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1

Spectrum properties analysis of different soil moisture content  

Microsoft Academic Search

Soil moisture content is one of the most important factors in soil business. The basic of detecting soil moisture content using remote sensing technology is to analyze the relationship between soil moisture content and emissivity. In this paper, based on the analysis of spectrum collection and processing by a portable spectrometer, a set of measure schemes were first established which

Shenghui Fang; Bo Hu; Fan Lin

2009-01-01

2

Soil Moisture  

NSDL National Science Digital Library

NOAA's Climate Prediction Center offers this useful data site on soil moisture across the US. Soil moisture data are provided here as color contour maps that represent calculated soil moisture, anomalies, and percentiles for the most recent day, monthly, and twelve-month time periods. Also provided here are 25-year average soil moisture & soil wetness summaries. In addition to providing recent and historical data, the Soil Moisture site features soil moisture forecasts for two-week, monthly, and seasonal intervals, based on the National Weather Service Medium Range Forecast (MRF) and the Constructed Analog on Soil Moisture (CAS).

2000-01-01

3

Analysis and modeling of soil moisture in Jiangsu, China  

NASA Astrophysics Data System (ADS)

There are large uncertainties in the observation of soil moisture. This study compares the two observation datasets of soil moisture data, including automatic and manual measurements, in Jiangsu Province, China from 2010 to 2012. More than 30 automatic monitoring instruments of soil moisture have been installed in Jiangsu since 2010. However, the automatic stations show various uncertainties, including improper site selection, such as shallow soil depth on rocks, underground river, and artificial soil. Compared to the manual observations, the values of automatic observations usually are lower, except for over saturation condition. With increasing soil depths, soil moisture of automatic observation becomes more stable with less variance and shows larger discrepancies with manual observations. Automatic measurements have greater advantage in temporal and spatial coverage, and indicate better relationship with observed precipitation patterns. At eight depths from 10 cm to 100 cm, manual soil moisture observations largely fluctuate than automatic ones, especially under relatively dry conditions. In general, observation errors in automatic measurements need careful analysis, and automatic measurements with quality control are more accurate in representing real soil moisture, and are less influenced by precipitation conditions. Also, the observed soil moisture data is used to evaluate the simulated soil moisture using the Weather Research and Forecasting (WRF) model and the global forecast system (GFS) model in July, 2012. Both models select the Noah land surface model and produce soil moisture for four layers. Several extremely dry periods are also investigated to predict potential drought using soil moisture.

Yuan, H.; Sun, R.; Fei, Q.

2013-12-01

4

Soil Moisture  

NSDL National Science Digital Library

This Flash animation renders the pattern of soil moisture storage at the surface. The increase/decrease in soil moisture are especially apparent for the in Africa because of the annual north-south march of the wet InterTropical Convergence Zone (ITC). In the Flash format, the animation can easily be rewound or paused to stress important points.

Climvis.org

5

Microwave soil moisture measurements and analysis  

NASA Technical Reports Server (NTRS)

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

Newton, R. W.; Howell, T. A.; Nieber, J. L.; Vanbavel, C. H. M. (principal investigators)

1980-01-01

6

Soil Moisture Project Evaluation Workshop  

NASA Technical Reports Server (NTRS)

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.

Gilbert, R. H. (editor)

1980-01-01

7

Parameter Sensitivity in LSMs: An Analysis Using Stochastic Soil Moisture Models and ELDAS Soil Parameters  

Microsoft Academic Search

Integration of simulated and observed states through data assimilation as well as model evaluation requires a realistic representation of soil moisture in land surface models (LSMs). However, soil moisture in LSMs is sensitive to a range of uncertain input parameters, and intermodel differences in parameter values are often large. Here, the effect of soil parameters on soil moisture and evapotranspiration

Adriaan J. Teuling; Remko Uijlenhoet; Bart van den Hurk; Sonia I. Seneviratne

2009-01-01

8

Correcting rainfall using satellite-based surface soil moisture retrievals: The Soil Moisture Analysis Rainfall Tool (SMART)  

NASA Astrophysics Data System (ADS)

Recently, Crow et al. (2009) developed an algorithm for enhancing satellite-based land rainfall products via the assimilation of remotely sensed surface soil moisture retrievals into a water balance model. As a follow-up, this paper describes the benefits of modifying their approach to incorporate more complex data assimilation and land surface modeling methodologies. Specific modifications improving rainfall estimates are assembled into the Soil Moisture Analysis Rainfall Tool (SMART), and the resulting algorithm is applied outside the contiguous United States for the first time, with an emphasis on West African sites instrumented as part of the African Monsoon Multidisciplinary Analysis experiment. Results demonstrate that the SMART algorithm is superior to the Crow et al. baseline approach and is capable of broadly improving coarse-scale rainfall accumulations measurements with low risk of degradation. Comparisons with existing multisensor, satellite-based precipitation data products suggest that the introduction of soil moisture information from the Advanced Microwave Scanning Radiometer via SMART provides as much coarse-scale (3 day, 1°) rainfall accumulation information as thermal infrared satellite observations and more information than monthly rain gauge observations in poorly instrumented regions.

Crow, W. T.; van den Berg, M. J.; Huffman, G. J.; Pellarin, T.

2011-08-01

9

McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis  

NASA Astrophysics Data System (ADS)

This paper introduces and describes the hourly high resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR) probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a cold and snowy climate and to capture soil moisture transitions in areas that have different topography, soil and land-cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal Canadian climate causes a transition in soil moisture patterns at seasonal time scales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was equally dominated by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm) or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting http://www.hydrology.mcmaster.ca.

Kornelsen, K. C.; Coulibaly, P.

2012-12-01

10

McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis  

NASA Astrophysics Data System (ADS)

This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR) probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm) or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

Kornelsen, K. C.; Coulibaly, P.

2013-04-01

11

Analysis of observed soil moisture patterns under different land covers in Western Ghats, India  

NASA Astrophysics Data System (ADS)

SummaryAn understanding of the soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology and physiography. In the changing land use scenario of Western Ghats, India, where deforestation along with extensive afforestation with exotic species is being undertaken, there is an urgent need to evaluate the impacts of these changes on regional hydrology. The objectives of the present study were: (a) to understand spatio-temporal variability of soil water potential and soil moisture content under different land covers in the humid tropical Western Ghats region and (b) to evaluate differences if any in spatial and temporal patterns of soil moisture content as influenced by nature of land cover. To this end, experimental watersheds located in the Western Ghats of Uttara Kannada District, Karnataka State, India, were established for monitoring of soil moisture. These watersheds possessed homogenous land covers of acacia plantation, natural forest and degraded forest. In addition to the measurements of hydro-meteorological parameters, soil matric potential measurements were made at four locations in each watershed at 50 cm, 100 cm and 150 cm depths at weekly time intervals during the period October 2004-December 2008. Soil moisture contents derived from potential measurements collected were analyzed to characterize the spatial and temporal variations across the three land covers. The results of ANOVA ( p < 0.01, LSD) test indicated that there was no significant change in the mean soil moisture across land covers. However, significant differences in soil moisture with depth were observed under forested watershed, whereas no such changes with depth were noticed under acacia and degraded land covers. Also, relationships between soil moisture at different depths were evaluated using correlation analysis and multiple linear regression models for prediction of soil moisture from climatic variables and antecedent moisture condition were developed and tested. A regression model relating near-surface soil moisture (50 cm) with profile soil moisture content was developed which may prove useful when surface soil moisture contents derived from satellite remote sensing are available. Overall results of this study indicate that while the nature of land cover has an influence on the spatio-temporal variability of soil moisture, other variables related to topography may have a more dominant effect.

Venkatesh, B.; Lakshman, Nandagiri; Purandara, B. K.; Reddy, V. B.

2011-02-01

12

Soil Moisture: Some Fundamentals.  

National Technical Information Service (NTIS)

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 un...

B. W. Milstead

1975-01-01

13

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

NASA Astrophysics Data System (ADS)

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

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

2012-12-01

14

Soil Moisture Workshop  

NASA Technical Reports Server (NTRS)

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.

Heilman, J. L. (editor); Moore, D. G. (editor); Schmugge, T. J. (editor); Friedman, D. B. (editor)

1978-01-01

15

A Global Analysis on Satellite Derived and DGVM Surface Soil Moisture Products  

Microsoft Academic Search

We evaluated the soil moisture component in a global dynamic vegetation model through a comparison of a recently developed global remotely sensed product with the modeled soil moisture. Quarter degree daily AMSR-E surface soil moisture, as derived from the Land Parameter Retrieval Model, was compared to the ORCHIDEE Global Dynamic Vegetation Model (GDVM) soil moisture products for the years 2003

R. de Jeu; K. Rebel; P. Ciais; H. Dolman; N. Viovy; S. Piao; N. Noblet-Ducoudré

2008-01-01

16

Analysis of the pathways relating soil moisture and subsequent rainfall in Illinois  

NASA Astrophysics Data System (ADS)

This study is a continuation of an earlier work [Findell and Eltahir, 1997] on the soil moisture-rainfall feedback using a data set of biweekly neutron probe measurements of soil moisture at up to 19 stations throughout Illinois. Analyses in this earlier work showed a positive correlation between initial soil saturation and subsequent rainfall from early June to mid-August. This correlation was more significant than the serial correlation within precipitation, suggesting the likelihood of a physical mechanism linking soil moisture to subsequent rainfall. This paper probes the nature of such a physical pathway linking soil moisture to subsequent rainfall. The pathway is divided into two stages: soil moisture and near-surface air, and near-surface air and rainfall. An analysis of the connections between an average daily soil saturation for the whole state of Illinois with statewide average near-surface air conditions did not yield the anticipated positive correlation between soil moisture and moist static energy (MSE). It is not clear if this is due to limitations of the data or of the theory. Other factors, such as clouds, could potentially be masking the impacts of soil moisture on the energy of the near-surface air. There was evidence, however, that moisture availability at the surface has a very strong impact on the wet-bulb depression of near-surface air, particularly from mid-May to the end of August, showing good correspondence to the period of significant soil moisture-rainfall association. The final set of analyses performed used hourly boundary layer and rainfall data. A link between high MSE and high rainfall was noted during some summer months, and a link between low wet-bulb depression and high rainfall was evident for all of the months analyzed (April through September). These analyses suggest that the significant but weak correlation between soil moisture and rainfall during Illinois summers is at least partially due to soil moisture controls on the wet-bulb depression of near-surface air.

Findell, Kirsten L.; Eltahir, Elfatih A. B.

1999-01-01

17

Scaled spatial variability of soil moisture fields  

Microsoft Academic Search

This study identifies soil moisture spatial variability patterns using measurements across different extents (i.e., field, watershed, and basin) and depths (i.e., from surface to root zone profile) from 18 different soil moisture field experiments. The spatial variability patterns are well represented by negative exponential functions between the mean and the coefficient of variation of soil moisture. Principal component analysis demonstrates

Minha Choi; Jennifer M. Jacobs; Michael H. Cosh

2007-01-01

18

Scaled spatial variability of soil moisture fields  

Microsoft Academic Search

(1) This study identifies soil moisture spatial variability patterns using measurements across different extents (i.e., field, watershed, and basin) and depths (i.e., from surface to root zone profile) from 18 different soil moisture field experiments. The spatial variability patterns are well represented by negative exponential functions between the mean and the coefficient of variation of soil moisture. Principal component analysis

Minha Choi; Jennifer M. Jacobs; Michael H. Cosh

2007-01-01

19

Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the Soil Moisture Analysis Rainfall Tool  

NASA Astrophysics Data System (ADS)

Using historical satellite surface soil moisture products, the Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the submonthly scale accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain gauge observations. In order to adapt to the irregular retrieval frequency of heritage soil moisture products, a new variable correction window method is developed that allows for better efficiency in leveraging temporally sparse satellite soil moisture retrievals. Results confirm the advantage of using this variable window method relative to an existing fixed-window version of SMART over a range of one- to 30-day accumulation periods. Using this modified version of SMART and heritage satellite surface soil moisture products, a 1.0-deg, 20-year (1979 to 1998) global rainfall dataset over land is corrected and validated. Relative to the original precipitation product, the corrected dataset demonstrates improved correlation with a global gauge-based daily rainfall product, lower root-mean-square-error (-13%) on a 10-day scale and provides a higher probability of detection (+5%) and lower false alarm rates (-3.4%) for five-day rainfall accumulation estimates. This corrected rainfall dataset is expected to provide improved rainfall forcing data for the land surface modeling community.

Chen, Fan; Crow, Wade T.; Holmes, Thomas R. H.

2012-01-01

20

Improving Long-term Global Precipitation Dataset Using Multi-sensor Surface Soil Moisture Retrievals and the Soil Moisture Analysis Rainfall Tool (SMART)  

NASA Astrophysics Data System (ADS)

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 gauge observations. In order to adapt to the irregular retrieval frequency of heritage soil moisture products, a new variable correction window method is developed which allows for better efficiency in leveraging temporally sparse satellite soil moisture retrievals. Results confirm the advantage of using this variable window method relative to an existing fixed-window version of SMART over a range of accumulation periods. Using this modified version of SMART, and heritage satellite surface soil moisture products, a 1.0-degree, 1979-1998 global rainfall dataset over land is corrected and validated. Relative to the original precipitation product, the updated correction scheme demonstrates improved root-mean-square-error and correlation accuracy and provides a higher probability of detection and lower false alarm rates for 3-day rainfall accumulation estimates, except for the heaviest (99th percentile) cases. This corrected rainfall dataset is expected to provide improved rainfall forcing data for the land surface modeling community.

Chen, F.; Crow, W. T.; Holmes, T. R.

2012-12-01

21

Frequency analysis of Earth Observation and hydrological model estimations of evapotranspiration and soil moisture  

NASA Astrophysics Data System (ADS)

Evapotranspiration and Soil Moisture are important variables for water resources management on the catchment level. However, to accurately measure these variables is difficult, if not impossible. Ground station measurements are reliable, but it is mostly not possible and costly to provide adequate spatial coverage of the catchment. Earth observation data does provide this spatial coverage and becomes accessible at lower costs. The algorithms to interpret satellites imagery have been evolving. Also spatially distributed hydrological models provide the estimates of Evapotranspiration and Soil Moisture covering the catchment. However, also hydrological models need validation. In this paper state-of-the-art recent estimates (2013) from the three information sources for Evapotranspiration and Soil Moisture are compared on the basis of sample locations and frequency analysis for the Rijnland area in the Netherlands.

Song, Yang; Hartanto, Isnaeni; Alexandridis, Thomas; van Andel, Schalk Jan; Solomatine, Dimitri

2014-05-01

22

Analysis and estimation of soil moisture at the catchment scale using EOFs  

Microsoft Academic Search

Soil moisture patterns and dynamics are important for numerous applications such as flood forecasting, climate modeling, and management of agricultural lands. Unfortunately, widespread observations of soil moisture are not currently available at the spatial scale of most of these applications. Given these data limitations and the complexity of soil moisture dynamics, there is a need to gain a better understanding

Mark A. Perry; Jeffrey D. Niemann

2007-01-01

23

GLOBE Videos: Soil Characterization - Soil Moisture (18:23 min)  

NSDL National Science Digital Library

This video describes how to select a soil moisture study site and sampling strategy, and identifies what laboratory instruments will be needed to complete a soil moisture analysis. Students are shown collecting soil moisture data and asking questions about what soil moisture data might tell them about the environment. The resource includes a video and a written transcript, and is supported by the Soil Moisture Protocol in the GLOBE Teacher's Guide. This is one of five videos about soils in the 24-part instructional video series describing scientific protocols used by GLOBE (Global Learning and Observation to Benefit the Environment), a worldwide, hands-on, K-12 school-based science education program.

24

Soil Moisture Memory in Climate Models  

NASA Technical Reports Server (NTRS)

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.

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

2000-01-01

25

Soil Moisture Variability and Mean Soil Moisture: A Stochastic Hydraulic Perspective  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable in understanding water and energy fluxes in terrestrial systems. The characterization of soil moisture variability is one of the major challenges in hydrological sciences today. Especially the relationship between soil moisture variability and mean soil water content is receiving considerable attention as it plays an important in upscaling and downscaling of soil moisture fields and in the parameterization of terrestrial and climate models. We show that the relationship between mean moisture content and its standard deviation can be predicted by stochastic analysis of unsaturated Brooks-Corey flow in heterogeneous soils. Based on a sensitivity analysis, it is found that parameters of the moisture retention characteristic and their spatial variability determine to a large extent the shape of the soil moisture variance-mean water content function. Predicting this function for eleven textural classes we found that the standard deviation of soil moisture peaked between 0.17 and 0.23 for most textural classes. Differing values were found for the more sandy soils. The simulated range of soil moisture agrees with field findings reported in the literature. It was found that pore-size distribution of soils is the primary parameter controlling the maximum value of the soil moisture standard deviation. We demonstrate the potential of inversely estimating soil hydraulic parameters and their statistics from soil moisture data using a case study with generated functions.

Vereecken, H.; Kamai, T.; Harter, T.; Kasteel, R.; Hopmans, J. W.; Vanderborght, J.

2007-12-01

26

Soil moisture retrieval from multi-instrument observations: Information content analysis and retrieval methodology  

NASA Astrophysics Data System (ADS)

algorithm has been developed that employs neural network technology to retrieve soil moisture from multi-wavelength satellite observations (active/passive microwave, infrared, and visible). This represents the first step in the development of a methodology aiming to combine beneficial aspects of existing retrieval schemes. Several quality metrics have been developed to assess the performance of a retrieval product on different spatial and temporal scales. Additionally, an innovative approach to estimate the retrieval uncertainty has been proposed. An information content analysis of different satellite observations showed that active microwave observations are best suited to capture the soil moisture temporal variability, while the amplitude of the surface temperature diurnal cycle is best suited to capture the spatial variability. In a synergy analysis, it has been found that through the combination of all observations the retrieval uncertainty could be reduced by 13%. Furthermore, it was found that synergy benefits are significantly larger using a data fusion approach compared to an a posteriori combination of retrieval products, supporting the combination of different retrieval methodology aspects in a single algorithm. In a comparison with model data, it was found that the proposed methodology also shows potential to be used for the evaluation of modeled soil moisture. A comparison with in situ observations showed that the algorithm is well able to capture soil moisture spatial variabilities. It was concluded that the temporal performance can be improved through incorporation of other existing retrieval approaches.

