precipitation soil moisture: Topics by Science.gov

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
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
Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

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 Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.
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.
Uncertain soil moisture feedbacks in model projections of Sahel precipitation

NASA Astrophysics Data System (ADS)

Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

2017-06-01

Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008257','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008257">Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018WRR....54.2199D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018WRR....54.2199D">Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUSM.B42A..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUSM.B42A..02S">Investigating Soil Moisture Feedbacks on Precipitation With Tests of Granger Causality</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Salvucci, G. D.; Saleem, J. A.; Kaufmann, R. 2002-05-01 Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture (S) feedback on precipitation (P) using data from Illinois. In this framework S is said to Granger cause P if F(Pt;At-dt)does not equal F(P;(A-S)t-dt) where F denotes the conditional distribution of P at time t, At-dt represents the set of all knowledge available at time t-dt, and (A-S)t-dt represents all knowledge available at t-dt except S. Critical for land-atmosphere interaction research is that At-dt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AdWR...25.1305S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AdWR...25.1305S">Investigating soil moisture feedbacks on precipitation with tests of Granger causality</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Salvucci, Guido D.; Saleem, Jennifer A.; Kaufmann, Robert Granger causality (GC) is used in the econometrics literature to identify the presence of one- and two-way coupling between terms in noisy multivariate dynamical systems. Here we test for the presence of GC to identify a soil moisture ( S) feedback on precipitation ( P) using data from Illinois. In this framework S is said to Granger cause P if F(P t|Ω t- Δt )≠F(P t|Ω t- Δt -S t- Δt ) where F denotes the conditional distribution of P, Ω t- Δt represents the set of all knowledge available at time t-Δ t, and Ω t- Δt -S t- Δt represents all knowledge except S. Critical for land-atmosphere interaction research is that Ω t- Δt includes all past information on P as well as S. Therefore that part of the relation between past soil moisture and current precipitation which results from precipitation autocorrelation and soil water balance will be accounted for and not attributed to causality. Tests for GC usually specify all relevant variables in a coupled vector autoregressive (VAR) model and then calculate the significance level of decreased predictability as various coupling coefficients are omitted. But because the data (daily precipitation and soil moisture) are distinctly non-Gaussian, we avoid using a VAR and instead express the daily precipitation events as a Markov model. We then test whether the probability of storm occurrence, conditioned on past information on precipitation, changes with information on soil moisture. Past information on precipitation is expressed both as the occurrence of previous day precipitation (to account for storm-scale persistence) and as a simple soil moisture-like precipitation-wetness index derived solely from precipitation (to account for seasonal-scale persistence). In this way only those fluctuations in moisture not attributable to past fluctuations in precipitation (e.g., those due to temperature) can influence the outcome of the test. The null hypothesis (no moisture influence) is evaluated by comparing observed </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020054243&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dseasonal%2Bforecast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020054243&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dseasonal%2Bforecast">The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor) 2002-01-01 Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.4869C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.4869C">Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H11L..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H11L..06T">Soil moisture - precipitation feedbacks in observations and models (Invited)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29507383','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29507383">Negative soil moisture-precipitation feedback in dry and wet regions.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Yang, Lingbin; Sun, Guoqing; Zhi, Lu; Zhao, Jianjun 2018-03-05 Soil moisture-precipitation (SM-P) feedback significantly influences the terrestrial water and energy cycles. However, the sign of the feedback and the associated physical mechanism have been debated, leaving a research gap regarding global water and climate changes. Based on Koster's framework, we estimate SM-P feedback using satellite remote sensing and ground observation data sets. Methodologically, the sign of the feedback is identified by the correlation between monthly soil moisture and next-month precipitation. The physical mechanism is investigated through coupling precipitation and soil moisture (P-SM), soil moisture ad evapotranspiration (SM-E) and evapotranspiration and precipitation (E-P) correlations. Our results demonstrate that although positive SM-P feedback is predominant over land, non-negligible negative feedback occurs in dry and wet regions. Specifically, 43.75% and 40.16% of the negative feedback occurs in the arid and humid climate zones. Physically, negative SM-P feedback depends on the SM-E correlation. In dry regions, evapotranspiration change is soil moisture limited. In wet regions, evapotranspiration change is energy limited. We conclude that the complex SM-E correlation results in negative SM-P feedback in dry and wet regions, and the cause varies based on the environmental and climatic conditions. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature">Soil Moisture, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo 1999-01-01 Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as soil moisture distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of soil moisture and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of soil moisture influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature affects the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (soil moisture and coastline curvature) are required to fully account for observed rainfall amounts. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.6413H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.6413H">Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..12111516K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..12111516K">A novel approach to validate satellite soil moisture retrievals using precipitation data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Karthikeyan, L.; Kumar, D. Nagesh 2016-10-01 A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex-concave-shaped curve, the characteristic of which was recently shown to be represented by mutual information estimated between soil moisture and precipitation. On this basis, with an emphasis over distribution-free nonparametric computations, a new measure called Copula-Kernel Density Estimator based Mutual Information (CKDEMI) is introduced. The validation approach is generic in nature and utilizes CKDEMI in tandem with a couple of proposed bootstrap strategies, to check accuracy of any two soil moisture products (here Advanced Microwave Scanning Radiometer-EOS sensor's Vrije Universiteit Amsterdam-NASA (VUAN) and University of Montana (MONT) products) using precipitation (India Meteorological Department) data. The proposed technique yields a "best choice soil moisture product" map which contains locations where any one of the two/none of the two/both the products have produced accurate retrievals. The results indicated that in general, VUA-NASA product has performed well over University of Montana's product for India. The best choice soil moisture map is then integrated with land use land cover and elevation information using a novel probability density function-based procedure to gain insight on conditions under which each of the products has performed well. Finally, the impact of using a different precipitation (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) data set over the best choice soil moisture product map is also analyzed. The proposed methodology assists researchers and practitioners in selecting the appropriate soil moisture product for various assimilation strategies at both basin and continental scales. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373">Precipitation estimation using L-Band and C-Band soil moisture retrievals</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3052C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3052C">Effect of soil moisture on diurnal convection and precipitation in Large-Eddy Simulations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cioni, Guido; Hohenegger, Cathy 2017-04-01 Soil moisture and convective precipitation are generally thought to be strongly coupled, although limitations in the modeling set-up of past studies due to coarse resolutions, and thus poorly resolved convective processes, have prevented a trustful determination of the strength and sign of this coupling. In this work the soil moisture-precipitation feedback is investigated by means of high-resolution simulations where convection is explicitly resolved. To that aim we use the LES (Large Eddy Simulation) version of the ICON model with a grid spacing of 250 m, coupled to the TERRA-ML soil model. We use homogeneous initial soil moisture conditions and focus on the precipitation response to increase/decrease of the initial soil moisture for various atmospheric profiles. The experimental framework proposed by Findell and Eltahir (2003) is revisited by using the same atmospheric soundings as initial condition but allowing a full interaction of the atmosphere with the land-surface over a complete diurnal cycle. In agreement with Findell and Eltahir (2003) the triggering of convection can be favoured over dry soils or over wet soils depending on the initial atmospheric sounding. However, total accumulated precipitation is found to always decrease over dry soils regardless of the employed sounding, thus highlighting a positive soil moisture-precipitation feedback (more rain over wetter soils) for the considered cases. To understand these differences and to infer under which conditions a negative feedback may occur, the total accumulated precipitation is split into its magnitude and duration component. While the latter can exhibit a dry soil advantage, the precipitation magnitude strongly correlates with the surface latent heat flux and thus always exhibits a wet soil advantage. The dependency is so strong that changes in duration cannot offset it. This simple argument shows that, in our idealised setup, a negative feedback is unlikely to be observed. The effects of other </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018WRR....54.1476A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018WRR....54.1476A">Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1395030-underestimated-role-precipitation-frequency-regulating-summer-soil-moisture','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1395030-underestimated-role-precipitation-frequency-regulating-summer-soil-moisture">An underestimated role of precipitation frequency in regulating summer soil moisture</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Wu, Chaoyang; Chen, Jing M.; Pumpanen, Jukka 2012-04-26 Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 andmore » 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.« less </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li class="active">1</li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_2" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active">2</li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="21"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PhDT.......181S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PhDT.......181S">Terrestrial precipitation and soil moisture: A case study over southern Arizona and data development</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stillman, Susan Quantifying climatological precipitation and soil moisture as well as interannual variability and trends requires extensive observation. This work focuses on the analysis of available precipitation and soil moisture data and the development of new ways to estimate these quantities. Precipitation and soil moisture characteristics are highly dependent on the spatial and temporal scales. We begin at the point scale, examining hourly precipitation and soil moisture at individual gauges. First, we focus on the Walnut Gulch Experimental Watershed (WGEW), a 150 km2 area in southern Arizona. The watershed has been measuring rainfall since 1956 with a very high density network of approximately 0.6 gauges per km2. Additionally, there are 19 soil moisture probes at 5 cm depth with data starting in 2002. In order to extend the measurement period, we have developed a water balance model which estimates monsoon season (Jul-Sep) soil moisture using only precipitation for input, and calibrated so that the modeled soil moisture fits best with the soil moisture measured by each of the 19 probes from 2002-2012. This observationally constrained soil moisture is highly correlated with the collocated probes (R=0.88), and extends the measurement period from 10 to 56 years and the number of gauges from 19 to 88. Then, we focus on the spatiotemporal variability within the watershed and the ability to estimate area averaged quantities. Spatially averaged precipitation and observationally constrained soil moisture from the 88 gauges is then used to evaluate various gridded datasets. We find that gauge-based precipitation products perform best followed by reanalyses and then satellite-based products. Coupled Model Intercomparison Project Phase 5 (CMIP5) models perform the worst and overestimate cold season precipitation while offsetting the monsoon peak precipitation forward or backward by a month. Satellite-based soil moisture is the best followed by land data assimilation systems and </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=316894','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=316894">Using a soil moisture and precipitation network for satellite validation</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> A long term in situ network for the study of soil moisture and precipitation was deployed in north central Iowa, in cooperation between USDA and NASA. A total of 20 dual precipitation gages were established across a watershed landscape with an area of approximately 600 km2. In addition, four soil mo... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A14F..05S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A14F..05S">Convection and the Soil-Moisture Precipitation Feedback</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Schar, C.; Froidevaux, P.; Keller, M.; Schlemmer, L.; Langhans, W.; Schmidli, J. 2014-12-01 The soil moisture - precipitation (SMP) feedback is of key importance for climate and climate change. A positive SMP feedback tends to amplify the hydrological response to external forcings (and thereby fosters precipitation and drought extremes), while a negative SMP feedback tends to moderate the influence of external forcings (and thereby stabilizes the hydrological cycle). The sign of the SMP feedback is poorly constrained by the current literature. Theoretical, modeling and observational studies partly disagree, and have suggested both negative and positive feedback loops. Can wet soil anomalies indeed result in either an increase or a decrease of precipitation (positive or negative SMP feedback, respectively)? Here we investigate the local SMP feedback using real-case and idealized convection-resolving simulations. An idealized simulation strategy is developed, which is able to replicate both signs of the feedback loop, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches, where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the mid-tropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection), and high CAPE over wet patches (for the generation of precipitation). The results of this study will also be discussed in relation to climate change scenarios that exhibit large biases in surface temperature and </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000070719','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000070719">The Influence of Soil Moisture, Coastline Curvature, and Land-Breeze Circulations on Sea-Breeze Initiated Precipitation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H11N..02T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H11N..02T">A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..4412197L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..4412197L">Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120016072','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120016072">Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf 2012-01-01 Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.1553C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.1553C">Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H51K1344C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H51K1344C">The South Fork Experimental Watershed: Soil moisture and precipitation network for satellite validation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cosh, M. H.; Prueger, J. H.; McKee, L.; Bindlish, R. 2013-12-01 A recently deployed long term network for the study of soil moisture and precipitation was deployed in north central iowa, in cooperation between USDA and NASA. This site will be a joint calibration/validation network for the Soil Moisture Active Passive (SMAP) and Global Precipitation Measurement (GPM) missions. At total of 20 dual gauge precipitation gages were established across a watershed landscape with an area of approximately 600 km2. In addition, four soil moisture probes were installed in profile at 5, 10, 20, and 50 cm. The network was installed in April of 2013, at the initiation of the Iowa Flood Study (IFloodS) which was a six week intensive ground based radar observation period, conducted in coordination with NASA and the University of Iowa. This site is a member watershed of the Group on Earth Observations Joint Experiments on Crop Assessment and Monitoring (GEO-JECAM) program. A variety of quality control procedures are examined and spatial and temporal stability aspects of the network are examined. Initial comparisons of the watershed to soil moisture estimates from satellites are also conducted. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.5531T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.5531T">Confounding factors in determining causal soil moisture-precipitation feedback</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tuttle, Samuel E.; Salvucci, Guido D. 2017-07-01 Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.tmp..232K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.tmp..232K">Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kutty, Govindan; Sandeep, S.; Vinodkumar; Nhaloor, Sreejith 2017-07-01 Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011277','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011277">Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koster, Randal D.; Walker, Gregory K.; Mahanama, Sarith P.; Reichle, Rolf H. 2013-01-01 Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001WRR....37.2169P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001WRR....37.2169P">Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I. 2001-08-01 An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160008073','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160008073">Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yang, Wenli; Pham, Long; Zhao, Peisheng; Kempler, Steve; Wei, Jennifer 2016-01-01 Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/20095','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/20095">Prediction of monthly-seasonal precipitation using coupled SVD patterns between soil moisture and subsequent precipitation</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Yongqiang Liu 2003-01-01 It was suggested in a recent statistical correlation analysis that predictability of monthly-seasonal precipitation could be improved by using coupled singular value decomposition (SVD) pattems between soil moisture and precipitation instead of their values at individual locations. This study provides predictive evidence for this suggestion by comparing skills of two... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=266165','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=266165">Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..750C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..750C">Linking precipitation, evapotranspiration and soil moisture content for the improvement of predictability over land</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Catalano, Franco; Alessandri, Andrea; De Felice, Matteo 2013-04-01 Climate change scenarios are expected to show an intensification of the hydrological cycle together with modifications of evapotranspiration and soil moisture content. Evapotranspiration changes have been already evidenced for the end of the 20th century. The variance of evapotranspiration has been shown to be strongly related to the variance of precipitation over land. Nevertheless, the feedbacks between evapotranspiration, soil moisture and precipitation have not yet been completely understood at present-day. Furthermore, soil moisture reservoirs are associated to a memory and thus their proper initialization may have a strong influence on predictability. In particular, the linkage between precipitation and soil moisture is modulated by the effects on evapotranspiration. Therefore, the investigation of the coupling between these variables appear to be of primary importance for the improvement of predictability over the continents. The coupled manifold (CM) technique (Navarra and Tribbia 2005) is a method designed to separate the effects of the variability of two variables which are connected. This method has proved to be successful for the analysis of different climate fields, like precipitation, vegetation and sea surface temperature. In particular, the coupled variables reveal patterns that may be connected with specific phenomena, thus providing hints regarding potential predictability. In this study we applied the CM to recent observational datasets of precipitation (from CRU), evapotranspiration (from GIMMS and MODIS satellite-based estimates) and soil moisture content (from ESA) spanning a time period of 23 years (1984-2006) with a monthly frequency. Different data stratification (monthly, seasonal, summer JJA) have been employed to analyze the persistence of the patterns and their characteristical time scales and seasonality. The three variables considered show a significant coupling among each other. Interestingly, most of the signal of the </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24889286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24889286">Short-term precipitation exclusion alters microbial responses to soil moisture in a wet tropical forest.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Waring, Bonnie G; Hawkes, Christine V 2015-05-01 Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. Soil microbial responses to altered rainfall are likely to be an important feedback on ecosystem carbon cycling, but the ecological mechanisms underpinning these responses are poorly understood. We examined how reduced rainfall affected soil microbial abundance, activity, and community composition using a 6-month precipitation exclusion experiment at La Selva Biological Station, Costa Rica. Thereafter, we addressed the persistent effects of field moisture treatments by exposing soils to a controlled soil moisture gradient in the lab for 4 weeks. In the field, compositional and functional responses to reduced rainfall were dependent on initial conditions, consistent with a large degree of spatial heterogeneity in tropical forests. However, the precipitation manipulation significantly altered microbial functional responses to soil moisture. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control soils at low soil moisture. These functional patterns suggest that changes in microbial physiology may drive positive feedbacks to rising atmospheric CO2 concentrations if wet tropical forests experience longer or more intense dry seasons in the future. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......103T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......103T">Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tawfik, Ahmed B. The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26748720','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26748720">Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active">2</li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active">3</li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28687741','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28687741">InSAR constraints on soil moisture evolution after the March 2015 extreme precipitation event in Chile.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Scott, C P; Lohman, R B; Jordan, T E 2017-07-07 Constraints on soil moisture can guide agricultural practices, act as input into weather, flooding and climate models and inform water resource policies. Space-based interferometric synthetic aperture radar (InSAR) observations provide near-global coverage, even in the presence of clouds, of proxies for soil moisture derived from the amplitude and phase content of radar imagery. We describe results from a 1.5 year-long InSAR time series spanning the March, 2015 extreme precipitation event in the hyperarid Atacama desert of Chile, constraining the immediate increase in soil moisture and drying out over the following months, as well as the response to a later, smaller precipitation event. The inferred temporal evolution of soil moisture is remarkably consistent between independent, overlapping SAR tracks covering a region ~100 km in extent. The unusually large rain event, combined with the extensive spatial and temporal coverage of the SAR dataset, present an unprecedented opportunity to image the time-evolution of soil characteristics over different surface types. Constraints on the timescale of shallow water storage after precipitation events are increasingly valuable as global water resources continue to be stretched to their limits and communities continue to develop in flood-prone areas. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H31F1253T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H31F1253T">Using Large-Scale Precipitation to Validate AMSR-E Satellite Soil Moisture Estimates by Means of Mutual Information</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tuttle, S. E.; Salvucci, G. 2013-12-01 Validation of remotely sensed soil moisture is complicated by the difference in scale between remote sensing footprints and traditional ground-based soil moisture measurements. To address this issue, a new method was developed to evaluate the useful information content of remotely sensed soil moisture data using only large-scale precipitation (i.e. without modeling). Under statistically stationary conditions [Salvucci, 2001], precipitation conditionally averaged according to soil moisture (denoted E[P|S]) results in a sigmoidal shape in a manner that reflects the dependence of drainage, runoff, and evapotranspiration on soil moisture. However, errors in satellite measurement and algorithmic conversion of satellite data to soil moisture can degrade this relationship. Thus, remotely sensed soil moisture products can be assessed by the degree to which the natural sigmoidal relationship is preserved. The metric of mutual information was used as an error-dependent measure of the strength of the sigmoidal relationship, calculated from a two-dimensional histogram of soil moisture versus precipitation estimated using Gaussian mixture models. Three AMSR-E algorithms (VUA-NASA [Owe et al., 2001], NASA [Njoku et al., 2003], and U. Montana [Jones & Kimball, 2010]) were evaluated with the method for a nine-year period (2002-2011) over the contiguous United States at ¼° latitude-longitude resolution, using precipitation from the North American Land Data Assimilation System (NLDAS). The U. Montana product resulted in the highest mutual information for 57% of the region, followed by VUA-NASA and NASA at 40% and 3%, respectively. Areas where the U. Montana product yielded the maximum mutual information generally coincided with low vegetation biomass and flatter terrain, while the VUA-NASA product contained more useful information in more rugged and highly vegetated areas. Additionally, E[P|S] curves resulting from the Gaussian mixture method can potentially be decomposed into </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3990H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3990H">Soil frost-induced soil moisture precipitation feedback and effects on atmospheric states</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hagemann, Stefan; Blome, Tanja; Ekici, Altug; Beer, Christian 2016-04-01 land atmosphere feedback to precipitation over the high latitudes, which reduces the model's wet biases in precipitation and evapotranspiration during the summer. This is noteworthy as soil moisture - atmosphere feedbacks have previously not been in the research focus over the high latitudes. These results point out the importance of high latitude physical processes at the land surface for the regional climate. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/972970-evaluating-influence-antecedent-soil-moisture-variability-north-american-monsoon-precipitation-coupled-mm5-vic-modeling-system','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/972970-evaluating-influence-antecedent-soil-moisture-variability-north-american-monsoon-precipitation-coupled-mm5-vic-modeling-system">Evaluating the influence of antecedent soil moisture on variability of the North American Monsoon precipitation in the coupled MM5/VIC modeling system</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.8807S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.8807S">Empirical Modeling of Planetary Boundary Layer Dynamics Under Multiple Precipitation Scenarios Using a Two-Layer Soil Moisture Approach: An Example From a Semiarid Shrubland</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sanchez-Mejia, Zulia Mayari; Papuga, Shirley A. 2017-11-01 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 Santa Rita Creosote Ameriflux and Tucson Airport atmospheric sounding data to generate empirical relationships between soil moisture, albedo, and PBLh. Empirical relationships showed that ˜50% of the variation in PBLh can be explained by soil moisture and albedo with additional knowledge gained by dividing the soil profile into two layers. Therefore, we coupled these empirical relationships with soil moisture estimated using a two-layer bucket approach to model PBLh under six precipitation scenarios. Overall we observed that decreases in precipitation tend to limit the recovery of the PBL at the end of the wet season. However, increases in winter precipitation despite decreases in summer precipitation may provide opportunities for positive feedbacks that may further generate more winter precipitation. Our results highlight that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface-atmosphere applications have great potential for exploring the consequences of climate change. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010PhDT.......280B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010PhDT.......280B">Generation of an empirical soil moisture initialization and its potential impact on subseasonal forecasting skill of continental precipitation and air temperature</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Boisserie, Marie The goal of this dissertation research is to produce empirical soil moisture initial conditions (soil moisture analysis) and investigate its impact on the short-term (2 weeks) to subseasonal (2 months) forecasting skill of 2-m air temperature and precipitation. Because of soil moisture has a long memory and plays a role in controlling the surface water and energy budget, an accurate soil moisture analysis is today widely recognized as having the potential to increase summertime climate forecasting skill. However, because of a lack of global observations of soil moisture, there has been no scientific consensus on the importance of the contribution of a soil moisture initialization as close to the truth as possible to climate forecasting skill. In this study, the initial conditions are generated using a Precipitation Assimilation Reanalysis (PAR) technique to produce a soil moisture analysis. This technique consists mainly of nudging precipitation in the atmosphere component of a land-atmosphere model by adjusting the vertical air humidity profile based on the difference between the rate of the model-derived precipitation rate and the observed rate. The unique aspects of the PAR technique are the following: (1) based on the PAR technique, the soil moisture analysis is generated using a coupled land-atmosphere forecast model; therefore, no bias between the initial conditions and the forecast model (spinup problem) is encountered; and (2) the PAR technique is physically consistent; the surface and radiative fluxes remains in conjunction with the soil moisture analysis. To our knowledge, there has been no attempt to use a physically consistent soil moisture land assimilation system into a land-atmosphere model in a coupled mode. The effect of the PAR technique on the model soil moisture estimates is evaluated using the Global Soil Wetness Project Phase 2 (GSWP-2) multimodel analysis product (used as a proxy for global soil moisture observations) and actual in </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28310221','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28310221">The influence of annual precipitation, topography, and vegetative cover on soil moisture and summer drought in southern California.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Miller, P C; Poole, D K 1983-02-01 The influence of annual precipitation and vegetation cover on soil moisture and on the length of the summer drought was estimated quantitatively using 9 years of soil moisture data collected at Echo Valley in southern California. The measurements support the conclusions that in the semi-arid mediterranean climate a soil drought will occur regardless of vegetation cover and annual precipitation, but the length of the drought is greatly dependent on soil depth and rockiness. Evergreen species which can survive this drought tend to accentuate the drought, especially in deep soil levels, by developing a canopy with a large transpiring surface. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H44B..05M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H44B..05M">Streamflow forecasting and data assimilation: bias in precipitation, soil moisture states, and groundwater fluxes.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> McCreight, J. L.; Gochis, D. J.; Hoar, T.; Dugger, A. L.; Yu, W. 2014-12-01 Uncertainty in precipitation forcing, soil moisture states, and model groundwater fluxes are first-order sources of error in streamflow forecasting. While near-surface estimates of soil moisture are now available from satellite, very few soil moisture observations below 5 cm depth or groundwater discharge estimates are available for operational forecasting. Radar precipitation estimates are subject to large biases, particularly during extreme events (e.g. Steiner et al., 2010) and their correction is not typically available in real-time. Streamflow data, however, are readily available in near-real-time and can be assimilated operationally to help constrain uncertainty in these uncertain states and improve streamflow forecasts. We examine the ability of streamflow observations to diagnose bias in the three most uncertain variables: precipitation forcing, soil moisture states, and groundwater fluxes. We investigate strategies for their subsequent bias correction. These include spinup and calibration strategies with and without the use of data assimilation and the determination of the proper spinup timescales. Global and spatially distributed multipliers on the uncertain states included in the assimilation state vector (e.g. Seo et al., 2003) will also be evaluated. We examine real cases and observing system simulation experiments for both normal and extreme rainfall events. One of our test cases considers the Colorado Front Range flood of September 2013 where the range of disagreement amongst five precipitation estimates spanned a factor of five with only one exhibiting appreciable positive bias (Gochis et al, submitted). Our experiments are conducted using the WRF-Hydro model with the NoahMP land surface component and the data assimilation research testbed (DART). A variety of ensemble data assimilation approaches (filters) are considered. ReferencesGochis, DJ, et al. "The Great Colorado Flood of September 2013" BAMS (Submitted 4-7-14). Seo, DJ, V Koren, and N </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B41E0251G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B41E0251G">Modeling soil moisture memory in savanna ecosystems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1454924-radiative-precipitation-controls-root-zone-soil-moisture-spectra','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1454924-radiative-precipitation-controls-root-zone-soil-moisture-spectra">Radiative and precipitation controls on root zone soil moisture spectra</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> Nakai, Taro; Katul, Gabriel G.; Kotani, Ayumi; ... 2014-10-20 Here, we present that temporal variability in root zone soil moisture content (w) exhibits a Lorentzian spectrum with memory dictated by a damping term when forced with white-noise precipitation. In the context of regional dimming, radiation and precipitation variability are needed to reproduce w trends prompting interest in how the w memory is altered by radiative forcing. A hierarchy of models that sequentially introduce the spectrum of precipitation, net radiation, and the effect of w on evaporative and drainage losses was used to analyze the spectrum of w at subtropical and temperate forested sites. Reproducing the w spectra at longmore » time scales necessitated simultaneous precipitation and net radiation measurements depending on site conditions. The w memory inferred from observed w spectra was 25–38 days, larger than that determined from maximum wet evapotranspiration and field capacity. Finally, the w memory can be reasonably inferred from the Lorentzian spectrum when precipitation and evapotranspiration are in phase.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B33C0417T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B33C0417T">Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data to Improve USDA's World Agricultural Supply and Demand Estimates</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Teng, W. L.; Shannon, H. 2010-12-01 The USDA World Agricultural Outlook Board (WAOB) coordinates the development of the monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Given the significant effect of weather on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments in the Global Agricultural Decision Support Environment (GLADSE). Because the timing of the precipitation is often as important as the amount, in their effects on crop production, WAOB frequently examines precipitation time series to estimate crop productivity. An effective method for such assessment is the use of analog year comparisons, where precipitation time series, based on surface weather stations, from several historical years are compared with the time series from the current year. Once analog years are identified, crop yields can be estimated for the current season based on observed yields from the analog years, because of the similarities in the precipitation patterns. In this study, NASA satellite precipitation and soil moisture time series are used to identify analog years. Given that soil moisture often has a more direct effect than does precipitation on crop water availability, the time series of soil moisture could be more effective than that of precipitation, in identifying those years with similar crop yields. Retrospective analyses of analogs will be conducted to determine any reduction in the level of uncertainty in identifying analog years, and any reduction in false negatives or false positives. The comparison of analog years could potentially be improved by quantifying the selection of analogs, instead of the current visual inspection method. Various approaches to quantifying are currently being evaluated. This study is part of a larger effort to improve WAOB estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE, including (1) the integration of the Land </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1203900-assessing-relative-influence-surface-soil-moisture-enso-sst-precipitation-predictability-over-contiguous-united-states','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1203900-assessing-relative-influence-surface-soil-moisture-enso-sst-precipitation-predictability-over-contiguous-united-states">Assessing the relative influence of surface soil moisture and ENSO SST on precipitation predictability over the contiguous United States</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Yoon, Jin-Ho; Leung, Lai-Yung R. This study assesses the relative influence of soil moisture memory and tropical sea surface temperature (SST) in seasonal rainfall over the contiguous United States. Using observed precipitation, the NINO3.4 index and soil moisture and evapotranspiration simulated by a land surface model for 61 years, analysis was performed using partial correlations to evaluate to what extent land surface and SST anomaly of El Niño and Southern Oscillation (ENSO) can affect seasonal precipitation over different regions and seasons. Results show that antecedent soil moisture is as important as concurrent ENSO condition in controlling rainfall anomalies over the U.S., but they generally dominatemore » in different seasons with SST providing more predictability during winter while soil moisture, through its linkages to evapotranspiration and snow water, has larger influence in spring and early summer. The proposed methodology is applicable to climate model outputs to evaluate the intensity of land-atmosphere coupling and its relative importance.