Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

NASA Astrophysics Data System (ADS)

van Wesemael, Bas; Nocita, Marco

2016-04-01

One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.

Soil moisture-soil temperature interrelationships on a sandy-loam soil exposed to full sunlight

Treesearch

David A. Marquis

1967-01-01

In a study of birch regeneration in New Hampshire, soil moisture and temperature were found to be intimately related. Not only does low moisture lead to high temperature, but high temperature undoubtedly accelerates soil drying, setting up a vicious cycle of heating and drying that may prevent seed germination or kill seedlings.

Soil-Site Factors Affecting Southern Upland Oak Managment and Growth

Treesearch

John K. Francis

1980-01-01

Soil supplies trees with physical support, moisture, oxygen, and nutrients. Amount of moisture most limits tree growth; and soil and topographic factors such as texture and aspect, which influence available soil moisture. are most useful in predicting growth. Equations that include soil and topographic variables can be used to predict site index. Foresters can also...

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data.

PubMed

Terry, Neil; Day-Lewis, Frederick D; Werkema, Dale; Lane, John W

2018-03-06

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data-analysis tools are needed to "translate" geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user-friendly tools are required to fully capitalize on the potential of geophysical information for soil-moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two- and three-dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status.

PubMed

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status

PubMed Central

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain. PMID:26098548

Different rates of soil drying after rainfall are observed by the SMOS satellite and the South Fork In Situ Soil Moisture Network

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...

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

NASA Astrophysics Data System (ADS)

Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

2014-05-01

Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.

[Variation characteristics of soil moisture in apple orchards of Luochuan County, Shaanxi Province of Northwest China].

PubMed

Wang, Yan-Ping; Han, Ming-Yu; Zhang, Lin-Sen; Dang, Yong-Jian; Qu, Jun-Tao

2012-03-01

To have an overall understanding on the soil moisture characteristics in the apple orchards of Luochuan County can not only provide theoretical basis for selecting apple orchard sites, choosing the best root-stock combination, and improving the soil water management, but also has reference importance in increasing the productive efficiency of our apple orchards. In this study, a fixed-point continuous monitoring was conducted on the overall soil moisture environment and the variation characteristics of soil moisture in the County apple orchards differed in age class, stand type, and tree type (standard or dwarfed). For the apple orchards in the County, the rhizosphere (0-200 cm) soils of most apple trees were water-deficient, and the deficit in 0-60 cm soil layer was less than that in 60-200 cm layer. During growth season, the water storage in 0-60 cm soil layer had the same variation trend as the rainfall pattern. The relative soil moisture content in most orchards was less than 60% , and seasonal drought was quite severe. The coefficient of variation of soil moisture content decreased with soil depth. With the increasing age of the orchards, soil water storage decreased. At the same planting density, the orchards with dwarfed trees had more water storage in 0-5 m soil layer than the orchards with standard trees. However, when the orchards were planted with dwarfed trees at a higher density, the soil water storage in the orchards with dwarfed trees was lesser than that in the standard orchards. The mature orchards on highland had the highest soil moisture content, followed by the mature orchards on flat land, and on terraced land. Tree density had great effects on the soil moisture content. When the tree density was the same, planting dwarfed trees could decrease the water consumption, and increase the soil moisture content significantly. To decrease the planting density through the removal of trees would be an effective way to maintain the soil water balance of apple orchards, and achieve the sustainable development of the orchards.

Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

2016-01-01

Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

Optimum moisture levels for biodegradation of mortality composting envelope materials.

PubMed

Ahn, H K; Richard, T L; Glanville, T D

2008-01-01

Moisture affects the physical and biological properties of compost and other solid-state fermentation matrices. Aerobic microbial systems experience different respiration rates (oxygen uptake and CO2 evolution) as a function of moisture content and material type. In this study the microbial respiration rates of 12 mortality composting envelope materials were measured by a pressure sensor method at six different moisture levels. A wide range of respiration (1.6-94.2mg O2/g VS-day) rates were observed for different materials, with alfalfa hay, silage, oat straw, and turkey litter having the highest values. These four envelope materials may be particularly suitable for improving internal temperature and pathogen destruction rates for disease-related mortality composting. Optimum moisture content was determined based on measurements across a range that spans the maximum respiration rate. The optimum moisture content of each material was observed near water holding capacity, which ranged from near 60% to over 80% on a wet basis for all materials except a highly stabilized soil compost blend (optimum around 25% w.b.). The implications of the results for moisture management and process control strategies during mortality composting are discussed.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor.

PubMed

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-08-15

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10-14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m³·m(-3) in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m³·m(-3), as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation.

Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor

PubMed Central

Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

2016-01-01

Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10–14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m3·m−3 in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m3·m−3, as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation. PMID:27537881

Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods

PubMed Central

Yang, Junjun; He, Zhibin; Du, Jun; Chen, Longfei; Zhu, Xi

2016-01-01

In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE. PMID:26963523

Passive Microwave Soil Moisture Retrieval through Combined Radar/Radiometer Ground Based Simulator with Special Reference to Dielectric Schemes

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.

2014-05-01

Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

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.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Variability of soil moisture proxies and hot days across the climate regimes of Australia

NASA Astrophysics Data System (ADS)

Holmes, A.; Rüdiger, C.; Mueller, B.; Hirschi, M.; Tapper, N.

2017-07-01

The frequency of extreme events such as heat waves are expected to increase due to the effect of climate change, particularly in semiarid regions of Australia. Recent studies have indicated a link between soil moisture deficits and heat extremes, focusing on the coupling between the two. This study investigates the relationship between the number of hot days (Tx90) and four soil moisture proxies (Standardized Precipitation Index, Antecedent Precipitation Index, Mount's Soil Dryness Index, and Keetch-Byram Drought Index), and how the strength of this relationship changes across various climate regimes within Australia. A strong anticorrelation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semiarid and arid regions. It is also shown that the Tx90-soil moisture relationship strengthens during the El Niño phases of El Niño-Southern Oscillation in regions which are more sensitive to changes in soil moisture.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States

NASA Astrophysics Data System (ADS)

Zweck, C.; Zreda, M.; Shuttleworth, J.; Zeng, X.