Kolassa, J.; Aires, F.; Polcher, J.; Prigent, C.; Jimenez, C.; Pereira, J. M.

2013-05-01

27

Passive Microwave Soil Moisture Research  

Microsoft Academic Search

During the four years of the AgRISTARS Program, significant progress was made in quantifying the capabilities of microwave sensors for the remote sensing of soil moisture. In this paper we discuss the results of numerous field and aircraft experiments, analysis of spacecraft data, and modeling activities which examined the various noise factors such as roughness and vegetation that affect the

Thomas Schmugge; Peggy O'Neill; James Wang

1986-01-01

28

Optional Soil Moisture Sensor Protocol  

NSDL National Science Digital Library

The purpose of this resource is to measure the water content of soil based on the electrical resistance of soil moisture sensors. Students install soil moisture sensors in holes that are 10 cm, 30 cm, 60 cm, and 90 cm deep. They take daily readings of soil moisture data by connecting a meter to the sensors and using a calibration curve to determine the soil water content at each depth.

The GLOBE Program, University Corporation for Atmospheric Research (UCAR)

2003-08-01

29

Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System  

Microsoft Academic Search

This paper presents the future European Centre for Medium-Range Weather Forecasts soil moisture analysis system based on a point-wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from

M. Drusch; K. Scipal; P. de Rosnay; G. Balsamo; E. Andersson; P. Bougeault; P. Viterbo

2009-01-01

30

A scaling analysis of soil moisture–precipitation interactions in a regional climate model  

Microsoft Academic Search

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil\\u000a moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine\\u000a whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found\\u000a that high soil moisture

A. R. Jones; N. A. Brunsell

2009-01-01

31

Soil-moisture ground truth, Hand County, South Dakota  

NASA Technical Reports Server (NTRS)

Soil samples were taken in the field and carefully preserved in taped metal containers for later laboratory gravimetric analysis to determine soil-moisture content. The typical sampling pattern used in this mission is illustrated, and the soil types encountered on the soil-moisture lines are summarized. The actual soil-moisture data were tabulated by range, township and section. Soil-moisture data obtained in fields of winter wheat and spring wheat are briefly summarized.

Jones, E. B.

1976-01-01

32

Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System  

NASA Astrophysics Data System (ADS)

This paper presents the future European Centre for Medium-Range Weather Forecasts soil moisture analysis system based on a point-wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from both analyses are comparable. However, the EKF-based increments are generally higher for the top soil layers then for the bottom layer. This gradient better reflects the underlying hydrological processes in that the strongest interaction between soil moisture and bare soil evaporation and transpiration through vegetation should occur in top layers where most of the roots are located. The impact on the forecast skill, e.g., air temperature at 2 m and 500 hPa height, is neutral. The new EKF surface analysis system offers a range of further development options for the exploitation of satellite observations for the initialization of the land surface in Numerical Weather Prediction.

Drusch, M.; Scipal, K.; de Rosnay, P.; Balsamo, G.; Andersson, E.; Bougeault, P.; Viterbo, P.

2009-05-01

33

The Global Soil Moisture Data Bank - Benchmark Soil Moisture Observations  

NASA Astrophysics Data System (ADS)

Soil moisture is a crucial component of the global hydrological cycle. Summer desiccation is a potential threat from some climate model simulations of global warming, but actual in situ soil moisture observations are needed to examine long term soil moisture changes as well as to develop accurate land surface models. Here we present a set of benchmark in situ soil moisture observations, from long-term observing programs in the United States, Europe, and Asia. The longest time series started in 1958, the same year as the Keeling Mauna Loa CO2 record, and is based on gravimetric observations from 141 stations at agricultural fields with winter and spring cereal crops in the Ukraine with a temporal resolution of 10 days (3 measurements per month) during the growing period, from April 8 to October 28. We discuss methods of observation, of quality control, and of achieving homogeneity. Shorter records from other locations will also be presented. These benchmark soil moisture observations are being used by the international research community to study climate change, as ground truth for remote sensing, to develop and evaluate land surface models, and to evaluate general circulation model and reanalysis calculations of soil moisture variations. While land data assimilation of remotely-sensed forcing and soil moisture, utilizing a validated land surface model, will be necessary to produce a global soil moisture data set, this goal cannot be achieved without these actual in situ observations.

Robock, A.; Vinnikov, K.; Li, H.

2005-12-01

34

Soil moisture: Some fundamentals. [agriculture - soil mechanics  

NASA Technical Reports Server (NTRS)

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.

Milstead, B. W.

1975-01-01

35

Global Soil Moisture Data Bank  

NSDL National Science Digital Library

This Data Bank is a collection of more than 400 observations of primarily Asian soil moisture. The data are freely available, and can be used for studying patterns of soil moisture variation, developing and testing land surface models, and ground truth for remote sensing.

1995-01-01

36

Global Soil Moisture Data Bank  

NSDL National Science Digital Library

This Data Bank is a collection of more than 400 observations of primarily Asian soil moisture. The data are freely available, and can be used for studying patterns of soil moisture variation, developing and testing land surface models, and ground truth for remote sensing.

Robock, Alan

2007-01-24

37

Applications of soil moisture information  

NASA Technical Reports Server (NTRS)

The needs of specific users within the areas of agriculture, hydrology, and meteorology are discussed. Sections are also included on the importance of drought, foreign needs for soil moisture information, some specific requirements for data information systems, and agency and organization uses of soil moisture.

Johannsen, C. J.; Engman, E. T.; Blanchard, B. J.; Bockes, O.; Brueck, D.; Deardorff, J.; Heilman, J. L.; Myrup, L.; Keener, M.

1978-01-01

38

Statistical analysis of simulated global soil moisture and its memory in an ensemble of CMIP5 general circulation models  

NASA Astrophysics Data System (ADS)

Soil moisture and its memory can have a strong impact on near surface temperature and precipitation and have the potential to promote severe heat waves, dry spells and floods. To analyze how soil moisture is simulated in recent general circulation models (GCMs), soil moisture data from a 23 model ensemble of Atmospheric Model Intercomparison Project (AMIP) type simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are examined for the period 1979 to 2008 with regard to parameterization and statistical characteristics. With respect to soil moisture processes, the models vary in their maximum soil and root depth, the number of soil layers, the water-holding capacity, and the ability to simulate freezing which all together leads to very different soil moisture characteristics. Differences in the water-holding capacity are resulting in deviations in the global median soil moisture of more than one order of magnitude between the models. In contrast, the variance shows similar absolute values when comparing the models to each other. Thus, the input and output rates by precipitation and evapotranspiration, which are computed by the atmospheric component of the models, have to be in the same range. Most models simulate great variances in the monsoon areas of the tropics and north western U.S., intermediate variances in Europe and eastern U.S., and low variances in the Sahara, continental Asia, and central and western Australia. In general, the variance decreases with latitude over the high northern latitudes. As soil moisture trends in the models were found to be negligible, the soil moisture anomalies were calculated by subtracting the 30 year monthly climatology from the data. The length of the memory is determined from the soil moisture anomalies by calculating the first insignificant autocorrelation for ascending monthly lags (insignificant autocorrelation folding time). The models show a great spread of autocorrelation length from a few months in the tropics, north western Canada, eastern U.S. and northern Europe up to few years in the Sahara, the Arabian Peninsula, continental Eurasia and central U.S. Some models simulate very long memory all over the globe. This behavior is associated with differences between the models in the maximum root and soil depth. Models with shallow roots and deep soils exhibit longer memories than models with similar soil and root depths. Further analysis will be conducted to clearly divide models into groups based on their inter-model spatial correlation of simulated soil moisture characteristics.

Wiß, Felix; Stacke, Tobias; Hagemann, Stefan

2014-05-01

39

Spatial patterns from EOF analysis of soil moisture at a large scale and their dependence on soil, land-use, and topographic properties  

Microsoft Academic Search

We hypothesize that the spatial and temporal variation in large-scale soil moisture patterns can be described by a small number of spatial structures that are related to soil texture, land use, and topography. To test this hypothesis, an empirical orthogonal function (EOF) analysis is conducted using data from the 1997 Southern Great Plains field campaign. When considering the spatial soil

Summer D. Jawson; Jeffrey D. Niemann

2007-01-01

40

SMALT - Soil Moisture from Altimetry  

NASA Astrophysics Data System (ADS)

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 comparison between Metop ASCAT and altimeter sigma0 over Saharan Africa. Geographical correlated areas of agreement and disagreement corresponding to underlying terrain are identified. SMALT products provide a first order estimation of soil moisture in areas of very dry terrain, where other datasets are limited. Potential to improve and expand the technique has been found, although further work is required to produce products with the same accuracy confidence as more established techniques. The data are made freely available to the scientific community through the website http://tethys.eaprs.cse.dmu.ac.uk/SMALT

Smith, Richard; Salloway, Mark; Berry, Philippa; Hahn, Sebastian; Wagner, Wolfgang; Egido, Alejandro; Dinardo, Salvatore; Lucas, Bruno Manuel; Benveniste, Jerome

2014-05-01

41

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method.  

National Technical Information Service (NTIS)

Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large- scale observed and simulated estimat...

A. S. Jones C. L. Combs M. Sengupta T. Lakhankar T. H. Vonder Haar

2010-01-01

42

Preliminary analysis of the sensitivity of AIRSAR images to soil moisture variations  

NASA Technical Reports Server (NTRS)

Synthetic Aperture Radar (SAR) images acquired from various sources such as Shuttle Imaging Radar B (SIR-B) and airborne SAR (AIRSAR) have been analyzed for signatures of soil moisture. The SIR-B measurements have shown a strong correlation between measurements of surface soil moisture (0-5 cm) and the radar backscattering coefficient sigma(sup o). The AIRSAR measurements, however, indicated a lower sensitivity. In this study, an attempt has been made to investigate the causes for this reduced sensitivity.

Pardipuram, Rajan; Teng, William L.; Wang, James R.; Engman, Edwin T.

1993-01-01

43

Bistatic Radar Configuration for Soil Moisture Retrieval: Analysis of the Spatial Coverage  

PubMed Central

Some outcomes of a feasibility analysis of a spaceborne bistatic radar mission for soil moisture retrieval are presented in this paper. The study starts from the orbital design of the configuration suitable for soil moisture estimation identified in a previous study. This configuration is refined according to the results of an analysis of the spatial resolution. The paper focuses on the assessment of the spatial coverage i.e., on the verification that an adequate overlap between the footprints of the antennas is ensured and on the duty cycle, that is the fraction of orbital period during which the bistatic data are acquired. A non-cooperating system is considered, in which the transmitter is the C-band Advanced Synthetic Aperture Radar aboard Envisat. The best performances in terms of duty cycle are achieved if the transmitter operates in Wide Swath Mode. The higher resolution Image Swath Modes that comply with the selected configuration have a duty cycle that is never less than 12% and can exceed 21%. When Envisat operates in Wide Swath Mode, the bistatic system covers a wide latitude range across the equator, while in some of the Image Swath Modes, the bistatic measurements, collected from the same orbit, cover mid-latitude areas. In the latter case, it might be possible to achieve full coverage in an Envisat orbit repeat cycle, while, for a very large latitude range such as that covered in Wide Swath Mode, bistatic acquisitions could be obtained over about 65% of the area.

Pierdicca, Nazzareno; De Titta, Ludovico; Pulvirenti, Luca; della Pietra, Giuliano

2009-01-01

44

Teleconnection analysis of runoff and soil moisture over the Pearl River basin in southern China  

NASA Astrophysics Data System (ADS)

This study explores the teleconnection of two climatic patterns, namely the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), with hydrological processes over the Pearl River basin in southern China, particularly on a sub-basin-scale basis. The Variable Infiltration Capacity (VIC) model is used to simulate the daily hydrological processes over the basin for the study period 1952-2000, and then, using the simulation results, the time series of the monthly runoff and soil moisture anomalies for its ten sub-basins are aggregated. Wavelet analysis is performed to explore the variability properties of these time series at 49 timescales ranging from 2 months to 9 yr. Use of the wavelet coherence and rank correlation method reveals that the dominant variabilities of the time series of runoff and soil moisture are basically correlated with IOD. The influences of ENSO on the terrestrial hydrological processes are mainly found in the eastern sub-basins. The teleconnections between climatic patterns and hydrological variability also serve as a reference for inferences on the occurrence of extreme hydrological events (e.g., floods and droughts).

Niu, J.; Chen, J.; Sivakumar, B.

2014-04-01

45

Soil Moisture Observations from Space - An Analysis of Existing Data Sets  

Microsoft Academic Search

This paper introduces two analyses undertaken in preparation for the work leading up to the assimilation of SMOS observations into the SVAT model ISBA at Météo France. First, inconsistencies between bare soil observations from MODIS and the vegetation data base used in the forward model to retrieve soil moisture from SMOS are presented. Second, a comparison study of different instruments

Christoph Rüdiger; Jean-Christophe Calvet; Thomas Holmes; Richard de Jeu; Wolfgang Wagner; André Chanzy; Jean-Pierre Wigneron

46

An empirical approach towards improved spatial estimates of soil moisture for vegetation analysis  

Microsoft Academic Search

Landscape-level spatial estimates of soil water content are critical to understanding ecological processes and predicting watershed response to environmental change. Because soil moisture influences are highly variable at the landscape scale, most meteorological datasets are not detailed enough to depict spatial trends in the water balance at these extents. We propose a tactical approach to gather high-resolution field data for

Todd Lookingbill; Dean Urban

2004-01-01

47

Active Microwave Soil Moisture Research  

Microsoft Academic Search

This paper summarizes the progress achieved in the active microwave remote sensing of soil moisture during the four years of the AgRISTARS program. Within that time period, from about 1980 to 1984, significant progress was made toward understanding 1) the fundamental dielectric properties of moist soils, 2) the influence of surface boundary conditions, and 3) the effects of intervening vegetation

M. CRAIG DOBSON; FAWWAZ T. ULABY

1986-01-01

48

Sensitivity Analysis of Distributed Soil Moisture Profiles by Active Distributed Temperature Sensing  

NASA Astrophysics Data System (ADS)

Monitoring and measuring the fluctuations of soil moisture at large scales in the filed remains a challenge. Although sensors based on measurement of dielectric properties such as Time Domain Reflectometers (TDR) and capacity-based probes can guarantee reasonable responses, they always operate on limited spatial ranges. On the other hand optical fibers, attached to a Distribute Temperature Sensing (DTS) system, can allow for high precision soil temperature measurements over distances of kilometers. A recently developed technique called Active DTS (ADTS) and consisting of a heat pulse of a certain duration and power along the metal sheath covering the optical fiber buried in the soil, has proven a promising alternative to spatially-limited probes. Two approaches have been investigated to infer distributed soil moisture profiles in the region surrounding the optic fiber cable by analyzing the temperature variations during the heating and the cooling phases. One directly relates the change of temperature to the soil moisture (independently measured) to develop specific calibration curve for the soil used; the other requires inferring the thermal properties and then obtaining the soil moisture by inversion of known relationships. To test and compare the two approaches over a broad range of saturation conditions a large lysimeter has been homogeneously filled with loamy soil and 52 meters of fiber optic cable have been buried in the shallower 0.8 meters in a double coil rigid structure of 15 loops along with a series of capacity-based sensors (calibrated for the soil used) to provide independent soil moisture measurements at the same depths of the optical fiber. Thermocouples have also been wrapped around the fiber to investigate the effects of the insulating cover surrounding the cable, and in between each layer in order to monitor heat diffusion at several centimeters. A high performance DTS has been used to measure the temperature along the fiber optic cable. Several soil moisture profiles have been generated in the lysimeter either varying the water table height or by wetting the soil from the top. The sensitivity of the ADTS method for heat pulses of different duration and power and ranges of spatial and temporal resolution are presented.

Ciocca, F.; Van De Giesen, N.; Assouline, S.; Huwald, H.; Lunati, I.

2012-12-01

49

Gravimetric Soil Moisture Protocols  

NSDL National Science Digital Library

The purpose of this resource is to measure soil water content by mass. Students collect soil samples with a trowel or auger and weigh them, dry them, and then weigh them again. The soil water content is determined by calculating the difference between the wet sample mass and the dry sample mass.

The GLOBE Program, University Corporation for Atmospheric Research (UCAR)

2003-08-01

50

Estimating root zone soil moisture from surface soil moisture data and soil-vegetation-atmosphere transfer modeling  

NASA Astrophysics Data System (ADS)

We studied the possibility of estimating root zone soil moisture through the combined use of a time series of observed surface soil moisture data and soil-vegetation-atmosphere transfer modeling. The analysis was based on the interactions between soil- biosphere-atmosphere surface scheme and two data sets obtained from soybean crops in 1989 and 1990. These data sets included detailed measurements of soil and vegetation characteristics and mass and energy transfer in the soil-plant-atmosphere system. The data measured during the 3-month experiment in 1989 are used to investigate the accuracy of soil reservoir retrievals, as a function of the time period and frequency of measurements of surface soil moisture involved in the retrieval process. This study contributes to better defining the requirements for the use of remotely sensed microwave measurements of surface soil moisture.