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A13M..12T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A13M..12T">Representing soil moisture - precipitation feedbacks in the Sahel: spatial scale and parameterisation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Taylor, C.; Birch, C.; Parker, D.; Guichard, F.; Nikulin, G.; Dixon, N. 2013-12-01 Land surface properties influence the life cycle of convective systems across West Africa via space-time variability in sensible and latent heat fluxes. Previous observational and modelling studies have shown that areas with strong mesoscale variability in vegetation cover or soil moisture induce coherent structures in the daytime planetary boundary layer. In particular, horizontal gradients in sensible heat flux can induce convergence zones which favour the initiation of deep convection. A recent study based on satellite data (Taylor et al. 2011), illustrated the climatological importance of soil moisture gradients in the initiation of long-lived Mesoscale Convective Systems (MCS) in the Sahel. Here we provide a unique assessment of how models of different spatial resolutions represent soil moisture - precipitation feedbacks in the region, and compare their behaviour to observations. Specifically we examine whether the inability of large-scale models to capture the observed preference for afternoon rain over drier soil in semi-arid regions [Taylor et al., 2012] is due to inadequate spatial resolution and/or systematic bias in convective parameterisations. Firstly, we use a convection-permitting simulation at 4km resolution to explore the underlying mechanisms responsible for soil moisture controls on daytime convective initiation in the Sahel. The model reproduces very similar spatial structure as the observations in terms of antecedent soil moisture in the vicinity of a large sample of convective initiations. We then examine how this same model, run at coarser resolution, simulates the feedback of soil moisture on daily rainfall. In particular we examine the impact of switching on the convective parameterisation on rainfall persistence, and compare the findings with 10 regional climate models (RCMs). Finally, we quantify the impact of the feedback on dry-spell return times using a simple statistical model. The results highlight important weaknesses in convective </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810019214','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810019214">Some effects of topography, soil moisture, and sea-surface temperature on continental precipitation as computed with the GISS coarse mesh climate model</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Spar, J.; Cohen, C. 1981-01-01 The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6315G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6315G">Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian 2017-04-01 West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.H23D..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.H23D..04B">Evaluation of a Soil Moisture Data Assimilation System Over West Africa</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010027896','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010027896">Soil Moisture Memory in Climate Models</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913775Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913775Z">Soil water dynamics during precipitation in genetic horizons of Retisol</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H23N..02Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H23N..02Z">Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J. 2016-12-01 The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B13D0646K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B13D0646K">Field measures show methanotroph sensitivity to soil moisture follows precipitation regime of the grassland sites across the US Great Plains</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Koyama, A.; Webb, C. T.; Johnson, N. G.; Brewer, P. E.; von Fischer, J. C. 2015-12-01 Methane uptake rates are known to have temporal variation in response to changing soil moisture levels. However, the relative importance of soil diffusivity vs. methanotroph physiology has not been disentangled to date. Testing methanotroph physiology in the laboratory can lead to misleading results due to changes in the fine-scale habitat where methanotrophs reside. To assay the soil moisture sensitivity of methanotrophs under field conditions, we studied 22 field plots scattered across eight Great Plains grassland sites that differed in precipitation regime and soil moisture, making ca. bi-weekly measures during the growing seasons over three years. Quantification of methanotroph activity was achieved from chamber-based measures of methane uptake coincident with SF6-derived soil diffusivity, and interpretation in a reaction-diffusion model. At each plot, we also measured soil water content (SWC), soil temperature and inorganic nitrogen (N) contents. We also assessed methanotroph community composition via 454 sequencing of the pmoA gene. Statistical analyses showed that methanotroph activity had a parabolic response with SWC (concave down), and significant differences in the shape of this response among sites. Moreover, we found that the SWC at peak methanotroph activity was strongly correlated with mean annual precipitation (MAP) of the site. The sequence data revealed distinct composition patterns, with structure that was associated with variation in MAP and soil texture. These results suggest that local precipitation regime shapes methanotroph community composition, which in turn lead to unique sensitivity of methane uptake rates with soil moisture. Our findings suggest that methanotroph activity may be more accurately modeled when the biological and environmental responses are explicitly described. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active">3</li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active">4</li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41C1453G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41C1453G">A multiyear study of soil moisture patterns across agricultural and forested landscapes</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.B41A0375T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.B41A0375T">Enhancing USDA's Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Teng, W. L.; Shannon, H. D. 2013-12-01 . Subsequent work has compared the relative performance of AI for time series derived from satellite-retrieved surface soil moisture data and from root zone soil moisture derived from the assimilation of surface soil moisture data into a land surface model. These results, which also showed the potential benefits of satellite data for analog year analyses, will be presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.H51N..03B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.H51N..03B">SoilNet - A Zigbee based soil moisture sensor network</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/20092','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/20092">Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Yongqiang Liu 2003-01-01 The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatGe..10..100M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatGe..10..100M">The global distribution and dynamics of surface soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970021687','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970021687">The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020066567','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020066567">Impact of Soil Moisture Initialization on Seasonal Weather Prediction</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor) 2002-01-01 The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP23E..07L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP23E..07L">Relating isotopic composition of precipitation to atmospheric patterns and local moisture recycling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Logan, K. E.; Brunsell, N. A.; Nippert, J. B. 2016-12-01 Local land management practices such as irrigation significantly alter surface evapotranspiration (ET), regional boundary layer development, and potentially modify precipitation likelihood and amount. How strong this local forcing is in comparison to synoptic-scale dynamics, and how much ET is recycled locally as precipitation are areas of great uncertainty and are especially important when trying to forecast the impact of local land management strategies on drought mitigation. Stable isotope analysis has long been a useful tool for tracing movement throughout the water cycle. In this study, reanalysis data and stable isotope samples of precipitation events are used to estimate the contribution of local moisture recycling to precipitation at the Konza Prairie LTER - located in the Great Plains, downwind of intensive agricultural areas. From 2001 to 2014 samples of all precipitation events over 5mm were collected and 18O and D isotopes measured. Comparison of observed precipitation totals and MERRA and ERA-interim reanalysis totals is used to diagnose periods of strong local moisture contribution (especially from irrigation) to precipitation. Large discrepancies in precipitation between observation and reanalysis, particularly MERRA, tend to follow dry periods during the growing season, presumably because while ERA-Interim adjusts soil moisture using observed surface temperature and humidity, MERRA includes no such local soil moisture adjustment and therefore lacks potential precipitation feedbacks induced by irrigation. The δ18O and δD signature of local irrigation recycling is evaluated using these incongruous observations. Self-organizing maps (SOM) are then used to identify a comprehensive range of synoptic conditions that result in precipitation at Konza LTER. Comparison of isotopic signature and SOM classification of rainfall events allows for identification of the primary moisture source and estimation of the contribution of locally recycled moisture. The </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H21G1512Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H21G1512Y">Evaluation of Long-term Soil Moisture Proxies in the U.S. Great Plains</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19800014268','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19800014268">Survey of methods for soil moisture determination</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H11M..01C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H11M..01C">Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Coopersmith, E. J.; Cosh, M. H. 2014-12-01 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 networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/ds/0837/pdf/ds837.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/ds/0837/pdf/ds837.pdf">Visualization of soil-moisture change in response to precipitation within two rain gardens in Ohio</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Dumouchelle, Denise H.; Darner, Robert A. 2014-01-01 Stormwater runoff in urban areas is increasingly being managed by means of a variety of treaments that reduce or delay runoff and promote more natural infiltration. One such treatment is a rain garden, which is built to detain runoff and allow for water infiltration and uptake by plants.Water flow into or out of a rain garden can be readily monitored with a variety of tools; however, observing the movement of water within the rain garden is less straightforward. Soil-moisture probes in combination with an automated interpolation procedure were used to document the infiltration of water into two rain gardens in Ohio. Animations show changes in soil moisture in the rain gardens during two precipitation events. At both sites, the animations demonstrate underutilization of the rain gardens. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000PhDT........38W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000PhDT........38W">Soil moisture profile variability in land-vegetation- atmosphere continuum</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040082182','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040082182">Potential Predictability of U.S. Summer Climate with "Perfect" Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yang, Fanglin; Kumar, Arun; Lau, K.-M. 2004-01-01 The potential predictability of surface-air temperature and precipitation over the United States continent was assessed for a GCM forced by observed sea surface temperatures and an estimate of observed ground soil moisture contents. The latter was obtained by substituting the GCM simulated precipitation, which is used to drive the GCM's land-surface component, with observed pentad-mean precipitation at each time step of the model's integration. With this substitution, the simulated soil moisture correlates well with an independent estimate of observed soil moisture in all seasons over the entire US continent. Significant enhancements on the predictability of surface-air temperature and precipitation were found in boreal late spring and summer over the US continent. Anomalous pattern correlations of precipitation and surface-air temperature over the US continent in the June-July-August season averaged for the 1979-2000 period increased from 0.01 and 0.06 for the GCM simulations without precipitation substitution to 0.23 and 0.3 1, respectively, for the simulations with precipitation substitution. Results provide an estimate for the limits of potential predictability if soil moisture variability is to be perfectly predicted. However, this estimate may be model dependent, and needs to be substantiated by other modeling groups. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27743651','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27743651">Precipitation gradient determines the tradeoff between soil moisture and soil organic carbon, total nitrogen, and species richness in the Loess Plateau, China.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Wang, Cong; Wang, Shuai; Fu, Bojie; Li, Zongshan; Wu, Xing; Tang, Qiang 2017-01-01 A tight coupling exists between biogeochemical cycles and water availability in drylands. However, studies regarding the coupling among soil moisture (SM), soil carbon/nitrogen, and plants are rare in the literature, and clarifying these relationships changing with climate gradient is challenging. Thus, soil organic carbon (SOC), total nitrogen (TN), and species richness (SR) were selected as soil-plant system variables, and the tradeoff relationships between SM and these variables and their variations along the precipitation gradient were quantified in the Loess Plateau, China. Results showed these variables increased linearly along the precipitation gradient in the woodland, shrubland, and grassland, respectively, except for the SR in the woodland and grassland, and SOC in the grassland (p>0.05). Correlation analysis showed that the SM-SOC and SM-TN tradeoffs were significantly correlated with mean annual precipitation (MAP) across the three vegetation types, and SM-SR tradeoff was significantly correlated with MAP in grassland and woodland. The linear piece-wise quantile regression was applied to determine the inflection points of these tradeoffs responses to the precipitation gradient. The inflection point for the SM-SOC tradeoff was detected at MAP=570mm; no inflection point was detected for SM-TN tradeoff; SM-SR tradeoff variation trends were different in the woodland and grassland, and the inflection points were detected at MAP=380mm and MAP=570mm, respectively. Before the turning point, constraint exerted by soil moisture on SOC and SR existed in the relatively arid regions, while the constraint disappears or is lessened in the relatively humid regions in this study. The results demonstrate the tradeoff revealed obvious trends along the precipitation gradient and were affected by vegetation type. Consequently, tradeoffs could be an ecological indicator and tool for restoration management in the Loess Plateau. In further study, the mechanism of how the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H13L..03S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H13L..03S">Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35..445Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35..445Z">Evaluating the Capabilities of Soil Enthalpy, Soil Moisture and Soil Temperature in Predicting Seasonal Precipitation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhao, Changyu; Chen, Haishan; Sun, Shanlei 2018-04-01 Soil enthalpy ( H) contains the combined effects of both soil moisture ( w) and soil temperature ( T) in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different (positive or negative) impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer (i.e., the fifth layer), H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation ( P) prediction, the Huanghe-Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer (June) P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors (e.g., T and w). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9543P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9543P">Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi 2014-05-01 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...8.1609D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...8.1609D">The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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; <a href="http://www.ipf.tuwien.ac.at/insitu" target="_blank">http://www.ipf.tuwien.ac.at/insitu</a>) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESS...15.1675D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESS...15.1675D">The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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; <a href="http://www.ipf.tuwien.ac.at/insitu" target="_blank">http://www.ipf.tuwien.ac.at/insitu</a>) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active">4</li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active">5</li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4366536','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4366536">Reconciling spatial and temporal soil moisture effects on afternoon rainfall</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I. 2015-01-01 Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks. PMID:25740589 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275">Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H12G..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H12G..03M">The Value of SMAP Soil Moisture Observations For Agricultural Applications</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.3275P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.3275P">Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise 2018-06-01 The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC <q>hot spots</q>. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1601M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1601M">Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S. 2017-12-01 Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B41I2077M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B41I2077M">Effect of soil moisture on the temperature sensitivity of Northern soils</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.7800U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.7800U">Spatial and temporal variability of soil moisture on the field with and without plants*</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/47251','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/47251">Long-term soil moisture patterns in a northern Minnesota forest</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Salli F. Dymond; Randall K. Kolka; Paul V. Bolstad; Stephen D. Sebestyen 2014-01-01 Forest hydrological and biogeochemical processes are highly dependent on soil water. At the Marcell Experimental Forest, seasonal patterns of soil moisture have been monitored at three forested locations since 1966. This unique, long-term data set was used to analyze seasonal trends in soil moisture as well as the influence of time-lagged precipitation and modified... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820006676','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820006676">A simulation study of the recession coefficient for antecedent precipitation index. [soil moisture and water runoff estimation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Choudhury, B. J.; Blanchard, B. J. 1981-01-01 The antecedent precipitation index (API) is a useful indicator of soil moisture conditions for watershed runoff calculations and recent attempts to correlate this index with spaceborne microwave observations have been fairly successful. It is shown that the prognostic equation for soil moisture used in some of the atmospheric general circulation models together with Thornthwaite-Mather parameterization of actual evapotranspiration leads to API equations. The recession coefficient for API is found to depend on climatic factors through potential evapotranspiration and on soil texture through the field capacity and the permanent wilting point. Climatologial data for Wisconsin together with a recently developed model for global isolation are used to simulate the annual trend of the recession coefficient. Good quantitative agreement is shown with the observed trend at Fennimore and Colby watersheds in Wisconsin. It is suggested that API could be a unifying vocabulary for watershed and atmospheric general circulation modelars. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27594213','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27594213">The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer 2017-05-01 Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459">Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990116494&hterms=atmosphere+wind+profile&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Datmosphere%2Bwind%2Bprofile','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990116494&hterms=atmosphere+wind+profile&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Datmosphere%2Bwind%2Bprofile">The Influence of Soil Moisture and Wind on Rainfall Distribution and Intensity in Florida</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo 1998-01-01 Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of soil moisture will affect sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of soil moisture and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of soil moisture distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial soil moisture distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of soil moisture and wind to rainfall distribution and intensity is determined. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100031160','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100031160">Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B">Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19637591','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19637591">[Soil moisture dynamics of artificial Caragana microphylla shrubs at different topographical sites in Horqin sandy land].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H31F1177M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H31F1177M">Agricultural Decision Support Through Robust Assimilation of Satellite Derived Soil Moisture Estimates</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mishra, V.; Cruise, J.; Mecikalski, J. R. 2012-12-01 Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43Q..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43Q..08S">Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034255','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034255">Remote sensing of soil moisture using airborne hyperspectral data</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H42A..06O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H42A..06O">Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ochsner, T.; Venterea, R. T. 2009-12-01 Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170002444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170002444">A Data-Driven Approach for Daily Real-Time Estimates and Forecasts of Near-Surface Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active">5</li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active">6</li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916217M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916217M">A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018NHESS..18..889P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018NHESS..18..889P">The effect of soil moisture anomalies on maize yield in Germany</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis 2018-03-01 Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMEP41C0924C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMEP41C0924C">Estimating soil moisture exceedance probability from antecedent rainfall</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cronkite-Ratcliff, C.; Kalansky, J.; Stock, J. D.; Collins, B. D. 2016-12-01 The first storms of the rainy season in coastal California, USA, add moisture to soils but rarely trigger landslides. Previous workers proposed that antecedent rainfall, the cumulative seasonal rain from October 1 onwards, had to exceed specific amounts in order to trigger landsliding. Recent monitoring of soil moisture upslope of historic landslides in the San Francisco Bay Area shows that storms can cause positive pressure heads once soil moisture values exceed a threshold of volumetric water content (VWC). We propose that antecedent rainfall could be used to estimate the probability that VWC exceeds this threshold. A major challenge to estimating the probability of exceedance is that rain gauge records are frequently incomplete. We developed a stochastic model to impute (infill) missing hourly precipitation data. This model uses nearest neighbor-based conditional resampling of the gauge record using data from nearby rain gauges. Using co-located VWC measurements, imputed data can be used to estimate the probability that VWC exceeds a specific threshold for a given antecedent rainfall. The stochastic imputation model can also provide an estimate of uncertainty in the exceedance probability curve. Here we demonstrate the method using soil moisture and precipitation data from several sites located throughout Northern California. Results show a significant variability between sites in the sensitivity of VWC exceedance probability to antecedent rainfall. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860018232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860018232">Preliminary assessment of soil moisture over vegetation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Carlson, T. N. 1986-01-01 Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159491','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159491">Remote sensing of soil moisture using airborne hyperspectral data</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC23C0658S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC23C0658S">Effects of altered soil moisture on respiratory quotient in the Edwards Plateau</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sellers, M. A.; Hawkes, C.; Breecker, D. 2014-12-01 Climate change is expected to alter precipitation patterns around the world. The impacts of altered precipitation on ecosystem function will be partly controlled by soil microbes because of their primary role in soil carbon cycling. However, microbial responses to drought remain poorly understood, particularly local responses that might partly reflect specialization based on historical conditions. Here, we investigated the respiratory response of microbial communities originating from historically wetter and drier sites to both low and high soil moistures. We focused on the respiratory quotient (RQ= moles of CO2 produced per mole of O2 consumed), which varies with the oxidation state of organic carbon being respired and/or the compounds being synthesized by soil microbes. We hypothesized that there would be a shift in RQ across the gradient of soil moisture. Soils were collected from 13 sites across a steep precipitation gradient on the Edwards plateau in central Texas, air-dried, rewet at low or high soil moisture (6% or 24% gravimetric, respectively), and incubated in an atmosphere of 21% O2, 1% Ar, and balance He. After eight weeks, CO2, O2 and Ar in the headspace of incubation vials were measured by gas chromatography after separation of Ar and O2 at subambient temperature. Because of the high calcite content in soils on the Edwards plateau, we corrected the RQ values by assuming pH was buffered at 8 and then adding the calculated amount of CO2 dissolved in water in the incubations vials to the measured CO2 in the headspace. We found that uncorrected RQ values were slightly less than one and increased significantly with increasing mean annual precipitation. In contrast, corrected RQ values were greater than one and decreased with increasing mean annual precipitation. In both cases, we see a shift in RQ across the gradient, suggesting that differences in substrate utilization may vary based on origin across the gradient and with current level of soil moisture </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930068715&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Devapotranspiration','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930068715&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Devapotranspiration">Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Mintz, Y.; Walker, G. K. 1993-01-01 The global fields of normal monthly soil moisture and land surface evapotranspiration are derived with a simple water budget model that has precipitation and potential evapotranspiration as inputs. The precipitation is observed and the potential evapotranspiration is derived from the observed surface air temperature with the empirical regression equation of Thornthwaite (1954). It is shown that at locations where the net surface radiation flux has been measured, the potential evapotranspiration given by the Thornthwaite equation is in good agreement with those obtained with the radiation-based formulations of Priestley and Taylor (1972), Penman (1948), and Budyko (1956-1974), and this provides the justification for the use of the Thornthwaite equation. After deriving the global fields of soil moisture and evapotranspiration, the assumption is made that the potential evapotranspiration given by the Thornthwaite equation and by the Priestley-Taylor equation will everywhere be about the same; the inverse of the Priestley-Taylor equation is used to obtain the normal monthly global fields of net surface radiation flux minus ground heat storage. This and the derived evapotranspiration are then used in the equation for energy conservation at the surface of the earth to obtain the global fields of normal monthly sensible heat flux from the land surface to the atmosphere. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/46775','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/46775">Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Tana Wood; M. Detto; W.L. Silver 2013-01-01 Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H">Surface Soil Moisture Memory Estimated from Models and SMAP Observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D. 2017-12-01 Soil moisture memory(SMM), which is loosely defined as the time taken by soil to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the soil moisture time series and the timescale which only considers soil moisture increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on soil moisture memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the soil moisture time series autocorrelation, deT0 based on the detrending soil moisture time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface soil moisture was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface Soil Moisture, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21F1530N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21F1530N">Quantifying agricultural drought impacts using soil moisture model and drought indices in South Korea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nam, W. H.; Bang, N.; Hong, E. M.; Pachepsky, Y. A.; Han, K. H.; Cho, H.; Ok, J.; Hong, S. Y. 2017-12-01 Agricultural drought is defined as a combination of abnormal deficiency of precipitation, increased crop evapotranspiration demands from high-temperature anomalies, and soil moisture deficits during the crop growth period. Soil moisture variability and their spatio-temporal trends is a key component of the hydrological balance, which determines the crop production and drought stresses in the context of agriculture. In 2017, South Korea has identified the extreme drought event, the worst in one hundred years according to the South Korean government. The objective of this study is to quantify agricultural drought impacts using observed and simulated soil moisture, and various drought indices. A soil water balance model is used to simulate the soil water content in the crop root zone under rain-fed (no irrigation) conditions. The model used includes physical process using estimated effective rainfall, infiltration, redistribution in soil water zone, and plant water uptake in the form of actual crop evapotranspiration. Three widely used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Self-Calibrated Palmer Drought Severity Index (SC-PDSI) are compared with the observed and simulated soil moisture in the context of agricultural drought impacts. These results demonstrated that the soil moisture model could be an effective tool to provide improved spatial and temporal drought monitoring for drought policy. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616875A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616875A">Soil moisture under contrasted atmospheric conditions in Eastern Spain</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9971Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9971Z">Soil moisture in sessile oak forest gaps</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter 2015-04-01 By social demands are being promoted the aspects of the natural forest management. In forestry the concept of continuous forest has been an accepted principle also in Hungary since the last decades. The first step from even-aged stand to continuous forest can be the forest regeneration based on gap cutting, so small openings are formed in a forest due to forestry interventions. This new stand structure modifies the hydrological conditions for the regrowth. Without canopy and due to the decreasing amounts of forest litter the interception is less significant so higher amount of precipitation reaching the soil. This research focuses on soil moisture patterns caused by gaps. The spatio-temporal variability of soil water content is measured in gaps and in surrounding sessile oak (Quercus petraea) forest stand. Soil moisture was determined with manual soil moisture meter which use Time-Domain Reflectometry (TDR) technology. The three different sizes gaps (G1: 10m, G2: 20m, G3: 30m) was opened next to Sopron on the Dalos Hill in Hungary. First, it was determined that there is difference in soil moisture between forest stand and gaps. Second, it was defined that how the gap size influences the soil moisture content. To explore the short term variability of soil moisture, two 24-hour (in growing season) and a 48-hour (in dormant season) field campaign were also performed in case of the medium-sized G2 gap along two/four transects. Subdaily changes of soil moisture were performed. The measured soil moisture pattern was compared with the radiation pattern. It was found that the non-illuminated areas were wetter and in the dormant season the subdaily changes cease. According to our measurements, in the gap there is more available water than under the forest stand due to the less evaporation and interception loss. Acknowledgements: The research was supported by TÁMOP-4.2.2.A-11/1/KONV-2012-0004 and AGRARKLIMA.2 VKSZ_12-1-2013-0034. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H43O..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H43O..06A">Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A. 2016-12-01 We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern 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 and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H33F1393K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H33F1393K">Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913136S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913136S">Assimilating soil moisture into an Earth System Model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940006468','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940006468">Design of a global soil moisture initialization procedure for the simple biosphere model</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Liston, G. E.; Sud, Y. C.; Walker, G. K. 1993-01-01 Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170003709&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170003709&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsoil">Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23F1753H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23F1753H">Patterns of Precipitation and Streamflow Responses to Moisture Fluxes during Atmospheric Rivers</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Henn, B. M.; Wilson, A. M.; Asgari Lamjiri, M.; Ralph, M. 2017-12-01 Precipitation from landfalling atmospheric rivers (ARs) have been shown to dominate the hydroclimate of many parts of the world. ARs are associated with saturated, neutrally-stable profiles in the lower atmosphere, in which forced ascent by topography induces precipitation. Understanding the spatial and temporal variability of precipitation over complex terrain during AR-driven precipitation is critical for accurate forcing of distributed hydrologic models and streamflow forecasts. Past studies using radar wind profilers and radiosondes have demonstrated predictability of precipitation rates based on upslope water vapor flux over coastal terrain, with certain levels of moisture flux exhibiting the greatest influence on precipitation. Additionally, these relationships have been extended to show that streamflow in turn responds predictably to upslope vapor flux. However, past studies have focused on individual pairs of profilers and precipitation gauges; the question of how orographic precipitation in ARs is distributed spatially over complex terrain, at different topographic scales, is less well known. Here, we examine profiles of atmospheric moisture transport from radiosondes and wind profilers, against a relatively dense network of precipitation gauges, as well as stream gauges, to assess relationships between upslope moisture flux and the spatial response of precipitation and streamflow. We focus on California's Russian River watershed in the 2016-2017 cool season, when regular radiosonde launches were made at two locations during an active sequence of landfalling ARs. We examine how atmospheric water vapor flux results in precipitation patterns across gauges with different topographic relationships to the prevailing moisture-bearing winds, and conduct a similar comparison of runoff volume response from several unimpaired watersheds in the upper Russian watershed, taking into account antecedent soil moisture conditions that influence runoff generation. Finally </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.7265H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.7265H">Variability of soil moisture proxies and hot days across the climate regimes of Australia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=235923','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=235923">The Development of Terrestrial Water Cycle Applications for SMAP Soil Moisture Data Products</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Soil moisture storage sits at the locus of the terrestrial water cycle and governs the relative partitioning of precipitation into various land surface flux components. Consequently, improved observational constraint of soil moisture variations should improve our ability to globally monitor the te... </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active">6</li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active">7</li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=303067','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=303067">Extending the soil moisture record of the climate reference network with machine learning</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...8.8063M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...8.8063M">Precipitation patterns and moisture fluxes in a sandy, tropical environment with a shallow water table</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Minihane, M. R.; Freyberg, D. L. 2011-08-01 Identifying the dominant mechanisms controlling recharge in shallow sandy soils in tropical climates has received relatively little attention. Given the expansion of coastal fill using marine sands and the growth of coastal populations throughout the tropics, there is a need to better understand the nature of water balances in these settings. We use time series of field observations at a coastal landfill in Singapore coupled with numerical modeling using the Richards' equation to examine the impact of precipitation patterns on soil moisture dynamics, including percolation past the root zone and recharge, in such an environment. A threshold in total precipitation event depth, much more so than peak precipitation intensity, is the strongest event control on recharge. However, shallow antecedent moisture, and therefore the timing between events along with the seasonal depth to water table, also play significant roles in determining recharge amounts. For example, at our field site, precipitation events of less than 3 mm per event yield little to no direct recharge, but for larger events, moisture content changes below the root zone are linearly correlated to the product of the average antecedent moisture content and the total event precipitation. Therefore, water resources planners need to consider identifying threshold precipitation volumes, along with the multiple time scales that capture variability in event antecedent conditions and storm frequency in assessing the role of recharge in coastal water balances in tropical settings. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B13H1840B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B13H1840B">Ecosystem-scale plant hydraulic strategies inferred from remotely-sensed soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017HESS...21.6049M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017HESS...21.6049M">Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 <q>rover</q>, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..552..620M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..552..620M">Drought monitoring with soil moisture active passive (SMAP) measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.4089A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.4089A">Understanding tree growth in response to moisture variability: Linking 32 years of satellite based soil moisture observations with tree rings</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Albrecht, Franziska; Dorigo, Wouter; Gruber, Alexander; Wagner, Wolfgang; Kainz, Wolfgang 2014-05-01 Climate change induced drought variability impacts global forest ecosystems and forest carbon cycle dynamics. Physiological drought stress might even become an issue in regions generally not considered water-limited. The water balance at the soil surface is essential for forest growth. Soil moisture is a key driver linking precipitation and tree development. Tree ring based analyses are a potential approach to study the driving role of hydrological parameters for tree growth. However, at present two major research gaps are apparent: i) soil moisture records are hardly considered and ii) only a few studies are linking tree ring chronologies and satellite observations. Here we used tree ring chronologies obtained from the International Tree ring Data Bank (ITRDB) and remotely sensed soil moisture observations (ECV_SM) to analyze the moisture-tree growth relationship. The ECV_SM dataset, which is being distributed through ESA's Climate Change Initiative for soil moisture covers the period 1979 to 2010 at a spatial resolution of 0.25°. First analyses were performed for Mongolia, a country characterized by a continental arid climate. We extracted 13 tree ring chronologies suitable for our analysis from the ITRDB. Using monthly satellite based soil moisture observations we confirmed previous studies on the seasonality of soil moisture in Mongolia. Further, we investigated the relationship between tree growth (as reflected by tree ring width index) and remotely sensed soil moisture records by applying correlation analysis. In terms of correlation coefficient a strong response of tree growth to soil moisture conditions of current April to August was observed, confirming a strong linkage between tree growth and soil water storage. The highest correlation was found for current April (R=0.44), indicating that sufficient water supply is vital for trees at the beginning of the growing season. To verify these results, we related the chronologies to reanalysis precipitation and </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=300598','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=300598">A modeling approach to soil type and precipitation seasonality interactions on bioenergy crop production</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Precipitation limits primary production by affecting soil moisture, and soil type interacts with soil moisture to determine soil water availability to plants. We used ALMANAC, a process-based model, to simulate switchgrass (Panicum virgatum var. Alamo) biomass production in Central Texas under thre... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860007354','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860007354">Soil temperature extrema recovery rates after precipitation cooling</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Welker, J. E. 1984-01-01 From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B21I0534W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B21I0534W">Responses of Soil CO2 Emissions to Extreme Precipitation Regimes: a Simulation on Loess Soil in Semi-arid Regions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, R.; Zhao, M.; Hu, Y.; Guo, S. 2016-12-01 Responses of soil CO2 emission to natural precipitation play an essential role in regulating regional C cycling. With more erratic precipitation regimes, mostly likely of more frequent heavy rainstorms, projected into the future, extreme precipitation would potentially affect local soil moisture, plant growth, microbial communities, and further soil CO2 emissions. However, responses of soil CO2 emissions to extreme precipitation have not yet been systematically investigated. Such performances could be of particular importance for rainfed arable soil in semi-arid regions where soil microbial respiration stress is highly sensitive to temporal distribution of natural precipitation.In this study, a simulated experiment was conducted on bare loess soil from the semi-arid Chinese Loess Plateau. Three precipitation regimes with total precipitation amounts of 150 mm, 300 mm and 600 mm were carried out to simulate the extremely dry, business as usual, and extremely wet summer. The three regimes were individually materialized by wetting soils in a series of sub-events (10 mm or 150 mm). Co2 emissions from surface soil were continuously measured in-situ for one month. The results show that: 1) Evident CO2 emission pulses were observed immediately after applying sub-events, and cumulative CO2 emissions from events of total amount of 600 mm were greater than that from 150 mm. 3) In particular, for the same total amount of 600 mm, wetting regimes by applying four times of 150 mm sub-events resulted in 20% less CO2 emissions than by applying 60 times of 10 mm sub-events. This is mostly because its harsh 150 mm storms introduced more over-wet soil microbial respiration stress days (moisture > 28%). As opposed, for the same total amount of 150 mm, CO2 emissions from wetting regimes by applying 15 times of 10 mm sub-events were 22% lower than by wetting at once with 150 mm water, probably because its deficiency of soil moisture resulted in more over-dry soil microbial respiration </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESS...15.3829D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESS...15.3829D">Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W. 2011-12-01 This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM) model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%), this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage) induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased) climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006PhDT........51N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006PhDT........51N">High resolution change estimation of soil moisture and its assimilation into a land surface model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11I1989H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11I1989H">Conceptualizing the self organization of cloud cells, cold pools and soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Henneberg, O.; Härter, J. O. M. 2017-12-01 Convective-type cloud is the cause of extreme, short-duration precipitation, challenging weather forecasting and climate modeling. Such extremes are ultimately tied to the uneven redistribution of water in the course of convective self organization and possibly the interaction between clouds [1]. Over land, moisture is organized through: cloud cells, cold pools, and the land surface. Each of these generally capture and release moisture at different rates, e.g. cold pools form quickly but dissipate slowly. Such distinct timescales have implications for the emergent dynamics.Incorporating such distinct time scales, we here present a conceptual model for the spatio-temporal self organization within the diurnal cycle of convection and describe the possible role of soil moisture memory in serving as a predisposition for extremes.We bolster our findings by high resolution, large eddy simulations: Sensible and latent heat fluxes, which are determined by the soil moisture content, can influence the stability of the atmosphere. The onset of initial precipitation is affected by such heat release, which in turn is modified by previous precipitation. Starting from static heat sources, we quantify how their spatial distribution affects the self organization and thus onset, duration and strength of precipitation events in an idealized model setup. Furthermore, an extended model setup with inhomogeneous, self organized distributions of latent and sensible heat fluxes is used to contrast how emergent soil moisture patterns impact on the selforganization structure of convection. Our findings may have implications for the role of land use changes regarding the development of extreme convective precipitation.Reference[1] Moseley et al. (2016) "Intensification of convective extremes driven by cloud-cloud interaction", Nature Geosc. , 9, 748-752 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/40009','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/40009">Long– and short-term precipitation effects on soil CO2 efflux and total belowground carbon allocation</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Chelcy R. Ford; Jason McGee; Francesca Scandellari; Erik A. Hobbie; Robert J. Mitchell 2012-01-01 Soil CO2 efflux (Esoil), the main pathway of C movement from the biosphere to the atmosphere, is critical to the terrestrial C cycle but how precipitation and soil moisture influence Esoil remains poorly understood. Here, we irrigated a longleaf pine wiregrass savanna for six years; this increased soil moisture by 41.2%. We tested how an altered precipitation regime... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1614340B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1614340B">Drought index driven by L-band microwave soil moisture data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre 2014-05-01 Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/53294','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/53294">Evapotranspiration and soil moisture dynamics in a temperate grassland ecosystem in Inner Mongolia China</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> L. Hao; Ge Sun; Yongqiang Liu; G. S. Zhou; J. H. Wan; L. B. Zhang; J. L. Niu; Y. H. Sang; J. J He 2015-01-01 Precipitation, evapotranspiration (ET), and soil moisture are the key controls for the productivity and functioning of temperate grassland ecosystems in Inner Mongolia, northern China. Quantifying the soil moisture dynamics and water balances in the grasslands is essential to sustainable grassland management under global climate change. We... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H33I..05B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H33I..05B">Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bolten, J. D.; Crow, W. T.; Zhan, X.; Reynolds, C. A.; Jackson, T. J. 2008-12-01 A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29124249','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29124249">Relating coccidioidomycosis (valley fever) incidence to soil moisture conditions.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Coopersmith, E J; Bell, J E; Benedict, K; Shriber, J; McCotter, O; Cosh, M H 2017-04-17 Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp. , in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ soil moisture data sets, it has not been feasible to perform a direct analysis of the relationships between soil moisture levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ soil moisture gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower soil moisture in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to soil moisture levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009280','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009280">NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-Comparing Soil Moisture Data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..559..684D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..559..684D">Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008055','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008055">The Contribution of Soil Moisture Information to Forecast Skill: Two Studies</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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 </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active">7</li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active">8</li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313269','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313269">Understanding Soil Moisture</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ESD.....8..147M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ESD.....8..147M">Role of moisture transport for Central American precipitation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> María Durán-Quesada, Ana; Gimeno, Luis; Amador, Jorge 2017-02-01 A climatology of moisture sources linked with Central American precipitation was computed based upon Lagrangian trajectories for the analysis period 1980-2013. The response of the annual cycle of precipitation in terms of moisture supply from the sources was analysed. Regional precipitation patterns are mostly driven by moisture transport from the Caribbean Sea (CS). Moisture supply from the eastern tropical Pacific (ETPac) and northern South America (NSA) exhibits a strong seasonal pattern but weaker compared to CS. The regional distribution of rainfall is largely influenced by a local signal associated with surface fluxes during the first part of the rainy season, whereas large-scale dynamics forces rainfall during the second part of the rainy season. The Caribbean Low Level Jet (CLLJ) and the Chocó Jet (CJ) are the main conveyors of regional moisture, being key to define the seasonality of large-scale forced rainfall. Therefore, interannual variability of rainfall is highly dependent of the regional LLJs to the atmospheric variability modes. The El Niño-Southern Oscillation (ENSO) was found to be the dominant mode affecting moisture supply for Central American precipitation via the modulation of regional phenomena. Evaporative sources show opposite anomaly patterns during warm and cold ENSO phases, as a result of the strengthening and weakening, respectively, of the CLLJ during the summer months. Trends in both moisture supply and precipitation over the last three decades were computed, results suggest that precipitation trends are not homogeneous for Central America. Trends in moisture supply from the sources identified show a marked north-south seesaw, with an increasing supply from the CS Sea to northern Central America. Long-term trends in moisture supply are larger for the transition months (March and October). This might have important implications given that any changes in the conditions seen during the transition to the rainy season may induce stronger </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43B1646Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43B1646Z">Spatial Distribution of the Relationship Between Soil Moisture and Soil Particle Size in Typical Plots on Loess Plateau</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, X.; Zhao, W.; Liu, Y.; Fang, X. 2017-12-01 Soil water overconsumption is threatening the sustainability of regional vegetation rehabilitation in the Loess Plateau of China. The use of fractal geometry theory in describing soil quality improves the accuracy of the relevant research. Typical grasslands, shrublands, forests, cropland and orchards under different precipitation regimes were selected, and in this study, the spatial distribution of the relationship between soil moisture and soil particle size in typical slopes on Loess Plateau were investigated to provide support for the predict of soil moisture by using soil physical characteristics in the Loess Plateau. During the sampling year, the mean annual precipitation gradients were divided at an interval of 70 mm from 370mm to 650mm. Grasslands with Medicago sativa L. or Stipa bungeana Trin., shrublands with Caragana Korshinskii Kom. or Hippophae rhamnoides L., forests with Robinia pseudoacacia Linn., orchards with apple trees and croplands with corn or potatoes were chosen to represent the natural grassland. A soil auger with a diameter of 5 cm was used to obtain soil samples at depths of 0-5 m at intervals of 20 cm.The Van Genuchten model, fractal theory and redundancy analysis (RDA) were used to estimate and analyze the soil water characteristic curve, soil particle size distribution, and fractal dimension and the correlations between the relevant parameters. The results showed that (1) the change of the singular fractal dimension is positively correlated with soil water content, while D0 (capacity dimension) is negatively correlated with soil water content as the depth increases; (2) the relationship between soil moisture and soil particle size shows differences under different plants and precipitation gradient. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3690Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3690Z">Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AdAtS..22..337L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AdAtS..22..337L">A nonlinear coupled soil moisture-vegetation model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Liu, Shikuo; Liu, Shida; Fu, Zuntao; Sun, Lan 2005-06-01 Based on the physical analysis that the soil moisture and vegetation depend mainly on the precipitation and evaporation as well as the growth, decay and consumption of vegetation a nonlinear dynamic coupled system of soil moisture-vegetation is established. Using this model, the stabilities of the steady states of vegetation are analyzed. This paper focuses on the research of the vegetation catastrophe point which represents the transition between aridness and wetness to a great extent. It is shown that the catastrophe point of steady states of vegetation depends mainly on the rainfall P and saturation value v0, which is selected to balance the growth and decay of vegetation. In addition, when the consumption of vegetation remains constant, the analytic solution of the vegetation equation is obtained. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6373M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6373M">Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca 2016-04-01 Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B24A..04M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B24A..04M">Relationships between Hg Air-surface exchange, Soil Moisture and Precipitation at a Background Vegetated Site in South-Eastern Australia.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Macsween, K.; Edwards, G. C. 2017-12-01 Despite many decades of research, the controlling mechanisms of mercury (Hg) air-surface exhange are still poorly understood. Particularly in Australian ecosystems where there are few anthropogenic inputs. A clear understanding of these mechanisms is vital for accurate representation in the global Hg models, particularly regarding re-emission. Water is known to have a considerable influence on Hg exchange within a terrestrial ecosystem. Precipitation has been found to cause spikes is Hg emissions during the initial stages of rain event. While, Soil moisture content is known to enhance fluxes between 15 and 30% Volumetric soil water (VSW), above which fluxes become suppressed. Few field experiments exist to verify these dominantly laboratory or controlled experiments. Here we present work looking at Hg fluxes over an 8-month period at a vegetated background site. The aim of this study is to identify how changes to precipitation intensity and duration, coupled with variable soil moisture content may influence Hg flux across seasons. As well as the influence of other meteorological variables. Experimentation was undertaken using aerodynamic gradient micrometeorological flux method, avoiding disruption to the surface, soil moisture probes and rain gauge measurements to monitor alterations to substrate conditions. Meteorological and air chemistry variables were also measured concurrently throughout the duration of the study. During the study period, South-Eastern Australia experienced several intense east coast low storm systems during the Autumn and Spring months and an unusually dry winter. VSW rarely reached above 30% even following the intense rainfall experienced during the east coast lows. The generally dry conditions throughout winter resulted in an initial spike in Hg emissions when rainfall occurred. Fluxes decreased shortly after the rain began but remained slightly elevated. Given the reduced net radiation and cooler temperatures experienced during the winter </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA514591','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA514591">Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2010-01-25 2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JHyd..387..176T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JHyd..387..176T">Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tramblay, Yves; Bouvier, Christophe; Martin, Claude; Didon-Lescot, Jean-François; Todorovik, Dragana; Domergue, Jean-Marc 2010-06-01 Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture, modelled soil moisture through the Interaction-Sol-Biosphère-Atmosphère (ISBA) component of the SIM model (Météo-France), antecedent precipitation and base flow. A modelling approach based on the Soil Conservation Service-Curve Number method (SCS-CN) is used to simulate the flood events in a small headwater catchment in the Cevennes region (France). The model involves two parameters: one for the runoff production, S, and one for the routing component, K. The S parameter can be interpreted as the maximal water retention capacity, and acts as the initial condition of the model, depending on the antecedent moisture conditions. The model was calibrated from a 20-flood sample, and led to a median Nash value of 0.9. The local TDR measurements in the deepest layers of soil (80-140 cm) were found to be the best predictors for the S parameter. TDR measurements averaged over the whole soil profile, outputs of the SIM model, and the logarithm of base flow also proved to be good predictors, whereas antecedent precipitations were found to be less efficient. The good correlations observed between the TDR predictors and the S calibrated values indicate that monitoring soil moisture could help setting the initial conditions for simplified event-based models in small basins. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5672948','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5672948">Relating coccidioidomycosis (valley fever) incidence to soil moisture conditions</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Coopersmith, E. J.; Bell, J. E.; Benedict, K.; Shriber, J.; McCotter, O.; Cosh, M. H. 2017-01-01 Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp., in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ soil moisture data sets, it has not been feasible to perform a direct analysis of the relationships between soil moisture levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ soil moisture gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower soil moisture in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to soil moisture levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location. PMID:29124249 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H43F1017B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H43F1017B">Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J. 2014-12-01 Urban impervious surfaces lead to increases in stormwater runoff. Green infrastructure, like bioretention cells, is being used to mitigate negative impacts of runoff by disconnecting impervious surfaces from storm water systems and redirecting flow to decentralized treatment areas. While bioretention soil characteristics are carefully designed, little research is available on soil moisture dynamics within the cells and how these might relate to inter-storm variability in performance. Bioretentions have been installed along a residential street in Parma, Ohio to determine the impact of green infrastructure on the West Creek watershed, a 36 km2 subwatershed of the Cuyahoga River. Bioretentions were installed in two phases (Phase I in 2013 and Phase II in 2014); design and vegetation density vary slightly between the two phases. Our research focuses on characterizing soil moisture dynamics of multiple bioretentions and assessing their impact on stormwater runoff at the street scale. Soil moisture measurements were collected in transects for eight bioretentions over the course of one summer. Vegetation indices of canopy height, percent vegetative cover, species richness and NDVI were also measured. A flow meter in the storm drain at the end of the street measured storm sewer discharge. Precipitation was recorded from a meteorological station 2 km from the research site. Soil moisture increased in response to precipitation and decreased to relatively stable conditions within 3 days following a rain event. Phase II bioretentions exhibited greater soil moisture and less vegetation than Phase I bioretentions, though the relationship between soil moisture and vegetative cover is inconclusive for bioretentions constructed in the same phase. Data from five storms suggest that pre-event soil moisture does not control the runoff-to-rainfall ratio, which we use as a measure of bioretention performance. However, discharge data indicate that hydrograph characteristics, such as lag </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830020234','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830020234">Soil Moisture Project Evaluation Workshop</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H21O..05Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H21O..05Z">Development of an Objective High Spatial Resolution Soil Moisture Index</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zavodsky, B.; Case, J.; White, K.; Bell, J. R. 2015-12-01 Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JHyd..498...89K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JHyd..498...89K">Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19790008158','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19790008158">Soil Moisture Workshop</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Heilman, J. L. (Editor); Moore, D. G. (Editor); Schmugge, T. J. (Editor); Friedman, D. B. (Editor) 1978-01-01 The Soil Moisture Workshop was held at the United States Department of Agriculture National Agricultural Library in Beltsville, Maryland on January 17-19, 1978. The objectives of the Workshop were to evaluate the state of the art of remote sensing of soil moisture; examine the needs of potential users; and make recommendations concerning the future of soil moisture research and development. To accomplish these objectives, small working groups were organized in advance of the Workshop to prepare position papers. These papers served as the basis for this report. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......268S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......268S">Monsoon dependent ecosystems: Implications of the vertical distribution of soil moisture on land surface-atmosphere interactions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sanchez-Mejia, Zulia M. Uncertainty of predicted change in precipitation frequency and intensity motivates the scientific community to better understand, quantify, and model the possible outcome of dryland ecosystems. In pulse dependent ecosystems (i.e. monsoon driven) soil moisture is tightly linked to atmospheric processes. Here, I analyze three overarching questions; Q1) How does soil moisture presence or absence in a shallow or deep layer influence the surface energy budget and planetary boundary layer characteristics?, Q2) What is the role of vegetation on ecosystem albedo in the presence or absence of deep soil moisture?, Q3) Can we develop empirical relationships between soil moisture and the planetary boundary layer height to help evaluate the role of future precipitation changes in land surface atmosphere interactions? . To address these questions I use a conceptual framework based on the presence or absence of soil moisture in a shallow or deep layer. I define these layers by using root profiles and establish soil moisture thresholds for each layer using four years of observations from the Santa Rita Creosote Ameriflux site. Soil moisture drydown curves were used to establish the shallow layer threshold in the shallow layer, while NEE (Net Ecosystem Exchange of carbon dioxide) was used to define the deep soil moisture threshold. Four cases were generated using these thresholds: Case 1, dry shallow layer and dry deep layer; Case 2, wet shallow layer and dry deep layer; Case 3, wet shallow layer and wet deep layer, and Case 4 dry shallow and wet deep layer. Using this framework, I related data from the Ameriflux site SRC (Santa Rita Creosote) from 2008 to 2012 and from atmospheric soundings from the nearby Tucson Airport; conducted field campaigns during 2011 and 2012 to measure albedo from individual bare and canopy patches that were then evaluated in a grid to estimate the influence of deep moisture on albedo via vegetation cover change; and evaluated the potential of using a </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70182493','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70182493">Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000713','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000713">Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33C1080Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33C1080Z">The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhao, Y.; Estes, L. D.; Vergopolan, N. 2017-12-01 Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8531E..14W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8531E..14W">Soil moisture retrieval by active/passive microwave remote sensing data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wu, Shengli; Yang, Lijuan 2012-09-01 This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active">8</li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active">9</li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H53G1738D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H53G1738D">L-band Soil Moisture Mapping using Small UnManned Aerial Systems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H11D1202Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H11D1202Y">Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H41C0908B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H41C0908B">Generation of a Realistic Soil Moisture Initialization System and its Potential Impact on Short-to-Seasonal Forecasting of Near Surface Variables</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Boisserie, M.; Cocke, S.; O'Brien, J. J. 2009-12-01 Although the amount of water contained in the soil seems insignificant when compared to the total amount of water on a global-scale, soil moisture is widely recognized as a crucial variable for climate studies. It plays a key role in regulating the interaction between the atmosphere and the land-surface by controlling the repartition between the surface latent and sensible heat fluxes. In addition, the persistence of soil moisture anomalies provides one of the most important components of memory for the climate system. Several studies have shown that, during the boreal summer in mid-latitudes, the soil moisture role in controlling the continental precipitation variability may be more important than that of the sea surface temperature (Koster et al. 2000, Hong and Kalnay 2000, Koster et al. 2000, Kumar and Hoerling 1995, Trenberth et al. 1998, Shukla 1998). Although all of the above studies have demonstrated the strong sensitivity of seasonal forecasts to the soil moisture initial conditions, they relied on extreme or idealized soil moisture levels. The question of whether realistic soil moisture initial conditions lead to improved seasonal predictions has not been adequately addressed. Progress in addressing this question has been hampered by the lack of long-term reliable observation-based global soil moisture data sets. Since precipitation strongly affects the soil moisture characteristics at the surface and in depth, an alternative to this issue is to assimilate precipitation. Because precipitation is a diagnostic variable, most of the current reanalyses do not directly assimilate it into their models (M. Bosilovitch, 2008). In this study, an effective technique that directly assimilates the precipitation is used. We examine two experiments. In the first experiment, the model is initialized by directly assimilating a global, 3-hourly, 1.0° precipitation dataset, provided by Sheffield et al. (2006), in a continuous assimilation period of a couple of months. For </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H43O..05B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H43O..05B">Enhancing the USDA Global Crop Assessment Decision Support System Using SMAP Soil Moisture Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bolten, J. D.; Mladenova, I. E.; Crow, W. T.; Reynolds, C. A. 2016-12-01 The Foreign Agricultural Services (FAS) is a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected crop supply and demand estimates. Knowledge of the amount of water in the root zone is an essential source of information for the crop analysts as it governs the crop development and crop growth, which in turn determine the end-of-season yields. USDA FAS currently relies on root zone soil moisture (RZSM) estimates generated using the modified two-layer Palmer Model (PM). PM is a simple water-balance hydrologic model that is driven by daily precipitation observations and minimum and maximum temperature data. These forcing data are based on ground meteorological station measurements from the World Meteorological Organization (WMO), and gridded weather data from the former U.S. Air Force Weather Agency (AFWA), currently called U.S. Air Force 557th Weather Wing. The PM was extended by adding a data assimilation (DA) unit that provides the opportunity to routinely ingest satellite-based soil moisture observations. This allows us to adjust for precipitation-related inaccuracies and enhance the quality of the PM soil moisture estimates. The current operational DA system is based on a 1-D Ensample Kalman Filter approach and relies on observations obtained from the Soil Moisture Ocean Salinity Mission (SMOS). Our talk will demonstrate the value of assimilating two satellite products (i.e. a passive and active) and discuss work that is done in preparation for ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780015703','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780015703">Soil moisture modeling review</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9877E..2BS','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9877E..2BS">Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=335275','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=335275">Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S">Pathways of soil moisture controls on boundary layer dynamics</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Siqueira, M.; Katul, G.; Porporato, A. 2007-12-01 Soil moisture controls on precipitation are now receiving significant attention in climate systems because the memory of their variability is much slower than the memory of the fast atmospheric processes. We propose a new model that integrates soil water dynamics, plant hydraulics and stomatal responses to water availability to estimate root water uptake and available energy partitioning, as well as feedbacks to boundary layer dynamics (in terms of water vapor and heat input to the atmospheric system). Using a simplified homogenization technique, the model solves the intrinsically 3-D soil water movement equations by two 1-D coupled Richards' equations. The first resolves the radial water flow from bulk soil to soil-root interface to estimate root uptake (assuming the vertical gradients in moisture persist during the rapid lateral flow), and then it solves vertical water movement through the soil following the radial moisture adjustments. The coupling between these two equations is obtained by area averaging the soil moisture in the radial domain (i.e. homogenization) to calculate the vertical fluxes. For each vertical layer, the domain is discretized in axi-symmetrical grid with constant soil properties. This is deemed to be appropriate given the fact that the root uptake occurs on much shorter time scales closely following diurnal cycles, while the vertical water movement is more relevant to the inter-storm time scale. We show that this approach was able to explicitly simulate known features of root uptake such as diurnal hysteresis of canopy conductance, water redistribution by roots (hydraulic lift) and downward shift of root uptake during drying cycles. The model is then coupled with an atmospheric boundary layer (ABL) growth model thereby permitting us to explore low-dimensional elements of the interaction between soil moisture and ABL states commensurate with the lifting condensation level. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12212653B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12212653B">Synoptic Conditions and Moisture Sources Actuating Extreme Precipitation in Nepal</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bohlinger, Patrik; Sorteberg, Asgeir; Sodemann, Harald 2017-12-01 Despite the vast literature on heavy-precipitation events in South Asia, synoptic conditions and moisture sources related to extreme precipitation in Nepal have not been addressed systematically. We investigate two types of synoptic conditions—low-pressure systems and midlevel troughs—and moisture sources related to extreme precipitation events. To account for the high spatial variability in rainfall, we cluster station-based daily precipitation measurements resulting in three well-separated geographic regions: west, central, and east Nepal. For each region, composite analysis of extreme events shows that atmospheric circulation is directed against the Himalayas during an extreme event. The direction of the flow is regulated by midtropospheric troughs and low-pressure systems traveling toward the respective region. Extreme precipitation events feature anomalous high abundance of total column moisture. Quantitative Lagrangian moisture source diagnostic reveals that the largest direct contribution stems from land (approximately 75%), where, in particular, over the Indo-Gangetic Plain moisture uptake was increased. Precipitation events occurring in this region before the extreme event likely provided additional moisture. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015BGD....12.1453Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015BGD....12.1453Z">Soil moisture influenced the interannual variation in temperature sensitivity of soil organic carbon mineralization in the Loess Plateau</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, Y.; Guo, S.; Zhao, M.; Du, L.; Li, R.; Jiang, J.; Wang, R.; Li, N. 2015-01-01 Temperature sensitivity of SOC mineralization (Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration, thus understanding the factors influencing the interannual variation in Q10 is important to accurately estimate the local soil carbon cycle. In situ SOC mineralization was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35° 12' N, 107° 40' E) in Changwu, Shaanxi, China form 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 y-1 (mean =253 g C m-2 y-1; CV =13%), annual Q10 ranged from 1.48 to 1.94 (mean =1.70; CV =10%), and annual soil moisture content ranged from 38.6 to 50.7% WFPS (mean =43.8% WFPS; CV =11%), which were mainly affected by the frequency and distribution of precipitation. Annual Q10 showed a negative quadratic correlation with soil moisture. In conclusion, understanding of the relationships between interannual variation in Q10 of SOC mineralization, soil moisture and precipitation is important to accurately estimate the local carbon cycle, especially under the changing climate. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014WRR....50.4038S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014WRR....50.4038S">Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170007429&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170007429&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil">Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012456','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012456">Assimilation of SMOS Retrieved Soil Moisture into the Land Information System</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T. 2014-01-01 Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=319551','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=319551">Improving root-zone soil moisture estimations using dynamic root growth and crop phenology</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Water Energy Balance (WEB) Soil Vegetation Atmosphere Transfer (SVAT) modelling can be used to estimate soil moisture by forcing the model with observed data such as precipitation and solar radiation. Recently, an innovative approach that assimilates remotely sensed thermal infrared (TIR) observatio... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33J0315K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33J0315K">Sensitivity of soil moisture initialization for decadal predictions under different regional climatic conditions in Europe</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C. 2015-12-01 The impact of soil initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to soil moisture initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different soil initialization procedures are investigated. The sensitivity of the decadal predictions to soil moisture initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of soil moisture on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) Soil moisture initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial soil conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that soil needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also soil reacts more sensitive when initialised during dry periods. (e) The initial soil perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution affecting atmospheric stability </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=280017','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=280017">Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.6410P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.6410P">Soil Moisture as an Estimator for Crop Yield in Germany</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan 2015-04-01 Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdWR..112..203S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdWR..112..203S">Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao 2018-02-01 Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/23635','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/23635">Deforestation effects on soil moisture, streamflow, and water balance in the central Appalachians</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> James H. Patric; James H. Patric 1973-01-01 Soil moisture, precipitation, and streamflow were measured on three watersheds in West Virginia, two deforested and one forested. Water content of barren soil always exceeded that of forest soil throughout the growing season and especially in dry weather. Streamflow increased 10 inches annually on the watersheds that were cleared, most of the increase occurring between... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1332724','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1332724">Soil Temperature and Moisture Profile (STAMP) System Handbook</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Cook, David R. The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are alsomore » useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.« less </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active">9</li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70162540','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70162540">Soil moisture and biogeochemical factors influence the distribution of annual Bromus species</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Belnap, Jayne; Stark, John Thomas; Rau, Benjamin; Allen, Edith B.; Phillips, Sue 2016-01-01 Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromusoccurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan), little or noBromus is found, likely due to timing or amount of soil moisture relative to Bromus phenology. In hot, winter-rainfall-dominated deserts (parts of the Mojave Desert), Bromus rubens is widespread and correlated with high phosphorus availability. It also responds positively to additions of nitrogen alone or with phosphorus. On the Colorado Plateau, with higher soil moisture availability, factors limiting Bromus tectorum populations vary with life stage: phosphorus and water limit germination, potassium and the potassium/magnesium ratio affect winter performance, and water and potassium/magnesium affect spring performance. Controlling nutrients also change with elevation. In cooler deserts with winter precipitation (Great Basin, Columbia Plateau) and thus even greater soil moisture availability, B. tectorum populations are controlled by nitrogen, phosphorus, or potassium. Experimental nitrogen additions stimulate Bromus performance. The reason for different nutrients limiting in dissimilar climatic regions is not known, but it is likely that site conditions such as soil texture (as it affects water and nutrient availability), organic matter, and/or chemistry interact in a manner that regulates nutrient availability and limitations. Under future drier, hotter conditions,Bromus distribution is likely to change due to changes in the interaction between moisture and nutrient availability. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22126031','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22126031">[Soil moisture dynamics and water balance of Salix psammophila shrubs in south edge of Mu Us Sandy Land].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> An, Hui; An, Yu 2011-09-01 Taking the artificial sand-fixing Salix psammophila shrubs with different plant density (0.2, 0.6, and 0.8 plants x m(-2)) in Mu Us Sandy Land as test objects, this paper studied the soil moisture dynamics and evapotranspiration during growth season. There existed obvious differences in the soil moisture dynamics and evapotranspiration among the shrubs. The soil moisture content changed in single-hump-shape with the increase of plant density, and in "S" shape during growth season, being closely correlated with precipitation. The evapotranspiration was the highest (114.5 mm) in the shrubs with a density 0.8 plants x m(-1), accounting for 90.8% of the total precipitation during growth season, and the lowest (109.7 mm) in the shrubs with a density 0.6 plants x m(-2) Based on the soil moisture dynamics and water balance characteristics, the appropriate planting density of S. psammophila shrubs in Mu Us Sandy Land could be 0.6 plants x m(-2). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760003525','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760003525">Soil moisture: Some fundamentals. [agriculture - soil mechanics</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=263649','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=263649">An intercomparison of available soil moisture estimates from thermal-infrared and passive microwave remote sensing and land-surface modeling</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Remotely-sensed soil moisture studies have mainly focused on retrievals using active and passive microwave (MW) sensors whose measurements provided a direct relationship to soil moisture (SM). MW sensors present obvious advantages such as the ability to retrieve through non-precipitating cloud cover... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918932P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918932P">SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H42A..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H42A..04Z">Spatial variation and driving factors of soil moisture at multi-scales: a case study in Loess Plateau of China</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhao, W.; Zhang, X.; Liu, Y.; Fang, X. 2017-12-01 Currently, the ecological restoration of the Loess Plateau has led to significant achievements such as increases in vegetation coverage, decreases in soil erosion, and enhancement of ecosystem services. Soil moisture shortages, however, commonly occur as a result of limited rainfall and strong evaporation in this semiarid region of China. Since soil moisture is critical in regulating plant growth in these semiarid regions, it is crucial to identify the spatial variation and factors affecting soil moisture at multi-scales in the Loess Plateau of China. In the last several years, extensive studies on soil moisture have been carried out by our research group at the plot, small watershed, watershed, and regional scale in the Loess Plateau, providing some information for vegetation restoration in the region. The main research results are as follows: (1) the highest soil moisture content was in the 0-0.1 m layer with a large coefficient of variation; (2) in the 0-0.1m layer, soil moisture content was negatively correlated with relative elevation, slope and vegetation cover, the correlations among slope, aspect and soil moisture increased with depth increased; (3) as for the deep soil moisture content, the higher spatial variation of deep SMC occurred at 1.2-1.4 m and 4.8-5.0m; (4) the deep soil moisture content in native grassland and farmland were significant higher than that of introduced vegetation; (5) at regional scale, the soil water content under different precipitation zones increased following the increase of precipitation, while, the influencing factors of deep SMC at watershed scale varied with land management types; (6) in the areas with multi-year precipitation of 370 - 440mm, natural grass is more suitable for restoration, and this should be treated as the key areas in vegetation restoration; (7) appropriate planting density and species selection should be taken into account for introduced vegetation management; (8) it is imperative to take the local </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013309','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013309">SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann 2011-01-01 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23359920','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23359920">[Relationships between soil moisture and needle-fall in Masson pine forests in acid rain region of Chongqing, Southwest China].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H33B1647B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H33B1647B">Land surface-precipitation feedback and ramifications on storm dynamics.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140007327','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140007327">Assimilation of SMOS Soil Moisture Retrievals in the Land Information System</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad 2014-01-01 Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050181940&hterms=soil+layers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil%2Blayers','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050181940&hterms=soil+layers&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil%2Blayers">Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29722217','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29722217">[Characteristics of soil moisture variation in different land use types in the hilly region of the Loess Plateau, China].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=264667','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=264667">The international soil moisture network: A data hosting facility for global in situ soil moisture measurements</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27668850','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27668850">Soil moisture and its role in growth-climate relationships across an aridity gradient in semiarid Pinus halepensis forests.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Manrique-Alba, Àngela; Ruiz-Yanetti, Samantha; Moutahir, Hassane; Novak, Klemen; De Luis, Martin; Bellot, Juan 2017-01-01 In Mediterranean areas with limited availability of water, an accurate knowledge of growth response to hydrological variables could contribute to improving management and stability of forest resources. The main goal of this study is to assess the temporal dynamic of soil moisture to better understand the water-growth relationship of Pinus halepensis forests in semiarid areas. The estimates of modelled soil moisture and measured tree growth were used at four sites dominated by afforested Pinus halepensis Mill. in south-eastern Spain with 300 to 609mm mean annual precipitation. Firstly, dendrochronological samples were extracted and the widths of annual tree rings were measured to compute basal area increments (BAI). Secondly, soil moisture was estimated over 20 hydrological years (1992-2012) by means of the HYDROBAL ecohydrological model. Finally, the tree growth was linked, to mean monthly and seasonal temperature, precipitation and soil moisture. Results depict the effect of soil moisture on growth (BAI) and explain 69-73% of the variance in semiarid forests, but only 51% in the subhumid forests. This highlights the fact that that soil moisture is a suitable and promising variable to explain growth variations of afforested Pinus halepensis in semiarid conditions and useful for guiding adaptation plans to respond pro-actively to water-related global challenges. Copyright © 2016 Elsevier B.V. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70162445','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70162445">Soil moisture response to experimentally altered snowmelt timing is mediated by soil, vegetation, and regional climate patterns</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Conner, Lafe G; Gill, Richard A.; Belnap, Jayne 2016-01-01 Soil moisture in seasonally snow-covered environments fluctuates seasonally between wet and dry states. Climate warming is advancing the onset of spring snowmelt and may lengthen the summer-dry state and ultimately cause drier soil conditions. The magnitude of either response may vary across elevation and vegetation types. We situated our study at the lower boundary of persistent snow cover and the upper boundary of subalpine forest with paired treatment blocks in aspen forest and open meadow. In treatments plots, we advanced snowmelt timing by an average of 14 days by adding dust to the snow surface during spring melt. We specifically wanted to know whether early snowmelt would increase the duration of the summer-dry period and cause soils to be drier in the early-snowmelt treatments compared with control plots. We found no difference in the onset of the summer-dry state and no significant differences in soil moisture between treatments. To better understand the reasons soil moisture did not respond to early snowmelt as expected, we examined the mediating influences of soil organic matter, texture, temperature, and the presence or absence of forest. In our study, late-spring precipitation may have moderated the effects of early snowmelt on soil moisture. We conclude that landscape characteristics, including soil, vegetation, and regional weather patterns, may supersede the effects of snowmelt timing in determining growing season soil moisture, and efforts to anticipate the impacts of climate change on seasonally snow-covered ecosystems should take into account these mediating factors. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.132..587C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.132..587C">Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chen, Hui; Wu, Wei; Liu, Hong-Bin 2018-04-01 Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1414537-shifts-pore-connectivity-from-precipitation-versus-groundwater-rewetting-increases-soil-carbon-loss-after-drought','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1414537-shifts-pore-connectivity-from-precipitation-versus-groundwater-rewetting-increases-soil-carbon-loss-after-drought">Shifts in pore connectivity from precipitation versus groundwater rewetting increases soil carbon loss after drought</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Smith, A. Peyton; Bond-Lamberty, Ben; Benscoter, Brian W. Droughts and other extreme precipitation events are predicted to increase in intensity, duration and extent, with uncertain implications for terrestrial carbon (C) sequestration. Soil wetting from above (precipitation) results in a characteristically different pattern of pore-filling than wetting from below (groundwater), with larger, well-connected pores filling before finer pore spaces, unlike groundwater rise in which capillary forces saturate the finest pores first. Here we demonstrate that pore-scale wetting patterns interact with antecedent soil moisture conditions to alter pore-, core- and field-scale C dynamics. Drought legacy and wetting direction are perhaps more important determinants of short-term C mineralization than current soilmore » moisture content in these soils. Our results highlight that microbial access to C is not solely limited by physical protection, but also by drought or wetting-induced shifts in hydrologic connectivity. We argue that models should treat soil moisture within a three-dimensional framework emphasizing hydrologic conduits for C and resource diffusion.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53D0921Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53D0921Z">Dynamics and characteristics of soil temperature and moisture of active layer in central Tibetan Plateau</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27859221','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27859221">Soil moisture mediates alpine life form and community productivity responses to warming.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Winkler, Daniel E; Chapin, Kenneth J; Kueppers, Lara M 2016-06-01 Climate change is expected to alter primary production and community composition in alpine ecosystems, but the direction and magnitude of change is debated. Warmer, wetter growing seasons may increase productivity; however, in the absence of additional precipitation, increased temperatures may decrease soil moisture, thereby diminishing any positive effect of warming. Since plant species show individual responses to environmental change, responses may depend on community composition and vary across life form or functional groups. We warmed an alpine plant community at Niwot Ridge, Colorado continuously for four years to test whether warming increases or decreases productivity of life form groups and the whole community. We provided supplemental water to a subset of plots to alleviate the drying effect of warming. We measured annual above-ground productivity and soil temperature and moisture, from which we calculated soil degree days and adequate soil moisture days. Using an information-theoretic approach, we observed that positive productivity responses to warming at the community level occur only when warming is combined with supplemental watering; otherwise we observed decreased productivity. Watering also increased community productivity in the absence of warming. Forbs accounted for the majority of the productivity at the site and drove the contingent community response to warming, while cushions drove the generally positive response to watering and graminoids muted the community response. Warming advanced snowmelt and increased soil degree days, while watering increased adequate soil moisture days. Heated and watered plots had more adequate soil moisture days than heated plots. Overall, measured changes in soil temperature and moisture in response to treatments were consistent with expected productivity responses. We found that available soil moisture largely determines the responses of this forb-dominated alpine community to simulated climate warming. © 2016 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015BGeo...12.3655Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015BGeo...12.3655Z">Soil moisture influence on the interannual variation in temperature sensitivity of soil organic carbon mineralization in the Loess Plateau</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, Y. J.; Guo, S. L.; Zhao, M.; Du, L. L.; Li, R. J.; Jiang, J. S.; Wang, R.; Li, N. N. 2015-06-01 Temperature sensitivity of soil organic carbon (SOC) mineralization (i.e., Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration; thus, understanding the factors influencing the interannual variation in Q10 is important for accurately estimating local soil carbon cycle. In situ SOC mineralization rate was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35°12' N, 107°40' E) in Changwu, Shaanxi, China from 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 yr-1, with a mean of 253 g C m-2 yr-1 and a coefficient of variation (CV) of 13%, annual Q10 ranged from 1.48 to 1.94, with a mean of 1.70 and a CV of 10%, and annual soil moisture content ranged from 38.6 to 50.7% soil water-filled pore space (WFPS), with a mean of 43.8% WFPS and a CV of 11%, which were mainly affected by the frequency and distribution of precipitation. Annual Q10 showed a quadratic correlation with annual mean soil moisture content. In conclusion, understanding of the relationships between interannual variation in Q10, soil moisture, and precipitation are important to accurately estimate the local carbon cycle, especially under the changing climate. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.4152W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.4152W">Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use">Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1415421-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use">Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1457599-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1457599-manipulative-experiments-demonstrate-how-long-term-soil-moisture-changes-alter-controls-plant-water-use">Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=338228','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=338228">Responses of switchgrass soil respiration and its components to precipitation gradient in a mescocosm study</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> The objectives of this study were to investigate the effects of the precipitation changes on soil, microbial and root respirations of switchgrass soils, and the relationships between soil respiration and plant growth, soil moisture and temperature. A mesocosm experiment was conducted with five prec... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018WRR....54.1353G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018WRR....54.1353G">Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JHyd..357..405G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JHyd..357..405G">Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70000240','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70000240">Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..561..833S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..561..833S">The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015E%26ES...25a2014B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015E%26ES...25a2014B">Soil moisture monitoring for crop management</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51R..01Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51R..01Z">A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B51G1896B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B51G1896B">Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W. 2017-12-01 Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1816685P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1816685P">Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peichl, Michael; Thober, Stephan; Schwarze, Reimund; Meyer, Volker; Samaniego, Luis 2016-04-01 Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27241203','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27241203">Soil moisture controls on phenology and productivity in a semi-arid critical zone.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Cleverly, James; Eamus, Derek; Restrepo Coupe, Natalia; Chen, Chao; Maes, Wouter; Li, Longhui; Faux, Ralph; Santini, Nadia S; Rumman, Rizwana; Yu, Qiang; Huete, Alfredo 2016-10-15 The Earth's Critical Zone, where physical, chemical and biological systems interact, extends from the top of the canopy to the underlying bedrock. In this study, we investigated soil moisture controls on phenology and productivity of an Acacia woodland in semi-arid central Australia. Situated on an extensive sand plain with negligible runoff and drainage, the carry-over of soil moisture content (θ) in the rhizosphere enabled the delay of phenology and productivity across seasons, until conditions were favourable for transpiration of that water to prevent overheating in the canopy. Storage of soil moisture near the surface (in the top few metres) was promoted by a siliceous hardpan. Pulsed recharge of θ above the hardpan was rapid and depended upon precipitation amount: 150mm storm(-1) resulted in saturation of θ above the hardpan (i.e., formation of a temporary, discontinuous perched aquifer above the hardpan in unconsolidated soil) and immediate carbon uptake by the vegetation. During dry and inter-storm periods, we inferred the presence of hydraulic lift from soil storage above the hardpan to the surface due to (i) regular daily drawdown of θ in the reservoir that accumulates above the hardpan in the absence of drainage and evapotranspiration; (ii) the dimorphic root distribution wherein most roots were found in dry soil near the surface, but with significant root just above the hardpan; and (iii) synchronisation of phenology amongst trees and grasses in the dry season. We propose that hydraulic redistribution provides a small amount of moisture that maintains functioning of the shallow roots during long periods when the surface soil layer was dry, thereby enabling Mulga to maintain physiological activity without diminishing phenological and physiological responses to precipitation when conditions were favourable to promote canopy cooling. Copyright © 2016 Elsevier B.V. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1087025-soil-microbial-community-response-precipitation-change-semi-arid-ecosystem','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1087025-soil-microbial-community-response-precipitation-change-semi-arid-ecosystem">Soil microbial community response to precipitation change in a semi-arid ecosystem</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Cregger, Melissa; Schadt, Christopher Warren; McDowell, Nathan 2012-01-01 Microbial communities regulate many belowground carbon cycling processes; thus, the impact of climate change on the struc- ture and function of soil microbial communities could, in turn, impact the release or storage of carbon in soils. Here we used a large-scale precipitation manipulation ( 18%, 50%, or ambient) in a pi on-juniper woodland (Pinus edulis-Juniperus mono- sperma) to investigate how changes in precipitation amounts altered soil microbial communities as well as what role seasonal variation in rainfall and plant composition played in the microbial community response. Seasonal variability in precipitation had a larger role in determining the composition of soilmore » microbial communities in 2008 than the direct effect of the experimental precipitation treatments. Bacterial and fungal communities in the dry, relatively moisture-limited premonsoon season were compositionally distinct from communities in the monsoon season, when soil moisture levels and periodicity varied more widely across treatments. Fungal abundance in the drought plots during the dry premonsoon season was particularly low and was 4.7 times greater upon soil wet-up in the monsoon season, suggesting that soil fungi were water limited in the driest plots, which may result in a decrease in fungal degradation of carbon substrates. Additionally, we found that both bacterial and fungal communities beneath pi on pine and juniper were distinct, suggesting that microbial functions beneath these trees are different. We conclude that predicting the response of microbial communities to climate change is highly dependent on seasonal dynam- ics, background climatic variability, and the composition of the associated aboveground community.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9784H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9784H">Impact of realistic soil moisture initialization on the representation of extreme events in the western Mediterranean</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Helgert, Sebastian; Khodayar, Samiro 2017-04-01 In a warmer Mediterranean climate an increase in the intensity and frequency of extreme events like floods, droughts and extreme heat is expected. The ability to predict such events is still a great challenge and exhibits many uncertainties in the weather forecast and climate predictions. Thereby the missing knowledge about soil moisture-atmosphere interactions and their representation in models is identified as one of the main sources of uncertainty. In this context the soil moisture(SM) plays an important role in the partitioning of sensible and latent heat fluxes on the surface and consequently influences the boundary-layer stability and the precipitation formation. The aim of this research work is to assess the influence of soil moisture-atmosphere interactions on the initiation and development of extreme events in the western Mediterranean (WMED). In this respect the impact of realistic SM initialization on the model representation of extreme events is investigated. High-resolution simulations of different regions in the WMED, including various climate zones from moderate to arid climate, are conducted with the atmospheric COSMO (Consortium for Small-scale Modeling) model in the numerical weather prediction and climate mode. A multiscale temporal and spatial approach is used (days to years, 7km to 2.8km grid spacing). Observational data provided by the framework of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) as well as satellite data such as precipitation from CMORPH (CPC MORPHing technique), evapotranspiration from Land Surface Analysis Satellite Applications Facility (LSA-SAF) and atmospheric moisture from MODIS (Moderate Resolution Imaging Spectroradiometer) are used for process understanding and model validation. To select extreme dry and wet periods the Effective Drought Index (EDI) is calculated. In these periods sensitivity studies of extreme SM initialization scenarios are performed to prove a possible impact of soil moisture on </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B51G1895B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B51G1895B">Landscape-scale soil moisture heterogeneity and its influence on surface fluxes at the Jornada LTER site: Evaluating a new model parameterization for subgrid-scale soil moisture variability</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S. 2017-12-01 Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=332939','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=332939">A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H31C1516D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H31C1516D">Stochastic Analysis and Probabilistic Downscaling of Soil Moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/35309','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/35309">Soil-moisture constants and their variation</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> 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... </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MeScT..28b4002E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MeScT..28b4002E">On-irrigator pasture soil moisture sensor</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.6882D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.6882D">Congo Basin precipitation: Assessing seasonality, regional interactions, and sources of moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dyer, Ellen L. E.; Jones, Dylan B. A.; Nusbaumer, Jesse; Li, Harry; Collins, Owen; Vettoretti, Guido; Noone, David 2017-07-01 Precipitation in the Congo Basin was examined using a version of the National Center for Atmospheric Research Community Earth System Model (CESM) with water tagging capability. Using regionally defined water tracers, or tags, the moisture contribution from different source regions to Congo Basin precipitation was investigated. We found that the Indian Ocean and evaporation from the Congo Basin were the dominant moisture sources and that the Atlantic Ocean was a comparatively small source of moisture. In both rainy seasons the southwestern Indian Ocean contributed about 21% of the moisture, while the recycling ratio for moisture from the Congo Basin was about 25%. Near the surface, a great deal of moisture is transported from the Atlantic into the Congo Basin, but much of this moisture is recirculated back over the Atlantic in the lower troposphere. Although the southwestern Indian Ocean is a major source of Indian Ocean moisture, it is not associated with the bulk of the variability in precipitation over the Congo Basin. In wet years, more of the precipitation in the Congo Basin is derived from Indian Ocean moisture, but the spatial distribution of the dominant sources is shifted, reflecting changes in the midtropospheric circulation over the Indian Ocean. During wet years there is increased transport of moisture from the equatorial and eastern Indian Ocean. Our results suggest that reliably capturing the linkages between the large-scale circulation patterns over the Indian Ocean and the local circulation over the Congo Basin is critical for future projections of Congo Basin precipitation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100031193&hterms=soil&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%26Nf%3DPublication-Date%257CBTWN%2B20050101%2B20180612','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100031193&hterms=soil&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%26Nf%3DPublication-Date%257CBTWN%2B20050101%2B20180612">Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco 2010-01-01 Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.7286D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.7286D">The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne 2015-04-01 Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=288987','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=288987">The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..546..393B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..546..393B">Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=337720','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=337720">Soil Moisture Sensing</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Soil moisture monitoring can be useful as an irrigation management tool for both landscapes and agriculture, sometimes replacing an evapotranspiration (ET) based approach or as a useful check on ET based approaches since the latter tend to drift off target over time. All moisture sensors, also known... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150014256','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150014256">Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AdWR..109..343C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AdWR..109..343C">Space-time modeling of soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.2007Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.2007Y">Impact of elevated precipitation, nitrogen deposition and warming on soil respiration in a temperate desert</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yue, Ping; Cui, Xiaoqing; Gong, Yanming; Li, Kaihui; Goulding, Keith; Liu, Xuejun 2018-04-01 Soil respiration (Rs) is the most important source of carbon dioxide emissions from soil to atmosphere. However, it is unclear what the interactive response of Rs would be to environmental changes such as elevated precipitation, nitrogen (N) deposition and warming, especially in unique temperate desert ecosystems. To investigate this an in situ field experiment was conducted in the Gurbantunggut Desert, northwest China, from September 2014 to October 2016. The results showed that precipitation and N deposition significantly increased Rs, but warming decreased Rs, except in extreme precipitation events, which was mainly through its impact on the variation of soil moisture at 5 cm depth. In addition, the interactive response of Rs to combinations of the factors was much less than that of any single-factor, and the main response was a positive effect, except for the response from the interaction of increased precipitation and high N deposition (60 kg N ha-1 yr-1). Although Rs was found to show a unimodal change pattern with the variation of soil moisture, soil temperature and soil NH4+-N content, and it was significantly positively correlated to soil dissolved organic carbon (DOC) and pH, a structural equation model found that soil temperature was the most important controlling factor. Those results indicated that Rs was mainly interactively controlled by the soil multi-environmental factors and soil nutrients, and was very sensitive to elevated precipitation, N deposition and warming. However, the interactions of multiple factors largely reduced between-year variation of Rs more than any single-factor, suggesting that the carbon cycle in temperate deserts could be profoundly influenced by positive carbon-climate feedback. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013591','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013591">Assimilation of Passive and Active Microwave Soil Moisture Retrievals</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820017732','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820017732">Plan of research for integrated soil moisture studies. Recommendations of the Soil Moisture Working Group</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913930C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913930C">Using satellite image data to estimate soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1411730B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1411730B">An experimental operative system for shallow landslide and flash flood warning based on rainfall thresholds and soil moisture modelling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brigandı, G.; Aronica, G. T.; Basile, G.; Pasotti, L.; Panebianco, M. 2012-04-01 On November 2011 a thunderstorms became almost exceptional over the North-East part of the Sicily Region (Italy) producing local heavy rainfall, mud-debris flow and flash flooding. The storm was concentrated on the Tyrrhenian sea coast near the city of Barcellona within the Longano catchment. Main focus of the paper is to present an experimental operative system for alerting extreme hydrometeorological events by using a methodology based on the combined use of rainfall thresholds, soil moisture indexes and quantitative precipitation forecasting. As matter of fact, shallow landslide and flash flood warning is a key element to improve the Civil Protection achievements to mitigate damages and safeguard the security of people. It is a rather complicated task, particularly in those catchments with flashy response where even brief anticipations are important and welcomed. It is well known how the triggering of shallow landslides is strongly influenced by the initial soil moisture conditions of catchments. Therefore, the early warning system here applied is based on the combined use of rainfall thresholds, derived both for flash flood and for landslide, and soil moisture conditions; the system is composed of several basic component related to antecedent soil moisture conditions, real-time rainfall monitoring and antecedent rainfall. Soil moisture conditions were estimated using an Antecedent Precipitation Index (API), similar to this widely used for defining soil moisture conditions via Antecedent Moisture conditions index AMC. Rainfall threshold for landslides were derived using historical and statistical analysis. Finally, rainfall thresholds for flash flooding were derived using an Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall. After the implementation and calibration of the model, a testing phase was carried out by using real data collected for the November 2001 event in the Longano catchment. Moreover, in </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.8017E..10H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.8017E..10H">High-resolution soil moisture mapping in Afghanistan</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H51J..08W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H51J..08W">Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18320428','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18320428">Deuterium excess in precipitation of Alpine regions - moisture recycling.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Froehlich, Klaus; Kralik, Martin; Papesch, Wolfgang; Rank, Dieter; Scheifinger, Helfried; Stichler, Willibald 2008-03-01 The paper evaluates long-term seasonal variations of the deuterium excess (d-excess = delta(2)H - 8. delta(18)O) in precipitation of stations located north and south of the main ridge of the Austrian Alps. It demonstrates that sub-cloud evaporation during precipitation and continental moisture recycling are local, respectively, regional processes controlling these variations. In general, sub-cloud evaporation decreases and moisture recycling increases the d-excess. Therefore, evaluation of d-excess variations in terms of moisture recycling, the main aim of this paper, includes determination of the effect of sub-cloud evaporation. Since sub-cloud evaporation is governed by saturation deficit and distance between cloud base and the ground, its effect on the d-excess is expected to be lower at mountain than at lowland/valley stations. To determine quantitatively this difference, we examined long-term seasonal d-excess variations measured at three selected mountain and adjoining valley stations. The altitude differences between mountain and valley stations ranged from 470 to 1665 m. Adapting the 'falling water drop' model by Stewart [J. Geophys. Res., 80(9), 1133-1146 (1975).], we estimated that the long-term average of sub-cloud evaporation at the selected mountain stations (altitudes between about 1600 and 2250 m.a.s.l.) is less than 1 % of the precipitation and causes a decrease of the d-excess of less than 2 per thousand. For the selected valley stations, the corresponding evaporated fraction is at maximum 7 % and the difference in d-excess ranges up to 8 per thousand. The estimated d-excess differences have been used to correct the measured long-term d-excess values at the selected stations. Finally, the corresponding fraction of water vapour has been estimated that recycled by evaporation of surface water including soil water from the ground. For the two mountain stations Patscherkofel and Feuerkogel, which are located north of the main ridge of the Alps, the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H33F0895R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H33F0895R">Evapotranspiration Controls Imposed by Soil Moisture: A Spatial Analysis across the United States</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rigden, A. J.; Tuttle, S. E.; Salvucci, G. 2014-12-01 We spatially analyze the control over evapotranspiration (ET) imposed by soil moisture across the United States using daily estimates of satellite-derived soil moisture and data-driven ET over a nine-year period (June 2002-June 2011) at 305 locations. The soil moisture data are developed using 0.25-degree resolution satellite observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), where the 9-year time series for each 0.25-degree pixel was selected from three potential algorithms (VUA-NASA, U. Montana, & NASA) based on the maximum mutual information between soil moisture and precipitation (Tuttle & Salvucci (2014), Remote Sens Environ, 114: 207-222). The ET data are developed independent of soil moisture using an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased ET rates, suggesting that land-atmosphere feedback processes minimize this variance (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from meteorological data measured at 305 common weather stations that are approximately uniformly distributed across the United States. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture. We fit evaporation efficiency curves across the United States at each of the 305 sites during the summertime (May-June-July-August-September). Spatial patterns are visualized by mapping optimal curve fitting coefficients across the Unites States. An analysis of efficiency curves and their spatial patterns will be presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=284733','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=284733">Patterns of soil community structure differ by scale and ecosystem type along a large-scale precipitation gradient</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Climate models predict increased variability in precipitation regimes, which will likely increase frequency/duration of drought. Reductions in soil moisture affect physical and chemical characteristics of the soil habitat and can influence soil organisms such as mites and nematodes. These organisms ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=345204','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=345204">Irrigation scheduling using soil moisture sensors</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1614086W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1614086W">Statistical analysis of simulated global soil moisture and its memory in an ensemble of CMIP5 general circulation models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313267','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313267">Soil-moisture sensors and irrigation management</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950048080&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSoil%2Buse','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950048080&hterms=Soil+use&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSoil%2Buse">Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=272036','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=272036">The moisture response of soil heterotrophic respiration: Interaction with soil properties.</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/958854-soil-moisture-surpasses-elevated-co2-temperature-control-soil-carbon-dynamics-multi-factor-climate-change-experiment','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/958854-soil-moisture-surpasses-elevated-co2-temperature-control-soil-carbon-dynamics-multi-factor-climate-change-experiment">Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Garten Jr, Charles T; Classen, Aimee T; Norby, Richard J 2009-01-01 Some single-factor experiments suggest that elevated CO2 concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO2 x temperature x soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO2 had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO2, indicated between 14 and 19% new soil carbon under two different watering treatmentsmore » with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr-1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO2 efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO2 and temperature as a control on soil carbon dynamics.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H23N..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H23N..04B">Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L. 2016-12-01 The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810058817&hterms=gravimetric+methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dgravimetric%2Bmethods','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810058817&hterms=gravimetric+methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dgravimetric%2Bmethods">Survey of in-situ and remote sensing methods for soil moisture determination</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmugge, T. J.; Jackson, T. J.; Mckim, H. L. 1981-01-01 General methods for determining the moisture content in the surface layers of the soil based on in situ or point measurements, soil water models and remote sensing observations are surveyed. In situ methods described include gravimetric techniques, nuclear techniques based on neutron scattering or gamma-ray attenuation, electromagnetic techniques, tensiometric techniques and hygrometric techniques. Soil water models based on column mass balance treat soil moisture contents as a result of meteorological inputs (precipitation, runoff, subsurface flow) and demands (evaporation, transpiration, percolation). The remote sensing approaches are based on measurements of the diurnal range of surface temperature and the crop canopy temperature in the thermal infrared, measurements of the radar backscattering coefficient in the microwave region, and measurements of microwave emission or brightness temperature. Advantages and disadvantages of the various methods are pointed out, and it is concluded that a successful monitoring system must incorporate all of the approaches considered. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28559315','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28559315">Historical climate controls soil respiration responses to current soil moisture.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5474806','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5474806">Historical climate controls soil respiration responses to current soil moisture</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JARS...11d5003W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JARS...11d5003W">Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000004216&hterms=Soil+sampling+radiation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSoil%2Bsampling%2Bradiation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000004216&hterms=Soil+sampling+radiation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DSoil%2Bsampling%2Bradiation">Passive Microwave Remote Sensing of Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810020956','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810020956">Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1596S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1596S">New Physical Algorithms for Downscaling SMAP Soil Moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/wsp/1619u/report.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/wsp/1619u/report.pdf">Methods of measuring soil moisture in the field</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050192452','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050192452">Estimating Surface Soil Moisture in Simulated AVIRIS Spectra</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020050922&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020050922&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson">Soil Moisture and Snow Cover: Active or Passive Elements of Climate?</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor) 2002-01-01 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. 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 reflectively of snow is the most important process by which snow cover cart impact climate, through lower </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNH13B..07D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNH13B..07D">L-band Soil Moisture Mapping using Small UnManned Aerial Systems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H23G..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H23G..02S">Verification of High Resolution Soil Moisture and Latent Heat in Germany</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V. 2012-12-01 Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.132....1L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.132....1L">Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70000194','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70000194">Soil texture drives responses of soil respiration to precipitation pulses in the sonoran desert: Implications for climate change</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Cable, J.M.; Ogle, K.; Williams, D.G.; Weltzin, J.F.; Huxman, T. E. 2008-01-01 Climate change predictions for the desert southwestern U.S. are for shifts in precipitation patterns. The impacts of climate change may be significant, because desert soil processes are strongly controlled by precipitation inputs ('pulses') via their effect on soil water availability. This study examined the response of soil respiration-an important biological process that affects soil carbon (C) storage-to variation in pulses representative of climate change scenarios for the Sonoran Desert. Because deserts are mosaics of different plant cover types and soil textures-which create patchiness in soil respiration-we examined how these landscape characteristics interact to affect the response of soil respiration to pulses. Pulses were applied to experimental plots of bare and vegetated soil on contrasting soil textures typical of Sonoran Desert grasslands. The data were analyzed within a Bayesian framework to: (1) determine pulse size and antecedent moisture (soil moisture prior to the pulse) effects on soil respiration, (2) quantify soil texture (coarse vs. fine) and cover type (bare vs. vegetated) effects on the response of soil respiration and its components (plant vs. microbial) to pulses, and (3) explore the relationship between long-term variation in pulse regimes and seasonal soil respiration. Regarding objective (1), larger pulses resulted in higher respiration rates, particularly from vegetated fine-textured soil, and dry antecedent conditions amplified respiration responses to pulses (wet antecedent conditions dampened the pulse response). Regarding (2), autotrophic (plant) activity was a significant source (???60%) of respiration and was more sensitive to pulses on coarse- versus fine-textured soils. The sensitivity of heterotrophic (microbial) respiration to pulses was highly dependent on antecedent soil water. Regarding (3), seasonal soil respiration was predicted to increase with both growing season precipitation and mean pulse size (but only for pulses </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA17798.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA17798.html">SMAP Radiometer Captures Views of Global Soil Moisture</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.1903M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.1903M">GLEAM v3: satellite-based land evaporation and root-zone soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Martens, Brecht; Miralles, Diego G.; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard A. M.; Fernández-Prieto, Diego; Beck, Hylke E.; Dorigo, Wouter A.; Verhoest, Niko E. C. 2017-05-01 The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090042731','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090042731">Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Reichle, Rolf; Mahanama, Sarith; Koster, Randal; Lettenmaier, Dennis 2009-01-01 In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/31692','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/31692">Soil moisture depletion patterns around scattered trees</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070018182','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070018182">Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Santanello, Joseph A.; Peters-Lidard, Christa D.; Garcia, Matthew E.; Mocko, David M.; Tischler, Michael A.; Moran, M. Susan; Thoma, D. P. 2007-01-01 Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9..712B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9..712B">Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian region</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=272272','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=272272">Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.3075M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.3075M">Precipitation alters plastic film mulching impacts on soil respiration in an arid area of northwest China</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ming, Guanghui; Hu, Hongchang; Tian, Fuqiang; Peng, Zhenyang; Yang, Pengju; Luo, Yiqi 2018-05-01 Plastic film mulching (PFM) has widely been used around the world to save water and improve crop yield. However, the effect of PFM on soil respiration (Rs) remains unclear and could be further confounded by irrigation and precipitation. To address these topics, controlled experiments were conducted in mulched and non-mulched fields under drip irrigation from 2014 to 2016 in an arid area of the Xinjiang Uygur Autonomous Region, northwest China. The spatio-temporal pattern of soil surface CO2 flux as an index of soil respiration under drip irrigation with PFM was investigated, and the confounded effects of PFM and irrigation/precipitation on soil respiration were explored. The main findings were as follows. (1) Furrows, planting holes, and plastic mulch are three important pathways of soil CO2 emissions in mulched fields, of which the planting hole efflux outweighs that from the furrow, with the largest values of 8.0 and 6.6 µmol m-2 s-1, respectively, and the plastic mulch itself can emit up to 3.6 µmol m-2 s-1 of CO2. (2) The frequent application of water (i.e. through irrigation and precipitation) elevates soil moisture and soil respiration and enhances their variation. The resultant higher variation of soil moisture further alleviates the sensitivity of soil respiration to soil temperature, leading to a weak correlation and lower Q10 values. (3) Soil CO2 effluxes from furrows and ridges in mulched fields outweigh the corresponding values in non-mulched fields in arid areas. However, this outweighing relation attenuates with increasing precipitation. Furthermore, by combining our results with those from the literature, we show that the difference in soil CO2 effluxes between non-mulched and mulched fields presents a linear relation with the amount of precipitation, which results in negative values in arid areas and positive values in humid areas. Therefore, whether PFM increases soil respiration or not depends on the amount of precipitation during the crop </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760008444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760008444">Electrical methods of determining soil moisture content</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51I1508E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51I1508E">Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990099275&hterms=landcover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dlandcover','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990099275&hterms=landcover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dlandcover">The Use of Indirect Estimates of Soil Moisture to Initialize Coupled Models and its Impact on Short-Term and Seasonal Simulations</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUSM.H31A..06M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUSM.H31A..06M">Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J. 2006-05-01 Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010000376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010000376">Ultrasound Algorithm Derivation for Soil Moisture Content Estimation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1513406Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1513406Y">A soil water budget model for precipitation-induced shallow landslides</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yeh, Hsin-Fu; Lee, Cheng-Haw 2013-04-01 Precipitation infiltration influences both the quantity and quality of slope systems. Knowledge of the mechanisms leading to precipitation-induced slope failures is of great importance to the management of landslide hazard. In this study, a soil water balance model is developed to estimate soil water flux during the process of infiltration from rainfall data, with consideration of storm periods and non-storm periods. Two important assumptions in this study are given: (1) instantaneous uniform distribution of the degree of effective saturation and (2) a linear relationship between evapotranspiration and the related degree of saturation degree. For storm periods, the Brooks and Corey model estimates both the soil water retention curve (SWRC) and soil water parameters. The infiltration partition is employed by an infinite-series solution of Philip in conjunction with the time compression approximation (TCA). For none-storm periods, evapotranspiration can be derived for the moisture depletion of soil water. This study presents a procedure for calculating the safety factor for an unsaturated slope suffering from precipitation infiltration. The process of infiltration into a slope due to rainfall and its effect on soil slope behavior are examined using modified Mohr-Coulomb failure criterion in conjunction with a soil water balance model. The results indicate that the matric suction, which is closely related to slope stability, is affected by the effective degree of saturation controlled by rainfall events. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28628198','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28628198">Pulse frequency and soil-litter mixing alter the control of cumulative precipitation over litter decomposition.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Joly, François-Xavier; Kurupas, Kelsey L; Throop, Heather L 2017-09-01 Macroclimate has traditionally been considered the predominant driver of litter decomposition. However, in drylands, cumulative monthly or annual precipitation typically fails to predict decomposition. In these systems, the windows of opportunity for decomposer activity may rather depend on the precipitation frequency and local factors affecting litter desiccation, such as soil-litter mixing. We used a full-factorial microcosm experiment to disentangle the relative importance of cumulative precipitation, pulse frequency, and soil-litter mixing on litter decomposition. Decomposition, measured as litter carbon loss, saturated with increasing cumulative precipitation when pulses were large and infrequent, suggesting that litter moisture no longer increased and/or microbial activity was no longer limited by water availability above a certain pulse size. More frequent precipitation pulses led to increased decomposition at high levels of cumulative precipitation. Soil-litter mixing consistently increased decomposition, with greatest relative increase (+194%) under the driest conditions. Collectively, our results highlight the need to consider precipitation at finer temporal scale and incorporate soil-litter mixing as key driver of decomposition in drylands. © 2017 by the Ecological Society of America. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8129E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8129E">Impacts of soil moisture content on visual soil evaluation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick 2017-04-01 Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..45..187W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..45..187W">Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917021H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917021H">Enhancement of the Automated Quality Control Procedures for the International Soil Moisture Network</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Heer, Elsa; Xaver, Angelika; Dorigo, Wouter; Messner, Romina 2017-04-01 In-situ soil moisture observations are still trusted to be the most reliable data to validate remotely sensed soil moisture products. Thus, the quality of in-situ soil moisture observations is of high importance. The International Soil Moisture Network (ISMN; http://ismn.geo.tuwien.ac.at/) provides in-situ soil moisture data from all around the world. The data is collected from individual networks and data providers, measured by different sensors in various depths. The data sets which are delivered in different units, time zones and data formats are then transformed into homogeneous data sets. An erroneous behavior of soil moisture data is very difficult to detect, due to annual and daily changes and most significantly the high influence of precipitation and snow melting processes. Only few of the network providers have a quality assessment for their data sets. Therefore, advanced quality control procedures have been developed for the ISMN (Dorigo et al. 2013). Three categories of quality checks were introduced: exceeding boundary values, geophysical consistency checks and a spectrum based approach. The spectrum based quality control algorithms aim to detect erroneous measurements which occur within plausible geophysical ranges, e.g. a sudden drop in soil moisture caused by a sensor malfunction. By defining several conditions which have to be met by the original soil moisture time series and their first and second derivative, such error types can be detected. Since the development of these sophisticated methods many more data providers shared their data with the ISMN and new types of erroneous measurements were identified. Thus, an enhancement of the automated quality control procedures became necessary. In the present work, we introduce enhancements of the existing quality control algorithms. Additionally, six completely new quality checks have been developed, e.g. detection of suspicious values before or after NAN-values, constant values and values that lie in a </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN43B0078S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN43B0078S">Drive by Soil Moisture Measurement: A Citizen Science Project</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3728L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3728L">Comparative estimation and assessment of initial soil moisture conditions for Flash Flood warning in Saxony</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Luong, Thanh Thi; Kronenberg, Rico; Bernhofer, Christian; Janabi, Firas Al; Schütze, Niels 2017-04-01 Flash Floods are known as highly destructive natural hazards due to their sudden appearance and severe consequences. In Saxony/Germany flash floods occur in small and medium catchments of low mountain ranges which are typically ungauged. Besides rainfall and orography, pre-event moisture is decisive, as it determines the available natural retention in the catchment. The Flash Flood Guidance concept according to WMO and Prof. Marco Borga (University of Padua) will be adapted to incorporate pre-event moisture in real-time flood forecast within the ESF EXTRUSO project (SAB-Nr. 100270097). To arrive at pre-event moisture for the complete area of the low mountain range with flash flood potential, a widely applicable, accurate but yet simple approach is needed. Here, we use radar precipitation as input time series, detailed orographic, land-use and soil information and a lumped parameter model to estimate the overall catchment soil moisture and potential retention. When combined with rainfall forecast and its intrinsic uncertainty, the approach allows to find the point in time when precipitation exceeds the retention potential of the catchment. Then, spatially distributed and complex hydrological modeling and additional measurements can be initiated. Assuming reasonable rainfall forecasts of 24 to 48hrs, this part can start up to two days in advance of the actual event. The lumped-parameter model BROOK90 is used and tested for well observed catchments. First, physical meaningful parameters (like albedo or soil porosity) a set according to standards and second, "free" parameters (like percentage of lateral flow) were calibrated objectively by PEST (Model-Independent Parameter Estimation and Uncertainty Analysis) with the target on evapotranspiration and soil moisture which both have been measured at the study site Anchor Station Tharandt in Saxony/Germany. Finally, first results are presented for the Wernersbach catchment in Tharandt forest for main flood events in the 50 </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29432925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29432925">Applicability of common stomatal conductance models in maize under varying soil moisture conditions.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Wang, Qiuling; He, Qijin; Zhou, Guangsheng 2018-07-01 In the context of climate warming, the varying soil moisture caused by precipitation pattern change will affect the applicability of stomatal conductance models, thereby affecting the simulation accuracy of carbon-nitrogen-water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a soil moisture consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying soil moisture conditions. The effects of soil moisture made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of soil relative water content (i.e., 55%-65%, 56%-67%, 37%-79% and 37%-95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying soil moisture conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions. Copyright © 2018 Elsevier B.V. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011279','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011279">State of the Art in Large-Scale Soil Moisture Monitoring</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140011279'); toggleEditAbsImage('author_20140011279_show'); toggleEditAbsImage('author_20140011279_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140011279_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140011279_hide"> 2013-01-01 Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008SPIE.7085E..0KB','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008SPIE.7085E..0KB">Implementation of a global-scale operational data assimilation system for satellite-based soil moisture retrievals</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bolten, J.; Crow, W.; Zhan, X.; Reynolds, C. 2008-08-01 Timely and accurate monitoring of global weather anomalies and drought conditions is essential for assessing global crop conditions. Soil moisture observations are particularly important for crop yield fluctuations provided by the US Department of Agriculture (USDA) Production Estimation and Crop Assessment Division (PECAD). The current system utilized by PECAD estimates soil moisture from a 2-layer water balance model based on precipitation and temperature data from World Meteorological Organization (WMO) and US Air Force Weather Agency (AFWA). The accuracy of this system is highly dependent on the data sources used; particularly the accuracy, consistency, and spatial and temporal coverage of the land and climatic data input into the models. However, many regions of the globe lack observations at the temporal and spatial resolutions required by PECAD. This study incorporates NASA's soil moisture remote sensing product provided by the EOS Advanced Microwave Scanning Radiometer (AMSR-E) into the U.S. Department of Agriculture Crop Assessment and Data Retrieval (CADRE) decision support system. A quasi-global-scale operational data assimilation system has been designed and implemented to provide CADRE a daily product of integrated AMSR-E soil moisture observations with the PECAD two-layer soil moisture model forecasts. A methodology of the system design and a brief evaluation of the system performance over the Conterminous United States (CONUS) is presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020022301&hterms=climate+change+deserts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange%2Bdeserts','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020022301&hterms=climate+change+deserts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange%2Bdeserts">Soil Moisture and Snow Cover: Active or Passive Elements of Climate?</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70187027','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70187027">Soil moisture sensors for continuous monitoring</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Amer, Saud A.; Keefer, T. O.; Weltz, M.A.; Goodrich, David C.; Bach, Leslie 1995-01-01 Certain physical and chemical properties of soil vary with soil water content. The relationship between these properties and water content is complex and involves both the pore structure and constituents of the soil solution. One of the most economical techniques to quantify soil water content involves the measurement of electrical resistance of a dielectric medium that is in equilibrium with the soil water content. The objective of this research was to test the reliability and accuracy of fiberglass soil-moisture electrical resistance sensors (ERS) as compared to gravimetric sampling and Time Domain Reflectometry (TDR). The response of the ERS was compared to gravimetric measurements at eight locations on the USDA-ABS Walnut Gulch Experimental Watershed. The comparisons with TDR sensors were made at three additional locations on the same watershed. The high soil rock content (>45 percent) at seven locations resulted in consistent overestimation of soil water content by the ERS method. Where rock content was less than 10 percent, estimation of soil water was within 5 percent of the gravimetric soil water content. New methodology to calibrate the ERS sensors for rocky soils will need to be developed before soil water content values can be determined with these sensors. (KEY TERMS: soil moisture; soil water; infiltration; instrumentation; soil moisture sensors.) </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6988M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6988M">Groundwater influence on soil moisture memory and land-atmosphere interactions over the Iberian Peninsula</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Martinez-de la Torre, Alberto; Miguez-Macho, Gonzalo 2017-04-01 We investigate the memory introduced in soil moisture fields by groundwater long timescales of variation in the semi-arid regions of the Iberian Peninsula with the LEAFHYDRO soil-vegetation-hydrology model, which includes a dynamic water table fully coupled to soil moisture and river flow via 2-way fluxes. We select a 10-year period (1989-1998) with transitions from wet to dry to again wet long lasting conditions and we carry out simulations at 2.5 km spatial resolution forced by ERA-Interim and a high-resolution precipitation analysis over Spain and Portugal. The model produces a realistic water table that we validate with hundreds of water table depth observation time series (ranging from 4 to 10 years) over the Iberian Peninsula. Modeled river flow is also compared to observations. Over shallow water table regions, results highlight the groundwater buffering effect on soil moisture fields over dry spells and long-term droughts, as well as the slow recovery of pre-drought soil wetness once climatic conditions turn wetter. Groundwater sustains river flow during dry summer periods. The longer lasting wet conditions in the soil when groundwater is considered increase summer evapotranspiration, that is mostly water-limited. Our results suggest that groundwater interaction with soil moisture should be considered for climate seasonal forecasting and climate studies in general over water-limited regions where shallow water tables are significantly present and connected to land surface hydrology. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170002508','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170002508">Evaluating ESA CCI Soil Moisture in East Africa</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29599664','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29599664">Evaluating ESA CCI soil moisture in East Africa.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41C2293M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41C2293M">Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H. 2017-12-01 Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp....7G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp....7G">The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Guo, Liang; Klingaman, Nicholas P.; Demory, Marie-Estelle; Vidale, Pier Luigi; Turner, Andrew G.; Stephan, Claudia C. 2018-01-01 We investigate the contribution of the local and remote atmospheric moisture fluxes to East Asia (EA) precipitation and its interannual variability during 1979-2012. We use and expand the Brubaker et al. (J Clim 6:1077-1089,1993) method, which connects the area-mean precipitation to area-mean evaporation and the horizontal moisture flux into the region. Due to its large landmass and hydrological heterogeneity, EA is divided into five sub-regions: Southeast (SE), Tibetan Plateau (TP), Central East (CE), Northwest (NW) and Northeast (NE). For each region, we first separate the contributions to precipitation of local evaporation from those of the horizontal moisture flux by calculating the precipitation recycling ratio: the fraction of precipitation over a region that originates as evaporation from the same region. Then, we separate the horizontal moisture flux across the region's boundaries by direction. We estimate the contributions of the horizontal moisture fluxes from each direction, as well as the local evaporation, to the mean precipitation and its interannual variability. We find that the major contributors to the mean precipitation are not necessarily those that contribute most to the precipitation interannual variability. Over SE, the moisture flux via the southern boundary dominates the mean precipitation and its interannual variability. Over TP, in winter and spring, the moisture flux via the western boundary dominates the mean precipitation; however, variations in local evaporation dominate the precipitation interannual variability. The western moisture flux is the dominant contributor to the mean precipitation over CE, NW and NE. However, the southern or northern moisture flux or the local evaporation dominates the precipitation interannual variability over these regions, depending on the season. Potential mechanisms associated with interannual variability in the moisture flux are identified for each region. The methods and results presented in this </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007425','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007425">AMSR2 Soil Moisture Product Validation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Bindlish, R.; Jackson, T.; Cosh, M.; Koike, T.; Fuiji, X.; de Jeu, R.; Chan, S.; Asanuma, J.; Berg, A.; Bosch, D.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170007425'); toggleEditAbsImage('author_20170007425_show'); toggleEditAbsImage('author_20170007425_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170007425_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170007425_hide"> 2017-01-01 The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W) mission. AMSR2 fills the void left by the loss of the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) after almost 10 years. Both missions provide brightness temperature observations that are used to retrieve soil moisture. Merging AMSR-E and AMSR2 will help build a consistent long-term dataset. Before tackling the integration of AMSR-E and AMSR2 it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites. Three products that rely on different algorithms were evaluated; the JAXA Soil Moisture Algorithm (JAXA), the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). Results indicate that overall the SCA has the best performance based upon the metrics considered. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H14B..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H14B..01S">Soil Moisture or Groundwater?</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Swenson, S. C.; Lawrence, D. M. 2017-12-01 Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19850014924','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19850014924">Microwave Remote Sensing of Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmugge, T. J. 1985-01-01 Because of the large contrast between the dielectric constant of liquid water and that of dry soil at microwave wavelength, there is a strong dependence of the thermal emission and radar backscatter from the soil on its moisture content. This dependence provides a means for the remote sensing of the moisture content in a surface layer approximately 5 cm thick. The feasibility of these techniques is demonstrated from field, aircraft and spacecraft platforms. The soil texture, surface roughness, and vegetative cover affect the sensitivity of the microwave response to moisture variations with vegetation being the most important. It serves as an attenuating layer which can totally obscure the surface. Research indicates that it is possible to obtain five or more levels of moisture discrimination and that a mature corn crop is the limiting vegetation situation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870052970&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Devapotranspiration','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870052970&hterms=evapotranspiration&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Devapotranspiration">Concerning the relationship between evapotranspiration and soil moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H13B1104B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H13B1104B">Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L. 2014-12-01 The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GeCoA.165..108K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GeCoA.165..108K">A simple reactive-transport model of calcite precipitation in soils and other porous media</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kirk, G. J. D.; Versteegen, A.; Ritz, K.; Milodowski, A. E. 2015-09-01 Calcite formation in soils and other porous media generally occurs around a localised source of reactants, such as a plant root or soil macro-pore, and the rate depends on the transport of reactants to and from the precipitation zone as well as the kinetics of the precipitation reaction itself. However most studies are made in well mixed systems, in which such transport limitations are largely removed. We developed a mathematical model of calcite precipitation near a source of base in soil, allowing for transport limitations and precipitation kinetics. We tested the model against experimentally-determined rates of calcite precipitation and reactant concentration-distance profiles in columns of soil in contact with a layer of HCO3--saturated exchange resin. The model parameter values were determined independently. The agreement between observed and predicted results was satisfactory given experimental limitations, indicating that the model correctly describes the important processes. A sensitivity analysis showed that all model parameters are important, indicating a simpler treatment would be inadequate. The sensitivity analysis showed that the amount of calcite precipitated and the spread of the precipitation zone were sensitive to parameters controlling rates of reactant transport (soil moisture content, salt content, pH, pH buffer power and CO2 pressure), as well as to the precipitation rate constant. We illustrate practical applications of the model with two examples: pH changes and CaCO3 precipitation in the soil around a plant root, and around a soil macro-pore containing a source of base such as urea. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19720004649','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19720004649">Summary: Remote sensing soil moisture research</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmer, F. A.; Werner, H. D.; Waltz, F. A. 1970-01-01 During the 1969 and 1970 growing seasons research was conducted to investigate the relationship between remote sensing imagery and soil moisture. The research was accomplished under two completely different conditions: (1) cultivated cropland in east central South Dakota, and (2) rangeland in western South Dakota. Aerial and ground truth data are being studied and correlated in order to evaluate the moisture supply and water use. Results show that remote sensing is a feasible method for monitoring soil moisture. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..561..509N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..561..509N">Perturbations in the initial soil moisture conditions: Impacts on hydrologic simulation in a large river basin</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Niroula, Sundar; Halder, Subhadeep; Ghosh, Subimal 2018-06-01 Real time hydrologic forecasting requires near accurate initial condition of soil moisture; however, continuous monitoring of soil moisture is not operational in many regions, such as, in Ganga basin, extended in Nepal, India and Bangladesh. Here, we examine the impacts of perturbation/error in the initial soil moisture conditions on simulated soil moisture and streamflow in Ganga basin and its propagation, during the summer monsoon season (June to September). This provides information regarding the required minimum duration of model simulation for attaining the model stability. We use the Variable Infiltration Capacity model for hydrological simulations after validation. Multiple hydrologic simulations are performed, each of 21 days, initialized on every 5th day of the monsoon season for deficit, surplus and normal monsoon years. Each of these simulations is performed with the initial soil moisture condition obtained from long term runs along with positive and negative perturbations. The time required for the convergence of initial errors is obtained for all the cases. We find a quick convergence for the year with high rainfall as well as for the wet spells within a season. We further find high spatial variations in the time required for convergence; the region with high precipitation such as Lower Ganga basin attains convergence at a faster rate. Furthermore, deeper soil layers need more time for convergence. Our analysis is the first attempt on understanding the sensitivity of hydrological simulations of Ganga basin on initial soil moisture conditions. The results obtained here may be useful in understanding the spin-up requirements for operational hydrologic forecasts. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..12112062B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..12112062B">Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann 2016-10-01 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 Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26672277','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26672277">[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H12B..08C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H12B..08C">Generating a global soil evaporation dataset using SMAP soil moisture data to estimate components of the surface water balance</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Carbone, E.; Small, E. E.; Badger, A.; Livneh, B. 2016-12-01 Evapotranspiration (ET) is fundamental to the water, energy and carbon cycles. However, our ability to measure ET and partition the total flux into transpiration and evaporation from soil is limited. This project aims to generate a global, observationally-based soil evaporation dataset (E-SMAP): using SMAP surface soil moisture data in conjunction with models and auxiliary observations to observe or estimate each component of the surface water balance. E-SMAP will enable a better understanding of water balance processes and contribute to forecasts of water resource availability. Here we focus on the flux between the soil surface and root zone layers (qbot), which dictates the proportion of water that is available for soil evaporation. Any water that moves from the surface layer to the root zone contributes to transpiration or groundwater recharge. The magnitude and direction of qbot are driven by gravity and the gradient in matric potential. We use a highly discretized Richards Equation-type model (e.g. Hydrus 1D software) with meteorological forcing from the North American Land Data Assimilation System (NLDAS) to estimate qbot. We verify the simulations using SMAP L4 surface and root zone soil moisture data. These data are well suited for evaluating qbot because they represent the most advanced estimate of the surface to root zone soil moisture gradient at the global scale. Results are compared with similar calculations using NLDAS and in situ soil moisture data. Preliminary calculations show that the greatest amount of variability between qbot determined from NLDAS, in situ and SMAP occurs directly after precipitation events. At these times, uncertainties in qbot calculations significantly affect E-SMAP estimates. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050238481','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050238481">NASA Soil Moisture Data Products and Their Incorporation in DREAM</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/28625','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/28625">Soil moisture and vegetation patterns in northern California forests</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27527683','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27527683">Precipitation overrides warming in mediating soil nitrogen pools in an alpine grassland ecosystem on the Tibetan Plateau.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Lin, Li; Zhu, Biao; Chen, Chengrong; Zhang, Zhenhua; Wang, Qi-Bing; He, Jin-Sheng 2016-08-16 Soils in the alpine grassland store a large amount of nitrogen (N) due to slow decomposition. However, the decomposition could be affected by climate change, which has profound impacts on soil N cycling. We investigated the changes of soil total N and five labile N stocks in the topsoil, the subsoil and the entire soil profile in response to three years of experimental warming and altered precipitation in a Tibetan alpine grassland. We found that warming significantly increased soil nitrate N stock and decreased microbial biomass N (MBN) stock. Increased precipitation reduced nitrate N, dissolved organic N and amino acid N stocks, but increased MBN stock in the topsoil. No change in soil total N was detected under warming and altered precipitation regimes. Redundancy analysis further revealed that soil moisture (26.3%) overrode soil temperature (10.4%) in explaining the variations of soil N stocks across the treatments. Our results suggest that precipitation exerted stronger influence than warming on soil N pools in this mesic and high-elevation grassland ecosystem. This indicates that the projected rise in future precipitation may lead to a significant loss of dissolved soil N pools by stimulating the biogeochemical processes in this alpine grassland. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://pubs.water.usgs.gov/ofr02348/+','USGSPUBS'); return false;" href="http://pubs.water.usgs.gov/ofr02348/+">Selected micrometeorological and soil-moisture data at Amargosa Desert Research Site, an arid site near Beatty, Nye County, Nevada, 1998-2000</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Johnson, Michael J.; Mayers, Charles J.; Andraski, Brian J. 2002-01-01 Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radioactive waste and hazardous chemical waste facility near Beatty, Nev., 1998-2000. Data were collected in support of ongoing research studies to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include precipitation, air temperature, solar radiation, net radiation, relative humidity, ambient vapor pressure, wind speed and direction, barometric pressure, soil temperature, and soil-heat flux. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily mean, maximum, and minimum values, and hourly mean values. For precipitation, data output consisted of daily, hourly, and 5-minute totals. Soil-moisture data included periodic measurements of soil-water content at nine neutron-probe access tubes with measurable depths ranging from 5.25 to 29.75 meters. The computer data files included in this report contain the complete micrometeorological and soil-moisture data sets. The computer data consists of seven files with about 14 megabytes of information. The seven files are in tabular format: (1) one file lists daily mean, maximum, and minimum micrometeorological data and daily total precipitation; (2) three files list hourly mean micrometeorological data and hourly precipitation for each year (1998-2000); (3) one file lists 5-minute precipitation data; (4) one file lists mean soil-water content by date and depth at four experimental sites; and (5) one file lists soil-water content by date and depth for each neutron-probe access tube. This report highlights selected data contained in the computer data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41D1482M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41D1482M">Measuring Soil Moisture in Skeletal Soils Using a COSMOS Rover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Medina, C.; Neely, H.; Desilets, D.; Mohanty, B.; Moore, G. W. 2017-12-01 The presence of coarse fragments directly influences the volumetric water content of the soil. Current surface soil moisture sensors often do not account for the presence of coarse fragments, and little research has been done to calibrate these sensors under such conditions. The cosmic-ray soil moisture observation system (COSMOS) rover is a passive, non-invasive surface soil moisture sensor with a footprint greater than 100 m. Despite its potential, the COSMOS rover has yet to be validated in skeletal soils. The goal of this study was to validate measurements of surface soil moisture as taken by a COSMOS rover on a Texas skeletal soil. Data was collected for two soils, a Marfla clay loam and Chinati-Boracho-Berrend association, in West Texas. Three levels of data were collected: 1) COSMOS surveys at three different soil moistures, 2) electrical conductivity surveys within those COSMOS surveys, and 3) ground-truth measurements. Surveys with the COSMOS rover covered an 8000-h area and were taken both after large rain events (>2") and a long dry period. Within the COSMOS surveys, the EM38-MK2 was used to estimate the spatial distribution of coarse fragments in the soil around two COSMOS points. Ground truth measurements included coarse fragment mass and volume, bulk density, and water content at 3 locations within each EM38 survey. Ground-truth measurements were weighted using EM38 data, and COSMOS measurements were validated by their distance from the samples. There was a decrease in water content as the percent volume of coarse fragment increased. COSMOS estimations responded to both changes in coarse fragment percent volume and the ground-truth volumetric water content. Further research will focus on creating digital soil maps using landform data and water content estimations from the COSMOS rover. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....4526W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....4526W">Gravity changes, soil moisture and data assimilation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Walker, J.; Grayson, R.; Rodell, M.; Ellet, K. 2003-04-01 Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140016698','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140016698">Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T. 2014-01-01 (LSM) simulations and includes an Ensemble Kalman Filter for conducting land surface DA. SPoRT has added a module to read, quality-control and bias-correct swaths of Level II SMOS soil moisture retrievals prior to assimilation within LIS. The impact of SMOS DA is being tested using the Noah LSM. Experiments are being conducted to examine the impacts of SMOS soil moisture DA on the resulting LISNoah fields and subsequent NWP simulations using the Weather Research and Forecasting (WRF) model initialized with LIS-Noah output. LIS-Noah soil moisture will be validated against in situ observations from Texas A&M's North American Soil Moisture Database to reveal the impact and possible improvement in soil moisture trends through DA. WRF model NWP case studies will test the impacts of DA on the simulated near-surface and boundary-layer environments, and precipitation during both quiescent and disturbed weather scenarios. Emphasis will be placed on cases with large analysis increments, especially due to contributions from regional irrigation patterns that are not represented by precipitation input in the baseline LIS-Noah run. This poster presentation will describe the soil moisture DA methodology and highlight LIS-Noah and WRF simulation results with and without assimilation. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1989JCli....2.1362O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1989JCli....2.1362O">Soil Moisture and the Persistence of North American Drought.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B41F2026K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B41F2026K">Changes in Soil Carbon and Moisture over the Six Year after Thinning of a Natural Oak Forest</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kim, S.; Han, S. H.; Li, G.; Chang, H.; Kim, H. J.; Son, Y. 2017-12-01 The objective of this study was to assess the effects of thinning on soil carbon (C) in a natural oak forest in central Korea. The study forest received three different thinning treatments consisting of un-thinned control (UTC) and two thinning intensities (15% and 30% basal area reductions) in March in 2010. Precipitation near the study forest maintained the normal level from 2010 to 2013 (average 1,400 mm year-1), but abnormally decreased from 2014 to 2016 (average 800 mm year-1). To measure total soil C stock and soil moisture conditions, soils were collected from 0-10, 10-20, and 20-30 cm depths in June, 2010, 2013, and 2016, respectively. Soil microbial biomass C and C-cycling enzymes (β-glucosidase, cellobiohydrolase, β-xylosidase, phenol oxidase, and peroxidase) at 0-10 cm depth were determined in June, 2016. Total soil C stock at 0-30 cm depth increased throughout the study period, whereas soil moisture decreased at all depths from 2013 to 2016. Both thinning treatments had higher total soil C stock at 0-30 cm depth and moisture at 10-20 and 20-30 cm depths than the UTC in 2013 and 2016, whereas the treatments showed no effects in 2010. Microbial biomass C at 0-10 cm depth in 2016 also increased because of the thinning treatments, which was positively correlated to total soil C stock. However, any effects of thinning on C-cycling enzymes were not significant. Our results indicate that thinning could contribute to relieving the impacts of decreasing precipitation by enhancing the storage of soil moisture. Furthermore, the change in total soil C stock under thinning might result from the stimulation of microbial potential for retaining organic C as a form of biomass. This study was supported by the Ministry of Environment (2014001810002) and the National Institute of Forest Science of Korea (FM0101-2009-01). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1602X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1602X">Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP33B2374D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP33B2374D">Iron content of soils as a precipitation proxy</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dzombak, R.; Sheldon, N. D. 2016-12-01 Given that different iron phases form under different precipitation and drainage regimes, soil iron content could be used as a proxy for both volume and seasonality of precipitation. Constraining these factors is important for predicting future precipitation trends, especially for a warmer climate that will likely see more frequent extreme weather events. Specifically, using paleoprecipitation data from periods of higher temperatures and atmospheric CO2 concentrations helps inform models of future `greenhouse' climate. Forty-five modern samples from across the continental United States were analyzed, with MAP ranging from 200 to 1200 mm yr-1 and MAT ranging from 5 to 22°C. Soil types included Alfisols (N=15), Inceptisols (N=8), Mollisols (N=15), and Aridisols (N=7), and ranged from seasonally wet to well-drained. Analytical techniques included combustion-elemental analysis and organic carbon isotope analysis, a sequential iron extraction modified with a sodium hypochlorite step for the extraction of organic matter-bound iron, and the extraction of iron sulfides. The sequential extractions yield five different `pools' of iron found in sediment: crystalline iron oxides (e.g., goethite, hematite), magnetite, carbonate-bound, organic matter-bound, and labile/easily reducible iron minerals (e.g., ferrihydrite). Analysis by ICP-OES yielded a strong relationship between magnetite-bound iron and MAP, and fair relationships between the other iron pools and MAP. Individual soil orders tended to show stronger relationships to the iron pools than all soils analyzed together, potentially indicating the need for separate proxy relationships for each soil order. Pyrite concentrations were well below 1% by weight for these soils, suggesting that none of these soils has a long enough wet season to encourage its formation and that the presence vs. absence of pyrite in paleosols may be a useful proxy for soil moisture state. In contrast to some earlier work, no significant </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H41C0899C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H41C0899C">What is the philosophy of modelling soil moisture movement?</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930036630&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930036630&hterms=Soil+sampling+radiation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSoil%2Bsampling%2Bradiation">An overview of the measurements of soil moisture and modeling of moisture flux in FIFE</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4122403','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4122403">Precipitation Regime Shift Enhanced the Rain Pulse Effect on Soil Respiration in a Semi-Arid Steppe</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi 2014-01-01 The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m−2) and 39.6% (61.7 g C m−2) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r 2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953–2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953–2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change. PMID:25093573 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25093573','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25093573">Precipitation regime shift enhanced the rain pulse effect on soil respiration in a semi-arid steppe.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi 2014-01-01 The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m(-2)) and 39.6% (61.7 g C m(-2)) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953-2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953-2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.1177R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.1177R">Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ruosteenoja, Kimmo; Markkanen, Tiina; Venäläinen, Ari; Räisänen, Petri; Peltola, Heli 2018-02-01 Projections for near-surface soil moisture content in Europe for the 21st century were derived from simulations performed with 26 CMIP5 global climate models (GCMs). Two Representative Concentration Pathways, RCP4.5 and RCP8.5, were considered. Unlike in previous research in general, projections were calculated separately for all four calendar seasons. To make the moisture contents simulated by the various GCMs commensurate, the moisture data were normalized by the corresponding local maxima found in the output of each individual GCM. A majority of the GCMs proved to perform satisfactorily in simulating the geographical distribution of recent soil moisture in the warm season, the spatial correlation with an satellite-derived estimate varying between 0.4 and 0.8. In southern Europe, long-term mean soil moisture is projected to decline substantially in all seasons. In summer and autumn, pronounced soil drying also afflicts western and central Europe. In northern Europe, drying mainly occurs in spring, in correspondence with an earlier melt of snow and soil frost. The spatial pattern of drying is qualitatively similar for both RCP scenarios, but weaker in magnitude under RCP4.5. In general, those GCMs that simulate the largest decreases in precipitation and increases in temperature and solar radiation tend to produce the most severe soil drying. Concurrently with the reduction of time-mean soil moisture, episodes with an anomalously low soil moisture, occurring once in 10 years in the recent past simulations, become far more common. In southern Europe by the late 21st century under RCP8.5, such events would be experienced about every second year. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840014939','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840014939">A microwave systems approach to measuring root zone soil moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA19338.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA19338.html">Southern U.S. Soil Moisture Map</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2015-05-19 Southern U.S. NASA's SMAP soil moisture retrievals from April 27, 2015, when severe storms were affecting Texas. Top: radiometer data alone. Bottom: combined radar and radiometer data with a resolution of 5.6 miles (9 kilometers). The combined product reveals more detailed surface soil moisture features. http://photojournal.jpl.nasa.gov/catalog/PIA19338 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JHyd..516....6R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JHyd..516....6R">Soil moisture at local scale: Measurements and simulations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740003078','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740003078">Detection of moisture and moisture related phenomena from Skylab. [Texas</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMIN31B1503C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMIN31B1503C">Field-scale soil moisture space-time geostatistical modeling for complex Palouse landscapes in the inland Pacific Northwest</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chahal, M. K.; Brown, D. J.; Brooks, E. S.; Campbell, C.; Cobos, D. R.; Vierling, L. A. 2012-12-01 Estimating soil moisture content continuously over space and time using geo-statistical techniques supports the refinement of process-based watershed hydrology models and the application of soil process models (e.g. biogeochemical models predicting greenhouse gas fluxes) to complex landscapes. In this study, we model soil profile volumetric moisture content for five agricultural fields with loess soils in the Palouse region of Eastern Washington and Northern Idaho. Using a combination of stratification and space-filling techniques, we selected 42 representative and distributed measurement locations in the Cook Agronomy Farm (Pullman, WA) and 12 locations each in four additional grower fields that span the precipitation gradient across the Palouse. At each measurement location, soil moisture was measured on an hourly basis at five different depths (30, 60, 90, 120, and 150 cm) using Decagon 5-TE/5-TM soil moisture sensors (Decagon Devices, Pullman, WA, USA). This data was collected over three years for the Cook Agronomy Farm and one year for each of the grower fields. In addition to ordinary kriging, we explored the correlation of volumetric water content with external, spatially exhaustive indices derived from terrain models, optical remote sensing imagery, and proximal soil sensing data (electromagnetic induction and VisNIR penetrometer) </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930063678&hterms=Soil+science&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSoil%2Bscience','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930063678&hterms=Soil+science&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSoil%2Bscience">Soil moisture needs in earth sciences</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Engman, Edwin T. 1992-01-01 The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H11B1167L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H11B1167L">Ground water level, Water storage, Soil moisture, Precipitation Variability Using Multi Satellite Data during 2003-2016 Associated with California Drought</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, J. W.; Singh, R. P. 2017-12-01 The agricultural market of California is a multi-billion-dollar industry, however in the recent years, the state is facing severe drought. It is important to have a deeper understanding of how the agriculture is affected by the amount of rainfall as well as the ground conditions in California. We have considered 5 regions (each 2 degree by 2 degree) covering whole of California. Multi satellite (MODIS Terra, GRACE, GLDAS) data through NASA Giovanni portal were used to study long period variability 2003 - 2016 of ground water level and storage, soil moisture, root zone moisture level, precipitation and normalized vegetation index (NDVI) in these 5 regions. Our detailed analysis of these parameters show a strong correlation between the NDVI and some of these parameters. NDVI represents greenness showing strong drought conditions during the period 2011-2016 due to poor rainfall and recharge of ground water in the mid and southern parts of California. Effect of ground water level and underground storage will be also discussed on the frequency of earthquakes in five regions of California. The mid and southern parts of California show increasing frequency of small earthquakes during drought periods. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50..629T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50..629T">Moisture sources and pathways associated with the spatial variability of seasonal extreme precipitation over Canada</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tan, Xuezhi; Gan, Thian Yew; Chen, Yongqin David 2018-01-01 Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified. Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading of moisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFMIN43B1184L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFMIN43B1184L">Soil Moisture Estimation Using Hyperspectral SWIR Imagery</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lewis, D. 2007-12-01 The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612163C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612163C">Validation of SURFEX Simulated Soil Moisture over the Valencia Anchor Station using SMOS products and in situ measurements.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Coll, M. Amparo; Khodayar, Samiro; Lopez-Baeza, Ernesto 2014-05-01 Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the SURFEX (Surface Externalisée) model developed at the Centre National de Recherches Météorologiques (CNRM) at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the Valencia Anchor Station. SURFEX integrates the ISBA (Interaction Sol-Biosphère-Atmosphère; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) and we introduced the ECOCLIMAP for the description of land covers. The Valencia Anchor Station was chosen as a validation site for the SMOS (Soil Moisture and Ocean Salinity) mission and as one of the hydrometeorological sites for the HyMeX (HYdrological cycle in Mediterranean EXperiment) programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few number of small industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry-sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields to be compared with level-2 and level-3 soil moisture maps generated </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=228413','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=228413">Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020072723&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020072723&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson">Soil Moisture and Snow Cover: Active or Passive Elements of Climate</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor) 2002-01-01 A key question 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. in determining the subsequent evolution of soil moisture and of snow cover. 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. 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 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. 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. An intriguing new statistical technique </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ESSD...10...61B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ESSD...10...61B">The Raam regional soil moisture monitoring network in the Netherlands</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier 2018-01-01 We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at <a href="https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56" target="_blank">https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56</a>. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950027382','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950027382">Measuring soil moisture with imaging radars</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Dubois, Pascale C.; Vanzyl, Jakob; Engman, Ted 1995-01-01 An empirical model was developed to infer soil moisture and surface roughness from radar data. The accuracy of the inversion technique is assessed by comparing soil moisture obtained with the inversion technique to in situ measurements. The effect of vegetation on the inversion is studied and a method to eliminate the areas where vegetation impairs the algorithm is described. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/8717','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/8717">Logging effects on soil moisture losses</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Robert R. Ziemer 1978-01-01 Abstract - The depletion of soil moisture within the surface 15 feet by an isolated mature sugar pine and an adjacent uncut forest in the California Sierra Nevada was measured by the neutron method every 2 weeks for 5 consecutive summers. Soil moisture recharge was measured periodically during the intervening winters. Groundwater fluctuations within the surface 50... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70168512','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70168512">Does the stress-gradient hypothesis hold water? Disentangling spatial and temporal variation in plant effects on soil moisture in dryland systems</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Butterfield, Bradley J.; Bradford, John B.; Armas, Cristina; Prieto, Ivan; Pugnaire, Francisco I. 2016-01-01 Taken together, the results of this simulation study suggest that plant effects on soil moisture are predictable based on relatively general relationships between precipitation inputs and differential evaporation and transpiration rates between plant and interspace microsites that are largely driven by temperature. In particular, this study highlights the importance of differentiating between temporal and spatial variation in weather and climate, respectively, in determining plant effects on available soil moisture. Rather than focusing on the somewhat coarse-scale predictions of the SGH, it may be more beneficial to explicitly incorporate plant effects on soil moisture into predictive models of plant-plant interaction outcomes in drylands. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9532S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9532S">Assessment of seasonal soil moisture forecasts over Southern South America with emphasis on dry and wet events</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Spennemann, Pablo; Rivera, Juan Antonio; Osman, Marisol; Saulo, Celeste; Penalba, Olga 2017-04-01 The importance of forecasting extreme wet and dry conditions from weeks to months in advance relies on the need to prevent considerable socio-economic losses, mainly in regions of large populations and where agriculture is a key value for the economies, like Southern South America (SSA). Therefore, to improve the understanding of the performance and uncertainties of seasonal soil moisture and precipitation forecasts over SSA, this study aims to: 1) perform a general assessment of the Climate Forecast System version-2 (CFSv2) soil moisture and precipitation forecasts; and 2) evaluate the CFSv2 ability to represent an extreme drought event merging observations with forecasted Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Anomalies (SSMA) based on GLDAS-2.0 simulations. Results show that both SPI and SSMA forecast skill are regionally and seasonally dependent. In general a fast degradation of the forecasts skill is observed as the lead time increases with no significant metrics for forecast lead times longer than 2 months. Based on the assessment of the 2008-2009 extreme drought event it is evident that the CFSv2 forecasts have limitations regarding the identification of drought onset, duration, severity and demise, considering both meteorological (SPI) and agricultural (SSMA) drought conditions. These results have some implications upon the use of seasonal forecasts to assist agricultural practices in SSA, given that forecast skill is still too low to be useful for lead times longer than 2 months. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/24123','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/24123">Evaluation of soil moisture barrier.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2000-06-01 This report is an extension report and examines one of the measures being tried to stabilize the development : of pavement damage on expansive soils, which is the use of horizontal moisture barriers. The moisture barrier : will not stop horizontal fl... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9762M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9762M">Value of Available Global Soil Moisture Products for Agricultural Monitoring</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007JGRD..112.3102D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007JGRD..112.3102D">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</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......496M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......496M">Estimating root-zone soil moisture in the West Africa Sahel using remotely sensed rainfall and vegetation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> McNally, Amy L. Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/9809915','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/9809915">Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C 1998-10-01 While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z">Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.2932K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.2932K">Inter-Comparison of Retrieved and Modelled Soil Moisture and Coherency of Remotely Sensed Hydrology Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kolassa, Jana; Aires, Filipe 2013-04-01 A neural network algorithm has been developed for the retrieval of Soil Moisture (SM) from global satellite observations. The algorithm estimates soil moisture from a synergy of passive and active microwave, infrared and visible satellite observations in order to capture the different SM variabilities that the individual sensors are sensitive to. The advantages and drawbacks of each satellite observation have been analysed and the information type and content carried by each observation have been determined. A global data set of monthly mean soil moisture for the 1993-2000 period has been computed with the neural network algorithm (Kolassa et al., in press, 2012). The resulting soil moisture retrieval product has then been used in an inter-comparison study including soil moisture from (1) the HTESSEL model (Balsamo et al., 2009), (2) the WACMOS satellite product (Liu et al., 2011), and (3) in situ measurements from the International Soil Moisture Network (Dorigo et al., 2011). The analysis showed that the satellite remote sensing products are well-suited to capture the spatial variability of the in situ data and even show the potential to improve the modelled soil moisture. Both satellite retrievals also display a good agreement with the temporal structures of the in situ data, however, HTESSEL appears to be more suitable for capturing the temporal variability (Kolassa et al., in press, 2012). The use of this type of neural network approach is currently being investigated as a retrieval option for the SMOS mission. Our soil moisture retrieval product has also been used in a coherence study with precipitation data from GPCP (Adler et al., 2003) and inundation estimates from GIEMS (Prigent et al., 2007). It was investigated on a global scale whether the three observation-based datasets are coherent with each other and show the expected behaviour. For most regions of the Earth, the datasets were consistent and the behaviour observed could be explained with the known </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H51H1487M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H51H1487M">Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016cosp...41E1188L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016cosp...41E1188L">Soil Moisture Remote Sensing with GNSS-R at the Valencia Anchor Station. The SOMOSTA (Soil Moisture Station) Experiment</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lopez-Baeza, Ernesto 2016-07-01 In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on soil moisture monitoring byGlobal Navigation Satellite System Reflected signals(GNSS-R) at the Valencia Anchor Station is introduced. L-band microwaves have very good advantages in soil moisture remote sensing, for being unaffected by clouds and the atmosphere, and for the ability to penetrate vegetation. During this experimental campaign, the ESA GNSS-R Oceanpal antenna was installed on the same tower as the ESA ELBARA-II passive microwave radiometer, both measuring instruments having similar field of view. This experiment is fruitfully framed within the ESA - China Programme of Collaboration on GNSS-R. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and two down-looking antennas for receiving LHCP (left-hand circular polarisation) and RHCP (right-hand circular polarisation) reflected signals from the soil surface. We could collect data from the three different antennas through the two channels of Oceanpal and, in addition, calibration could be performed to reduce the impact from the differing channels. Reflectivity was thus measured and soil moisture could be retrieved by the L- MEB (L-band Microwave Emission of the Biosphere) model considering the effect of vegetation optical thickness and soil roughness. By contrasting GNSS-R and ELBARA-II radiometer data, a negative correlation existed between reflectivity measured by GNSS-R and brightness temperature measured by the radiometer. The two parameters represent reflection and absorption of the soil. Soil moisture retrieved by both L-band remote sensing methods shows good agreement. In addition, correspondence with in-situ measurements and rainfall is also good. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20120009941&hterms=soil+layers&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%2Blayers','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20120009941&hterms=soil+layers&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsoil%2Blayers">Diagnosing the Sensitivity of Local Land-Atmosphere Coupling via the Soil Moisture-Boundary Layer Interaction</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347939','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347939">Temporal transferability of soil moisture calibration equations</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H53Q..04G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H53Q..04G">Moisture sources and pathways associated with the spatial variability of seasonal extreme precipitation over Canada</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gan, T. Y. Y.; Tan, X.; Chen, Y. D. 2017-12-01 Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified.Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading ofmoisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008706','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008706">Using Historical Precipitation, Temperature, and Runoff Observations to Evaluate Evaporation Formulations in Land Surface Models</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koster, Randal D.; Mahanama, P. P. 2012-01-01 Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUSM.A34B..07K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUSM.A34B..07K">Impact of vegetation feedback at subseasonal & seasonal timescales on precipitation over North America</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kim, Y.; Wang, G. 2006-05-01 Soil moisture-vegetation-precipitation feedbacks tend to enhance soil moisture memory in some areas of the globe, which contributes to the subseasonal and seasonal climate prediction skill. In this study, the impact of vegetation on precipitation over North America is investigated using a coupled land-atmosphere model CAM3- CLM3. The coupled model has been modified to include a predictive vegetation phenology scheme and validated against the MODIS data. Vegetation phenology is modeled by updating the leaf area index (LAI) daily in response to cumulative and concurrent hydrometeorological conditions. First, driven with the climatological SST, a large group of 5-member ensembles of simulations from the late spring and summer to the end of year are generated with the different initial conditions of soil moisture. The impact of initial soil moisture anomalies on subsequent precipitation is examined with the predictive vegetation phenology scheme disabled/enabled ("SM"/"SM_Veg" ensembles). The simulated climate differences between "SM" and "SM_Veg" ensembles represent the role of vegetation in soil moisture-vegetation- precipitation feedback. Experiments in this study focus on how the response of precipitation to initial soil moisture anomalies depends on their characteristics, including the timing, magnitude, spatial coverage and vertical depth, and further how it is modified by the interactive vegetation. Our results, for example, suggest that the impact of late spring soil moisture anomalies is not evident in subsequent precipitation until early summer when local convective precipitation dominates. With the summer wet soil moisture anomalies, vegetation tends to enhance the positive feedback between soil moisture and precipitation, while vegetation tends to suppress such positive feedback with the late spring anomalies. Second, the impact of vegetation feedback is investigated by driving the model with the inter-annually varying monthly SST (1983-1994). With the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780009499','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780009499">Microwave remote sensing and its application to soil moisture detection</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4985624','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4985624">Precipitation overrides warming in mediating soil nitrogen pools in an alpine grassland ecosystem on the Tibetan Plateau</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Lin, Li; Zhu, Biao; Chen, Chengrong; Zhang, Zhenhua; Wang, Qi-Bing; He, Jin-Sheng 2016-01-01 Soils in the alpine grassland store a large amount of nitrogen (N) due to slow decomposition. However, the decomposition could be affected by climate change, which has profound impacts on soil N cycling. We investigated the changes of soil total N and five labile N stocks in the topsoil, the subsoil and the entire soil profile in response to three years of experimental warming and altered precipitation in a Tibetan alpine grassland. We found that warming significantly increased soil nitrate N stock and decreased microbial biomass N (MBN) stock. Increased precipitation reduced nitrate N, dissolved organic N and amino acid N stocks, but increased MBN stock in the topsoil. No change in soil total N was detected under warming and altered precipitation regimes. Redundancy analysis further revealed that soil moisture (26.3%) overrode soil temperature (10.4%) in explaining the variations of soil N stocks across the treatments. Our results suggest that precipitation exerted stronger influence than warming on soil N pools in this mesic and high-elevation grassland ecosystem. This indicates that the projected rise in future precipitation may lead to a significant loss of dissolved soil N pools by stimulating the biogeochemical processes in this alpine grassland. PMID:27527683 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8087G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8087G">Soil moisture retrival from Sentinel-1 and Modis synergy</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53D0923D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53D0923D">Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29722212','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29722212">[Sap flow characteristics of Quercus liaotungensis in response to sapwood area and soil moisture in the loess hilly region, China].