2008-12-01

Because soil water exerts a critical control on weather, climate, ecosystem, and water cycle, understanding soil moisture changes in time and space is crucial for many fields within natural sciences. A serious handicap in soil moisture measurements is the mismatch between limited point measurements using contact methods and remote sensing estimates over large areas. We present a novel method to measure soil moisture non- invasively at an intermediate spatial scale that will alleviate this problem. The method takes advantage of the dependence of cosmic-ray neutron intensity on the hydrogen content of soils (Zreda et al., Geophysical Research Letters, accepted). Low-energy cosmic-ray neutrons are produced and moderated in the soil, transported from the soil into the atmosphere where they are measured with a cosmic-ray neutron probe to provide integrated soil moisture content over a footprint of several hundred meters and a depth of a few decimeters. The method and the instrument are intended for deployment in the continental-scale COSMOS network that is designed to cover the contiguous region of the USA. Fully deployed, the COSMOS network will consist of up to 500 probes, and will provide continuous soil moisture content (together with atmospheric pressure, temperature and relative humidity) measured and reported hourly. These data will be used for initialization and assimilation of soil moisture conditions in weather and short-term (seasonal) climate forecasting, and for other land-surface applications.

Dynamics of riparian plant communities, a new integrative ecohydrological modelling approach

NASA Astrophysics Data System (ADS)

García-Arias, Alicia; Francés, Félix

2015-04-01

The Riparian Vegetation Dynamic Model (RVDM) integrates the impacts of the hydrological extremes on the vegetation, the vegetation evolution and the competition between different vegetation classes. Considering a daily time step and a detailed spatial resolution, RVDM allows the analysis of the dynamic vegetation distribution in riverine areas during a simulated period. The riparian vegetation wellbeing and distribution are considered to be conditioned by the river hydrodynamics in RVDM. Using biomass loss functions, the stress caused by hydrological extreme events is translated into changes on the distribution of the vegetation. These extreme events are considered as removal and asphyxia associated to floods, and wilt related to droughts. The variables considered to determine the impacts are water shear stress, water table elevation and the soil moisture, respectively. RVDM includes the modelling of the natural evolution of the vegetation. The potential recruitment in bared areas, the plant growth and the succession/retrogression between plant categories are included in the model conceptualization. The recruitment takes place when seeds presence, germination and seedlings establishment overcome, so it depends on the plant reproductive period and the environmental conditions. Light use efficiency determines the vegetation growth in terms of biomass production while the soil moisture limits this biomass production and the successional evolution. Finally, the competition modelling considers the advantages between successional patterns under the specific soil moisture conditions of each unit area. Several meteorological, morphological, hydrological and hydraulic inputs are required. In addition, an initial vegetation condition is required for RVDM to start the simulation period. The model results on new vegetation maps that are considered as new inputs in the next model step. Following this approach the model simulates iteratively al the processes day by day. This model represents an improvement respect to previous models in the way of understanding the riparian dynamics. Currently, RVDM has been already implemented in a Mediterranean semi-arid river reach and a sensitivity analysis to analyze the influence of the different vegetation parameters has been performed. The good results obtained indicate that the model is suitable for scenarios analysis and for environmental flows establishment.

Exchange of carbonyl sulfide (OCS) between soils and atmosphere under various CO2 concentrations

NASA Astrophysics Data System (ADS)

Bunk, Rüdiger; Behrendt, Thomas; Yi, Zhigang; Andreae, Meinrat O.; Kesselmeier, Jürgen

2017-06-01

A new continuous integrated cavity output spectroscopy analyzer and an automated soil chamber system were used to investigate the exchange processes of carbonyl sulfide (OCS) between soils and the atmosphere under laboratory conditions. The exchange patterns of OCS between soils and the atmosphere were found to be highly dependent on soil moisture and ambient CO2 concentration. With increasing soil moisture, OCS exchange ranged from emission under dry conditions to an uptake within an optimum moisture range, followed again by emission at high soil moisture. Elevated CO2 was found to have a significant impact on the exchange rate and direction as tested with several soils. There is a clear tendency toward a release of OCS at higher CO2 levels (up to 7600 ppm), which are typical for the upper few centimeters within soils. At high soil moisture, the release of OCS increased sharply. Measurements after chloroform vapor application show that there is a biotic component to the observed OCS exchange. Furthermore, soil treatment with the fungi inhibitor nystatin showed that fungi might be the dominant OCS consumers in the soils we examined. We discuss the influence of soil moisture and elevated CO2 on the OCS exchange as a change in the activity of microbial communities. Physical factors such as diffusivity that are governed by soil moisture also play a role. Comparing KM values of the enzymes to projected soil water CO2 concentrations showed that competitive inhibition is unlikely for carbonic anhydrase and PEPCO but might occur for RubisCO at higher CO2 concentrations.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

An approach to constructing a homogeneous time series of soil mositure using SMOS

USDA-ARS?s Scientific Manuscript database

Overlapping soil moisture time series derived from two satellite microwave radiometers (SMOS, Soil Moisture and Ocean Salinity; AMSR-E, Advanced Microwave Scanning Radiometer - Earth Observing System) are used to generate a soil moisture time series from 2003 to 2010. Two statistical methodologies f...

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739

A simplified model of precipitation enhancement over a heterogeneous surface

NASA Astrophysics Data System (ADS)

Cioni, Guido; Hohenegger, Cathy

2018-06-01

Soil moisture heterogeneities influence the onset of convection and subsequent evolution of precipitating systems through the triggering of mesoscale circulations. However, local evaporation also plays a role in determining precipitation amounts. Here we aim at disentangling the effect of advection and evaporation on precipitation over the course of a diurnal cycle by formulating a simple conceptual model. The derivation of the model is inspired by the results of simulations performed with a high-resolution (250 m) large eddy simulation model over a surface with varying degrees of heterogeneity. A key element of the conceptual model is the representation of precipitation as a weighted sum of advection and evaporation, each weighed by its own efficiency. The model is then used to isolate the main parameters that control precipitation variations over a spatially drier patch. It is found that these changes surprisingly do not depend on soil moisture itself but instead purely on parameters that describe the atmospheric initial state. The likelihood for enhanced precipitation over drier soils is discussed based on these parameters. Additional experiments are used to test the validity of the model.

Enhancing soil moisture monitoring via cosmic-ray neutron sensing in farmlands by combining field site tests with an uncertainty analysis

NASA Astrophysics Data System (ADS)

Oswald, S. E.; Scheiffele, L. M.; Baroni, G.; Ingwersen, J.; Schrön, M.