Wigneron, Jean-Pierre; Olioso, Albert; Calvet, Jean-Christophe; Bertuzzi, Patrick

1999-12-01

51

Analysis of impact of heterogeneity at landscape level in retrieval of soil moisture from low-frequency radars  

NASA Astrophysics Data System (ADS)

Knowledge of soil moisture dynamics on a global scale is key in understanding the water and energy cycles. This understanding has critical impact on predicting future water resources and sustainability, and is invaluable across many disciplines such as hydrology, meteorology, and ecology, as well as in weather and climate prediction. To accommodate this need for global observations of surface soil moisture, NASA is developing the soil moisture active passive (SMAP) spaceborne mission carrying an L-band radar and radiometer to be launched in late 2014. The SMAP mission will carry both a radar and a radiometer allowing synergistic use of the two data types for soil moisture retrieval. Radar data are delivered at higher resolution (3 km) than the radiometer data (36 km), and allow finer analysis of the connection between land cover type and soil moisture. Most satellite resolution pixels contain highly heterogeneous scenes with small scale variability of soil moisture, soil texture, topography, and vegetation cover types. Traditional algorithms for radar soil moisture retrieval assume a homogeneous scene within each satellite resolution cell, which is not a reasonable assumption even for the 3 km resolution radar data from SMAP. This illuminates the need to develop spatial aggregation and disaggregation techniques using radar forward scattering models that assume homogeneity over finer scale sub-pixels and derive tailor-made models for their contribution to the coarse-scale satellite pixel for effective soil moisture retrieval. A physics-based remote sensing (radar) landscape simulator to analyze potentially large groups of georeferenced pixels by utilizing ancillary data has been developed. The inversion capability to compare different scaled retrieval results has been separately developed and shown to be suitable for retrieval of soil moisture values over a monospecies boreal forest in Canada. These tools facilitate the analysis of heterogeneity at landscape level by enabling the investigation of spatial aggregation and joint aggregation and disaggregation techniques. In this work, we build on preliminary findings and will further investigate and present results of a physics-based spatial aggregation strategy for a forested area. We will focus on retrieving soil moisture based on active radar measurements, which although at much finer resolution than a radiometer of the same frequency, is still at a coarse enough resolution to suffer from the effects of landscape heterogeneity. The total measured coarse-scale radar backscattering coefficient of a scene can be expressed as a weighted linear sum of the contributions of the fine-scale subpixels; these weights are functions of landscape parameters. By aggregating the radar backscattering coefficients of the simulated subpixels and disaggregating the measured radar backscattering coefficient of the coarse-scale pixel, we aim to find the total soil moisture of the satellite pixel. We adopt a block kriging strategy for radar backscattering coefficients using available ancillary data, followed by the development of an inversion strategy that takes into account the non-uniform contribution of different regions of the landscape. Thorough validation and error analysis will be shown through simulations as well as with the use of airborne radar data and ground-based observations.

Burgin, M.; Tabatabaeenejad, A.; Moghaddam, M.

2012-12-01

52

Use of SMOS data for Numerical Weather Prediction (NWP): The ECMWF soil moisture analysis  

Microsoft Academic Search

This paper presents the contribution of the European Centre for Medium-Range Weather Forecasts (ECMWF) to the SMOS (Soil Moisture and Ocean Salinity) mission. ECMWF plays a major role in developing and implementing the use of SMOS brightness temperature data in NWP models. The contribution of ECMWF to the SMOS mission is two-fold. - Development of a global data monitoring system

P. de Rosnay; M. Drusch; J. Muñoz Sabater; G. Balsamo; K. Scipal

2009-01-01

53

A soil moisture climatology of Illinois  

Microsoft Academic Search

Ten years of soil moisture measurements (biweekly from March through September and monthly during winter) within the top 1 m of soil at 17 grass-covered sites across Illinois are analyzed to provide a climatology of soil moisture for this important Midwest agricultural region. Soil moisture measurements were obtained with neutron probes that were calibrated for each site. Measurement errors are

Steven E. Hollinger; Scott A. Isard

1994-01-01

54

Interactive Analysis Tools for the Soil Moisture and Ocean Salinity (SMOS) mission  

NASA Astrophysics Data System (ADS)

The Interactive Analysis Tools (IAT) is a set of software elements that ESA has developed in the context of the SMOS mission ground segment. These IAT will be used off-line by different SMOS users according to the needs of each team like: sensor monitoring (instrument commissioning team), problem investigation (Data Processing Ground Segment team), calibration and validation support (Expert Support Laboratories), long term monitoring and data analysis (Calibration and Expertise Centre team). The poster will present an overview and description of the main functionalities of the IATs available to the user community. In particular the IATs considered are the following: the L1 processor prototype that provides Geolocated Calibrated Brightness temperature on antenna frame (L1c data) from the raw digital correlation measured by the sensor. The L2 Sea surface salinity prototype that provides geolocated Sea salinity measurements retrieved by the L1c data. The L2 Soil Moisture prototype that provides geolocated Soil Moisture measurements retrieved by the L1c data. The SMOS Data Viewer that provides browse functionality for all the SMOS data products and auxiliary file. Specific visualization functions are also available for L1 and L2 in order to proper analyze the data content. The SMOS Global Mapping Tool (GMT) that provides averaged maps over a user defined time period (e.g one week, one month) of the key parameters available in the L1 and L2 data as well as maps of derived parameters like the first Stokes and the polarization index. The SMOS Comparison Tool (SCoT) that provides data comparison between different L1 products. SCoT can be used in the context of L1 processor test acceptance (to verified the operational processor vs the prototype) and in the context of scientific analysis in order to compare L1 data processed with different configuration parameters. The SMOSBox developed as module extensions of the existing BEAM tool. SMOSBox provides tools to analyse L1b, L1c and L2 data. In particular will be available: advances plots: density plots, contour plots, 3-D plots, computation of derived quantities like Stokes parameter and pseudo L3 salinity maps and specific L2 data export function in NetCDF format.

Crapolicchio, R.; Delwart, S.; Zundo, M.

2009-04-01

55

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

NASA Technical Reports Server (NTRS)

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.

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

56

Passive microwave remote sensing of soil moisture  

Microsoft Academic Search

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

Eni G. Njokul; Dara Entekhabi

1996-01-01

57

Optimum Radar Parameters for Mapping Soil Moisture  

Microsoft Academic Search

The radar response to soil moisture content was experimentally determined for each of three bare fields with considerably different surface roughnesses at eight frequencies in the 2-8 GHz band for HH and VV polarizations. Analysis of the data indicates that the effect of roughness on the radar backscattering coefficient can be minimized by proper choice of the radar parameters. If,

Fawwaz Ulaby; Percy Batlivala

1976-01-01

58

Determination of the thermal conductivity of sands under varying moisture, drainage\\/wetting, and porosity conditions- applications in near-surface soil moisture distribution analysis  

Microsoft Academic Search

A class of problems in hydrology and remote sensing requires improved understanding of how water and heat flux boundary conditions affect the soil moisture processes in the shallow subsurface near the land\\/atmospheric interface. In these systems, a clear understanding of how variations in water content, soil drainage\\/wetting and porosity conditions affect the soil's thermal behavior is needed for the accurate

Kathleen M. Smits; Toshihiro Sakaki; Anuchit Limsuwat; Tissa H. Illangasekare

59

The North American Soil Moisture Database  

NASA Astrophysics Data System (ADS)

Soil moisture is an important variable in the climate system, yet in situ observations of soil moisture are not prevalent in most regions of the world. The Soil Moisture and Ocean Salinity (SMOS) satellite recently launched by the European Space Agency and NASA's Soil Moisture Active and Passive (SMAP) mission underscore the need for better in situ soil moisture data for validation and accuracy assessment. The North American Soil Moisture Database is a harmonized and quality-controlled soil moisture dataset that is being developed to support investigations of land-atmosphere interactions, validating the accuracy of soil moisture simulations in global land surface models, and describing how soil moisture influences climate on seasonal to interannual timescales. Currently the database is comprised of well over 1,300 soil moisture observation stations from more than 20 networks in the United States. The data is subjected to rigorous quality control procedures. Upon completion, the database will consist of homogenized and standardized soil moisture data products that will be published on a dedicated website and made available to the scientific community to support research efforts such as EaSM, SMAP and SMOS.

Ford, T.; Quiring, S.

2012-12-01

60

Relating Soil Moisture to TRMMPR Backscatter in Southern United States  

NASA Astrophysics Data System (ADS)

Soil Moisture is an important variable in hydrological cycle. It plays a vital role in agronomy, meteorology, and hydrology. In spite of being an important variable, soil moisture measuring stations are sparse. This is due to high cost involved in the installation of dense network of measuring stations required to map a comprehensive spatio-temporal behavior of soil moisture. Hence, there is a need to develop an alternate method to measure soil moisture. This research relates soil moisture (SM) to backscatter (?°) obtained from Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) and Normalized Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer. SM data is obtained from Soil Climate Analysis Network (SCAN). ?° measurements are normalized at an incidence angle of 10° at which it has the highest sensitivity to SM. An empirical model that relates SM to normalized ?° and NDVI is developed. NDVI takes into account the different vegetation densities. The relationship between model variables is approximated to be linear. The model is applied to data from 1998 to 2008 where 75% of the data is used for calibration and the remaining 25% for validation. Figure 1 shows the comparison of observed and modeled soil moisture for a site with low vegetation. Even though the model underestimates the soil moisture content, it captures the signal well and produces peaks similar to the observed soil moisture. The model performs well with a correlation of 0.71 and root mean square error of 4.0%. The accuracy of the model depends on vegetation density. Table 1 summarizes the model performance for different vegetation densities. The model performance decreases with the increase in vegetation as the leaves in the vegetation canopy attenuate the incident microwaves which reduces the penetration depth and subsequently the sensitivity to soil moisture. This research provides a new insight into the microwave remote sensing of soil moisture. Figure 1. Plot of observed vs. modeled soil moisture. Table 1. Soil moisture model performance based on different vegetation densities.

Puri, S.; Stephen, H.; Ahmad, S.

2009-12-01

61

Nitrogen Probe for Soil-Moisture Sampling  

Microsoft Academic Search

Moisture determinations were made on soil cores frozen to hollow probes into which liquid nitrogen had been poured. Values compared closely with those from samples extracted by more conventional methods. In this paper a method of using liquid nitro- gen to obtain soil-moisture samples is described. It is applicable where very high moisture con- tent makes conventional techniques difficult or

D. BURKE

1959-01-01

62

Spectral Analysis of Soil Moisture Time Series From the NOAA-CREST Observation Site in Millbrook, NY  

NASA Astrophysics Data System (ADS)

Soil moisture is the water content located within the soil. It affects our weather and climate, agriculture, and irrigation. The study of soil moisture enables the study of runoff potential and flood control, soil erosion and slope failure, reservoir management, and water quality. The ultimate goal of this project is to examine the relationship of soil moisture to temperature and precipitation, as well as to statistically analyze the collected data. These measurements are provided by L-band (1.4 GHZ) microwave readings and soil moisture and temperature sensors (Stevens Digital Hydra Probe II) mounted at two locations (A and B) and depths of 2.5, 5, and 10 cm; here, we focus on the data provided by the sensors. These measurements include hourly data from the time of deployment of the soil moisture probes in November 2010. The probes are located close to the National Oceanic and Atmospheric Administration (NOAA) US Climate Reference Network (USCRN) Millbrook station, which measures soil moisture at depths down to 1 m as well as surface temperature and precipitation. To achieve this goal we analyze in situ observations from Millbrook, NY. We analyzed the relationship between precipitation and temperature as well as that of the soil moisture and diurnal temperature range. We then analyzed the correlation, lagged auto and cross correlation, and coherence of the different measurement time series. The soil moisture shows a great variation over time. We see a strong correlation coefficient between the different soil moisture data collected at the Millbrook site, and a weak correlation coefficient at the hourly scale of the precipitation data with the soil moisture data from Millbrook.

Bonhomme, A. C.; Tesfagiorgis, K. B.; Temimi, M.; Krakauer, N.

2012-12-01

63

The prototype SMOS soil moisture Algorithm  

NASA Astrophysics Data System (ADS)

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, to be launched in September 2007. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 will consists mainly of angular brightness temperatures while level 2 will consist of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The consortium of institutes preparing the Soil moisture algorithm is led by CESBIO (Centre d'Etudes Spatiales de la BIOsphère) and Service d'Aéronomie and consists of the institutes represented by the authors. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to retrieve soil moisture over fairly large and thus inhomogeneous areas. The retrieval is carried out at nodes of a fixed Earth surface grid. To achieve this purpose, after checking input data quality and ingesting auxiliary data, the retrieval process per se can be initiated. This cannot be done blindly as the direct model will be dependent upon surface characteristics. It is thus necessary to first assess what is the dominant land use of a node. For this, an average weighing function (MEAN_WEF) which takes into account the "antenna" pattern is run over the high resolution land use map to assess the dominant cover type. This is used to drive the decision tree which, step by step, selects the type of model to be used as per surface conditions. All this being said and done the retrieval procedure starts if all the conditions are satisfied, ideally to retrieve 3 parameters over the dominant class (the so-called rich retrieval). If the algorithm does not converge satisfactorily, a new trial is made with less floating parameters ("poorer retrieval") until either results are satisfactory or the algorithm is considered to fail. The retrieval algorithm also delivers whenever possible a dielectric constant parameter (using the-so called cardioid approach). Finally, once the retrieval converged, it is possible to compute the brightness temperature at a given fixed angle (42.5°) using the selected forward models applied to the set of parameters obtained at the end of the retrieval process. So the output product of the level 2 soil moisture algorithm should be node position, soil moisture, dielectric constants, computed brightness temperature at 42.5°, flags and quality indices. The work around the ATBD also encompasses the making of breadboards and prototype, analysis of specific cases (snow, frozen soil, topography, flo

Kerr, Y.; Waldteufel, P.; Richaume, P.; Cabot, F.; Wigneron, J. P.; Ferrazzoli, P.; Mahmoodi, A.; Delwart, S.

2009-04-01

64

Space-time soil moisture variability for two different land use types: analysis at the plot scale  

NASA Astrophysics Data System (ADS)

Understanding space-time soil moisture variability at various scales is a key issue in hydrological research. At the plot scale soil moisture variability is expected to be explained by physical factors such as soil hydraulic properties, local topography and vegetation cover. This study aims to: i) characterize the spatial and temporal variability of soil moisture at the plot scale at two soil depths and for two different types of land use (meadow and vineyard); ii) investigate the role of vegetation cover on the seasonal variability of soil moisture; iii) assess the capability of a dynamic model to explain soil moisture variability and the control exerted by land use. The work is based on soil moisture data collected on a plot (about 200 m2) in Grugliasco (Po River basin, Northern Italy) by means of Time Domain Reflectometry (TDR) measurements. The plot is divided into two subplots: one covered by grapevine plants, the other covered homogeneously by grass. The soil is sandy, the slope is about 1%, and there is a buffer grass area about 20 m wide around the measurement field. The characteristics of the site allow to isolate the contribution of soil hydraulic properties and land use to space-time soil moisture variability. We used the data of 40 probes distributed in the two subplots, vertically inserted into the soil at 0-30 cm and 0-60 cm depths. Precipitation and temperature are recorded continuously on site. Statistics were computed based on soil moisture measurements collected continuously at daily time step over three years (2006-2008). Results show that soil moisture spatial patterns at the two sampling depths are highly correlated for both land uses. Higher values of mean soil moisture at 0-60 cm depth with respect to 0-30 cm for both types of land use likely reflect the evaporation processes affecting more the surface layer. Spatial mean soil moisture is always higher in the vineyard than in the meadow (especially at 0-30 cm depth), implying the influence of vegetation cover during the growing season. An exponential equation fits well the relationship between the spatial coefficient of variation and the mean soil moisture. An increasing variability of the coefficient of variation is observed during periods with high potential evapotranspiration rates (June-August). This is more evident for the grass site at 0-30 cm depth, highlighting again the important shading effect performed by the grapevine leaves. The application of a simple soil moisture dynamic model reveals a general good capability to capture soil moisture temporal dynamics at the plot scale. Moreover, the model reproduces consistently the observed relationships between soil moisture spatial mean and variability. Thus, the model provides a preliminary link between physical processes and statistical variability patterns. Keywords: soil moisture, plot scale, space-time variability, land use.

Zuecco, Giulia; Borga, Marco; Penna, Daniele; Canone, Davide; Ferraris, Stefano

2013-04-01

65

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra  

NASA Technical Reports Server (NTRS)

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.

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

2004-01-01

66

Development of an Aquarius Soil Moisture Product  

NASA Astrophysics Data System (ADS)

Aquarius observations over land offer a new resource for measuring soil moisture from space. Our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to land applications through the retrieval of soil moisture. This research increases the value and impact of the Aquarius mission by including a broader scientific community, allowing the exploration of new algorithm approaches that exploit the active-passive observations, and will contribute to a better understanding of the Earth's climate and water cycle. The first stage of our Aquarius soil moisture research focused on the use of the radiometer data because of the extensive heritage that this type of observations has in soil moisture applications. The calibration of the Aquarius radiometer over the entire dynamic range is a key element for the successful implementation of the soil moisture algorithm. Results to date indicate that the Aquarius observations are well calibrated for ocean targets but have a warm bias over land. This bias needed to be addressed if the Aquarius observations are to be used in land applications. Our approach was to use the gain and offsets computed using the Soil Moisture Ocean Salinity (SMOS) comparisons to adjust the Aquarius brightness temperatures. The Single Channel Algorithm (SCA) was implemented using the Aquarius observations. SCA is also the baseline algorithm for the SMAP radiometer-only soil moisture product. Aquarius radiometer observations from the three beams (after bias/gain modification) along with the National Centers for Environmental Prediction (NCEP) surface temperature model forecast were then used to estimate soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters derived based on land cover. The spatial patterns of the soil moisture estimates are consistent with the climatology and with the other satellite missions (Advanced Microwave Scanning Radiometer-E and SMOS). The soil moisture and temperature products were validated using in situ observations from the Little Washita and Little River watershed soil moisture networks. Results show good performance by the algorithm for these land surface conditions for the period of August 2011-June-2013 (RMSE=0.031 m3/m3, Bias=0.007 m3/m3, and R=0.855). The validated radiometer soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The soil moisture product was implemented as part of the routine Aquarius data processing and will be available from National Snow and Ice Data Center both in swath and gridded formats in the near future. Acknowledgement: USDA is an equal opportunity employer.

Bindlish, R.; Jackson, T. J.; Zhao, T.; Cosh, M. H.