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=228415','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=228415">The Soil Moisture Active/Passive Mission (SMAP)</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> The Soil Moisture Active/Passive (SMAP) mission will deliver global views of soil moisture content and its freeze/thaw state that are critical terrestrial water cycle state variables. Polarized measurements obtained with a shared antenna L-band radar and radiometer system will allow accurate estima... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1213463P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1213463P">Topographical controls on soil moisture distribution and runoff response in a first order alpine catchment</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Penna, Daniele; Gobbi, Alberto; Mantese, Nicola; Borga, Marco 2010-05-01 Hydrological processes driving runoff generation in mountain basins depend on a wide number of factors which are often strictly interconnected. Among them, topography is widely recognized as one of the dominant controls influencing soil moisture distribution in the root zone, depth to water table and location and extent of saturated areas possibly prone to runoff production. Morphological properties of catchments are responsible for the alternation between steep slopes and relatively flat areas which have the potentials to control the storage/release of water and hence the hydrological response of the whole watershed. This work aims to: i) identify the role of topography as the main factor controlling the spatial distribution of near-surface soil moisture; ii) evaluate the possible switch in soil moisture spatial organization between wet and relatively dry periods and the stability of patterns during triggering of surface/subsurface runoff; iii) assess the possible connection between the develop of an ephemeral river network and the groundwater variations, examining the influence of the catchment topographical properties on the hydrological response. Hydro-meteorological data were collected in a small subcatchment (Larch Creek Catchment, 0.033 km²) of Rio Vauz basin (1.9 km²), in the eastern Italian Alps. Precipitation, discharge, water table level over a net of 14 piezometric wells and volumetric soil moisture at 0-30 cm depth were monitored continuously during the late spring-early autumn months in 2007 and 2008. Soil water content at 0-6 and 0-20 cm depth was measured manually during 22 field surveys in summer 2007 over a 44-sampling point experimental plot (approximately 3000 m²). In summer 2008 the sampling grid was extended to 64 points (approximately 4500 m²) and 28 field surveys were carried out. The length of the ephemeral stream network developed during rainfall events was assessed by a net of 24 Overland Flow Detectors (OFDs), which are able to </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70027983','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70027983">Use of soil moisture probes to estimate ground water recharge at an oil spill site</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Delin, G.N.; Herkelrath, W.N. 2005-01-01 Soil moisture data collected using an automated data logging system were used to estimate ground water recharge at a crude oil spill research site near Bemidji, Minnesota. Three different soil moisture probes were tested in the laboratory as well as the field conditions of limited power supply and extreme weather typical of northern Minnesota: a self-contained reflectometer probe, and two time domain reflectometry (TDR) probes, 30 and 50 cm long. Recharge was estimated using an unsaturated zone water balance method. Recharge estimates for 1999 using the laboratory calibrations were 13 to 30 percent greater than estimates based on the factory calibrations. Recharge indicated by the self-contained probes was 170 percent to 210 percent greater than the estimates for the TDR probes regardless of calibration method. Results indicate that the anomalously large recharge estimates for the self-contained probes are not the result of inaccurate measurements of volumetric moisture content, but result from the presence of crude oil, or bore-hole leakage. Of the probes tested, the 50 cm long TDR probe yielded recharge estimates that compared most favorably to estimates based on a method utilizing water table fluctuations. Recharge rates for this probe represented 24 to 27 percent of 1999 precipitation. Recharge based on the 30 cm long horizontal TDR probes was 29 to 37 percent of 1999 precipitation. By comparison, recharge based on the water table fluctuation method represented about 29 percent of precipitation. (JAWRA) (Copyright ?? 2005). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...8.5427D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...8.5427D">Assimilation of ASCAT near-surface soil moisture into the French SIM hydrological model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W. 2011-06-01 The impact of assimilating near-surface soil moisture into the SAFRAN-ISBA-MODCOU (SIM) hydrological model over France is examined. Specifically, the root-zone soil moisture in the ISBA land surface model is constrained over three and a half years, by assimilating the ASCAT-derived surface degree of saturation product, using a Simplified Extended Kalman Filter. In this experiment ISBA is forced with the near-real time SAFRAN analysis, which analyses the variables required to force ISBA from relevant observations available before the real time data cut-off. The assimilation results are tested against ISBA forecasts generated with a higher quality delayed cut-off SAFRAN analysis. Ideally, assimilating the ASCAT data will constrain the ISBA surface state to correct for errors in the near-real time SAFRAN forcing, the most significant of which was a substantial dry bias caused by a dry precipitation bias. The assimilation successfully reduced the mean root-zone soil moisture bias, relative to the delayed cut-off forecasts, by close to 50 % of the open-loop value. The improved soil moisture in the model then led to significant improvements in the forecast hydrological cycle, reducing the drainage, runoff, and evapotranspiration biases (by 17 %, 11 %, and 70 %, respectively). When coupled to the MODCOU hydrogeological model, the ASCAT assimilation also led to improved streamflow forecasts, increasing the mean discharge ratio, relative to the delayed cut off forecasts, from 0.68 to 0.76. These results demonstrate that assimilating near-surface soil moisture observations can effectively constrain the SIM model hydrology, while also confirming the accuracy of the ASCAT surface degree of saturation product. This latter point highlights how assimilation experiments can contribute towards the difficult issue of validating remotely sensed land surface observations over large spatial scales. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011762','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011762">Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917873G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917873G">Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090038719','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090038719">The Soil Moisture Active and Passive (SMAP) Mission</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Entekhabi, Dara; Nijoku, Eni G.; ONeill, Peggy E.; Kellogg, Kent H.; Crow, Wade T.; Edelstein, Wendy N.; Entin, Jared K.; Goodman, Shawn D.; Jackson, Thomas J.; Johnson, Joel; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20090038719'); toggleEditAbsImage('author_20090038719_show'); toggleEditAbsImage('author_20090038719_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20090038719_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20090038719_hide"> 2009-01-01 The Soil Moisture Active and Passive (SMAP) Mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy and carbon transfers between land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP soil moisture and freeze/thaw timing observations will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept would utilize an L-band radar and radiometer. These instruments will share a rotating 6-meter mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. The SMAP instruments provide direct measurements of surface conditions. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and estimates of land surface-atmosphere exchanges of water, energy and carbon. SMAP is scheduled for a 2014 launch date </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.8427B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.8427B">Soil moisture retrieval from Sentinel-1 satellite data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo 2016-04-01 Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080004233','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080004233">Method for evaluating moisture tensions of soils using spectral data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760020542','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760020542">Soil moisture and evapotranspiration predictions using Skylab data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Myers, V. I. (Principal Investigator); Moore, D. G.; Horton, M. L.; Russell, M. J. 1975-01-01 The author has identified the following significant results. Multispectral reflectance and emittance data from the Skylab workshop were evaluated for prediction of evapotranspiration and soil moisture for an irrigated region of southern Texas. Wavelengths greater than 2.1 microns were required to spectrally distinguish between wet and dry fallow surfaces. Thermal data provided a better estimate of soil moisture than did data from the reflective bands. Thermal data were dependent on soil moisture but not on the type of agricultural land use. The emittance map, when used in conjunction with existing models, did provide an estimate of evapotranspiration rates. Surveys of areas of high soil moisture can be accomplished with space altitude thermal data. Thermal data will provide a reliable input into irrigation scheduling. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900028789&hterms=drought+california&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought%2Bcalifornia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900028789&hterms=drought+california&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Ddrought%2Bcalifornia">Soil moisture and the persistence of North American drought</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010000505','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010000505">Use of Ultrasonic Technology for Soil Moisture Measurement</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356">Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29883420','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29883420">Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H13B1511O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H13B1511O">Ecohydrologic relationships of two juniper woodlands with different precipitation regimes</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ochoa, C. G.; Guldan, S. J.; Deboodt, T.; Fernald, A.; Ray, G. 2015-12-01 The significant expansion of juniper (Juniperus spp.) woodlands throughout the western U.S. during the last two centuries has disrupted important ecological functions and hydrologic processes. The relationships between water and vegetation distribution are highly impacted by the ongoing shift from shrub steppe and grassland to woodland-dominated landscapes. We investigated vegetation dynamics and hydrologic processes occurring in two distinct juniper landscapes with different precipitation regimes in the Intermountain West region: A winter snow-dominated (Oregon) and a summer rain-dominated with some winter precipitation (New Mexico) landscape. Results from the Oregon site showed marginal differences (1-2%) in soil moisture in treated vs untreated watersheds throughout the dry and wet seasons. In general, soil moisture was greater in the treated watershed in both seasons. Canopy cover affected soil moisture over time. Perennial grass cover was positively correlated with changes in soil moisture, whereas juniper cover was negatively correlated with changes in soil moisture. Shallow groundwater response observed in upland and valley monitoring wells indicate there are temporary hydrologic connections between upland and valley locations during the winter precipitation season. Results from the New Mexico site provided valuable information regarding timing and intensity of monsoon-driven precipitation and the rainfall threshold (5 mm/15 min) that triggers runoff. Long-term vegetation dynamics and hydrologic processes were evaluated based on pre- and post-juniper removal (70%) in three watersheds. In general, less runoff and greater forage response was observed in the treated watersheds. During rainfall events, soil moisture was less under juniper canopy compared with inter-canopy; this difference in soil moisture was intensified during high intensity, short duration rainstorms in the summer months. We found that winter snow precipitation helped recharge soil moisture </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910031252&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910031252&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dsoil%2Bmaps">Remotely sensed soil moisture input to a hydrologic model</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980018613','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980018613">Microstrip Ring Resonator for Soil Moisture Measurements</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Sarabandi, Kamal; Li, Eric S. 1993-01-01 Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007PhDT........79C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007PhDT........79C">Low-cost microwave radiometry for remote sensing of soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chikando, Eric Ndjoukwe 2007-12-01 Remote sensing is now widely regarded as a dominant means of studying the Earth and its surrounding atmosphere. This science is based on blackbody theory, which states that all objects emit broadband electromagnetic radiation proportional to their temperature. This thermal emission is detectable by radiometers---highly sensitive receivers capable of measuring extremely low power radiation across a continuum of frequencies. In the particular case of a soil surface, one important parameter affecting the emitted radiation is the amount of water content or, soil moisture. A high degree of precision is required when estimating soil moisture in order to yield accurate forecasting of precipitations and short-term climate variability such as storms and hurricanes. Rapid progress within the remote sensing community in tackling current limitations necessitates an awareness of the general public towards the benefits of the science. Information about remote sensing instrumentation and techniques remain inaccessible to many higher-education institutions due to the high cost of instrumentation and the current general inaccessibility of the science. In an effort to draw more talent within the field, more affordable and reliable scientific instrumentation are needed. This dissertation introduces the first low-cost handheld microwave instrumentation fully capable of surface soil moisture studies. The framework of this research is two-fold. First, the development of a low-cost handheld microwave radiometer using the well-known Dicke configuration is examined. The instrument features a super-heterodyne architecture and is designed following a microwave integrated circuit (MIC) system approach. Validation of the instrument is performed by applying it to various soil targets and comparing measurement results to gravimetric technique measured data; a proven scientific method for determining volumetric soil moisture content. Second, the development of a fully functional receiver RF front </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=325197','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=325197">Evaluation of the validated soil moisture product from the SMAP radiometer</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5260S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5260S">Comparing soil moisture memory in satellite observations and models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stacke, Tobias; Hagemann, Stefan; Loew, Alexander 2013-04-01 A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1454920','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1454920">Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Berryman, E. M.; Barnard, H. R.; Adams, H. R. Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1454920-complex-terrain-alters-temperature-moisture-limitations-forest-soil-respiration-across-semiarid-subalpine-gradient','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1454920-complex-terrain-alters-temperature-moisture-limitations-forest-soil-respiration-across-semiarid-subalpine-gradient">Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> Berryman, E. M.; Barnard, H. R.; Adams, H. R.; ... 2015-02-10 Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70147570','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70147570">Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D. 2015-01-01 Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H21C1045S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H21C1045S">Application of Cosmic-ray Soil Moisture Sensing to Understand Land-atmosphere Interactions in Three North American Monsoon Ecosystems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Schreiner-McGraw, A.; Vivoni, E. R.; Franz, T. E.; Anderson, C. 2013-12-01 Human impacts on desert ecosystems have wide ranging effects on the hydrologic cycle which, in turn, influence interactions between the critical zone and the atmosphere. In this contribution, we utilize cosmic-ray soil moisture sensors at three human-modified semiarid ecosystems in the North American monsoon region: a buffelgrass pasture in Sonora, Mexico, a woody-plant encroached savanna ecosystem in Arizona, and a woody-plant encroached shrubland ecosystem in New Mexico. In each case, landscape heterogeneity in the form of bare soil and vegetation patches of different types leads to a complex mosaic of soil moisture and land-atmosphere interactions. Historically, the measurement of spatially-averaged soil moisture at the ecosystem scale (on the order of several hundred square meters) has been problematic. Thus, new advances in measuring cosmogenically-produced neutrons present an opportunity for observational and modeling studies in these ecosystems. We discuss the calibration of the cosmic-ray soil moisture sensors at each site, present comparisons to a distributed network of in-situ measurements, and verify the spatially-aggregated observations using the watershed water balance method at two sites. We focus our efforts on the summer season 2013 and its rainfall period during the North American monsoon. To compare neutron counts to the ground sensors, we utilized an aspect-elevation weighting algorithm to compute an appropriate spatial average for the in-situ measurements. Similarly, the water balance approach utilizes precipitation, runoff, and evapotranspiration measurements in the footprint of the cosmic-ray sensors to estimate a spatially-averaged soil moisture field. Based on these complementary approaches, we empirically determined a relationship between cosmogenically-produced neutrons and the spatially-aggregated soil moisture. This approach may improve upon existing methods used to calculate soil moisture from neutron counts that typically suffer from </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41D1462D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41D1462D">L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2818899','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2818899">Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Sugiyama, Masahiro; Shiogama, Hideo; Emori, Seita 2010-01-01 Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models. PMID:20080720 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=304445','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=304445">Iowa flood studies (IFloodS) in the South Fork experimental watershed: soil moisture and precipitation monitoring</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse ¬in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived h... </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23736549','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23736549">Soil microbial responses to warming and increased precipitation and their implications for ecosystem C cycling.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Zhang, Naili; Liu, Weixing; Yang, Haijun; Yu, Xingjun; Gutknecht, Jessica L M; Zhang, Zhe; Wan, Shiqiang; Ma, Keping 2013-11-01 A better understanding of soil microbial ecology is critical to gaining an understanding of terrestrial carbon (C) cycle-climate change feedbacks. However, current knowledge limits our ability to predict microbial community dynamics in the face of multiple global change drivers and their implications for respiratory loss of soil carbon. Whether microorganisms will acclimate to climate warming and ameliorate predicted respiratory C losses is still debated. It also remains unclear how precipitation, another important climate change driver, will interact with warming to affect microorganisms and their regulation of respiratory C loss. We explore the dynamics of microorganisms and their contributions to respiratory C loss using a 4-year (2006-2009) field experiment in a semi-arid grassland with increased temperature and precipitation in a full factorial design. We found no response of mass-specific (per unit microbial biomass C) heterotrophic respiration to warming, suggesting that respiratory C loss is directly from microbial growth rather than total physiological respiratory responses to warming. Increased precipitation did stimulate both microbial biomass and mass-specific respiration, both of which make large contributions to respiratory loss of soil carbon. Taken together, these results suggest that, in semi-arid grasslands, soil moisture and related substrate availability may inhibit physiological respiratory responses to warming (where soil moisture was significantly lower), while they are not inhibited under elevated precipitation. Although we found no total physiological response to warming, warming increased bacterial C utilization (measured by BIOLOG EcoPlates) and increased bacterial oxidation of carbohydrates and phenols. Non-metric multidimensional scaling analysis as well as ANOVA testing showed that warming or increased precipitation did not change microbial community structure, which could suggest that microbial communities in semi-arid grasslands are </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/33766','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/33766">Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9693C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9693C">Exploring the Role of Soil Moisture Conditions for Rainfall Triggered Landslides on Catchment Scale: the case of the Ialomita Sub Carpathians, Romania</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331905','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331905">Downscaled soil moisture from SMAP evaluated using high density observations</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347544','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347544">Data assimilation to extract soil moisture information from SMAP observations</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/31968','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/31968">Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.8904L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.8904L">Spatial variability of soil moisture retrieved by SMOS satellite</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy 2015-04-01 Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330382','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330382">Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps">Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005PhDT.......214B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005PhDT.......214B">Soil moisture observations using L-, C-, and X-band microwave radiometers</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1513286A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1513286A">Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..535..637Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..535..637Z">Misrepresentation and amendment of soil moisture in conceptual hydrological modelling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9299E..0JW','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9299E..0JW">An integrated GIS application system for soil moisture data assimilation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24743980','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24743980">Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören 2014-01-01 Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170002025&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsoil','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170002025&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsoil">Assessment of the SMAP Passive Soil Moisture Product</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170002025'); toggleEditAbsImage('author_20170002025_show'); toggleEditAbsImage('author_20170002025_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170002025_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170002025_hide"> 2016-01-01 The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H13K1738P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H13K1738P">A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121..607L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121..607L">Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H51H1601B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H51H1601B">Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41D1464Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41D1464Y">Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4656P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4656P">Soil moisture downscaling using a simple thermal based proxy</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1132230-atmospheric-moisture-budget-spatial-resolution-dependence-precipitation-extremes-aquaplanet-simulations','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1132230-atmospheric-moisture-budget-spatial-resolution-dependence-precipitation-extremes-aquaplanet-simulations">Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080038045','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080038045">Microwave Soil Moisture Retrieval Under Trees</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> O'Neill, P.; Lang, R.; Kurum, M.; Joseph, A.; Jackson, T.; Cosh, M. 2008-01-01 Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740014835','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740014835">Detection of moisture and moisture related phenomena from Skylab. [infrared photography of Texas/New Mexico</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Eagleman, J. R.; Pogge, E. C.; Moore, R. K. (Principal Investigator); Hardy, N.; Lin, W.; League, L. 1974-01-01 The author had identified the following significant results. Soil moisture and precipitation variations were not detectable as tonal variations on the S19OA IR B and W photography. Some light tonal areas contained high precipitation .83 inches and high moisture content 21.1% while other light tonal areas contained only .02 inches precipitation and as little as 0.7% moisture. Similar variations were observed in dark tonal areas. This inconsistency may be caused by a lapse of 3 to 4 days from the time precipitation occurred until the photographs were taken and the fact that in the first inch of soil the measured soil moisture was generally less than 5.0%. For overall tonal contrast, the aerial color, color IR and aerial B and W appear to be the best. Cities stand out from the landscape best in the aerial color and color IR, however, to see major street patterns a combination of the two aerial B and W bands and the two IR B and W bands may be desirable. For mapping roads it is best use all 6 bands. For lake detection, the IR B and W bands would be the best but for streams the aerial B and W band would be better. The aerial color, color IR, and the two IR B and W bands are best for distinguishing cultivated and non-cultivated areas, whereas the two aerial B and W bands are better for seeing local relief. Clouds may be best seen in the aerial color and color IR bands. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51E1307K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51E1307K">Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kathuria, D.; Mohanty, B.; Katzfuss, M. 2017-12-01 Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016cosp...41E.369C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016cosp...41E.369C">SURFEX modeling of soil moisture fields over the Valencia Anchor Station and their comparison to different SMOS products and in situ measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Coll Pajaron, M. Amparo; Lopez-Baeza, Ernesto; Fernandez-Moran, Roberto; Samiro Khodayar-Pardo, D. 2016-07-01 Soil moisture is a difficult variable to obtain proper representation because of its high temporal and spatial variability. It is a significant parameter in agriculture, hydrology, meteorology and related disciplines. {it SVAT (Soil-Vegetation-Atmosphere-Transfer)} models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the {bf SURFEX (Surface Externalisée)} model developed at the {it Centre National de Recherches Météorologiques (CNRM)} at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the {bf Valencia Anchor Station}. SURFEX integrates the {bf ISBA (Interaction Sol-Biosphère-Atmosphère}; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) that have been adapted to describe the land covers of our study area. The Valencia Anchor Station was chosen as a core validation site for the {it SMOS (Soil Moisture and Ocean Salinity)} mission and as one of the hydrometeorological sites for the {it HyMeX (HYdrological cycle in Mediterranean EXperiment)} programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few small scattered industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields over the Valencia Anchor Station to be compared with SMOS level-2 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916428C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916428C">Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658">SMOS soil moisture validation with U.S. in situ newworks</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23579833','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23579833">Soil moisture dynamics modeling considering multi-layer root zone.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Kumar, R; Shankar, V; Jat, M K 2013-01-01 The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010WRR....46.2516B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010WRR....46.2516B">Spatial-temporal variability of soil moisture and its estimation across scales</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780">Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813014W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813014W">From ASCAT to Sentinel-1: Soil Moisture Monitoring using European C-Band Radars</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wagner, Wolfgang; Bauer-Marschallinger, Bernhard; Hochstöger, Simon 2016-04-01 The Advanced Scatterometer (ASCAT) is a C-Band radar instrument flown on board of the series of three METOP satellites. Albeit not operating in one of the more favorable longer wavelength ranges (S, L or P-band) as the dedicated Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, it is one of main microwave sensors used for monitoring of soil moisture on a global scale. Its attractiveness for soil moisture monitoring applications stems from its operational status, high radiometric accuracy and stability, short revisit time, multiple viewing directions and long heritage (Wagner et al. 2013). From an application perspective, its main limitation is its spatial resolution of about 25 km, which does not allow resolving soil moisture patterns driven by smaller-scale hydrometeorological processes (e.g. convective precipitation, runoff patterns, etc.) that are themselves related to highly variable land surface characteristics (soil characteristics, topography, vegetation cover, etc.). Fortunately, the technique of aperture synthesis allows to significantly improve the spatial resolution of spaceborne radar instruments up to the meter scale. Yet, past Synthetic Aperture Radar (SAR) missions had not yet been designed to achieve a short revisit time required for soil moisture monitoring. This has only changed recently with the development and launch of SMAP (Entekhabi et al. 2010) and Sentinel-1 (Hornacek et al. 2012). Unfortunately, the SMAP radar failed only after a few months of operations, which leaves Sentinel-1 as the only currently operational SAR mission capable of delivering high-resolution radar observations with a revisit time of about three days for Europe, about weekly for most crop growing regions worldwide, and about bi-weekly to monthly over the rest of the land surface area. Like ASCAT, Sentinel-1 acquires C-band backscatter data in VV polarization over land. Therefore, for the interpretation of both ASCAT and Sentinel-1 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23B1649J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23B1649J">Effects of Afforestation and Natural Revegetation on Soil Moisture Dynamics in Paired Watersheds in the Loess Plateau of China</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jin, Z.; Guo, L.; Lin, H.; Wang, Y.; Chu, G. 2017-12-01 In this study, a paired of small watersheds, which are artificial forestland and natural grassland, respectively, were selected. The two watersheds have been set up since 1954 and the time of revegetation is more than 60 years. Their differences in event and seasonal dynamics of soil moisture were investigated and the effects of vegetation and landform were analyzed. Results showed that consecutive small events higher than 22 mm and single events higher than 16.6 mm could recharge the soil moisture of the two watersheds, but no rainfall event was observed to recharge the soil moisture of 100 cm within 2 weeks after rainfall initiation. Moreover, the two contrasting watersheds showed no difference in rainfall threshold for effective soil moisture replenishment and also had similar patterns of soil water increment with the increase of initial soil water content and rainfall intensity. The changing vegetation cover and coverage at different landforms (uphill slope land and downhill gully) showed the most significant impact on event and seasonal dynamics of soil moisture. The strong interception, evaporation and transpiration of tree canopy and understory vegetation in the gully of the forestland showed the most negative impacts on soil moisture replenishment. Moreover, dense surface grass biomass (living and dead) in the grassland also showed negative impacts on effective soil moisture recharge. Landform itself showed no significant impact on event soil moisture dynamics through changing the initial soil water content and soil texture, while site differences in slope gradient and soil temperature could affect the seasonal soil water content. During the growing season of May-October, the forestland showed 1.3% higher soil water content than that of the grassland in the landform of uphill slope land; while in the landform of downhill gully, the grassland showed 4.3% higher soil water content than that of the forestland. Many studies have predicted that there will be </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29726179','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29726179">[Rainfall and soil moisture redistribution induced by xerophytic shrubs in an arid desert ecosystem].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Wang, Zheng Ning; Wang, Xin Ping; Liu, Bo 2016-03-01 Rainfall partitioning by desert shrub canopy modifies the redistribution of incident rainfall under the canopy, and may affect the distribution pattern of soil moisture around the plant. This study examined the distribution of rainfall and the response of soil moisture beneath the canopy of two dominant desert shrubs, Caragana korshinskii and Artemisia ordosica, in the revegetation area at the southeastern edge of the Tengger Desert. The results showed that throughfall and stemflow ave-ragely occupied 74.4%, 11.3% and 61.8%, 5.5% of the gross precipitation for C. korshinskii and A. ordosica, respectively. The mean coefficients of variation (CV) of throughfall were 0.25 and 0.30, respectively. C. korshinski were more efficient than A. ordosica on stemflow generation. The depth of soil wetting front around the stem area was greater than other areas under shrub canopy for C. korshinski, and it was only significantly greater under bigger rain events for A. ordosica. The shrub canopy could cause the unevenness of soil wetting front under the canopy in consequence of rainfall redistribution induced by xerophytic shrub. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3106F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3106F">Integration of soil moisture and geophysical datasets for improved water resource management in irrigated systems</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Finkenbiner, Catherine; Franz, Trenton E.; Avery, William Alexander; Heeren, Derek M. 2016-04-01 Global trends in consumptive water use indicate a growing and unsustainable reliance on water resources. Approximately 40% of total food production originates from irrigated agriculture. With increasing crop yield demands, water use efficiency must increase to maintain a stable food and water trade. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Fixed and roving cosmic-ray neutron probes were combined in order to characterize the spatial and temporal patterns of soil moisture at three study sites across an East-West precipitation gradient in the state of Nebraska, USA. A coarse scale map was generated for the entire domain (122 km2) at each study site. We used a simplistic data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler (˜102m2) for variable rate irrigation, the individual wedge (˜103m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. Additionally, we were able to generate a daily soil moisture product over the entire study area at various key modeling and remote sensing scales 12, 32, and 122 km2. Our soil moisture products and derived soil properties were then compared against spatial datasets (i.e. field capacity and wilting point) from the US Department of Agriculture Web Soil Survey. The results show that our "observed" field capacity was higher compared to the Web Soil Survey products. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depth and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of this non-contact and pragmatic geophysical method into current irrigation practices across the state and globe has the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820018884','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820018884">Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.3523S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.3523S">Is soil moisture initialization important for seasonal to decadal predictions?