2017-12-01

One application of Cosmic-Ray Neutron Sensing (CRNS) is to investigate soil moisture on agricultural fields during the crop season. This fully employs the non-invasive character of CRNS without interference with agricultural practices of the farmland. The changing influence of vegetation on CRNS has to be dealt with as well as spatio-temporal influences, e.g. by irrigation or harvest. Previous work revealed that the CRNS signal on farmland shows complex and non-unique response because of the hydrogen pools in different depths and distances. This creates a challenge for soil moisture estimation and subsequent use for irrigation management or hydrological modelling. Thus, a special aim of our study was to assess the uncertainty of CRNS in cropped fields and to identify underlying causes of uncertainty. We have applied CRNS at two field sites during the growing season that were accompanied by intensive measurements of soil moisture, vegetation parameters, and irrigation events. Sources of uncertainty were identified from the experimental data. A Monte Carlo approach was used to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis was performed to identify the most important factors explaining this uncertainty. Results showed that CRNS soil moisture compares well to the soil moisture network when the point values were converted to weighted water content with all hydrogen pools included. However, when considered as a stand-alone method to retrieve volumetric soil moisture, the performance decreased. The support volume including its penetration depth showed also a considerable uncertainty, especially in relatively dry soil moisture conditions. Of seven factors analyzed, actual soil moisture profile, bulk density, incoming neutron correction and calibrated parameter N0 were found to play an important role. One possible improvement could be a simple correction factor based on independent data of soil moisture profiles to better account for the sensitivity of the CRNS signal to the upper soil layers. This is an important step to improve the method for validation of remote sensing products or agricultural water management and establish CRNS as an applied monitoring tool on farmland.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian region

NASA Astrophysics Data System (ADS)

Baisya, Himadri; Pattnaik, Sandeep; Rajesh, P. V.

2017-03-01

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.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System

NASA Technical Reports Server (NTRS)

Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.

2017-01-01

New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from 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. The perpendicular vegetation index (PVI) 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. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

A Data-Driven Approach for Daily Real-Time Estimates and Forecasts of Near-Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Reichle, Rolf H.; Mahanama, Sarith P. P.

2017-01-01

NASAs Soil Moisture Active Passive (SMAP) mission provides global surface soil moisture retrievals with a revisit time of 2-3 days and a latency of 24 hours. Here, to enhance the utility of the SMAP data, we present an approach for improving real-time soil moisture estimates (nowcasts) and for forecasting soil moisture several days into the future. The approach, which involves using an estimate of loss processes (evaporation and drainage) and precipitation to evolve the most recent SMAP retrieval forward in time, is evaluated against subsequent SMAP retrievals themselves. The nowcast accuracy over the continental United States (CONUS) is shown to be markedly higher than that achieved with the simple yet common persistence approach. The accuracy of soil moisture forecasts, which rely on precipitation forecasts rather than on precipitation measurements, is reduced relative to nowcast accuracy but is still significantly higher than that obtained through persistence.

Plan of research for integrated soil moisture studies. Recommendations of the Soil Moisture Working Group

NASA Technical Reports Server (NTRS)

1980-01-01

Soil moisture information is a potentially powerful tool for applications in agriculture, water resources, and climate. At present, it is difficult for users of this information to clearly define their needs in terms of accuracy, resolution and frequency because of the current sparsity of data. A plan is described for defining and conducting an integrated and coordinated research effort to develop and refine remote sensing techniques which will determine spatial and temporal variations of soil moisture and to utilize soil moisture information in support of agricultural, water resources, and climate applications. The soil moisture requirements of these three different application areas were reviewed in relation to each other so that one plan covering the three areas could be formulated. Four subgroups were established to write and compile the plan, namely models, ground-based studies, aircraft experiments, and spacecraft missions.

Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter.

PubMed

Huang, Wenjuan; Hall, Steven J

2017-11-24

Moisture response functions for soil microbial carbon (C) mineralization remain a critical uncertainty for predicting ecosystem-climate feedbacks. Theory and models posit that C mineralization declines under elevated moisture and associated anaerobic conditions, leading to soil C accumulation. Yet, iron (Fe) reduction potentially releases protected C, providing an under-appreciated mechanism for C destabilization under elevated moisture. Here we incubate Mollisols from ecosystems under C 3 /C 4 plant rotations at moisture levels at and above field capacity over 5 months. Increased moisture and anaerobiosis initially suppress soil C mineralization, consistent with theory. However, after 25 days, elevated moisture stimulates cumulative gaseous C-loss as CO 2 and CH 4 to >150% of the control. Stable C isotopes show that mineralization of older C 3 -derived C released following Fe reduction dominates C losses. Counter to theory, elevated moisture may significantly accelerate C losses from mineral soils over weeks to months-a critical mechanistic deficiency of current Earth system models.

Historical climate controls soil respiration responses to current soil moisture

PubMed Central

Waring, Bonnie G.; Rocca, Jennifer D.; Kivlin, Stephanie N.

2017-01-01

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. PMID:28559315

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

Effects of land preparation and artificial vegetation on soil moisture variation in a loess hilly catchment of China

NASA Astrophysics Data System (ADS)

Feng, Tianjiao; Wei, Wei; Chen, Liding; Yu, Yang

2017-04-01

In the dryland regions, soil moisture is the main factor to determine vegetation growth and ecosystem restoration. Land preparation and vegetation restoration are the principal means for improving soil water content(SWC). Thus, it is important to analyze the coupling role of these two means on soil moisture. In this study, soil moisture were monitored at a semi-arid loess hilly catchment of China, during the growing season of 2014 and 2015. Four different land preparation methods (level ditches, fish-scale pits, adverse grade tablelands and level benches)and vegetation types(Prunus armeniaca, Platycladus orientalis, Platycladus orientalis and Caragana microphylla) were included in the experimental design. Our results showed that: (1)Soil moisture content differed across land preparation types, which is higher for fish-scale pits and decreased in the order of level ditches and adverse grade tablelands.(2) Rainwater harvesting capacity of fish-scale pits is greater than adverse grade tablelands. However the water holding capacity is much higher at soils prepared with the adverse grade tablelands method than the ones prepared by fish-scale pits methods. (3) When land preparation method is similar, vegetation play a key role in soil moisture variation. For example, the mean soil moisture under a Platycladus orientalis field is 26.72% higher than a Pinus tabulaeformis field, with the same land preparation methods. (4)Soil moisture in deeper soil layers is more affected by changes in the vegetation cover while soil moisture in the shallower layers is more affected by the variation in the land preparation methods. Therefore, we suggest that vegetation types such as: Platycladus orientalisor as well as soil preparation methods such as level ditch and fish-scale pit are the most appropriate vegetation cover and land preparation methods for landscape restoration in semi-arid loess hilly area. This conclusion was made based on the vegetation type and land preparation with the best water-holding capacity.

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.