2013-12-01

67

Soil Moisture Information And Thermal Microwave Emission  

Microsoft Academic Search

This paper presents theoretical and experimental results that demonstrate the depth to which soil moisture can be directly measured using microwave radiometers. The experimental results also document the effect of uniform surface roughness on the response of thermal microwave emission to soil moisture. Experimental measurements were executed in July 1980 at the Texas A&M University Research Farm near College Station,

Richard W. Newton; Quentin Robert Black; Shahab Makanvand; Andrew J. Blanchard; Buford Randall Jean

1982-01-01

68

On the spatial scaling of soil moisture  

Microsoft Academic Search

The spatial scale of soil moisture measurements is often inconsistent with the scale at which soil moisture predictions are needed. Consequently a change of scale (upscaling or downscaling) from the measurements to the predictions or model values is needed. The measurement or model scale can be defined as a scale triplet, consisting of spacing, extent and support. ‘Spacing’ refers to

Günter Blöschl

1999-01-01

69

Evaluation of the AMIP soil moisture simulations  

Microsoft Academic Search

The Atmospheric Model Intercomparison Project (AMIP) conducted simulations by 30 different atmospheric general circulation models forced by observed sea surface temperatures for the 10-year period, 1979–1988. These models include a variety of different soil moisture parameterizations which influence their simulations of the entire land surface hydrology, including evaporation, soil moisture, and runoff, and their simulations of the energy balance at

Alan Robock; C. Adam Schlosser; Konstantin Ya Vinnikov; Nina A Speranskaya; Jared K Entin; Shuang Qiu

1998-01-01

70

Operational Downscaling of Soil Moisture Fields Using Ancillary Data  

NASA Astrophysics Data System (ADS)

The scaling analysis of large-scale soil moisture data from the Southern Great Plains Hydrology experiment (SGP'97) showed that the scaling behavior of soil moisture is multifractal varying with the scale of observations and hydroclimatological conditions which can be explained with scaling behavior of soil hydraulic properties. These results suggested that it should be possible to use the spatial patterns of ancillary data at high resolution such as the sand content of soils as spatial basis functions for downscaling. This hypothesis was investigated by applying a modified fractal interpolation method for downscaling soil moisture from the SGP'97 experiment using ancillary data. The methodology should be especially useful for downscaling large-scale remotely-sensed estimates of soil moisture (e.g. AMSR) to the scales of operational hydrologic models.

Kim, G.; Barros, A. P.

2001-05-01

71

Investigation of remote sensing techniques of measuring soil moisture  

NASA Technical Reports Server (NTRS)

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.

Newton, R. W. (principal investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

72

Retrieving pace in vegetation growth using precipitation and soil moisture  

NASA Astrophysics Data System (ADS)

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

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

2013-12-01

73

Investigating storage-discharge relations in a lowland catchment using hydrograph fitting, recession analysis, and soil moisture data  

NASA Astrophysics Data System (ADS)

The relation between storage and discharge is an essential characteristic of many rainfall-runoff models. The simple dynamical systems approach, in which a rainfall-runoff model is constructed from a single storage-discharge relation, has been successfully applied to humid catchments. Here we investigate (1) if and when the less humid lowland Hupsel Brook catchment also behaves like a simple dynamical system by hydrograph fitting, and (2) if system parameters can be inferred from streamflow recession rates or more directly from soil moisture storage observations. Only 39% of the fitted monthly hydrographs yielded Nash-Sutcliffe efficiencies above 0.5, from which we can conclude that the Hupsel Brook catchment does not always behave like a simple dynamical system. Model results were especially poor in summer, when evapotranspiration is high and the thick unsaturated zone attenuates the rainfall input. Using soil moisture data to obtain system parameters is not trivial, mainly because there is a discrepancy between local and catchment storage. Parameters obtained with direct storage-discharge fitting led to a strong underestimation of the response of runoff to rainfall, while recession analysis leads to an overestimation.

Brauer, C. C.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.

2013-07-01

74

Soil moisture measurements from airborne SAR  

NASA Technical Reports Server (NTRS)

The preliminary results of algorithm development and testing for soil moisture retrieval at high incidence angles are reported. Based on first-order surface backscattering models, a physically based algorithm for retrieval of soil moisture was developed and evaluated using NASA/JPL aircraft synthetic aperture radar (SAR) data. It shows that the copolarization ratio is sensitive to soil moisture change but not to surface roughness at high incidence angles. This algorithm performed well at L-band and should be useful. This study suggests that incidence angles greater than 40 degrees are optimal for such monitoring.

Shi, Jiancheng; Soares, Joao V.; Hess, Laura; Engman, Edwin T.; Vanzyl, Jakob J.

1991-01-01

75

Passive Microwave Soil Moisture Disaggregation radar data and relationship between soil moisture, vegetation and surface temperature  

NASA Astrophysics Data System (ADS)

Soil moisture is an important variable in weather and climate. The passive microwave sensors have provided soil moisture of various spatial resolutions and are available for all-weather conditions, including AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System), AMSR2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). However, the spatial resolution of passive microwave soil moisture product is restricted at tens of kilometers level and needs to be improved. Toward this issue, the SMAP (Soil Moisture Active Passive) is set to be launched in October 2014 will be the first mission to provide L-band radar/radiometer soil moisture retrievals at three resolutions. In this paper we present two distinct methods to obtain higher spatial resolution soil moisture. The first one is use of active radar data to downscale soil moisture obtained by passive radiometers. The SMAP Validation Experiment 2012 (SMAPVEX12) was taken place and provided Passive/Active L-band Sensor (PALS) observations of two along-track resolutions (650 m and 1590 m), as well as ground soil moisture measurements. Consequently the PALS data can be used for disaggregating coarse resolution passive soil moisture retrievals. Based on a change detection theory, the relationships between change in radar backscatter and change in soil moisture at both coarse and fine resolutions are examined and used for calculating high spatial resolution soil moisture from AMSR-E and SMOS. Using SMAPVEX12 ground measurements validates the disaggregation results. The second method is use of the relationship between vegetation and surface temperature to downscale soil moisture obtained from passive radiometers. The physical relationships amongst soil moisture, land surface temperature and vegetation index (Normalized Difference Vegetation Index, NDVI), the historic soil moisture data of recent 30 years at 1/8 degree NLDAS (North America Land Data Assimilation Systems) scale were studied and modeled by using the long term records of land surface model and remote sensing products, NLDAS, MODIS (Moderate Resolution Imaging Spectroradiometer) and AVHRR (Advanced Very High Resolution Radiometer). This modeled relationship was then applied to the 1 km MODIS land surface temperature for disaggregating the microwave soil moisture estimates AMSR-E and SMOS in Oklahoma. Two sets of in-situ measurements Oklahoma Mesonet and Little Washita watershed Micronet were used for validating the disaggregated soil moisture.

Lakshmi, Venkat; Fang, Bin

2014-05-01

76

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis  

NASA Technical Reports Server (NTRS)

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.

Reichle, Rolf; Mahanama, Sarith; Koster, Randal; Lettenmaier, Dennis

2009-01-01

77

Electrical Methods of Determining Soil Moisture Content.  

National Technical Information Service (NTIS)

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, how...

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

1975-01-01

78

Error in Radar-Derived Soil Moisture due to Roughness Parameterization: An Analysis Based on Synthetical Surface Profiles  

PubMed Central

In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration.

Lievens, Hans; Vernieuwe, Hilde; Alvarez-Mozos, Jesus; De Baets, Bernard; Verhoest, Niko E.C.

2009-01-01

79

Improving hydrologic forecasting using spaceborne soil moisture retrievals  

Microsoft Academic Search

Using existing data sets of passive microwave spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios. The predictive ability

Wade T. Crow; Rajat Bindlish; Thomas J. Jackson

80

Sensitivity analysis of C- and Ku-band synthetic aperture radar data to soil moisture content in a semiarid region  

NASA Astrophysics Data System (ADS)

In this study, the sensitivity of the C-band (5.3 GHz) with a 23sp° incidence angle and the Ku-band (14.85 GHz) with 35sp° ,\\ 55sp° , and 75sp° incidence angles to surface soil moisture content from a semiarid region were evaluated. To obtain an improved soil moisture estimation, a practical technique to reduce the influence of soil roughness and vegetation in the SAR data was developed in a study area located in the Walnut Gulch Experimental Watershed, a representative site of shrub- and grass-dominated rangelands of the southwestern part of the United States. To correct for soil roughness effects, the C-band radar backscattering coefficients sigmasp° from a wet season image were subtracted from sigmasp° derived from a dry season image. The assumption was that, in semiarid regions, the SAR data from the dry season was dependent only on the soil roughness effects. To correct for vegetation effects, an empirical relation between sigmasp° and leaf area index was used, the latter derived from Landsat Thematic Mapper data. The results showed that when both soil roughness and vegetation effects were corrected for, the sensitivity of sigmasp° to soil moisture improved substantially. The sensitivity of sigmasp° to soil moisture was also evaluated in agricultural fields with bare soil and periodic roughness components (planting row and furrow structures). Four types of SAR system configurations were analyzed: C-band with a 23sp° incidence angle and Ku-band with 35sp° ,\\ 55sp° , and 75sp° incidence angles. The test sites were located at the University of Arizona's Maricopa Agricultural Center, south of Phoenix, Arizona. The results showed that the sensitivity of sigmasp° to soil moisture was strongly dependent upon the field conditions. The SAR signal was nearly insensitive to soil moisture for furrowed fields (furrow spacing ˜95 cm; amplitude ˜22 cm), but for fields with planting row structures (row spacing ˜24 cm; amplitude ˜2 cm), the SAR data was sensitive to soil moisture, particularly with the C-band at a 23sp° incidence angle and the Ku-band with a 35sp° incidence angle, regardless of the row direction.

Sano, Edson Eyji

81

Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture  

NASA Astrophysics Data System (ADS)

In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.

Draper, C. S.; Mahfouf, J.-F.; Walker, J. P.

2011-01-01

82

Estimating root zone soil moisture using near-surface observations from SMOS  

NASA Astrophysics Data System (ADS)

Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5 to 10 cm) and root zone (25 to 60 cm) soil moisture. An exponential decay filter is applied to estimate root zone soil moisture from near-surface observations. Reasonably skillful predictions of root zone soil moisture can be made using near-surface observations. The same method is then applied to evaluate whether soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to accurately estimate root zone soil moisture. We conclude that the exponential filter method is a useful approach for accurately predicting root zone soil moisture from SMOS surface retrievals.

Ford, T.; Harris, L.; Quiring, S. M.

2013-12-01

83

Soil moisture estimation with limited soil characterization for decision making  

NASA Astrophysics Data System (ADS)

Many decisions in agriculture are conditional to soil moisture. For instance in wet conditions, farming operations as soil tillage, organic waste spreading or harvesting may lead to degraded results and/or induce soil compaction. The development of a tool that allows the estimation of soil moisture is useful to help farmers to organize their field work in a context where farm size tends to increase as well as the need to optimize the use of expensive equipments. Soil water transfer models simulate soil moisture vertical profile evolution. These models are highly sensitive to site dependant parameters. A method to implement the mechanistic soil water and heat flow model (the TEC model) in a context of limited information (soil texture, climatic data, soil organic carbon) is proposed [Chanzy et al., 2008]. In this method the most sensitive model inputs were considered i.e. soil hydraulic properties, soil moisture profile initialization and the lower boundary conditions. The accuracy was estimated by implementing the method on several experimental cases covering a range of soils. Simulated soil moisture results were compared to soil moisture measurements. The obtained accuracy in surface soil moisture (0-30 cm) was 0.04 m3/m3. When a few soil moisture measurements are available (collected for instance by the farmer using a portable moisture sensor), significant improvement in soil moisture accuracy is obtained by assimilating the results into the model. Two assimilation strategies were compared and led to comparable results: a sequential approach, where the measurement were used to correct the simulated moisture profile when measurements are available and a variational approach which take moisture measurements to invert the TEC model and so retrieve soil hydraulic properties of the surface layer. The assimilation scheme remains however heavy in terms of computing time and so, for operational purposed fast code should be taken to simulate the soil moisture as with the Ross model [Ross, 2003, Crevoisier et al, 2009]. To meet the decision support context, we evaluated the model ability of evaluating the soil moisture level in comparison to a moisture threshold that splits soil conditions into desirable and undesirable cases. This threshold depends on soil properties, the farming operation and equipment characteristics. We evaluate the rate of making good decisions using either the TEC model with and without soil moisture measurements or an empirical algorithm that simulate the decision processes followed by farmers, currently. This later is a reference case that allows appreciating the adding value of using soil water transfer models. We found a significant improvement with a rate of success, which increases from 65% with the reference case to 90% when using the model with soil moisture assimilation. Chanzy, A., Mumen M., Richard, G.. (2008), Accuracy of top soil moisture simulation using a mechanistic model with limited soil characterization, Water Resources Research, 44(3), W03432. Crevoisier, D., Chanzy, A., Voltz M. (2009), Evaluation of the Ross Fast Solution of Richards' Equation in Unfavourable Conditions for Standard Finite Element Methods, Advances in Water Ressources, In revision. Ross, P. J. (2003). Modeling soil water and solute transport - Fast, simplified numerical solutions. Agronomy Journal 95:1352-1361.

Chanzy, A.; Richard, G.; Boizard, H.; Défossez, P.

2009-04-01

84

A Frequency Shift Dielectric Soil Moisture Sensor  

Microsoft Academic Search

Field implantable and laboratory sensors for the measurement of moisture in soil based on the increase of soil dielectric permittivity with volume fraction of water were developed. A typical sensor consists of a case containing a high-frequency (31-MHz) oscillator whose frequency determining resonance LC network is coupled to the built-in electrode via a capacitor T network. Increases in moisture cause

Darold Wobschall

1978-01-01

85

Radar for Measuring Soil Moisture Under Vegetation  

NASA Technical Reports Server (NTRS)

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.

Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya

2004-01-01

86

Overview of soil moisture measurements with neutrons  

NASA Astrophysics Data System (ADS)

Soil moisture measurements are useful for hydrological and agricultural applications. Soil moisture can be measured with a range of in-situ sensors in the soil, such as probes based on the difference in dielectric permittivity of wet and dry soil. At a large scale of tenths of kilometres, soil moisture can be measured with microwave remote sensing from satellites. At the intermediate scale, detection methods such as GPS reflectometry and the use of cosmic rays have been developed recently. One of the principles that can be used to measure soil moisture, is the difference in behaviour of neutrons in wet and dry soil. Neutrons are massive, electrically neutral particles that transfer their energy easily to light atoms, such as hydrogen. Therefore, in wet soil, neutrons lose their energy quickly. In dry soil, they scatter elastically from the heavy atoms and can be detected. The amount of detected neutrons is therefore inversely correlated with the amount of hydrogen in the soil. In this research we look for an overview of the possibilities to measure soil moisture with neutrons and how neutrons can be detected. Neutrons can be used to measure at the point scale and at a larger scale of approximately 1 km. We discuss in-situ measurements, in which a neutron source is put into the soil. Immediately next to the source is a detector, that counts the amount of neutrons that scatters back if the soil is dry. At a larger scale or measurement volume, we discuss the measurement of soil moisture with neutrons from cosmic rays. Cosmic rays are charged particles, accelerated by astrophysical sources (such as a Supernova). When the particles enter the atmosphere, they interact with the atmospheric atoms and form a shower. At sea level, we find several types of particles, such as muons and neutrons. We discuss why neutrons would be more useful for soil moisture measurements than other particles and how the use of cosmic-ray neutrons influences the measurement volume. Here we present an overview of the principles of soil moisture measurements at different scales with neutrons.

Hendriks, Aagje; Steele-Dunne, Susan; van de Giesen, Nick

2014-05-01

87

Soil moisture at local scale: Measurements and simulations  

NASA Astrophysics Data System (ADS)

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.

Romano, Nunzio

2014-08-01

88

Microwave remote sensing of soil moisture  

NASA Technical Reports Server (NTRS)

Knowledge of soil moisture is important to many disciplines, such as agriculture, hydrology, and meteorology. Soil moisture distribution of vast regions can be measured efficiently only with remote sensing techniques from airborne or satellite platforms. At low microwave frequencies, water has a much larger dielectric constant than dry soil. This difference manifests itself in surface emissivity (or reflectivity) change between dry and wet soils, and can be measured by a microwave radiometer or radar. The Microwave Sensors and Data Communications Branch is developing microwave remote sensing techniques using both radar and radiometry, but primarily with microwave radiometry. The efforts in these areas range from developing algorithms for data interpretation to conducting feasibility studies for space systems, with a primary goal of developing a microwave radiometer for soil moisture measurement from satellites, such as EOS or the Space Station. These efforts are listed.

Shiue, J. C.; Wang, J. R.

1988-01-01

89

Microwave remote sensing of soil moisture  

NASA Technical Reports Server (NTRS)

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.

Schmugge, T. J.

1985-01-01

90

Microwave remote sensing of soil moisture  

NASA Technical Reports Server (NTRS)

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.

Schmugge, T. J.

1984-01-01

91

Soil Moisture Data Assimilation in Soil Water Flow Modeling  

Microsoft Academic Search

Soil water flow modeling has multiple applications. This modeling is based on simplifications stemming from both conceptual uncertainty and lack of detailed knowledge about parameters. Modern soil moisture sensors can provide detailed information about changes in soil water content in time and with depth. This information can be used for data assimilation in soil water flow modeling. The ensemble Kalman

Y. A. Pachepsky; A. Guber; D. Jacques; F. Pan; M. van Genuchten; R. E. Cady; T. J. Nicholson

2010-01-01

92

Remote sensing applications to hydrology: soil moisture  

Microsoft Academic Search

Passive and active microwave remote sensing instruments are capable of measuring the surface soil moisture (0-5 cm) and can be implemented on high altitude platforms, e.g. spacecraft, for repetitive large area observations. The amount of water present in a soil affects its dielectric properties. The dielectric properties, along with several other physical characteristics, determine the microwave measurement. In addi­ tion,

T. J. JACKSON; J. SCHMUGGE; E. T. ENGMAN

1997-01-01

93

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles  

NASA Technical Reports Server (NTRS)

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

Khankhoje, Uday K.; van Zyl, Jakob; Kim, Yunjin; Cwik, Thomas

2012-01-01

94

Physical controls of soil moisture variability at multiple scales  

NASA Astrophysics Data System (ADS)

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. Soil moisture, and, by association, soil hydraulic parameters have been known to be a function of location, and the support scale at which they are measured. Recent increase in remote sensing platforms necessitates increased calibration/validation efforts of their soil moisture products with ground-based measurements. Such cal/val operations require some form of up- or down-scaling process. Understanding the factors that drive soil hydrological processes at different scales, and their variability, is very critical to minimize errors due to this step in the cal/val procedure. Existing literature provides a description of the different sources of soil moisture variability across a range of resolutions from point to continental scales, classified under four categories: soil texture and structure, topography, vegetation, and meteorological forcings. While it is accepted that a dynamic relationship exists between these physical controls and the soil hydraulic properties across spatial scales, the nature of the relationship is not very well understood. In order to formulate better scaling algorithms, it is first necessary to determine the form and amount of influence exerted by the controlling factors on the variability of the soil moisture or hydraulic parameters at each scale of interest. One method to understand the effect of the physical controls is to analyze the covariance or coherence of the physical controls with the soil hydraulic properties across multiple scales and different hydro-climates. Such a study, using wavelet analysis, is presented here. A variety of datasets from multiple platforms across the globe were employed in this study. The AMSR-E soil moisture product was used as the remotely sensed, coarse resolution dataset. Fine resolution, ground-based soil moisture data at the study sites were obtained from the International Soil Moisture Network (ISMN) database. Elevation and slope were derived from SRTM Digital Elevation Data. Soil physical properties such as sand, silt, and clay contents, and precipitation information were obtained from the respective ancillary data from the ISMN database. Vegetation information was derived from the LAI product of the MODIS platform. Similarities in behavior of soil moisture dynamics across hydroclimates at corresponding scales were observed. It was also observed that the influence of the physical controls depended not only on the spatial scale of observation but also on the degree of saturation of the soil. We present these and other inferences drawn from the study.