</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19890058149&hterms=LOSS+SOIL&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DLOSS%2BSOIL','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19890058149&hterms=LOSS+SOIL&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DLOSS%2BSOIL">Mapping surface soil moisture with L-band radiometric measurements</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H13I1516C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H13I1516C">SMERGE: A multi-decadal root-zone soil moisture product for CONUS</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B34C..06G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B34C..06G">Global response of the growing season to soil moisture and topography</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19223120','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19223120">Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1588H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1588H">An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hunt, E. D.; Otkin, J.; Zhong, Y. 2017-12-01 Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M">A Round Robin evaluation of AMSR-E soil moisture retrievals</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004SPIE.5590...84C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004SPIE.5590...84C">Microstrip transmission line for soil moisture measurement</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chen, Xuemin; Li, Jing; Liang, Renyue; Sun, Yijie; Liu, C. Richard; Rogers, Richard; Claros, German 2004-12-01 Pavement life span is often affected by the amount of voids in the base and subgrade soils, especially moisture content in pavement. Most available moisture sensors are based on the capacitive sensing using planar blades. Since the planar sensor blades are fabricated on the same surface to reduce the overall size of the sensor, such structure cannot provide very high accuracy for moisture content measurement. As a consequence, a typical capacitive moisture sensor has an error in the range of 30%. A more accurate measurement is based on the time domain refelctometer (TDR) measurement. However, typical TDR system is fairly expensive equipment, very large in size, and difficult to operate, the moisture content measurement is limited. In this paper, a novel microstrip transmission line based moisture sensor is presented. This sensor uses the phase shift measurement of RF signal going through a transmission line buried in the soil to be measured. Since the amplitude of the transmission measurement is a strong function of the conductivity (loss of the media) and the imaginary part of dielectric constant, and the phase is mainly a strong function of the real part of the dielectric constant, measuring phase shift in transmission mode can directly obtain the soil moisture information. This sensor was designed and implemented. Sensor networking was devised. Both lab and field data show that this sensor is sensitive and accurate. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H13C1117R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H13C1117R">The influence of subsurface hydrodynamics on convective precipitation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rahman, A. S. M. M.; Sulis, M.; Kollet, S. J. 2014-12-01 The terrestrial hydrological cycle comprises complex processes in the subsurface, land surface, and atmosphere, which are connected via complex non-linear feedback mechanisms. The influence of subsurface hydrodynamics on land surface mass and energy fluxes has been the subject of previous studies. Several studies have also investigated the soil moisture-precipitation feedback, neglecting however the connection with groundwater dynamics. The objective of this study is to examine the impact of subsurface hydrodynamics on convective precipitation events via shallow soil moisture and land surface processes. A scale-consistent Terrestrial System Modeling Platform (TerrSysMP) that consists of an atmospheric model (COSMO), a land surface model (CLM), and a three-dimensional variably saturated groundwater-surface water flow model (ParFlow), is used to simulate hourly mass and energy fluxes over days with convective rainfall events over the Rur catchment, Germany. In order to isolate the effect of groundwater dynamics on convective precipitation, two different model configurations with identical initial conditions are considered. The first configuration allows the groundwater table to evolve through time, while a spatially distributed, temporally constant groundwater table is prescribed as a lower boundary condition in the second configuration. The simulation results suggest that groundwater dynamics influence land surface soil moisture, which in turn affects the atmospheric boundary layer (ABL) height by modifying atmospheric thermals. It is demonstrated that because of this sensitivity of ABL height to soil moisture-temperature feedback, the onset and magnitude of convective precipitation is influenced by subsurface hydrodynamics. Thus, the results provide insight into the soil moisture-precipitation feedback including groundwater dynamics in a physically consistent manner by closing the water cycle from aquifers to the atmosphere. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810059143&hterms=801&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3D801','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810059143&hterms=801&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3D801">Aircraft active microwave measurements for estimating soil moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Jackson, T. J.; Chang, A.; Schmugge, T. J. 1981-01-01 Both active and passive microwave sensors are sensitive to variations in near-surface soil moisture. The principal advantage of active microwave systems for soil moisture applications is that high spatial resolution can be retained even at satellite attitudes. The considered investigation is concerned with the use of active microwave scatterometers for estimating near-surface soil moisture. Microwave scatterometer data were obtained during a series of three aircraft flights over a group of Oklahoma research watersheds during May 1978. Data were obtained for the C, L, and P bands at angles of incidence between 5 and 50 degrees. The best results were obtained using C band data at incidence angles of 10 and 15 degrees and soil moisture depth of 0 to 15 cm. These results were in excellent agreement with the conclusions of the truck-mounted scatterometer measurement program reported by Ulaby et al. (1978, 1979). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19730000503','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19730000503">Soil moisture by extraction and gas chromatography</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Merek, E. L.; Carle, G. C. 1973-01-01 To determine moisture content of soils rapidly and conveniently extract moisture with methanol and determine water content of methanol extract by gas chromatography. Moisture content of sample is calculated from weight of water and methanol in aliquot and weight of methanol added to sample. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26098202','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26098202">Galvanic Cell Type Sensor for Soil Moisture Analysis.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Gaikwad, Pramod; Devendrachari, Mruthyunjayachari Chattanahalli; Thimmappa, Ravikumar; Paswan, Bhuneshwar; Raja Kottaichamy, Alagar; Makri Nimbegondi Kotresh, Harish; Thotiyl, Musthafa Ottakam 2015-07-21 Here we report the first potentiometric sensor for soil moisture analysis by bringing in the concept of Galvanic cells wherein the redox energies of Al and conducting polyaniline are exploited to design a battery type sensor. The sensor consists of only simple architectural components, and as such they are inexpensive and lightweight, making it suitable for on-site analysis. The sensing mechanism is proved to be identical to a battery type discharge reaction wherein polyaniline redox energy changes from the conducting to the nonconducting state with a resulting voltage shift in the presence of soil moisture. Unlike the state of the art soil moisture sensors, a signal derived from the proposed moisture sensor is probe size independent, as it is potentiometric in nature and, hence, can be fabricated in any shape or size and can provide a consistent output signal under the strong aberration conditions often encountered in soil moisture analysis. The sensor is regenerable by treating with 1 M HCl and can be used for multiple analysis with little read out hysteresis. Further, a portable sensor is fabricated which can provide warning signals to the end user when the moisture levels in the soil go below critically low levels, thereby functioning as a smart device. As the sensor is inexpensive, portable, and potentiometric, it opens up avenues for developing effective and energy efficient irrigation strategies, understanding the heat and water transfer at the atmosphere-land interface, understanding soil mechanics, forecasting the risk of natural calamities, and so on. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4569388','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4569388">Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Wernerehl, Robert W.; Givnish, Thomas J. 2015-01-01 Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis’ continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward “drier” sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500–1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward “wetter” sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26368936','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26368936">Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Wernerehl, Robert W; Givnish, Thomas J 2015-01-01 Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis' continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward "drier" sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500-1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward "wetter" sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/10464','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/10464">Soil moisture-soil temperature interrelationships on a sandy-loam soil exposed to full sunlight</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D">Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023007','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023007">Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=300473','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=300473">Soil animal responses to moisture availability are largely scale, not ecosystem dependent: Insight from a cross-site study</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Climate change will result in reduced soil water availability in much of the world either due to changes in precipitation or increased temperature and evapotranspiration. Responses of communities of mites and nematodes to changes in moisture availability are not well known, yet these organisms play ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=336401','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=336401">Use of soil moisture sensors for irrigation scheduling</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Various types of soil moisture sensing devices have been developed and are commercially available for water management applications. Each type of soil moisture sensors has its advantages and shortcomings in terms of accuracy, reliability, and cost. Resistive and capacitive based sensors, and time-d... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70185708','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70185708">Divergent surface and total soil moisture projections under global warming</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830006286','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830006286">Investigation of remote sensing techniques of measuring soil moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100003344&hterms=by-product&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dby-product','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100003344&hterms=by-product&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dby-product">The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John 2010-01-01 that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B">Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L. 2017-12-01 Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27764203','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27764203">The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5072646','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5072646">The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> 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 </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17..830S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17..830S">Assessment of soil moisture dynamics on an irrigated maize field using cosmic ray neutron sensing</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E. 2015-04-01 In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate soil moisture at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is affected by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting soil moisture. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three soil sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different soil sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and soil organic carbon, thus representing an equivalent water content of the soil, the differences decreased. Soil moisture estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the soil moisture determined with point scale measurements but they are less affected by the heterogeneous moisture conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760025537','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760025537">Remote sensing of soil moisture with microwave radiometers</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmugge, T.; Wilheit, T.; Webster, W., Jr.; Gloerson, P. 1976-01-01 Results are presented that were derived from measurements made by microwave radiometers during the March 1972 and February 1973 flights of National Aeronautics and Space Administration (NASA) Convair-9900 aircraft over agricultural test sites in the southwestern part of United States. The purpose of the missions was to study the use of microwave radiometers for the remote sensing of soil moisture. The microwave radiometers covered the 0.8- to 21-cm wavelength range. The results show a good linear correlation between the observed microwave brightness temperature and moisture content of the 0- to 1-cm layer of the soil. The results at the largest wavelength (21 cm) show the greatest sensitivity to soil moisture variations and indicate the possibility of sensing these variations through a vegetative canopy. The effect of soil texture on the emission from the soil was also studied and it was found that this effect can be compensated for by expressing soil moisture as a percent of field capacity for the soil. The results were compared with calculations based on a radiative transfer model for layered dielectrics and the agreement is very good at the longer wavelengths. At the shorter wavelengths, surface roughness effects are larger and the agreement becomes poorer. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H31A1391G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H31A1391G">Evaluating Land-Atmosphere Interactions with the North American Soil Moisture Database</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/ds/725/pdf/ds725.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/ds/725/pdf/ds725.pdf">Micrometeorological, evapotranspiration, and soil-moisture data at the Amargosa Desert Research site in Nye County near Beatty, Nevada, 2006-11</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Arthur, Jonathan M.; Johnson, Michael J.; Mayers, C. Justin; Andraski, Brian J. 2012-11-13 This report describes micrometeorological, evapotranspiration, and soil-moisture data collected since 2006 at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada. Micrometeorological data include precipitation, solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, near-surface soil temperature, soil-heat flux, and soil-water content. Evapotranspiration (ET) data include latent-heat flux, sensible-heat flux, net radiation, soil-heat flux, soil temperature, air temperature, vapor pressure, and other principal energy-budget data. Soil-moisture data include periodic measurements of volumetric water-content at experimental sites that represent vegetated native soil, devegetated native soil, and simulated waste disposal trenches - maximum measurement depths range from 5.25 to 29.25 meters. All data are compiled in electronic spreadsheets that are included with this report. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810020962','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810020962">Soil moisture inferences from thermal infrared measurements of vegetation temperatures</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70184223','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70184223">Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=317570','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=317570">Recent advances in (soil moisture) triple collocation analysis</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> To date, triple collocation (TC) analysis is one of the most important methods for the global scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method.... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170006035','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170006035">Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Akbar, Ruzbeh; Cosh, Michael H.; O'Neill, Peggy E.; Entekhabi, Dara; Moghaddam, Mahta 2017-01-01 A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal soil moisture retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithms performance and to demonstrate soil moisture estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3cm3 for two different land cover types of corn and soybean. In summary, in the context of soil moisture retrieval, the importance of consistent forward emission and scattering development is discussed and presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29657350','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29657350">Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Akbar, Ruzbeh; Cosh, Michael H; O'Neill, Peggy E; Entekhabi, Dara; Moghaddam, Mahta 2017-07-01 A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal soil moisture retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithm's performance and to demonstrate soil moisture estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3/cm3 for two different land cover types of corn and soybean. In summary, in the context of soil moisture retrieval, the importance of consistent forward emission and scattering development is discussed and presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1592K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1592K">Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R. 2017-12-01 The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN21A1724P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN21A1724P">A Citizen Science Soil Moisture Sensor to Support SMAP Calibration/Validation</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..562..635S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..562..635S">Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Suo, Lizhu; Huang, Mingbin; Zhang, Yongkun; Duan, Liangxia; Shan, Yan 2018-07-01 Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R2) and goodness of prediction (Q2) were >0.5 and >0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6692U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6692U">An inversion method for retrieving soil moisture information from satellite altimetry observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H21C1423J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H21C1423J">Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034418','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034418">Response of spectral vegetation indices to soil moisture in grasslands and shrublands</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H43C0976J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H43C0976J">Mode Decomposition Methods for Soil Moisture Prediction</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jana, R. B.; Efendiev, Y. R.; Mohanty, B. 2014-12-01 Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004JGRD..10910102F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004JGRD..10910102F">Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fan, Yun; van den Dool, Huug 2004-05-01 We have produced a 0.5° × 0.5° monthly global soil moisture data set for the period from 1948 to the present. The land model is a one-layer "bucket" water balance model, while the driving input fields are Climate Prediction Center monthly global precipitation over land, which uses over 17,000 gauges worldwide, and monthly global temperature from global Reanalysis. The output consists of global monthly soil moisture, evaporation, and runoff, starting from January 1948. A distinguishing feature of this data set is that all fields are updated monthly, which greatly enhances utility for near-real-time purposes. Data validation shows that the land model does well; both the simulated annual cycle and interannual variability of soil moisture are reasonably good against the limited observations in different regions. A data analysis reveals that, on average, the land surface water balance components have a stronger annual cycle in the Southern Hemisphere than those in the Northern Hemisphere. From the point of view of soil moisture, climates can be characterized into two types, monsoonal and midlatitude climates, with the monsoonal ones covering most of the low-latitude land areas and showing a more prominent annual variation. A global soil moisture empirical orthogonal function analysis and time series of hemisphere means reveal some interesting patterns (like El Niño-Southern Oscillation) and long-term trends in both regional and global scales. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015242','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015242">The NASA Soil Moisture Active Passive (SMAP) Mission: Overview</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> O'Neill, Peggy; Entekhabi, Dara; Njoku, Eni; Kellogg, Kent 2011-01-01 The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council?s Decadal Survey [1]. Its mission design consists of L-band radiometer and radar instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every 2-3 days. The combined active/passive microwave soil moisture product will have a spatial resolution of 10 km and a mean latency of 24 hours. In addition, the SMAP surface observations will be combined with advanced modeling and data assimilation to provide deeper root zone soil moisture and net ecosystem exchange of carbon. SMAP is expected to launch in the late 2014 - early 2015 time frame. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007932','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007932">SMAP Level 4 Surface and Root Zone Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R. 2017-01-01 The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050210137','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050210137">AGCM Biases in Evaporation Regime: Impacts on Soil Moisture Memory and Land-Atmosphere Feedback</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Mahanama, Sarith P. P.; Koster, Randal D. 2005-01-01 Because precipitation and net radiation in an atmospheric general circulation model (AGCM) are typically biased relative to observations, the simulated evaporative regime of a region may be biased, with consequent negative effects on the AGCM s ability to translate an initialized soil moisture anomaly into an improved seasonal prediction. These potential problems are investigated through extensive offline analyses with the Mosaic land surface model (LSM). We first forced the LSM globally with a 15-year observations-based dataset. We then repeated the simulation after imposing a representative set of GCM climate biases onto the forcings - the observational forcings were scaled so that their mean seasonal cycles matched those simulated by the NSIPP-1 (NASA Global Modeling and Assimilation Office) AGCM over the same period-The AGCM s climate biases do indeed lead to significant biases in evaporative regime in certain regions, with the expected impacts on soil moisture memory timescales. Furthermore, the offline simulations suggest that the biased forcing in the AGCM should contribute to overestimated feedback in certain parts of North America - parts already identified in previous studies as having excessive feedback. The present study thus supports the notion that the reduction of climate biases in the AGCM will lead to more appropriate translations of soil moisture initialization into seasonal prediction skill. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813">Validation of SMAP surface soil moisture products with core validation sites</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007420','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007420">Development and Validation of The SMAP Enhanced Passive Soil Moisture Product</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chan, S.; Bindlish, R.; O'Neill, P.; Jackson, T.; Chaubell, J.; Piepmeier, J.; Dunbar, S.; Colliander, A.; Chen, F.; Entekhabi, D.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170007420'); toggleEditAbsImage('author_20170007420_show'); toggleEditAbsImage('author_20170007420_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170007420_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170007420_hide"> 2017-01-01 Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110016746','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110016746">Radar for Measuring Soil Moisture Under Vegetation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya 2004-01-01 A two-frequency, polarimetric, spaceborne synthetic-aperture radar (SAR) system has been proposed for measuring the moisture content of soil as a function of depth, even in the presence of overlying vegetation. These measurements are needed because data on soil moisture under vegetation canopies are not available now and are necessary for completing mathematical models of global energy and water balance with major implications for global variations in weather and climate. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.7170B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.7170B">Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=298905','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=298905">Land surface controls on afternoon precipitation diagnosed from observational data: Uncertainties and confounding factors</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface fluxes (the Evaporative F... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810004909','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810004909">Joint microwave and infrared studies for soil moisture determination</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..536..327M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..536..327M">Examining diel patterns of soil and xylem moisture using electrical resistivity imaging</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28632172','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28632172">Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea 2017-06-20 This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5492425','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5492425">Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea 2017-01-01 This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil. PMID:28632172 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098">On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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 ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B41F0375S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B41F0375S">Effects of experimental warming on soil temperature, moisture and respiration in northern Mongolia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sharkhuu, A.; Plante, A. F.; Casper, B. B.; Helliker, B. R.; Liancourt, P.; Boldgiv, B.; Petraitis, P. 2010-12-01 Mean annual air temperature in the Lake Hövsgöl region of northern Mongolia has increased by 1.8 °C over the last 40 years, greater than global average temperature increases. A decrease of soil moisture due to changes in precipitation regime is also predicted over the northern region of Mongolia. Warmer temperatures generally result in higher soil CO2 efflux, but responses of soil efflux to climate change may differ among ecosystems due to response variations in soil temperature and moisture regime. The objectives of our study were to examine the environmental responses (soil temperature and moisture) to experimental warming, and to test responses of soil CO2 efflux to experimental warming, in three different ecozones. The experimental site is located in Dalbay Valley, on the eastern shore of Lake Hövsgöl in northern Mongolia (51.0234° N 100.7600° E; 1670 m elevation). Replicate plots with ITEX-style open-top passive warming chambers (OTC) and non-warmed control areas were installed in three ecosystems: (1) semi-arid grassland on the south-facing slope not underlain by permafrost, (2) riparian zone, and (3) larch forest on the north-facing slope underlain by permafrost. Aboveground air temperature and belowground soil temperature and moisture (10 and 20 cm) were monitored using sensors and dataloggers. Soil CO2 efflux was measured periodically using a portable infra-red gas analyzer with an attached soil respiration chamber. The warming chambers were installed and data collected during the 2009 and 2010 growing seasons. Passive warming chambers increased nighttime air temperatures; more so in grassland compared to the forest. Increases in daytime air temperatures were observed in the grassland, but were not significant in the riparian and forest areas. Soil temperatures in warmed plots were consistently higher in all three ecozones at 10 cm depth but not at 20 cm depth. Warming chambers had a slight drying effect in the grassland, but no consistent effect in </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/11472','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/11472">Acid precipitation and forest soils</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> C. O. Tamm 1976-01-01 Many soil processes and properties may be affected by a change in chemical climate such as that caused by acidification of precipitation. The effect of additions of acid precipitation depends at first on the extent to which this acid is really absorbed by the soil and on the changes in substances with actual or potential acidity leaving the soil. There is for instance... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017SPIE10426E..0JH','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017SPIE10426E..0JH">Creating soil moisture maps based on radar satellite imagery</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr 2017-10-01 The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186">Hydrologic downscaling of soil moisture using global data without site-specific calibration</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D">On the assimilation of satellite derived soil moisture in numerical weather prediction models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711676H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711676H">Soil moisture trends in the Czech Republic between 1961 and 2012</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hlavinka, Petr; Trnka, Miroslav; Brázdil, Rudolf; Možný, Martin; Štěpánek, Petr; Dobrovolný, Petr; Zahradníček, Pavel; Balek, Jan; Semerádová, Daniela; Dubrovský, Martin; Eitzinger, Josef; Wardlow, Brian; Svoboda, Mark; Hayes, Michael; Žalud, Zdeněk 2015-04-01 Central Europe is generally not considered a drought-prone region, and the drought research and support is traditionally focused on the Mediterranean and southeastern part of the continent and drying trends there. However, Central Europe, including the Czech Republic, recently experienced a series of drought events with substantial impacts, especially on crop production. Because agriculture systems, and vegetation in general, have adapted to evenly distributed precipitation, the region is susceptible to even short-term droughts. The recent drought events may be the result of multi-decadal climate variability or a more general trend, with some studies showing a link to a more frequent occurrence of atmospheric circulation patterns that are conducive to drought. This study introduces an innovation to the standard methodological approaches in evaluating drought climatology by analyzing soil moisture conditions over more than fifty years. This approach relies on state-of-the art observed weather data and tested soil moisture model, and focuses on the dynamic simulation of soil moisture content with high temporal (daily) and spatial (500 m) resolution in a diverse landscape. Statistically significant trends of decreasing soil moisture content were found, notably during May and June between 1961 and 2012. In contrast, trends toward higher soil moisture content were noted during the October-March time period. When the periods of 2001-2012 and 1961-1980 were compared, the probability of drought between April and June was found to increase by 50%. This indicates a loading of the "climate dice" toward drier conditions. The probability of extreme drought events has been also found to increase. These results support the concerns about the potentially increased severity of drought events in Central Europe under projected climate change and has been submitted to International Journal of Climatology. The study was funded by project "Establishment of International Scientific Team </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1615537S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1615537S">SMALT - Soil Moisture from Altimetry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Smith, Richard; Salloway, Mark; Berry, Philippa; Hahn, Sebastian; Wagner, Wolfgang; Egido, Alejandro; Dinardo, Salvatore; Lucas, Bruno Manuel; Benveniste, Jerome 2014-05-01 Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. DREAMS have been created over a number of arid and semi-arid deserts worldwide to produce historical SMALT timeseries over soil moisture variation. These products are available in two formats - a high resolution track product which utilises the altimeter's high frequency content alongtrack and a multi-looked 6" gridded product at facilitate easy comparison/integeration with other remote sensing techniques. An overview of the SMALT processing scheme, covering the progression of the data from altimeter sigma0 through to final soil moisture estimate, is included along with example SMALT products. Validation has been performed over a number of deserts by comparing SMALT products with other remote sensing techniques, results of the comparison between SMALT and Metop Warp 5.5 are presented here. Comparisons with other remote sensing techniques have been limited in scope due to differences in the operational aspects of the instruments, the restricted geographical coverage of the DREAMS and the low repeat temporal sampling rate of the altimeter. The potential to expand the SMALT technique into less arid areas has been investigated. Small-scale comparison with in-situ and GNSS-R data obtained by the LEiMON experimental campaign over Tuscany, where historical trends exist within both SMALT and SMC probe datasets. A qualitative analysis of unexpected backscatter characteristics in dedicated dry environments is performed with </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013">Calibration and validation of the COSMOS rover for surface soil moisture</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> 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... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H53J1615A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H53J1615A">Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=337772','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=337772">Soil moisture remote sensing: State of the science</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac... </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1595M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1595M">A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000116624','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000116624">BOREAS HYD-6 Ground Gravimetric Soil Moisture Data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Carroll, Thomas; Knapp, David E. (Editor); Hall, Forrest G. (Editor); Peck, Eugene L.; Smith, David E. (Technical Monitor) 2000-01-01 The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H54D..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H54D..04D">Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N. 2015-12-01 Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESS...19.3845T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESS...19.3845T">Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=338693','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=338693">Combined radar-radiometer surface soil moisture and roughness estimation</a> <a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution rad... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4607364','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4607364">Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29604221','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29604221">Quantifying soil moisture impacts on light use efficiency across biomes.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I 2018-06-01 Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913342B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913342B">Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16345610','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16345610">Variation in microbial activity in histosols and its relationship to soil moisture.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120016510','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120016510">Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T">Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.5338W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.5338W">Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M. 2012-04-01 Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011773','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011773">NASA Soil Moisture Active Passive (SMAP) Mission Formulation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared 2011-01-01 The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29143143','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29143143">Soil respiration patterns and rates at three Taiwanese forest plantations: dependence on elevation, temperature, precipitation, and litterfall.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Huang, Yu-Hsuan; Hung, Chih-Yu; Lin, I-Rhy; Kume, Tomonori; Menyailo, Oleg V; Cheng, Chih-Hsin 2017-11-15 Soil respiration contributes to a large quantity of carbon emissions in the forest ecosystem. In this study, the soil respiration rates at three Taiwanese forest plantations (two lowland and one mid-elevation) were investigated. We aimed to determine how soil respiration varies between lowland and mid-elevation forest plantations and identify the relative importance of biotic and abiotic factors affecting soil respiration. The results showed that the temporal patterns of soil respiration rates were mainly influenced by soil temperature and soil water content, and a combined soil temperature and soil water content model explained 54-80% of the variation. However, these two factors affected soil respiration differently. Soil temperature positively contributed to soil respiration, but a bidirectional relationship between soil respiration and soil water content was revealed. Higher soil moisture content resulted in higher soil respiration rates at the lowland plantations but led to adverse effects at the mid-elevation plantation. The annual soil respiration rates were estimated as 14.3-20.0 Mg C ha -1 year -1 at the lowland plantations and 7.0-12.2 Mg C ha -1 year -1 at the mid-elevation plantation. When assembled with the findings of previous studies, the annual soil respiration rates increased with the mean annual temperature and litterfall but decreased with elevation and the mean annual precipitation. A conceptual model of the biotic and abiotic factors affecting the spatial and temporal patterns of the soil respiration rate was developed. Three determinant factors were proposed: (i) elevation, (ii) stand characteristics, and (iii) soil temperature and soil moisture. The results indicated that changes in temperature and precipitation significantly affect soil respiration. Because of the high variability of soil respiration, more studies and data syntheses are required to accurately predict soil respiration in Taiwanese forests. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESSD..12.2945T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESSD..12.2945T">Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064542&hterms=desertification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Ddesertification','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064542&hterms=desertification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Ddesertification">Estimating Soil Moisture from Satellite Microwave Observations</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E. 1998-01-01 Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70040458','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70040458">Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Ralph, F.M.; Coleman, T.; Neiman, P.J.; Zamora, R.J.; Dettinger, Mike 2013-01-01 This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004-10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitation and runoff requires accurate prediction of AR duration at landfall and observations of precursor soil moisture conditions. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017RvGeo..55..341P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017RvGeo..55..341P">A review of spatial downscaling of satellite remotely sensed soil moisture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5087863','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5087863">Effects of Soil Temperature and Moisture on Soil Respiration on the Tibetan Plateau</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying 2016-01-01 Understanding of effects of soil temperature and soil moisture on soil respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two soil moistures (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow. PMID:27798671 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.7936B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.7936B">Investigating local controls on soil moisture temporal stability using an inverse modeling approach</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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Sample records for precipitation soil moisture