PubMed

Ambebe, Titus F; Dang, Qing-Lai

2009-11-01

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.

Optimizing available water capacity using microwave satellite data for improving irrigation management

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2015-04-01

This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into two steps during one time interval: the state variable is optimized through the state filter and the optimal parameter values are then transferred for retrieving soil moisture. However, soil moisture from sensors such as AMSR-E can only be retrieved for the top few centimeters of soil. So, for the present study, a homogeneous soil system has been considered. By assimilating this information into the model, the accuracy of model structure in relating surface moisture dynamics to deeper soil profiles can be ascertained. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments alongwith the available water capacity, the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the soil moisture simulations. The optimized parameters as compared to the pedo-transfer based parameters were found to reduce the RMSE from 0.14 to 0.04 and 0.15 to 0.07 in surface layer and root zone respectively.

Fate of 14C-labeled dissolved organic matter in paddy and upland soils in responding to moisture.

PubMed

Chen, Xiangbi; Wang, Aihua; Li, Yang; Hu, Lening; Zheng, Hua; He, Xunyang; Ge, Tida; Wu, Jinshui; Kuzyakov, Yakov; Su, Yirong

2014-08-01

Soil organic matter (SOM) content in paddy soils is higher than that in upland soils in tropical and subtropical China. The dissolved organic matter (DOM) concentration, however, is lower in paddy soils. We hypothesize that soil moisture strongly controls the fate of DOM, and thereby leads to differences between the two agricultural soils under contrasting management regimens. A 100-day incubation experiment was conducted to trace the fate and biodegradability of DOM in paddy and upland soils under three moisture levels: 45%, 75%, and 105% of the water holding capacity (WHC). (14)C labeled DOM, extracted from the (14)C labeled rice plant material, was incubated in paddy and upland soils, and the mineralization to (14)CO2 and incorporation into microbial biomass were analyzed. Labile and refractory components of the initial (14)C labeled DOM and their respective half-lives were calculated by a double exponential model. During incubation, the mineralization of the initial (14)C labeled DOM in the paddy soils was more affected by moisture than in the upland soils. The amount of (14)C incorporated into the microbial biomass (2.4-11.0% of the initial DOM-(14)C activity) was less affected by moisture in the paddy soils than in the upland soils. At any of the moisture levels, 1) the mineralization of DOM to (14)CO2 within 100 days was 1.2-2.1-fold higher in the paddy soils (41.9-60.0% of the initial DOM-(14)C activity) than in the upland soils (28.7-35.7%), 2) (14)C activity remaining in solution was significantly lower in the paddy soils than in the upland soils, and 3) (14)C activity remaining in the same agricultural soil solution was not significantly different among the three moisture levels after 20 days. Therefore, moisture strongly controls DOM fate, but moisture was not the key factor in determining the lower DOM in the paddy soils than in the upland soils. The UV absorbance of DOM at 280 nm indicates less aromaticity of DOM from the paddy soils than from the upland soils. At any of the moisture levels, much more labile DOM was found in paddy soils (34.3-49.2% of the initial (14)C labeled DOM) compared with that in upland soils (19.4-23.9%). This demonstrates that the lower DOM content in the paddy soil compared with that in the upland soil is probably determined by the less complex components and structure of the DOM. Copyright © 2014 Elsevier B.V. All rights reserved.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

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.

Is soil moisture initialization important for seasonal to decadal predictions?

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2014-05-01

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.

[Relationships between soil moisture and needle-fall in Masson pine forests in acid rain region of Chongqing, Southwest China].

PubMed

Wang, Yi-Hao; Wang, Yan-Hui; Li, Zhen-Hua; Yu, Peng-Tao; Xiong, Wei; Hao, Jia; Duan, Jian

2012-10-01

From March 2009 to November 2011, an investigation was conducted on the spatiotemporal variation of soil moisture and its effects on the needle-fall in Masson pine (Pinus massoniana) forests in acid rain region of Chongqing, Southeast China, with the corresponding soil moisture thresholds determined. No matter the annual precipitation was abundant, normal or less than average, the seasonal variation of soil moisture in the forests could be obviously divided into four periods, i.e., sufficient (before May), descending (from June to July), drought (from August to September), and recovering (from October to November). With increasing soil depth, the soil moisture content increased after an initial decrease, but the difference of the soil moisture content among different soil layers decreased with decreasing annual precipitation. The amount of monthly needle-fall in the forests in growth season was significantly correlated with the water storage in root zone (0-60 cm soil layer), especially in the main root zone (20-50 cm soil layer). Soil field capacity (or capillary porosity) and 82% of field capacity (or 80% of capillary porosity) were the main soil moisture thresholds affecting the litter-fall. It was suggested that in acid rain region, Masson pine forest was easily to suffer from water deficit stress, especially in dry-summer period. The water deficit stress, together with already existed acid rain stress, would further threaten the health of the Masson forest.

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

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2012-12-01

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.

A procedure for calculating daily moisture stress and its utility in regressions of growth and weather

Treesearch

Robert Zahner; Albert R. Stage

1966-01-01

A method is described for computing daily values of moisture stress on forest vegetation, or water deficits, based on the differences between Thornthwaite's potential evapotranspiration and computed soil-moisture depletion. More realistic functions are used for soil-moisture depletion on specific soil types than have been customary. These functions relate daily...

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

Field-Scale Soil Moisture Observations in Irrigated Agriculture Fields Using the Cosmic-ray Neutron Rover

NASA Astrophysics Data System (ADS)

Franz, T. E.; Avery, W. A.; Finkenbiner, C. E.; Wang, T.; Brocca, L.

2014-12-01

Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 11 x11 km study domain also contained 3 stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong inverted parabolic relationship between the mean and variance of soil moisture. The relationship between the mean and higher order moments were not as strong. Geostatistical analysis indicated the range of the soil moisture semi-variogram was significantly shorter during periods of heavy irrigation as compared to non-irrigated periods. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. Statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

Using SMAP to identify structural errors in hydrologic models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.

2017-12-01

Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.

A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies

NASA Astrophysics Data System (ADS)

Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.