Jana, R. B.; Mohanty, B.

2013-12-01

95

Analysis of the relationship between bare soil evaporation and soil moisture simulated by 13 land surface schemes for a simple non-vegetated site  

Microsoft Academic Search

Atmospheric and land surface data collected from the HAPEX-MOBILHY field experiment were used to compare the bare soil evaporation simulations of 13 land surface schemes and to examine the relationship between differences in evaporation and differences in soil moisture. For a 120-day period in which there was no vegetation present, computed total evaporation ranged between 100 and 250 mm. This

C. E. Desborough; A. J. Pitman; P. Iranneiad

1996-01-01

96

A soil moisture network in Switzerland: Analyses from the Swiss Soil Moisture Experiment  

NASA Astrophysics Data System (ADS)

Soil moisture is an essential terrestrial variable as it strongly affects land-surface fluxes with consequent impact on runoff generation, temperature, and evapotranspiration. Measurements of soil moisture are crucial to investigate processes in hydrology as well as in climate and environmental science. However, soil moisture is still not routinely measured and there is a lack of observations in many parts of the world. Within the Swiss Soil Moisture Experiment (SwissSMEX, www.iac.ethz.ch/url/research/SwissSMEX) the large-scale and long-term SwissSMEX soil moisture network was established in 2008/2010 in Switzerland. The network has a spatial extent of about 150x210 km and consists of overall 19 sites at 17 different locations, including 14 grassland, 4 forest, and 1 arable land site. For each site measurements of soil moisture and soil temperature down to 120 cm, as well as detailed information about the topography, soil characteristics, and the main meteorological variables are available. The analyses conducted using the SwissSMEX soil moisture data set provide helpful insights on the performance of soil moisture sensors, distinction in soil moisture behavior across different land covers, as well as on the spatio-temporal dynamics of soil moisture. Here we present the design of the SwissSMEX soil moisture network as well as an overview on the analyses based on the developed data set. As for any measurements the performance of the sensor is important, we will focus on the evaluation of the applied capacitance-based 10HS (Decagon Devises, United States) soil moisture sensor. Its measurements agreed well for low volumetric water contents using both laboratory and field measurements. A considerable limitation is found in the decreasing sensitivity of sensor reading for volumetric water contents variations above 0.4 m3/m3. In addition, the applicability of a laboratory calibration function is limited due to a dependency of the sensor on soil characteristics. However, with site-specific calibration functions the measurement error of the 10HS sensor can be decreased and the day-to-day variability of soil moisture is captured (Mittelbach et al., 2011). Furthermore, we present a comparison of soil moisture recession over grassland and nearby forest sites with consequent impact on evapotranspiration, as well as on the spatio-temporal variability of soil moisture within the network using 14 grassland sites (Mittelbach et al. 2012). Reference: Mittelbach, H., F. Casini, I. Lehner, A.J. Teuling, and S.I. Seneviratne, 2011: Soil moisture monitoring for climate research: Evaluation of a low-cost soil moisture sensor in the framework of the Swiss Soil Moisture Experiment (SwissSMEX). Journal of Geophysical Research, 1616, D05111. Mittelbach, H. and S.I. Seneviratne, 2012: A new perspective on the spatio-temporal variability of soil moisture: Temporal dynamics versus time invariant contributions. Submitted to HESS.

Mittelbach, H.; Lehner, I.; Teuling, A. J.; Seneviratne, S. I.

2012-04-01

97

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

USGS Publications Warehouse

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. ?? 2011 Taylor & Francis.

Zhang, L.; Ji, L.; Wylie, B. K.

2011-01-01

98

Soil moisture estimation by using multipolarization SAR image  

NASA Astrophysics Data System (ADS)

In the past studies, different soil moisture estimation models were developed for bare soil areas by using remotely-sensed data. However, there are few models that can be used to estimate soil moisture in vegetated areas. Water Cloud Model (WCM) model is a widely used soil moisture estimation model has been developed for vegetated areas. In this study, the WCM model was extended to take soil roughness parameter into consideration. The modeling and its accuracy assessment were done by using multi-polarization Airborne Synthetic Aperture Radar (AIRSAR) images and ground data collected during field Soil Moisture Experiments. It was shown that the backscatter coefficient of HV cross-polarization is more accurate than HH or VV co-polarization to be used in the proposed Improved Water Cloud Model (IWCM) model. Also, experiments showed that the co-polarization ratio ? HH/ ? VV has high correlation with Vegetation Water Content (VWC). Therefore, in order to make the model independent from ground measurements, the ratio was used alternatively in the proposed IWCM model. The analysis on the IWCM model showed a meaningful improvement on soil moisture estimation accuracy.

Saradjian, M. R.; Hosseini, M.

2011-07-01

99

Assimilation of Passive and Active Microwave Soil Moisture Retrievals.  

National Technical Information Service (NTIS)

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 assim...

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

2012-01-01

100

Comparing soil moisture memory in satellite observations and models  

NASA Astrophysics Data System (ADS)

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 latter in the deepest layer. From this we conclude that the seasonal soil moisture variations dominate the memory close to the surface but these are dampened in lower layers where the memory is mainly affected by longer term variations.

Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

2013-04-01

101

Measuring soil moisture with imaging radars  

SciTech Connect

An empirical algorithm for the retrieval of soil moisture content and surface Root Mean Square (RMS) height from remotely sensed radar data was developed using scatterometer data. The algorithm is optimized for bare surfaces and requires two copolarized channels at a frequency between 1.5 and 11 GHz. It gives best results for kh {le} 2.5, {mu}{sub {upsilon}}{le}35%, and {theta}{ge}30{degree}. Omitting the usually weaker hv-polarized returns makes the algorithm less sensitive to system cross-talk and system noise, simplify the calibration process and adds robustness to the algorithm in the presence of vegetation. However, inversion results indicate that significant amounts of vegetation (NDVI>0.4) cause the algorithm to underestimate soil moisture and overestimate RMS height. A simple criteria based on the {sigma}{sub hv}{sup 0}/{sigma}{sub vv}{sup 0} ratio is developed to select the areas where the inversion is not impaired by the vegetation. The inversion accuracy is assessed on the original scatterometer data sets but also on several SAR data sets by comparing the derived soil moisture values with in-situ measurements collected over a variety of scenes between 1991 and 1994. Both spaceborne (SIR-C) and airborne (AIRSAR) data are used in the test. Over this large sample of conditions, the RMS error in the soil moisture estimate is found to be less than 4.2% soil moisture.

Dubois, P.C.; Zyl, J. van [California Inst. of Tech., Pasadena, CA (United States). Jet Propulsion Lab.] [California Inst. of Tech., Pasadena, CA (United States). Jet Propulsion Lab.; Engman, T. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)] [NASA Goddard Space Flight Center, Greenbelt, MD (United States)

1995-07-01

102

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

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

103

Assimilation of streamflow and in situ soil moisture data into operational distributed hydrologic models: Effects of uncertainties in the data and initial model soil moisture states  

Microsoft Academic Search

We assess the potential of updating soil moisture states of a distributed hydrologic model by assimilating streamflow and in situ soil moisture data for high-resolution analysis and prediction of streamflow and soil moisture. The model used is the gridded Sacramento (SAC) and kinematic-wave routing models of the National Weather Service (NWS) Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM) operating at

Haksu Lee; Dong-Jun Seo; Victor Koren

2011-01-01

104

Soil moisture needs in earth sciences  

NASA Technical Reports Server (NTRS)

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.

Engman, Edwin T.

1992-01-01

105

Soil moisture-temperature coupling: revisited using remote sensing soil moisture  

NASA Astrophysics Data System (ADS)

Hot extremes have been shown to be induced by antecedent soil moisture deficits and drought conditions in several regions (e.g., Mueller and Seneviratne, 2012). While most previous studies on this topic relied on modeling results or precipitation-based soil moisture information (in particular the standardized precipitation index, SPI), we use here a new merged remote sensing (RS) soil moisture product combining data from active and passive microwave sensors to investigate the relation between the number of hot days (NHD) and preceding soil moisture deficits. Overall, the global patterns of soil moisture-NHD correlations from RS data and from SPI as used in previous studies agree relatively well, suggesting that these patterns are partly independent of the chosen dataset. Nonetheless, the strength of the relationship appears underestimated with RS-based soil mois- ture data compared to SPI-based estimates, in particular in previously iden- tified regions of strong soil moisture-temperature coupling. This is mainly due to the fact that the temporal hydrological variability is less pronounced in the RS data than the SPI estimates in these regions, and that pronounced (dry or wet) anomalies appear underestimated. Further, complementary anal- yses with data from the Global Land Data Assimilation System (GLDAS) suggest that the differences between the RS-based soil moisture-NHD and the precipitation-based SPI-NHD coupling estimates are not primarily due to the use of soil moisture instead of SPI, or to the shallow depth of the RS- based soil moisture retrievals. Mueller, B., and S. I. Seneviratne (2012). Hot days induced by precipitation deficits at the global scale. Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1204330109.

Hirschi, Martin; Mueller, Brigitte; Dorigo, Wouter; Seneviratne, Sonia I.

2013-04-01

106

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

NASA Astrophysics Data System (ADS)

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

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

107

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

NASA Astrophysics Data System (ADS)

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

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

108

Modelling of Soil Moisture Movement in a Watershed using SWIM  

Microsoft Academic Search

The present study aims at modelling of soil moisture movement in Barchi watershed (Karnataka) using SWIM (Soil Water Infiltration and Movement). Field and laboratory investigations were carried out to determine the saturated hydraulic conductivity at eight locations using Guelph Permeameter and soil moisture retention characteristics using the Pressure Plate Apparatus. The van Genuchten parameters of soil moisture retention function and

C P Kumar; B K Purandara

109

Scales of temporal and spatial variability of midlatitude soil moisture  

Microsoft Academic Search

Soil moisture observations from direct gravimetric measurements in Russia are used to study the relationship between soil moisture, runoff, and water table depth for catchments with different vegetation types, and to estimate the spatial and temporal correlation functions of soil moisture for different soil layers. For three catchments at Valdai, Russia, one with a grassland, one with an old forest,

Konstantin Y. Vinnikov; Alan Robock; Nina A. Speranskaya; C. Adam Schlosser

1996-01-01

110

Gravity changes, soil moisture and data assimilation  

NASA Astrophysics Data System (ADS)

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-based gravity measurements will also be made on a monthly basis at each monitoring site. There will be two levels of modelling and monitoring; regional across the entire Murrumbidgee Catchment (100,000 km2), and local across a small sub-catchment (150 km2).

Walker, J.; Grayson, R.; Rodell, M.; Ellet, K.

2003-04-01

111

Spatial and temporal variability of modeled and remotely sensed soil moisture products  

NASA Astrophysics Data System (ADS)

Improving numerical weather prediction, as well as hydrological and climate modeling requires reliable information about soil moisture and its spatial and temporal variability, because soil moisture is an essential variable in energy and water balance. Furthermore, knowledge about the spatio-temporal variability of soil moisture is important for up- and downscaling of soil moisture products and for data assimilation. For many applications representative soil moisture time series from large areas or even a global coverage are necessary. While in situ measurements cannot satisfy these criteria, soil moisture products from models and remote sensing are able to provide this data on large scale and in reasonable temporal and spatial resolution. Nevertheless, these products are constrained by the characteristics of the respective model or sensor and retrieval method. In this study, we investigated the temporal and spatial variability of several soil moisture products on a global scale. Two of them are remotely sensed products, the Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture product and the Advanced Scatterometer (ASCAT) surface soil moisture product. To include a product with different characteristics than those inherent to remotely sensed products, we also used the modeled ERA Interim soil moisture product from the ECMWF (European Centre for Medium-Range Weather Forecast). Where available, we also included in situ data from the Global Soil Moisture database in our study. We used the following approaches: (1) With a temporal stability analysis the differences in the products were assessed. Mean relative differences were calculated and ranked from low to high on basis of different soil types of the USDA soil classification. The rankings of the different products were compared. Similar rankings show similar spatio-temporal behavior of the products. (2) We analyzed the relationship between spatial mean soil moisture content and spatial variance of soil moisture to characterize the spatial variability of soil moisture for different soil types and climate zones of the Koeppen-Geiger classification. (3) For the identification and quantification of influence factors on soil moisture distribution, the spatial variance of soil moisture was decomposed into time-varying and time-invariant components. This allows distinguishing between 'stable' factors like topography or land use and changing factors, for example seasonal weather changes or vegetation phenology. Through differences of spatio-temporal variability of the soil moisture products, we assessed the characteristics of the different products and thus determined their usefulness for different applications in different regions. Furthermore, we identified influencing factors on the temporal and spatial variability of soil moisture on large scale.

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

2013-12-01

112

Towards an integrated soil moisture drought monitor for East Africa  

NASA Astrophysics Data System (ADS)

East Africa contains a number of highly drought prone regions, and the humanitarian consequences of drought in those regions can be severe. The severity of these drought impacts combined with a paucity of in situ monitoring networks has given rise to numerous efforts to develop reliable remote drought monitoring systems based on satellite data, physically-based models, or a combination of the two. Here we present the results of a cross-comparison and preliminary integration of three soil moisture monitoring methodologies that, combined, offer the potential for a soil moisture based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa. Three independent methods for estimating soil moisture anomalies, the AMSR-E microwave based satellite sensor, the ALEXI thermal infrared based model and the Noah land surface model, are evaluated using triple collocation error analysis (TCEA). TCEA is used to estimate the reliability of each soil moisture anomaly methodology through statistical cross-comparison-a particularly useful approach given the virtual absence of in situ soil moisture data in this region. While AMSR-E, ALEXI, and Noah each appear to produce reliable soil moisture anomaly estimates over some areas within East Africa, many areas posed significant challenges to one or more methods. These challenges include seasonal cloud cover that hinders ALEXI estimates, dense vegetation that impedes AMSR-E retrievals, and complex hydrology that tests the limits of Noah model assumptions. TCEA allows for assessment of the reliability of each method across seasonal and geographic gradients and provides systematic criteria for merging the three methods into an integrated estimate of spatially distributed soil moisture anomalies for all of East Africa. Results for the period 2007-2011 demonstrate the potential and the limitations of this approach in application to real time drought monitoring.

Anderson, W. B.; Hain, C.; Zaitchik, B. F.; Anderson, M. C.; Alo, C. A.; Yilmaz, M. T.

2011-12-01

113

Comparison of neutron probe and time domain reflectometry techniques of soil moisture analysis.  

National Technical Information Service (NTIS)

The Environmental Science Group of Los Alamos National Laboratory collected soil water content data using Time Domain Reflectometry (TDR) and neutron probe in order to correlate the results from the two techniques in a study performed at Los Alamos, NM. T...

T. G. Schofield, G. J. Langhorst, G. Trujillo, K. V. Bostick, W. R. Hansen

1994-01-01

114

Impact of Soil Moisture Initialization on Seasonal Weather Prediction  

NASA Technical Reports Server (NTRS)

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.

Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)

2002-01-01

115

Soil Moisture Variability Beneath a Melting Snowpack  

NASA Astrophysics Data System (ADS)

The melting of the winter snowpack often enters the soil surface prior to flowing to a stream. Spatio-temporal variability in snowmelt infiltration can impact lateral and vertical hydraulic gradients. Previous snow hydrology modeling efforts often model the snowmelt as a uniform precipitation (or input to the soil) event, which this is known to not be the manner which snowmelt actually occurs. To model the hydrologic processes occurring at the site, variable surface boundary conditions are necessary and were investigated. The Dry Lake campground near Steamboat Springs, CO was selected to study the variability in which melting snowpack infiltrates the soil. The Dry Lake study site contains a small watershed of approximately 0.2 km2, and ranges in elevation from 2510 m to 2690 m containing deciduous and evergreen forests, and open grasslands. Both a Remote Automated Weather Station and Snow Telemetry site lie within the Dry Lake study site and provide meteorological, snow, and soil moisture and temperature data. During the spring of 2013, the variability in the snowpack was surveyed along with soil moisture beneath the snowpack. A time domain reflectometer was used at the bottom of snowpits and gravimetric samples were collected for calibration at the freezing temperatures. The results of the survey show the variability in the soil moisture and implicated infiltration variability which occurs. Such results may be used to improve modeling efforts through the inclusion of variable surface boundary conditions.

Webb, R.; Fassnacht, S. R.

2013-12-01

116

Estimating Subcanopy Soil Moisture with RADAR  

NASA Technical Reports Server (NTRS)

The subcanopy soil moisture of a boreal old jack pine forest is estimated using polarimetric L- and P-band AIRSAR data. Model simulations have shown that for this stand, the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground.

Moghaddam, M.; Saatchi, S.; Cuenca, R. H.

1998-01-01

117

Simulation Test for Soil Moisture Sensing.  

National Technical Information Service (NTIS)

The sample-on-plank simulation test for the remote sensing of bare soil moisture by X-band scatterometer during two months is summarized. The process and the general observations of the test are presented. The sample test shows the advantage in reducing t...

J. Ji

1988-01-01

118

Vegetation Response to Rainfall and Soil Moisture Variability in Botswana.  

National Technical Information Service (NTIS)

This paper presents the results of a study of the relationships between rainfall, soil moisture, and the Normalized Difference Vegetation Index (NDVI) in Botswana. Soil moisture values were calculated via a surface hydrologic model. Spatial and temporal r...

T. J. Farrar

1991-01-01

119

Estimation of Soil Moisture from Diurnal Surface Temperature Observations.  

National Technical Information Service (NTIS)

A coupled heat and moisture balance model was used to determine the thermal inertia of a grass covered top soil under different meteorological conditions. Relations between thermal inertia and soil moisture were established using the De Vries models for t...

A. A. Vandegriend P. J. Camillo

1986-01-01

120

Estimates of monthly mean soil moisture for 1979-1989  

NASA Technical Reports Server (NTRS)

This technical report presents estimated monthly mean global soil moisture distributions for 1979-1989. The soil moisture datasets were prepared as part of the boundary conditions for an atmospheric general circulation model (GEOS-1). Also included are the 11-year averages of monthly mean soil moisture, surface air temperature, monthly total precipitation, evapotranspiration, and potential evapotranspiration. The standard deviation of the monthly mean soil moisture is provided as a measure of year-to-year variability.

Schemm, J.; Schubert, S.; Terry, J.; Bloom, S.

1992-01-01

121

Global High Resolution Soil Moisture Product from the Soil Moisture Active Passive (SMAP) Mission  

NASA Astrophysics Data System (ADS)

The SMAP mission is under development with a target launch date in late 2014. The SMAP mission will provide high resolution (~9 km) and frequent revisit (2-3 days) soil moisture product at a global extent. The SMAP instrument architecture incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer that share a single feedhorn and parabolic mesh reflector. The SMAP radiometer and radar instruments are capable of measuring surface soil moisture under moderate vegetation cover individually, however, the instruments suffer from limitations on spatial resolution (radiometer) and sensitivity (radar), respectively. To overcome the limitations of the individual passive and active approaches, the SMAP mission will combine the two data streams to generate an active-passive intermediate resolution and accuracy soil moisture product. The baseline active-passive algorithm disaggregates the coarse resolution (~36 km) radiometer brightness temperature (Tb) measurements using the spatial pattern within the radiometer footprint as inferred from the high resolution coincident radar co-pol and cross-pol backscatter measurements, and then inverts the disaggregated Tb to retrieve soil moisture.Studies are conducted to evaluate the baseline and optional active-passive algorithms at a global extent using a SMAP orbit simulator that provides capability for end-to-end simulation environment. Various aspects of the baseline active/passive algorithm are evaluated that are to be included in the 9 km global soil moisture product. Soil moisture retrieval results from global-extent study area demonstrate that the mission will meet its requirements of global coverage with an accuracy of <0.04 cm3/cm3 in soil moisture for region below 5 kg/m2 vegetation water content having ~9 km spatial and 3 days temporal resolution.The presentation will introduce the scientific community on the SMAP combined active-passive soil moisture product by especially focusing on product accuracy, retrieval characteristics, flags, retrieval thresholds and masks. SMAP

Das, N. N.; Entekhabi, D.; Njoku, E. G.

2013-12-01

122

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

NASA Technical Reports Server (NTRS)

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

Jones, E. B.

1975-01-01

123

Summer soil moisture regulated by precipitation frequency in China  

Microsoft Academic Search

Drought is one of the most important but least understood issues in global environmental changes. Decrease in soil moisture is an indicator of drought. Here, we analyze summer (June-August) soil moisture measurement data across 50 sites in China in order to investigate the linkage between climate change and drought. At the country scale, a significant decrease in summer soil moisture

Shilong Piao; Lei Yin; Xuhui Wang; Philippe Ciais; Shushi Peng; Zehao Shen; Sonia I. Seneviratne

2009-01-01

124

Status of microwave soil moisture measurements with remote sensing  

Microsoft Academic Search

Active and passive zaicrowave remote sensing techniques have demonstrated their potential for measurements of soil moisture. However, the soil moisture response from them is coupled to vegetation and surface roughness effects, and therefore the interaction among all three needs to be understood. This paper reviews the progress made in the measurement of soil moisture and the factors such as vegetation

Edwin T. Engman; Narinder Chauhan

1995-01-01

125

Overview of the Hydros radar soil moisture algorithm  

NASA Technical Reports Server (NTRS)

In this paper, we will describe the Hydors algorithms to derive soil moisture from L-band polarimetric radar measurements. the baseline Hydros radar algorithm to estimate soil moisture is composed of three steps: land classification, preliminary soil moisture estimation, and final time-series improvement.

Kim, Yunjin; van Zyl, Jakob

2005-01-01

126

National Airborne Field Experiments for Soil Moisture Remote Sensing  

Microsoft Academic Search

Remote sensing technology has a huge potential for improving hydrologic prediction through soil moisture measurement. This is particularly so given that the first dedicated soil moisture satellite is to be launched in 2007; the Soil Moisture and Ocean Salinity (SMOS) mission. However, targeted field experiments must be undertaken now so that immediate use can be made of this data when

Jeffrey Walker; Olivier Merlin; Rocco Panciera; Jetse Kalma; Edward Kim; Jorg Hacker

127

Soil moisture inferences from thermal infrared measurements of vegetation temperatures  

NASA Technical Reports Server (NTRS)

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.

Jackson, R. D. (principal investigator)

1981-01-01

128

Preliminary assessment of soil moisture over vegetation  

NASA Technical Reports Server (NTRS)

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.

Carlson, T. N.

1986-01-01

129

Microwave soil moisture estimation in humid and semiarid watersheds  

NASA Technical Reports Server (NTRS)

Land surface hydrologic-atmospheric interactions in humid and semi-arid watersheds were investigated. Active and passive microwave sensors were used to estimate the spatial and temporal distribution of soil moisture at the catchment scale in four areas. Results are presented and discussed. The eventual use of this information in the analysis and prediction of associated hydrologic processes is examined.

O'Neill, P. E.; Jackson, T. J.; Chauhan, N. S.; Seyfried, M. S.

1993-01-01

130

Analysis of ASAR Wide Swath Mode time series for the retrieval of soil moisture in mountainous areas  

NASA Astrophysics Data System (ADS)

Soil moisture is a key element in the global cycles of water, energy, and carbon. Knowledge on the spatial and temporal distribution of the soil moisture content (SMC) is therefore essential for a number of hydrological applications as well as earth sciences like meteorology or climatology (Heathman et al., 2003). In the last few years there has been an increasing interest towards the estimation of SMC at local scales using active microwave sensors (Barret et al., 2009). Compared to passive microwave sensors, SAR offers the potential to provide data at high spatial resolution (modern sensors can acquire images with up to approximately 1 m), which is particularly important in mountainous areas. So far, these areas have been considered only marginally in research and only pioneer studies can be found in the literature (Brocca et al., 2012; Bertoldi et al. 2013). In this work we analyzed the temporal and spatial dynamics of the surface SMC (0 - 5 cm depth) on the basis of ground data collected by fixed meteorological stations located in the emerging Long-Term Ecological Research (LTER) site Mazia Valley (Province of Bolzano, South Tyrol, Italy), SAR data from ENVISATs ASAR sensor, wide swath (WS) mode (acquired between 2005 and 2012), and SMC estimates from the hydrological model GEOtop (Endrizzi et al., 2013). The SMC retrieval process was based on the support vector regression (SVR) method introduced by Pasolli et al. (2011). The training of the algorithm was based on data acquired in 2010. Furthermore, the SAR backscatter and derived SMC have been compared with time-series derived from the distributed hydrological model GEOtop. The differences in terms of temporal and spatial dynamic have been analyzed. The main goal of this work is to evaluate the spatial and temporal patterns of SAR derived SMC at field scale and to correlate them with ground information. This is a preparatory study to establish a methodology for the retrieval of SMC with high spatial and temporal sampling and to improve retrieval accuracies by integrating temporal information from different sources of ancillary data and from SAR time-series. It was found that the dynamics of both, temporal and spatial SMC patterns obtained from various data sources (ASAR, GEOtop and meteorological stations), show a similar general temporal behaviour that indicates the robustness of the retrieval algorithm with ASAR WS. However, depending on land cover, soil type and local topographic conditions different spatial patters can be found between SMC estimations coming from ASAR and from the GEOtop model. Introducing information on the temporal behaviour of the SAR signal proves to be a promising method for increasing the confidence and accuracy in estimating SMC, complementing hydrological model predictions. Following steps were identified as critical for the retrieval process: the topographic correction and geocoding of SAR data and the calibration of the meteorological stations. Both factors can have significant influence on the quality of SMC estimation. The accuracy of meteorological input and soil parameterization were identified as the most crucial challenges for SMC derived from hydrological modeling. References Barrett, B. W., E. Dwyer, and P. Whelan. "Soil moisture retrieval from active spaceborne microwave observations: An evaluation of current techniques." Remote Sensing 1, no. 3 (2009): 210-242. Bertoldi, G., S. Della Chiesa, C. Notarnicola, L. Pasolli, G. Niedrist, and U. Tappeiner. "Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT 2 images and hydrological modeling." Journal of Hydrology (2014). under revision. Brocca, L., A. Tarpanelli, T. Moramarco, F. Melone, S. M. Ratto, M. Cauduro, S. Ferraris et al. "Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations." Vadose Zone Journal (2013). Endrizzi, S., S. Gruber, M. Dall'Amico, and R. Rigon. "GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil fr

Greifeneder, Felix; Notarnicola, Claudia; Cuozzo, Giovanni; Spindler, Nadine; Bertoldi, Giacomo; Della Chiesa, Stefano; Niedrist, Georg; Stamenkovic, Jelena; Wagner, Wolgang

2014-05-01

131

Microwave Soil Moisture Retrieval Under Trees  

NASA Technical Reports Server (NTRS)

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 vegetation opacity and single scattering albedo. One goal of our current research is to determine whether the tau-omega model can work for tree canopies given the increased scatter from trees compared to grasses and crops, and. if so, what are effective values for tau and omega for trees.

O'Neill, P.; Lang, R.; Kurum, M.; Joseph, A.; Jackson, T.; Cosh, M.

2008-01-01

132

Soil Moisture Active-Passive Mission (SMAP)  

NASA Astrophysics Data System (ADS)

NASA plans to launch the Soil Moisture Active-Passive (SMAP) Satellite in 2012 as the initial mission in response to the National Academy's Earth Science and Applications From Space — National Imperatives for the Next Decade and Beyond. The goals of the SMAP mission are to measure near-surface soil moisture and its freeze/thaw state. The mission will combine both active and passive remote sensing techniques using the L-band channel. This will allow for spatial resolutions on the order of ten kilometers near global coverage with 2-3 day repeat times and an accuracy of roughly 4% for volumetric soil moisture. Through this new level of a combined capabilities and an ability to sense through moderate levels of vegetation, the mission will make large contributions to science by: 1) providing for improvements in estimates of land surface evaporation, 2) improving our understanding of land-atmosphere water and energy exchange, and 3) helping to determine the transition of boreal ecosystems between carbon sink and source regions. The mission will also provide valuable information to decision makers, by improving capabilities to predict, detect, and evaluate floods and droughts. The SMAP project enjoys a lot of heritage: 1) mission planning through the Hydros Project, 2) satellite instrumentation from Aquarius, 3) numerous field campaign activities to evaluate soil moisture remote sensing techniques (e.g. SMEXs, SGPs, etc.), and 4) significant community research in data assimilation of soil moisture (e.g. LDAS, JCSDA, etc). This final aspect, which includes much ongoing work, should enable the use of SMAP's soil moisture data, in near real-time, soon after launch. The data is expected to be useful to weather forecasting by the National Weather Service and potentially ECMWF, and short-term climate predications by numerous groups, including NASA's Global Modeling and Assimilation Office. The adoption of SMAP data into these systems via data assimilation techniques will not be without difficulty and will require rigorous testing to ensure that the SMAP data in used in such a way that improves forecast and prediction capability.

Entin, J. K.

2008-05-01

133

Synergies and complementarities between ASCAT and SMOS soil moisture products  

NASA Astrophysics Data System (ADS)

Soil moisture is a critical variable in many kinds of applications including agriculture, water management, meteorology or climatology. This is especially true in the Mediterranean context, where soil moisture plays an important role in water resources management and hydrometeorological risks such as floods and droughts. Unfortunately, this variable is not widely observed in situ, so we lack data on its time evolution and spatial structure. Remote sensing has been used to estimate surface soil moisture because it provides comprehensive data over large surfaces. In this study we compared two different surface soil moisture remote sensing products; one derived from active microwave data of the ASCAT scatterometer instrument onboard METOP and the other from passive microwave data of the SMOS mission the first dedicated to estimate soil moisture. SMOS measuring frequency (1.4 GHz) is theoretically more suited to measure soil moisture than ASCAT measuring frequency (5.255 GHz) because of its lower vegetation effects. On the other hand, ASCAT- like instruments have been providing measurements for more than 2 decades and have been a key input in building the CCI Soil Moisture Variable. In order to get the best global soil moisture products it is thus essential to understand their respective performances and restrictions. The comparison has been carried out in Catalonia where we have implemented the SURFEX/ISBA land-surface model, which we forced with the SAFRAN meteorological analysis system. A downscaling algorithm has been also implemented and validated over the area to provide SMOS derived soil moisture fields at 1 km spatial resolution. Catalonia is located in the northeast of the Iberian Peninsula and its climate is typically Mediterranean, mild in winter and warm in summer. The Pyrenees and the neighbouring areas have a high-altitude climate, with minimum temperatures below 0º C, annual rainfall above 1000 mm and abundant snow during the winter. Along the coast, the climate is mild and temperate with temperatures increasing from north to south, while the rain behaves the opposite way. The hinterland, far from the sea, has a continental Mediterranean climate, with cold winters and very hot days in summer. Precipitation in Catalonia is very variable spatially and temporally. As a consequence, precipitation is very unevenly distributed within the year and it is also very variable from year to year. The range of altitudes covers over 3,000 metres and the major relief feature are the Pyrenees. Given its varied landscape, in which plains alternate with mountainous areas, Catalonia has a wide range of bioclimatic habitats. The comparison concerns ASCAT soil moisture product and SMOS at its native and increased resolution versus the hydrological model outputs. The comparison shows in general good agreement for both ASCAT and SMOS on the temporal series simulated over flat, non irrigated areas which are not close to the sea. This result gives us confidence, as both methods of estimating the soil moisture (simulation and remote sensing) are very different. However, the comparison also shows the limitations of the different products. On the one hand, SMOS has difficulties in areas close to the sea and in areas with steep relief. On the other hand, the hydrological model is not able to simulate non natural processes such as irrigation. ASCAT, in its turn, shows some limitations over agriculture surfaces where it shows an increase of soil moisture from June to October clearly correlated with vegetation cycle but seems to show better performances in areas close to the sea.

Escorihuela, Maria Jose; Quintana, Pere; Merlin, Olivier

2014-05-01

134

Soil moisture retrieval from satellite images and its application to heavy rainfall simulation in eastern China  

NASA Astrophysics Data System (ADS)

The soil water index (SWI) from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient (CORR), root-mean-squaxe-error (RMSE) and bias (BIAS) shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture (NCEP) in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model's performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy rainfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.

Zhao, D. M.; Su, B. K.; Zhao, M.

2006-03-01

135

Methods of measuring soil moisture in the field  

USGS Publications Warehouse

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.

Johnson, A. I.

1962-01-01

136

Soil moisture at watershed scale: Remote sensing techniques  

NASA Astrophysics Data System (ADS)

Soil moisture at high spatial resolution is required for various land processes related studies. However, currently the resolution of passive microwave retrieved soil moisture is low - around 25 km. To solve this problem, a soil moisture disaggregation algorithm based on thermal inertia relationship between daily temperature change and average soil moisture modulated by vegetation conditions has been formulated. This algorithm was applied to the AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) as well as SMOS (Soil Moisture and Ocean Salinity satellite) to produce the 1 km downscaled soil moisture over the Little Washita Watershed in Oklahoma for the growing season in 2010 and 2011.The disaggregated soil moisture has been compared to in situ observations. The results of this approach are very encouraging.

Fang, Bin; Lakshmi, Venkat

2014-08-01

137

NASA Soil Moisture Data Products and Their Incorporation in DREAM  

NASA Technical Reports Server (NTRS)

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.

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

138

NASA Soil Moisture Active Passive (SMAP) Applications  

NASA Astrophysics Data System (ADS)

The launch of the NASA Soil Moisture Active Passive (SMAP) mission in 2014 will provide global soil moisture and freeze-thaw measurements at moderate resolution (9 km) with latency as short as 24 hours. The resolution, latency and global coverage of SMAP products will enable new applications in the fields of weather, climate, drought, flood, agricultural production, human health and national security. To prepare for launch, the SMAP mission has engaged more than 25 Early Adopters. Early Adopters are users who have a need for SMAP-like soil moisture or freeze-thaw data, and who agreed to apply their own resources to demonstrate the utility of SMAP data for their particular system or model. In turn, the SMAP mission agreed to provide Early Adopters with simulated SMAP data products and pre-launch calibration and validation data from SMAP field campaigns, modeling, and synergistic studies. The applied research underway by Early Adopters has provided fundamental knowledge of how SMAP data products can be scaled and integrated into users' policy, business and management activities to improve decision-making efforts. This presentation will cover SMAP applications including weather and climate forecasting, vehicle mobility estimation, quantification of greenhouse gas emissions, management of urban potable water supply, and prediction of crop yield. The presentation will end with a discussion of potential international applications with focus on the ESA/CEOS TIGER Initiative entitled "looking for water in Africa", the United Nations (UN) Convention to Combat Desertification (UNCCD) which carries a specific mandate focused on Africa, the UN Framework Convention on Climate Change (UNFCCC) which lists soil moisture as an Essential Climate Variable (ECV), and the UN Food and Agriculture Organization (FAO) which reported a food and nutrition crisis in the Sahel.

Orr, Barron; Moran, M. Susan; Escobar, Vanessa; Brown, Molly E.