2017-12-01

Water is essential for sustaining life on our planet Earth and water cycle is one of the most important processes of out weather and climate system. As one of the major components of the water cycle, soil moisture impacts significantly the other water cycle components (e.g. evapotranspiration, runoff, etc) and the carbon cycle (e.g. plant/crop photosynthesis and respiration). Understanding of soil moisture status and dynamics is crucial for monitoring and predicting the weather, climate, hydrology and ecological processes. Satellite remote sensing has been used for soil moisture observation since the launch of the Scanning Multi-channel Microwave Radiometer (SMMR) on NASA's Nimbus-7 satellite in 1978. Many satellite soil moisture data products have been made available to the science communities and general public. The soil moisture operational product system (SMOPS) of NOAA NESDIS has been operationally providing global soil moisture data products from each of the currently available microwave satellite sensors and their blends. This presentation will provide an update of SMOPS products. The time series of each of these soil moisture data products are analyzed against other data products, such as precipitation and evapotranspiration from other independent data sources such as the North America Land Data Assimilation System (NLDAS). Temporal characteristics of these water cycle components are explored against some historical events, such as the 2010 Russian, 2010 China and 2012 United States droughts, 2015 South Carolina floods, etc. Finally whether a merged global soil moisture data product can be used as a climate data record is evaluated based on the above analyses.

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

USGS Publications Warehouse

McNally, Amy; Gregory J. Husak,; Molly Brown,; Carroll, Mark L.; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

2015-01-01

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

NASA Astrophysics Data System (ADS)

Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni

2015-10-01

The mineral dust emissions from arid/semiarid soils were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the soil moisture and clay fraction in the emissions. For this purpose, an extensive data set of Soil Moisture and Ocean Salinity soil moisture, European Centre for Medium-Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization soil texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the soil surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground-based measurements of near-surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of soil moisture and clay fraction on the emissions flux. The results showed that soil moisture and soil texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the soil moisture and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the soil clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is observed at high friction velocity. The magnitude of the percentage reduction/increase in the sandblasting flux decreases with the increase of the friction velocity for both soil moisture and soil clay fraction. Furthermore, these variables are interdependent leading to a gradual decrease in the percentage increase in the sandblasting flux for higher soil moisture values.

Improvment of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (usa) High Plains

NASA Astrophysics Data System (ADS)

Shafian, S.; Maas, S. J.

2015-12-01

Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.

NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.

2013-01-01

Water in the soil, both its amount (soil moisture) and its state (freeze/thaw), plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China

NASA Astrophysics Data System (ADS)

Wang, Hui-Lin; An, Ru; You, Jia-jun; Wang, Ying; Chen, Yuehong; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballard, Jonathan Arthur

2017-10-01

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1 km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

WaterSense Soil Moisture-Based Control Technologies Notice of Intent (NOI)

EPA Pesticide Factsheets

By directly measuring the amount of moisture in the soil, soil moisture-based control technologies tailor irrigation schedules to meet landscape water needs based on seasonal patterns, as well as prevailing conditions in the landscape.

Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

2016-04-01

Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Al-Shrafany, D., Islam, T., 2013b. Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resources Management 27, 5069-5087. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O'Neill, P., Islam, T., Gupta, M., 2014. Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation. Journal of Hydrology 519, 574-587.

An Arduino Based Citizen Science Soil Moisture Sensor in Support of SMAP and GLOBE

NASA Astrophysics Data System (ADS)

Podest, E.; Das, N. N.; Rajasekaran, E.; Jeyaram, R.; Lohrli, C.; Hovhannesian, H.; Fairbanks, G.

2017-12-01

Citizen science allows individuals anywhere in the world to engage in science by collecting environmental variables. One of the longest running platforms for the collection of in situ variables is the GLOBE program, which is international in scope and encourages students and citizen scientists alike to collect in situ measurements. NASA's Soil Moisture Active Passive (SMAP) satellite mission, which has been acquiring global soil moisture measurements every 3 days of the top 5 cm of the soil since 2015, 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- 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. In addition, we have developed a phone app, which interfaces with the Arduino, displays the soil moisture value and send the measurement to the GLOBE database. 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.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Inter-Annual Variability of Soil Moisture Stress Function in the Wheat Field

NASA Astrophysics Data System (ADS)

Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.

2014-12-01

Root-zone soil moisture content is a key variable that controls the exchange of water and energy fluxes between land and atmosphere. In the soil-vegetation-atmosphere transfer (SVAT) schemes, the influence of root-zone soil moisture on evapotranspiration (ET) is parameterized by the soil moisture stress function (SSF). Dependence of actual ET: potential ET (fPET) or evaporative fraction to the root-zone soil moisture via SSF can also be used inversely to estimate root-zone soil moisture when fPET is estimated by remotely sensed land surface states. In this work we present fPET versus available soil water (ASW) in the root zone observed in the experimental farm sites in Victoria, Australia in 2012-2013. In the wheat field site, fPET vs ASW exhibited distinct features for different soil depth, net radiation, and crop growth stages. Interestingly, SSF in the wheat field presented contrasting shapes for two cropping years of 2012 and 2013. We argue that different temporal patterns of rainfall (and resulting soil moisture) during the growing seasons in 2012 and 2013 are responsible for the distinctive SSFs. SSF of the wheat field was simulated by the Agricultural Production Systems sIMulator (APSIM). The APSIM was able to reproduce the observed fPET vs. ASW. We discuss implications of our findings for existing modeling and (inverse) remote sensing approaches relying on SSF and alternative growth-stage-dependent SSFs.

Detection of moisture and moisture related phenomena from Skylab. [Texas

NASA Technical Reports Server (NTRS)

Eagleman, J. R.; Pogge, E. C.; Moore, R. K. (Principal Investigator); Hardy, N.; Lin, W.; League, L.

1973-01-01

The author has identified the following significant results. This is a preliminary report on the ability to detect soil moisture variation from the two different sensors on board Skylab. Initial investigations of S190A and Sl94 Skylab data and ground truth has indicated the following significant results. (1) There was a decrease in Sl94 antenna temperature from NW to SE across the Texas test site. (2) Soil moisture increases were measured from NW to SE across the test site. (3) There was a general increase in precipitation distribution and radar echoes from NW to SE across the site for the few days prior to measurements. This was consistent with the soil moisture measurements and gives more complete coverage of the site. (4) There are distinct variations in soil textures over the test site. This affects the moisture holding capacity of soils and must be considered. (5) Strong correlation coefficients were obtained between S194 antenna temperature and soil moisutre content. As the antenna temperature decreases soil moisture increases. (6) The Sl94 antenna temperature correlated best with soil mositure content in the upper two inches of the soil. A correlation coefficient of .988 was obtained. (7) Sl90A photographs in the red-infrared region were shown to be useful for identification of Abilene clay loam and for determining the distribution of this soil type.

Mapping surface soil moisture with L-band radiometric measurements

NASA Technical Reports Server (NTRS)

Wang, James R.; Shiue, James C.; Schmugge, Thomas J.; Engman, Edwin T.