2014-05-01

139

Soil moisture retrieval from AMSR-E  

Microsoft Academic Search

The Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System (EOS) Aqua satellite was launched on May 4, 2002. The AMSR-E instrument provides a potentially improved soil moisture sensing capability over previous spaceborne radiometers such as the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave\\/Imager due to its combination of low frequency and higher spatial resolution (approximately 60 km

Eni G. Njoku; Thomas J. Jackson; Venkataraman Lakshmi; Tsz K. Chan; Son V. Nghiem

2003-01-01

140

Absolute and relative soil moisture spatial-temporal variability over large areas in Europe  

NASA Astrophysics Data System (ADS)

Knowledge about soil moisture spatial-temporal variability over large areas is fundamental for improving our understanding of land-atmosphere interaction and hydrological processes. The analysis of soil moisture spatial-temporal variability can be carried out considering the absolute (original) soil moisture values, usually expressed in volumetric terms (m³/m³), or relative values, such as the percent of saturation (dimensionless) or temporal anomalies with respect to a long-term mean value (in the same units as the absolute soil moisture values). Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum (absolute) values, even though in relative terms their temporal patterns are very similar. Therefore, a large fraction of the spatial variability of soil moisture might be time invariant, i.e., only due to the differences in the range of variability between sites (Mittelbach and Seneviratne, 2012). In these cases, the analysis considering absolute and relative soil moisture values can provide very different results thus highlighting the requirement of a new perspective in the analysis of soil moisture variability. In fact, if soil moisture observations are used within modelling approaches (for hydrological, meteorological or climatic studies), the variability of relative soil moisture values is much of interest (Seneviratne et al., 2010; Brocca et al., 2012). By considering absolute soil moisture values only, misleading conclusions might be drawn with respect to climate-relevant spatiotemporal features of soil moisture. In this study, in situ observations from different soil moisture networks in Italy, Spain, France and Germany are collected and analyzed to investigate the soil moisture variability over large areas (500-5000 km²). Specifically, the statistical and temporal stability classical analyses of soil moisture have been carried out for both absolute and relative values. The comparison of the results with the different approaches highlights the relative contribution of time invariant and time varying components on soil moisture variability. Moreover, the effect of the variability of the soil texture, land use and climatic conditions of the analyzed soil moisture networks is discussed. Overall, in accordance with a previous study (Mittelbach and Seneviratne, 2012), we obtained that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to relative soil moisture values. Therefore, similar analysis should be carried out for past and present soil moisture data sets for better addressing their use within modelling studies. References Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S., 2012: Assimilation of surface and root-zone ASCAT soil moisture products into rainfall-runoff modelling. IEEE Transactions on Geoscience and Remote Sensing, 50(7), 2542-2555. Mittelbach, H., and S.I. Seneviratne, 2012: A new perspective on the spatio-temporal variability of soil moisture: temporal dynamics versus time invariant contributions. Hydrol. Earth Syst. Sci., 16, 2169-2179. Seneviratne, S I, Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., and Orlowsky, B., 2010: Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3-4), 125-161.

Zucco, Graziano; Brocca, Luca; Moramarco, Tommaso; Seneviratne, Sonia; Mittelbach, Heidi

2013-04-01

141

Root-zone soil moisture estimation using data-driven methods  

NASA Astrophysics Data System (ADS)

soil moisture state partitions both mass and energy fluxes and is important for many hydro-geochemical cycles, but is often only measured within the surface layer. Estimating the amount of soil moisture in the root-zone from this information is difficult due to the nonlinear and heterogeneous nature of the various processes which alter the soil moisture state. Data-driven methods, such as artificial neural networks (ANN), mine data for nonlinear interdependencies and have potential for estimating root-zone soil moisture from surface soil moisture observations. To create an ANN root-zone model that was nonsite-specific and physically constrained, a training set was generated by forcing HYDRUS-1D with meteorological observations for different soil profiles from the unsaturated soil hydraulic database. Ensemble ANNs were trained to provide soil moisture at depths of 10, 20, and 50 cm below the surface using surface soil moisture observations and local meteorological information. Insights into the processes represented by the ANNs were derived from a clamping sensitivity analysis and by changing the ANNs input data. Further model testing based on synthetic soil moisture profiles from three McMaster Mesonet and three USDA soil climate analysis network sites suggests that ANNs are a flexible tool capable of predicting root-zone soil moisture with good accuracy. It was found that ANNs could well represent soil moisture as estimated by HYDRUS-1D, but performance was reduced in comparison to in situ soil moisture observations outside the training conditions. The transferability of the model appears limited to the same geographic region.

Kornelsen, Kurt C.; Coulibaly, Paulin

2014-04-01

142

NASA's Soil Moisture Active Passive (SMAP) observatory  

NASA Astrophysics Data System (ADS)

The Soil Moisture Active Passive (SMAP) mission, one of the first-tier missions recommended by the 2007 U.S. National Research Council Committee on Earth Science and Applications from Space, was confirmed in May 2012 by NASA to proceed into Implementation Phase (Phase C) with a planned launch in October 2014. SMAP will produce high-resolution and accurate global maps of soil moisture and its freeze/thaw state using data from a non-imaging synthetic aperture radar and a radiometer, both operating at L-band. Major challenges addressed by the observatory design include: (1) achieving global coverage every 2-3 days with a single observatory; (2) producing both high resolution and high accuracy soil moisture data, including through moderate vegetation; (3) using a mesh reflector antenna for L-band radiometry; (4) minimizing science data loss from terrestrial L-band radio frequency interference; (5) designing fault protection that also minimizes science data loss; (6) adapting planetary heritage avionics to meet SMAP's unique application and data volume needs; (7) ensuring observatory electromagnetic compatibility to avoid degrading science; (8) controlling a large spinning instrument with a small spacecraft; and (9) accommodating launch vehicle selection late in the observatory's development lifecycle.

Kellogg, K.; Thurman, S.; Edelstein, W.; Spencer, M.; Chen, Gun-Shing; Underwood, M.; Njoku, E.; Goodman, S.; Jai, Benhan

143

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

USGS Publications Warehouse

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

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

2008-01-01

144

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

NASA Astrophysics Data System (ADS)

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

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

2008-08-01

145

Effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge: A Field observation and analysis  

USGS Publications Warehouse

The effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge were studied with water level measurements collected from two monitoring wells over a period of 122 days. The two wells were installed under similar conditions except that one was drilled on the east side of a creek which was covered with grass, and the other on the west side of the creek which was burned into a bare ground. Substantial differences in water level fluctuations were observed at these two wells. The water level in the east grass (EG) well was generally lower and had much less response to rainfall events than the west no-grass (WNG) well. Grass cover lowered the water table, reduced soil moisture through ET losses, and thus reduced groundwater recharge. The amount of ET by the grass estimated with a water table recession model decreased exponentially from 7.6 mm/day to zero as the water table declined from near the ground surface to 1.42 m below the ground surface in 33 days. More groundwater recharge was received on the WNG side than on the EG side following large rainfall events and by significant slow internal downward drainage which may last many days after rainfall. Because of the decreased ET and increased R, significantly more baseflow and chemical loads may be generated from a bare ground watershed compared to a vegetated watershed. ?? 2005 Elsevier Ltd All rights reserved.

Zhang, Y. -K.; Schilling, K. E.

2006-01-01

146

The added value of spaceborne passive microwave soil moisture retrievals for forecasting rainfall-runoff partitioning  

NASA Astrophysics Data System (ADS)

Using existing data sets of spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios. The predictive ability of spaceborne soil moisture retrievals is objectively compared to that obtainable using only available rainfall observations and the antecedent precipitation index (API). The assimilation of spaceborne observations into an API soil moisture proxy is demonstrated to add skill to the forecasting of land surface response to precipitation.

Crow, W. T.; Bindlish, R.; Jackson, T. J.

2005-09-01

147

Assimilation of Passive and Active Microwave Soil Moisture Retrievals  

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

148

Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin  

NASA Astrophysics Data System (ADS)

SummaryThis research investigates the interannual variability of soil moisture as related to large-scale climate variability and also evaluates the spatial and temporal variability of modeled deep layer (40-140 cm) soil moisture in the Upper Colorado River Basin (UCRB). A three layers hydrological model VIC-3L (Variable Infiltration Capacity Model - 3 layers) was used to generate soil moisture in the UCRB over a 50-year period. By using wavelet analysis, deep layer soil moisture was compared to the Palmer Drought Severity Index (PDSI), precipitation, and streamflow to determine whether deep soil moisture is an indicator of climate extremes. Wavelet and coherency analysis for the UCRB indicated a strong relationship between the PDSI, climate variability and the deep soil moisture. The spatial variability of soil moisture during drought, normal, and wet years was analyzed by using map analysis. Distinct regions showing higher vulnerability to drought and wet conditions were identified in the spatial analysis. The temporal variation in soil moisture was performed by utilizing map analysis in pre-drought, drought, and post-drought years for four drought events, 1953-1956, 1959-1964, 1974-1977, and 1988-1992. Less than 50% of the basin had dry conditions (soil moisture anomaly below -10 mm) for the pre-drought years. Soil moisture anomalies were lower than -10 mm for more than 50% of the basin in 15 out of 19 drought years. Generally, droughts did not end until the average soil moisture anomalies increased to positive values for two consecutive years.

Tang, Chunling; Piechota, Thomas C.

2009-12-01

149

Soil Moisture Response to a Changing Climate in Arctic Regions  

Microsoft Academic Search

Soil moisture is the land surface hydrologic variable that most strongly affects land-atmosphere moisture and energy fluxes. In Arctic regions, these interactions are complicated by the role of permafrost. Especially in northern regions, soil moisture therefore is important not only as a hydrological storage component, also as a result of its strong influence on the hydrological cycle through controls on

L. D. Hinzman; D. L. Kane; D. Lettenmaier; D. Yang; Y. Zhao

2002-01-01

150

Preparing for NASA's Soil Moisture Active Passive (SMAP) Mission  

Microsoft Academic Search

Soil Moisture Active\\/Passive (SMAP) Mission is one of the first 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 better estimates of

T. Jackson; D. Entekhabi; E. Njoku; P. O'Neill; J. Entin

2009-01-01

151

Soil Moisture Dynamics in Deep Southern Sierra Nevada Soils  

NASA Astrophysics Data System (ADS)

As part of the Southern Sierra Critical Zone Observatory, the soil surrounding a white fir tree has been instrumented with volumetric water content (VWC), temperature, and soil matric potential sensors. The VWC (5-TM (Decagon Devices, Inc.) and neutron probe) and temperature (5-TM) associated with the deep vadose zone monitoring are being measured by 5-TM sensors. The soil matric potential is measured using tensiometers and MPS-1 sensors (Decagon Devices, Inc.). This instrumentation has been installed at depths of 150, 200, and 250 cm, so as to quantify subsurface soil moisture dynamics. The soil is quite sandy to varying depths after which a saprolyte layer exists moving into a more coarse textured subsurface. As snowmelt and rainfall infiltrate the soil at the surface it wets the soil profile to field capacity with the excess water replenishing deep water resources. The deep water resources are utilized as the shallower subsurface moisture is depleted leading to a more negative soil matric suction causing an upward movement of water for the latter part of the summer. This upward movement of water is assumed to occur via total soil water potential gradients. The tensiometers can only yield data for soil matric suctions less than 600 cm of water, where the MPS-1 sensors can reach suctions up 500 kPa. Thus, since the deep vadose zone instrument installation in summer 2011, it was seen that water started moving upward in late July to early August depending on the profile and winter precipitation.

Malazian, A. I.; Hartsough, P. C.; Hopmans, J. W.

2012-12-01

152

Ultrasonic Velocity Variations with Soil Composition for Moisture Measurement  

NASA Technical Reports Server (NTRS)

Soil moisture content may be measured by many methods, but the presently available techniques all have drawbacks when used in ground truth measurements for remote sensing. Ultrasonic velocity varies with soil moisture content, and may be used as the basis of a new measurement technique. In order to characterize a sensor capable of field use, soil particle size distribution data are compared to ultrasonic velocity in a variety of soils over a wide moisture range.

Metzl, R.; Choi, J.; Aggarwal, M. D.; Manu, A.

1998-01-01

153

Research on Regional Spatial Variability of Soil Moisture Based on GIS  

NASA Astrophysics Data System (ADS)

As one of soil dynamics properties, soil moisture content is an important factor of soil fertility which counts for much to crop growth situation and scientific irrigation management. A design plan of regional spatial variation of soil moisture measurement was introduced. Its main job includes the use of differential GPS technology for each sampling points in farmland, collecting data of high-precision geo-spatial information and soil moisture in farmland resorting on measure instruments of soil moisture, communicating the data between measuring instrument and portable data analysis devices or computer with cable or wireless network based on ZigBee technology, analyzing data of experimental farmland of the topography and terrain, processing and interpolating data of soil moisture content.

Fan, Yongcun; Zhang, Changli; Fang, Junlong; Tian, Lei

154

Intercomparison of spring soil moisture among multiple reanalysis data sets over eastern China  

NASA Astrophysics Data System (ADS)

characteristics of spring soil moisture in different reanalysis data sets of ERA-Interim, Modern Era Retrospective-Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis, Climate Forecast System Reanalysis, and National Centers for Environmental Prediction/National Center for Atmospheric Research-Reanalysis 1 (NCEP/NCAR-R1) are intercompared with each other and with the observations over China. The spring soil moisture is largest in southeastern China and smallest in northwestern China in climatology. It exhibits a pronounced interannual variability with opposite variation in the midlatitude zone and northeastern China. There exist a wet trend at midlatitudes and a dry trend in northeastern China. The intercomparison shows that, except NCEP/NCAR-R1, the reanalyses can reproduce the observed gradual increases of climatological soil moisture in China from the northwest to the northeast and to the southeast. MERRA presents the best climatological soil moisture. Only ERA-Interim can well represent the interannual variations of observed soil moisture. The first empirical orthogonal function mode of observed soil moisture demonstrates that the variability of soil moisture is most robust in the midlatitude zone of eastern China and the ERA-Interim is the best in reproducing the spatial and temporal features. The reasons causing differences between reanalyses of soil moisture are also investigated in terms of two main factors affecting soil moisture, precipitation and evaporation. The ERA-Interim can well reproduce the precipitation and evaporation from observations as well as their relations to soil moisture, resulting in a preferable ability to represent the spatial and temporal characteristics of observed soil moisture. Although the other four reanalysis data sets reproduce precipitation well, their poor ability to describe the evaporation causes large differences of soil moisture between their simulations and observations.

Liu, Li; Zhang, Renhe; Zuo, Zhiyan

2014-01-01

155

Comparing upper soil moisture estimates from SMOS and a land surface model over the Iberian Peninsula  

NASA Astrophysics Data System (ADS)

The recent availability of remotely sensed products for soil moisture opens new possibilities for validating land surface model state variables. Here we compare the Soil Moisture and Ocean Salinity (SMOS) level 2 products with the output of the ORCHIDEE land surface model. ORCHIDEE is well suited for this exercise as it has a very high vertical resolution and simulates soil moisture over the nominal penetration depth of SMOS (5cm) with 5 layers. Over the Iberian Peninsula, the annual cycle and the response to rainfall events of the simulated and remotely sensed products are in good agreement. In a small sub-catchment of the Duero basin (REMEDHUS), the two soil moisture products are highly correlated to the in-situ observations as well. On the other hand, spatial correlations between modelled and remote sensed upper-soil moisture are weak. An analysis of the spectral signatures of both soil moisture estimates has shown that over some parts of the Iberian Peninsula the amplitude of the annual cycle can be very different. An examination of the co-variance of precipitation and upper soil moisture showed that some rainfall patterns do not impact soil moisture in the same way in both products. This allows to propose some hypothesis for the low spatial correlation noted between the SMOS and ORCHIDEE upper soil moisture.

Polcher, Jan; Piles, Maria; Gelati, Emiliano; Tello, Marivi; Barella Ortiz, Anaïs

2014-05-01

156

Comparison of deep soil moisture in two re-vegetation watersheds in semi-arid regions  

NASA Astrophysics Data System (ADS)

Soil moisture stored below rainfall infiltration depth is a reliable water resource for plant growth in semi-arid ecosystems. Along with the large-scale ecological restoration in Chinese Loess Plateau, identifying the ecohydrological response to human-introduced vegetation restoration has become an important issue in current research. In this study, soil moisture data in depth of 0-5 m was obtained by field observation and geostatistical method in two neighboring re-vegetation watersheds. Profile characteristics and spatial pattern of soil moisture was compared between different land use types, transects, and watersheds. The results showed that: (1) Introduced vegetation drastically decreased deep soil moisture when compared with farmland and native grassland. No significant differences in deep soil moisture were found between different introduced vegetation types. (2) An analysis of differences in soil moisture for different land use patterns indicated that land use had significant influence on deep soil moisture spatial variability. Land use structure determined the soil moisture condition and its spatial variation. (3) Vegetation restoration with introduced plants diminished the spatial heterogeneity of deep soil moisture on watershed scale. The improvement of land use management was suggested to improve the water management and maintain the sustainability of vegetation restoration.

Yang, Lei; Chen, Liding; Wei, Wei; Yu, Yang; Zhang, Handan

2014-05-01

157

Determining Soil Volumetric Moisture Content Using Time Domain Reflectometry.  

National Technical Information Service (NTIS)

Time domain reflectometry (TDR) is a technique used to measure indirectly the in situ volumetric moisture content of soil. Current research provides a variety of prediction equations that estimate the volumetric moisture content using the dielectric const...

J. Klemunes

1998-01-01

158

Concerning the relationship between evapotranspiration and soil moisture  

NASA Technical Reports Server (NTRS)

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.

Wetzel, Peter J.; Chang, Jy-Tai

1987-01-01

159

MoistureMap: A soil moisture monitoring, prediction and reporting system for sustainable land and water management  

Microsoft Academic Search

A prototype soil moisture monitoring, prediction and reporting system is being developed for Australia, with the Murrumbidgee catchment as the demonstration catchment. The system will provide current and future soil moisture information and its uncertainty at 1km resolution, by combining weather, climate and land surface model predictions with soil moisture data from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite;

C. Rudiger; J. P. Walker; D. J. Barrett; R. J. Gurney; Y. H. Kerr; E. J. Kim; J. Lemarshall

2009-01-01

160

The added value of spaceborne passive microwave soil moisture retrievals for forecasting rainfall-runoff partitioning  

Microsoft Academic Search

Received 18 May 2005; revised 22 July 2005; accepted 18 August 2005; published 17 September 2005. (1) Using existing data sets of spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Measuring Mission (TRMM)

W. T. Crow; R. Bindlish; T. J. Jackson

2005-01-01

161

Remote sensing of soil moisture with microwave radiometers  

NASA Technical Reports Server (NTRS)

Microwave radiometry has been used for the remote sensing of soil moisture in a series of aircraft flights over an agricultural test area in the vicinity of Phoenix, Arizona. The radiometers covered the wavelength range 0.8-21 cm. Ground truth in the form of gravimetric measurements of the soil moisture in the top 15 cm were obtained for 200 fields at this site. The results indicate that it is possible to monitor moisture variations with airborne radiometers. The emission is a function of the radiometer wavelength and the distribution of the moisture in the soil. At a wavelength of 1.55 cm there is little or no variation in the emission for soil moisture values below 10 or 15% moisture content by weight. Above this value, there is a linear decrease in the emission with a slope of approximately 3 K for each percentage point increase in soil moisture.