1989-01-01

A NASA C-130 airborne remote sensing aircraft was used to obtain four-beam pushbroom microwave radiometric measurements over two small Kansas tall-grass prairie region watersheds, during a dry-down period after heavy rainfall in May and June, 1987. While one of the watersheds had been burned 2 months before these measurements, the other had not been burned for over a year. Surface soil-moisture data were collected at the time of the aircraft measurements and correlated with the corresponding radiometric measurements, establishing a relationship for surface soil-moisture mapping. Radiometric sensitivity to soil moisture variation is higher in the burned than in the unburned watershed; surface soil moisture loss is also faster in the burned watershed.

Soil moisture gradients and controls on a southern Appalachian hillslope from drought through recharge

Treesearch

J.A. Yeakley; W.T. Swank; L.W. Swift; G.M. Hornberger; H.H. Shugart

1998-01-01

Soil moisture gradients along hillslopes in humid watersheds, although indicated by vegetation gradients and by studies using models, have been difficult to confirm empirically. While soil properties and topographic features are the two general physiographic factors controlling soil moisture on hillslopes, studies have shown conflicting results regarding which factor...

Seedling establishment and physiological responses to temporal and spatial soil moisture changes

Treesearch

Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

2016-01-01

In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

USDA-ARS?s Scientific Manuscript database

Mapping of soil moisture is important for many applications such as flood forecasting, soil protection, and crop management. Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Mois...

Improving the soil moisture data record of the U.S. Climate Reference Network (USCRN) and Soil Climate Analysis Network (SCAN)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling, drought prediction and management, climate change analysis, and agricultural decision support. However, in situ measurements of soil moisture have only become available within the past few decades with additional sensors being installed ...

A time-series approach to estimating soil moisture from vegetated surfaces using L-band radar backscatter

USDA-ARS?s Scientific Manuscript database

Many previous studies have shown the sensitivity of radar backscatter to surface soil moisture content, particularly at L-band. Moreover, the estimation of soil moisture from radar for bare soil surfaces is well-documented, but estimation underneath a vegetation canopy remains unsolved. Vegetation s...

Mapping high-resolution soil moisture and properties using distributed temperature sensing data and an adaptive particle batch smoother

USDA-ARS?s Scientific Manuscript database

This study demonstrated a new method for mapping high-resolution (spatial: 1 m, and temporal: 1 h) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed...

About | USDA Plant Hardiness Zone Map

Science.gov Websites

of plants. Wind, soil type, soil moisture, humidity, pollution, snow, and winter sunshine can greatly it might cause rapid changes in the plant's temperature. Soil moisture: Plants have different requirements for soil moisture, and this might vary seasonally. Plants that might otherwise be hardy in your

Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15

USDA-ARS?s Scientific Manuscript database

The SMAP (Soil Moisture Active Passive) mission provides global surface soil moisture product at 36 km resolution from its L-band radiometer. While the coarse resolution is satisfactory to many applications there are also a lot of applications which would benefit from a higher resolution soil moistu...

Topographic, edaphic, and vegetative controls on plant-available water

Treesearch

Salli F. Dymond; John B. Bradford; Paul V. Bolstad; Randall K. Kolka; Stephen D. Sebestyen; Thomas M. DeSutter

2017-01-01

Soil moisture varies within landscapes in response to vegetative, physiographic, and climatic drivers, which makes quantifying soil moisture over time and space difficult. Nevertheless, understanding soil moisture dynamics for different ecosystems is critical, as the amount of water in a soil determines a myriad ecosystem services and processes such as net primary...

Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds

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...

The SMAP level 4 surface and root zone soil moisture data assimilation product

USDA-ARS?s Scientific Manuscript database

The NASA Soil Moisture Active Passive (SMAP) mission is scheduled for launch in January 2015 and will provide L-band radar and radiometer observations that are sensitive to surface soil moisture (in the top few centimeters of the soil column). For several of the key applications targeted by SMAP, ho...

Information and Complexity Measures Applied to Observed and Simulated Soil Moisture Time Series

USDA-ARS?s Scientific Manuscript database

Time series of soil moisture-related parameters provides important insights in functioning of soil water systems. Analysis of patterns within these time series has been used in several studies. The objective of this work was to compare patterns in observed and simulated soil moisture contents to u...

Persistence and memory timescales in root-zone soil moisture dynamics

Treesearch

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,...

The Use of Indirect Estimates of Soil Moisture to Initialize Coupled Models and its Impact on Short-Term and Seasonal Simulations

NASA Technical Reports Server (NTRS)

Lapenta, William M.; Crosson, William; Dembek, Scott; Lakhtakia, Mercedes

1998-01-01

It is well known that soil moisture is a characteristic of the land surface that strongly affects the partitioning of outgoing radiation into sensible and latent heat which significantly impacts both weather and climate. Detailed land surface schemes are now being coupled to mesoscale atmospheric models in order to represent the effect of soil moisture upon atmospheric simulations. However, there is little direct soil moisture data available to initialize these models on regional to continental scales. As a result, a Soil Hydrology Model (SHM) is currently being used to generate an indirect estimate of the soil moisture conditions over the continental United States at a grid resolution of 36 Km on a daily basis since 8 May 1995. The SHM is forced by analyses of atmospheric observations including precipitation and contains detailed information on slope soil and landcover characteristics.The purpose of this paper is to evaluate the utility of initializing a detailed coupled model with the soil moisture data produced by SHM.

Correlation of spacecraft passive microwave system data with soil moisture indices (API). [great plains corridor

NASA Technical Reports Server (NTRS)

Blanchard, B. J.; Mcfarland, M. J.; Theis, S.; Richter, J. G.

1981-01-01

Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil moisture is most important to winter wheat yield. Other significant results are reported.

Use of Ultrasonic Technology for Soil Moisture Measurement

NASA Technical Reports Server (NTRS)

Choi, J.; Metzl, R.; Aggarwal, M. D.; Belisle, W.; Coleman, T.

1997-01-01

In an effort to improve existing soil moisture measurement techniques or find new techniques using physics principles, a new technique is presented in this paper using ultrasonic techniques. It has been found that ultrasonic velocity changes as the moisture content changes. Preliminary values of velocities are 676.1 m/s in dry soil and 356.8 m/s in 100% moist soils. Intermediate values can be calibrated to give exact values for the moisture content in an unknown sample.

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Jackson, Thomas J.; Manu, Andrew; Tsegaye, Teferi D.; Soman, V.; Arnold, James E. (Technical Monitor)

2001-01-01

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Soil moisture - precipitation feedbacks in observations and models (Invited)

NASA Astrophysics Data System (ADS)

Taylor, C.

2013-12-01

There is considerable uncertainty about the strength, geographical extent, and even the sign of feedbacks between soil moisture and precipitation. Whilst precipitation trivially increases soil moisture, the impact of soil moisture, via surface fluxes, on convective rainfall is far from straight-forward, and likely depends on space and time scale, soil and synoptic conditions, and the nature of the convection itself. In considering how daytime convection responds to surface fluxes, large-scale models based on convective parameterisations may not necessarily provide reliable depictions, particularly given their long-standing inability to reproduce a realistic diurnal cycle of convection. On the other hand, long-term satellite data provide the potential to establish robust relationships between soil moisture and precipitation across the world, notwithstanding some fundamental weaknesses and uncertainties in the datasets. Here, results from regional and global satellite-based analyses are presented. Globally, using 3-hourly precipitation and daily soil moisture datasets, a methodology has been developed to compare the statistics of antecedent soil moisture in the region of localised afternoon rain events (Taylor et al 2012). Specifically the analysis tests whether there are any significant differences in pre-event soil moisture between rainfall maxima and nearby (50-100km) minima. The results reveal a clear signal across a number of semi-arid regions, most notably North Africa, indicating a preference for afternoon rain over drier soil. Analysis by continent and by climatic zone reveals that this signal (locally a negative feedback) is evident in other continents and climatic zones, but is somewhat weaker. This may be linked to the inherent geographical differences across the world, as detection of a feedback requires water-stressed surfaces coincident with frequent active convective initiations. The differences also reflect the quality and utility of the soil moisture datasets outside of sparsely-vegetated regions. No evidence is found for afternoon convection developing preferentially above locally moister soils. Higher resolution datasets are used to provide a clearer relationship between soil moisture patterns and convective initiation in both the Sahel (Taylor et al 2011) and Europe. The observations indicate a preference for convection to initiate on soil moisture gradients, consistent with many high resolution numerical studies. The ability of models to capture the observed relationships between soil moisture and rainfall in the Sahel has been evaluated. This focuses on models run at different resolutions, and with convective parameterisations switched on or off, and highlights issues associated with the parameterisation of convection. Taylor, C.M., Gounou, A., Guichard, F., Harris, P.P., Ellis, R.J.,Couvreux, F., and M. De Kauwe. 2011, Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns, Nature Geoscience, 4, 430-433, doi:10.1038/ngeo1173 Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P, and W.A. Dorigo. 2012, Afternoon rain more likely over drier soils, Nature, 489, 423-426, doi:10.1038/nature11377

Statistical analysis of simulated global soil moisture and its memory in an ensemble of CMIP5 general circulation models

NASA Astrophysics Data System (ADS)

Wiß, Felix; Stacke, Tobias; Hagemann, Stefan

2014-05-01

Soil moisture and its memory can have a strong impact on near surface temperature and precipitation and have the potential to promote severe heat waves, dry spells and floods. To analyze how soil moisture is simulated in recent general circulation models (GCMs), soil moisture data from a 23 model ensemble of Atmospheric Model Intercomparison Project (AMIP) type simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are examined for the period 1979 to 2008 with regard to parameterization and statistical characteristics. With respect to soil moisture processes, the models vary in their maximum soil and root depth, the number of soil layers, the water-holding capacity, and the ability to simulate freezing which all together leads to very different soil moisture characteristics. Differences in the water-holding capacity are resulting in deviations in the global median soil moisture of more than one order of magnitude between the models. In contrast, the variance shows similar absolute values when comparing the models to each other. Thus, the input and output rates by precipitation and evapotranspiration, which are computed by the atmospheric component of the models, have to be in the same range. Most models simulate great variances in the monsoon areas of the tropics and north western U.S., intermediate variances in Europe and eastern U.S., and low variances in the Sahara, continental Asia, and central and western Australia. In general, the variance decreases with latitude over the high northern latitudes. As soil moisture trends in the models were found to be negligible, the soil moisture anomalies were calculated by subtracting the 30 year monthly climatology from the data. The length of the memory is determined from the soil moisture anomalies by calculating the first insignificant autocorrelation for ascending monthly lags (insignificant autocorrelation folding time). The models show a great spread of autocorrelation length from a few months in the tropics, north western Canada, eastern U.S. and northern Europe up to few years in the Sahara, the Arabian Peninsula, continental Eurasia and central U.S. Some models simulate very long memory all over the globe. This behavior is associated with differences between the models in the maximum root and soil depth. Models with shallow roots and deep soils exhibit longer memories than models with similar soil and root depths. Further analysis will be conducted to clearly divide models into groups based on their inter-model spatial correlation of simulated soil moisture characteristics.

Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

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.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this 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 approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 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. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. 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 and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

[Characteristics of soil moisture variation in different land use types in the hilly region of the Loess Plateau, China].

PubMed

Tang, Min; Zhao, Xi Ning; Gao, Xiao Dong; Zhang, Chao; Wu, Pu Te

2018-03-01

Soil water availability is a key factor restricting the ecological construction and sustainable land use in the loess hilly region. It is of great theoretical and practical significance to understand the soil moisture status of different land use types for the vegetation restoration and the effective utilization of land resources in this area. In this study, EC-5 soil moisture sensors were used to continuously monitor the soil moisture content in the 0-160 cm soil profile in the slope cropland, terraced fields, jujube orchard, and grassland during the growing season (from May to October) in the Yuanzegou catchment on the Loess Plateau, to investigate soil moisture dynamics in these four typical land use types. The results showed that there were differences in seasonal variation, water storage characteristics, and vertical distribution of soil moisture under different land use types in both the normal precipitation (2014) and dry (2015) years. The terraced fields showed good water retention capacity in the dry year, with the average soil moisture content of 0-60 cm soil layer in the growing season being 2.6%, 4.2%, and 1.8% higher than that of the slope cropland, jujube orchard, and grassland (all P<0.05). The water storage of 0-160 cm soil profile was 43.90, 32.08, and 18.69 mm higher than that of slope cropland, jujube orchard, and grassland, respectively. In the normal precipitation year, the average soil moisture content of 0-60 cm soil layer in jujube orchard in the growing season was 2.9%, 3.8%, and 4.5% lower than that of slope cropland, terraced fields, and grassland, respectively (all P<0.05). In the dry year, the effective soil water storage of 0-160 cm soil profile in the jujube orchard accounted for 35.0% of the total soil water storage. The grey relational grade between the soil moisture in the surface layer (0-20 cm) and soil moisture in the middle layer (20-100 cm) under different land use types was large, and the trend for the similarity degree of soil moisture variation followed terraced fields > grassland > slope cropland > jujube orchard. The slope cropland in this area could be transformed into terraced fields to improve the utilization of precipitation and promote the construction of ecological agriculture. Aiming at resolving the severe water shortage in the rain-fed jujube orchard for the sustainable development of jujube orchard in the loess hilly region, appropriate water management measures should be taken to reduce the water consumption of jujube trees and other inefficient water consumption.

Joint microwave and infrared studies for soil moisture determination

NASA Technical Reports Server (NTRS)

Njoku, E. G.; Schieldge, J. P.; Kahle, A. B. (Principal Investigator)

1980-01-01

The feasibility of using a combined microwave-thermal infrared system to determine soil moisture content is addressed. Of particular concern are bare soils. The theoretical basis for microwave emission from soils and the transport of heat and moisture in soils is presented. Also, a description is given of the results of two field experiments held during vernal months in the San Joaquin Valley of California.

Modeling soil heating and moisture transport under extreme conditions: Forest fires and slash pile burns

NASA Astrophysics Data System (ADS)

Massman, W. J.

2012-10-01

Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improved understanding and modeling of heat and mass transport during extreme conditions should provide insights into the associated transport mechanisms under more normal conditions. The present study describes a numerical model developed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 W m-2 for several minutes to several hours. Basically, the model extends methods commonly used to model coupled heat flow and moisture evaporation at ambient conditions into regions of extreme dryness and heat. But it also incorporates some infrequently used formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve, as well as advective effects due to the large changes in volume that occur when liquid water is rapidly volatilized. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events. Qualitatively, the model agrees with the laboratory observations, namely, it simulates an increase in soil moisture ahead of the drying front (due to the condensation of evaporated soil water at the front) and a hiatus in the soil temperature rise during the strongly evaporative stage of the soil drying. Nevertheless, it is shown that the model is incapable of producing a physically realistic solution because it does not (and, in fact, cannot) represent the relationship between soil water potential and soil moisture at extremely low soil moisture contents (i.e., residual or bound water: θ < 0.01 m3 m-3, for example). Diagnosing the model's performance yields important insights into how to make progress on modeling soil evaporation and heating under conditions of high temperatures and very low soil moisture content.

Temporal transferability of soil moisture calibration equations

USDA-ARS?s Scientific Manuscript database

Several large-scale field campaigns have been conducted over the last 20 years that require accurate estimates of soil moisture conditions. These measurements are manually conducted using soil moisture probes which require calibration. The calibration process involves the collection of hundreds of...

Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

NASA Astrophysics Data System (ADS)

Yatheendradas, S.; Vivoni, E.

2007-12-01

A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

NASA Astrophysics Data System (ADS)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study

PubMed Central

Zhou, Weiping; Hui, Dafeng; Shen, Weijun

2014-01-01

The temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each moisture treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC), microbial community structure and soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC) than at higher moisture level (80% WHC) during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three moisture levels during the late stage of incubation. In contrast, soil Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the moisture-induced Q10 changes. This study implies that global warming’s impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

NASA Technical Reports Server (NTRS)

Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

2011-01-01

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

Survey of methods for soil moisture determination

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

1979-01-01

Existing and proposed methods for soil moisture determination are discussed. These include: (1) in situ investigations including gravimetric, nuclear, and electromagnetic techniques; (2) remote sensing approaches that use the reflected solar, thermal infrared, and microwave portions of the electromagnetic spectrum; and (3) soil physics models that track the behavior of water in the soil in response to meteorological inputs (precipitation) and demands (evapotranspiration). The capacities of these approaches to satisfy various user needs for soil moisture information vary from application to application, but a conceptual scheme for merging these approaches into integrated systems to provide soil moisture information is proposed that has the potential for meeting various application requirements.

Role of extrinsic arbuscular mycorrhizal fungi in heavy metal-contaminated wetlands with various soil moisture levels.

PubMed

Zheng, S; Wang, C; Shen, Z; Quan, Y; Liu, X

2015-01-01

This study presents an efficient heavy metal (HM) control method in HM-contaminated wetlands with varied soil moisture levels through the introduction of extrinsic arbuscular mycorrhizal fungi (AMF) into natural wetland soil containing indigenous AMF species. A pot culture experiment was designed to determine the effect of two soil water contents (5-8% and 25-30%), five extrinsic AMF inoculants (Glomus mosseae, G. clarum, G. claroideum, G. etunicatum, and G. intraradices), and HM contamination on root colonization, plant growth, and element uptake of common reed (Phragmites australis (Cav.) Trin. ex Steudel) plantlets in wetland soils. This study showed the prevalence of mycorrhizae in the roots of all P. australis plantlets, regardless of extrinsic AMF inoculations, varied soil moisture or HM levels. It seems that different extrinsic AMF inoculations effectively lowered HM concentrations in the aboveground tissues of P. australis at two soil moisture levels. However, metal species, metal concentrations, and soil moisture should also be very important factors influencing the elemental uptake performance of plants in wetland ecosystems. Besides, the soil moisture level significantly influenced plant growth (including height, and shoot and root dry weight (DW)), and extrinsic AMF inoculations differently affected shoot DW.

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2013-01-01

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

[Edge influence of soil moisture at farmland-grassland boundary in agriculture-pasturage ecotone of northern China].

PubMed

Liu, Hong-lai; Zhang, Wei-hua; Wang, Kun; Zhao, Na

2009-03-01

In the agriculture-pasturage ecotone of Northern China, a typical zone with linear boundary of cropland and grassland was chosen to investigate its soil moisture regime, and the moving split-window technique was adopted to study the edge influence of soil moisture at the boundary. The results showed that the edge influence was 10 m, from 6 m within grassland and 4 m within cropland, and was categorized as the acute change type boundary. Accordingly, the farmland-grassland landscape boundary could be divided into three functional zones, i.e., grassland zone, farmland zone, and compositional ecotone zone. Soil moisture content varied abruptly in the ecotone zone, but presented linear distribution in both grassland zone and farmland zone. The average soil moisture content in grassland was about 1 g x g(-1) higher than that in farmland, which was mainly caused by the decreased capillary moisture capacity of farmland. Owing to the different vegetation cover, farmland and grassland had different transpiration and evaporation, which led to the diverse soil moisture regime, making soil water potential changed and water movement from one ecosystem to another possible.

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

NASA Astrophysics Data System (ADS)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.