Schmugge, T.; Gloersen, P.; Wilheit, T.; Geiger, F.

1974-01-01

162

Quantifying mesoscale soil moisture with the cosmic-ray rover  

NASA Astrophysics Data System (ADS)

Soil moisture governs the surface fluxes of mass and energy and is a major influence on floods and drought. Existing techniques measure soil moisture either at a point or over a large area many kilometers across. To bridge these two scales we used the cosmic-ray rover, an instrument similar to the recently developed COSMOS probe, but bigger and mobile. This paper explores the challenges and opportunities for mapping soil moisture over large areas using the cosmic-ray rover. In 2012, soil moisture was mapped 22 times in a 25 km × 40 km survey area of the Tucson Basin at 1 km2 resolution, i.e., a survey area extent comparable to that of a pixel for the Soil Moisture and Ocean Salinity (SMOS) satellite mission. The soil moisture distribution is dominated by climatic variations, notably by the North American monsoon, that results in a systematic increase in the standard deviation, observed up to 0.022 m3 m-3, as a function of the mean, between 0.06 and 0.14 m3 m-3. Two techniques are explored to use the cosmic-ray rover data for hydrologic applications: (1) interpolation of the 22 surveys into a daily soil moisture product by defining an approach to utilize and quantify the observed temporal stability producing an average correlation coefficient of 0.82 for the soil moisture distributions that were surveyed and (2) estimation of soil moisture profiles by combining surface moisture from satellite microwave sensors with deeper measurements from the cosmic-ray rover. The interpolated soil moisture and soil moisture profile estimates allow for basin-wide mass balance calculation of evapotranspiration, totaling 241 mm for the year 2012. Generating soil moisture maps with cosmic-ray rover at this intermediate scale may help in the calibration and validation of satellite campaigns and may also aid in various large scale hydrologic studies.

Chrisman, B.; Zreda, M.

2013-06-01

163

Soil moisture-vegetation-precipitation feedback over North America: Its sensitivity to soil moisture climatology  

NASA Astrophysics Data System (ADS)

Our previous studies examined how vegetation feedback at the seasonal time scale influenced the impact of soil moisture anomalies (SMAs) on subsequent summer precipitation with a modified version of the coupled Community Atmosphere Model-Community Land Model 3 that includes a predictive phenology scheme. Here we investigate the climatology sensitivity of soil moisture-vegetation-precipitation feedback using the same model as the baseline model (BASE) and its derivative with modifications to the model runoff parameterization as the experiment model (EXP), in which we eliminate the subsurface lateral drainage to reduce the known dry biases of BASE. With vegetation feedback ignored, precipitation is more sensitive to wet SMAs than dry SMAs in BASE; opposite to BASE, the wetter mean soil moisture in EXP leads to higher sensitivity of precipitation to dry SMAs than to wet SMAs. However, in both BASE and EXP, the impact of dry SMAs on subsequent precipitation persists longer than the impact of wet SMAs. With vegetation feedback included, EXP shows a positive feedback between vegetation and precipitation following both dry and wet SMAs in summer, while BASE shows a positive feedback following wet SMAs only, with no clear signal following dry SMAs due to dry soil biases. In BASE, the magnitude of precipitation changes due to vegetation feedback is comparable to that due to soil moisture feedback when more realistic SMAs are applied. In addition, a major difference is found in spring when the vegetation impact on subsequent precipitation is negative and significant in BASE, but not significant in EXP.

Kim, Yeonjoo; Wang, Guiling

2012-09-01

164

Ultrasound Algorithm Derivation for Soil Moisture Content Estimation  

NASA Technical Reports Server (NTRS)

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.

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

1997-01-01

165

Soil moisture profile variability in land-vegetation- atmosphere continuum  

Microsoft Academic Search

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

Wanru Wu

2000-01-01

166

Quantifying mesoscale soil moisture with the cosmic-ray rover  

NASA Astrophysics Data System (ADS)

Existing techniques measure soil moisture either at a point or over a large area many kilometers across. To bridge these two scales, we used the mobile cosmic-ray probe, or cosmic-ray rover, an instrument similar to the recently developed COSMOS probe, but bigger and mobile. This study explores the challenges and opportunities for making maps of soil moisture over large areas using the cosmic-ray rover. In 2012, soil moisture was mapped 22 times in a 25 km x 40 km survey area of the Tucson Basin at 1 km 2 resolution, i.e., at a scale comparable to that of a pixel for the Soil Moisture and Ocean Salinity (SMOS) satellite mission. The soil moisture distribution is influenced mainly by climatic variations, notably by the North American monsoon, which resulted in a systematic change in the regional variance as a function of the mean soil moisture.

Chrisman, Bobby B.

167

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

NASA Technical Reports Server (NTRS)

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.

Arya, L. M.; Phinney, D. E. (principal investigators)

1980-01-01

168

Use of Ultrasonic Technology for Soil Moisture Measurement  

NASA Technical Reports Server (NTRS)

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.

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

1997-01-01

169

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System  

NASA Technical Reports Server (NTRS)

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

170

On the spatio-temporal dynamics of soil moisture at the field scale  

NASA Astrophysics Data System (ADS)

In this paper, we review the state of the art of characterizing and analyzing spatio-temporal dynamics of soil moisture content at the field scale. We discuss measurement techniques that have become available in recent years and that provide unique opportunities to characterize field scale soil moisture variability with high spatial and/or temporal resolution. These include soil moisture sensor networks, hydrogeophysical measurement techniques, novel remote sensing platforms, and cosmic ray probes. Techniques and methods to analyze soil moisture fields are briefly discussed and include temporal stability analysis, wavelet analysis and empirical orthogonal functions. We revisit local and non-local controls on field scale soil moisture dynamics and discuss approaches to model these dynamics at the field scale. Finally, we address the topic of optimal measurement design and provide an outlook and future research perspectives.

Vereecken, H.; Huisman, J. A.; Pachepsky, Y.; Montzka, C.; van der Kruk, J.; Bogena, H.; Weihermüller, L.; Herbst, M.; Martinez, G.; Vanderborght, J.

2014-08-01

171

Relationships between oceanic-atmospheric patterns and soil moisture in the Upper Colorado River Basin  

NASA Astrophysics Data System (ADS)

SummarySoil moisture is an important drought index in the Upper Colorado River Basin (UCRB) and understanding its relationships with oceanic-atmospheric patterns provides valuable information for sustainable water management. To begin with, this study generated 50 years (1950-2000) of soil moisture data in the UCRB using the Variable Infiltration Capacity (VIC) model. This was followed by a temporal evaluation of Pacific Ocean Sea Surface Temperatures (SSTs) and soil moisture in the UCRB during drought, normal, and wet years. Besides in-phase analysis, lead time analysis was also performed in which the previous year's SSTs were evaluated with the current year soil moisture. Furthermore, the Singular Value Decomposition (SVD) analysis revealed strong correlation between the first temporal expansion series of SSTs and soil moisture in the UCRB. Finally, this study examined the relationships between multiple oceanic-atmospheric patterns and soil moisture in the UCRB in drought, normal, and wet years. Both in-phase and lead time analyses indicated that the Pacific Decadal Oscillation (PDO) strongly influenced soil moisture by displaying positive coupled regions (significance >95%). In drought and wet years, the lead time analysis showed a positive correlation between the El Niño-Southern Oscillation (ENSO) and soil moisture but the in-phase analysis resulted in a negative correlation. The Atlantic Multi-decadal Oscillation (AMO) displayed similar coupled regions for both in-phase and lead time analyses in drought and wet years. Understanding the relationships between soil moisture and oceanic-atmospheric patterns has increasingly important implications for the water resources management in the UCRB since soil moisture plays a key role in predicting the runoff and streamflow.

Tang, Chunling; Piechota, Thomas C.; Chen, Dong

2011-12-01

172

Estimating profile soil moisture and groundwater variations using GRACE and Oklahoma Mesonet soil moisture data  

Microsoft Academic Search

In this study we estimate a time series of regional groundwater anomalies by combining terrestrial water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) satellite mission with in situ soil moisture observations from the Oklahoma Mesonet. Using supplementary data from the Department of Energy's Atmospheric Radiation Measurement (DOE ARM) network, we develop an empirical scaling factor with which

Sean Swenson; James Famiglietti; Jeffrey Basara; John Wahr

2008-01-01

173

Relating TRMM precipitation radar land surface backscatter response to soil moisture in the Southern United States  

NASA Astrophysics Data System (ADS)

SummarySoil moisture is an important variable in the hydrological cycle and plays a vital role in agronomy, meteorology, and hydrology. It regulates the exchange of water and heat between land surface and atmosphere and thus plays an important role in the development of weather patterns. It is difficult to obtain a comprehensive spatio-temporal map of soil moisture because of expensive installation of soil moisture measuring instruments. In this paper, a model to estimate soil moisture ( m s) using Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) backscatter ( ?°) and Normalized Difference Vegetation Index (NDVI) is developed for the Southern United States. Soil moisture data from Soil and Climate Analysis Network (SCAN) stations is used to calibrate and validate the model. The estimated values of m s compare well with the ground measurements of soil moisture. The model works well for various landcovers but works best for low density vegetated areas (closed shrubland). All the soil moisture estimates in this landcover have an absolute error of less than 8%. The model performance deteriorates with increase in vegetation density (crops and forest). Overall, the model performance is satisfactory for all landcover types with RMSE less than 6.3% and absolute error of 10% or less for 90% of the estimates. Estimation of soil moisture over a large area with low error provides another use of TRMMPR data.

Puri, Sumit; Stephen, Haroon; Ahmad, Sajjad

2011-05-01

174

SAR-derived soil moisture measurements for bare fields  

NASA Technical Reports Server (NTRS)

The results of algorithm development and testing for soil moisture retrieval at high incidence angles are reported. Based on first-order surface backscattering models, a physically based algorithm for retrieval of soil moisture has been developed and evaluated using NASA/JPL aircraft SAR (synthetic aperture radar) data. It shows that the co-polarization ratio is sensitive to soil moisture change but not to surface roughness at high incidence angles. This algorithm performed well at L-band and should be useful for repetitive, large-area soil moisture monitoring, without requiring surface roughness measurements. This study suggests that incidence angles greater than 40 deg are optimal for such monitoring.

Shi, Jiancheng; Soares, Joao V.; Hess, Laura; Engman, Edwin T.; Van Zyl, Jakob J.

1991-01-01

175

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations  

NASA Technical Reports Server (NTRS)

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 L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

2010-01-01

176

Surface Soil Moisture Assimilation From ASAR Imagery for Root Zone Moisture Predictions at Basin Scale  

NASA Astrophysics Data System (ADS)

The state of the root-zone soil moisture is a key variable controlling surface water and energy balances. Emerging efforts in data assimilation seek to guide land surface models (LSMs) with periodic observations of surface soil moisture. Montaldo et al. (Water Resour. Res., 2001) and Montaldo and Albertson (Adv. Water Resour., 2003) developed an operational multi-scale assimilation system for robust root zone soil moisture predictions at the local scale. The assimilation scheme, developed for a force-restore method based LSM, updates the measured surface soil moisture, the root zone soil water content and the soil hydraulic conductivity, in a manner that compensates for both inaccurate initial conditions and model parameter estimates. In this presentation we describe the development and testing of an operational assimilation system for robust root-zone soil moisture predictions at the basin scale. High resolution data of the new ASAR (advanced synthetic aperture radar) sensor aboard European Space Agency's Envisat satellite offers the opportunity for monitoring surface soil moisture at high resolution (up to 30 m), which is suitable for distributed mapping within the small scales of typical Mediterranean basins. Indeed, adequate spatio-temporal monitoring of the soil moisture is essential to improve our capability to simulate the water balance. As part of a recently-approved European Space Agency (ESA) Envisat AO project, ASAR-based soil moisture mapping of the Mulargia basin (area of about 65 sq.km), sub-basin of the Flumendosa basin in Sardinia, are available . This semi-arid basin has a key role in the water resources management of Sardinia. Semi-arid regions, such as Sardinia island, suffers from water scarcity, which is increasingly due to the broad desertification processes of the Mediterranean area. Within the basin, land surface fluxes are well monitored through two evapotraspiration measurement systems (one eddy correlation technique based station, and one Bowen ratio station), and spatially distributed soil moisture ground-truth data needed to assess the ASAR imagery are collected over the whole basin through the TDR technique and the gravimetric method. The objectives of this work are to: 1) test the high resolution ASAR imagery accuracy for producing maps of surface soil moisture patterns at the catchment scale, 2) develop and test an operational assimilation system for robust root-zone soil moisture predictions at the basin scale. The developed assimilation system will have two components, 1) ASAR observations will be merged with the model for robust surface soil moisture estimates though the Ensemble Kalman Filter, and 2) the surface soil moisture estimates will then drive an assimilation engine for robust root-zone soil moisture predictions.

Caschili, A.; Montaldo, N.; Mancini, M.; Albertson, J. D.; Botti, P.; Dessena, M. A.; Carboni, E.

2003-12-01

177

Understanding tree growth in response to moisture variability: Linking 32 years of satellite based soil moisture observations with tree rings  

NASA Astrophysics Data System (ADS)

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 temperature datasets. Precipitation was important during both the current and previous growth season. Temperature showed the strongest correlation for previous (R=0.12) and current October (R=0.21). Hence, our results demonstrated that water supply is most likely limiting tree growth during the growing season, while temperature is determining its length. We are confident that long-term satellite based soil moisture observations can bridge spatial and temporal limitations that are inherent to in situ measurements, which are traditionally used for tree ring research. Our preliminary results are a foundation for further studies linking remotely sensed datasets and tree ring chronologies, an approach that has not been widely investigated among the scientific community.

Albrecht, Franziska; Dorigo, Wouter; Gruber, Alexander; Wagner, Wolfgang; Kainz, Wolfgang

2014-05-01

178

Inflatable Antenna Microwave Radiometer for Soil Moisture Measurement  

NASA Technical Reports Server (NTRS)

Microwave measurements of soil moisture are not being obtained at the required spatial Earth resolution with current technology. Recently, new novel designs for lightweight reflector systems have been developed using deployable inflatable antenna structures which could enable lightweight real-aperture radiometers. In consideration of this, a study was conducted at the NASA Langley Research Center (LaRC) to determine the feasibility of developing a microwave radiometer system using inflatable reflector antenna technology to obtain high spatial resolution radiometric measurements of soil moisture from low Earth orbit and which could be used with a small and cost effective launch vehicle. The required high resolution with reasonable swath width coupled with the L-band measurement frequency for soil moisture dictated the use of a large (30 meter class) real aperture antenna in conjunction with a pushbroom antenna beam configuration and noise-injection type radiometer designs at 1.4 and 4.3 GHz to produce a 370 kilometer cross-track swath with a 10 kilometer resolution that could be packaged for launch with a Titan 2 class vehicle. This study includes design of the inflatable structure, control analysis, structural and thermal analysis, antenna and feed design, radiometer design, payload packaging, orbital analysis, and electromagnetic losses in the thin membrane inflatable materials.

Bailey, M. C.; Kendall, Bruce M.; Schroeder, Lyle C.; Harrington, Richard F.

1993-01-01

179

Dissecting soil moisture-precipitation coupling  

NASA Astrophysics Data System (ADS)

The ability of soil moisture to affect precipitation (SM-P) can be dissected into the ability of soil moisture to affect evapotranspiration (ET; SM-ET) and the ability of ET to affect precipitation (ET-P). SM-ET is a local process that is relatively easy to quantify, but ET-P includes nonlocal atmospheric processes and is more complex. Here, ET-P is quantified both locally and remotely with a back-trajectory method for water vapor transport, using corrected reanalysis data. It is found that, for SM-P and ET-P, local impact is greater than that from remote for most land areas with significant local impacts. By examining the responses of the three metrics (SM-ET, ET-P, and SM-P) to climate variations over different climate regimes, we show that SM-ET is the principal factor that determines the spatial pattern and variation of SM-P. For climatologically wet regions, SM-ET and SM-P are higher during dry periods, and vice versa for climatologically dry regions. All three metrics show highest values over the transitional zones.

Wei, Jiangfeng; Dirmeyer, Paul A.

2012-10-01

180

Evaluation and Application of Remotely Sensed Soil Moisture Products  

NASA Technical Reports Server (NTRS)

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.; Rodell, Matt

2010-01-01

181

A methodology for initializing soil moisture in a global climate model: Assimilation of near-surface soil moisture observations  

Microsoft Academic Search

Due to its long-term persistence, accurate initialization of land surface soil moisture infully-coupled global climate models has the potential to greatly increase the accuracy ofclimatological and hydrological prediction. To improve the initialization of soil moisture in theNASA Seasonal-to-Interannual Prediction Project (NSIPP), a one-dimensional Kalman filter hasbeen developed to assimilate near-surface soil moisture observations into the catchment-basedland surface model used by

Jeffrey P. Walker; Paul R. Houser

2001-01-01

182

A methodology for initializing soil moisture in a global climate model: Assimilation of near-surface soil moisture observations  

Microsoft Academic Search

Because of its long-term persistence, accurate initialization of land surface soil moisture in fully coupled global climate models has the potential to greatly increase the accuracy of climatological and hydrological prediction. To improve the initialization of soil moisture in the NASA Seasonal-to-Interannual Prediction Project (NSIPP), a one-dimensional Kalman filter has been developed to assimilate near-surface soil moisture observations into the

Jeffrey P. Walker; Paul R. Houser

2001-01-01

183

Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part II-Vegetation-Covered Soil  

Microsoft Academic Search

Results are presented of an experimental investigation to determine the relationship between radar backscatter coefficient ¿° and soil moisture for vegetation-covered soil. These results extend a previous report which showed the experimental relationship between ¿° and soil moisture for bare soil [1]. It is shown that the highest correlation between ¿° and soil moisture is 0.92 for the combined response

Fawwaz Ulaby; Gerald Bradley; Myron Dobson

1979-01-01

184

Soil Moisture Data Assimilation in Soil Water Flow Modeling  

NASA Astrophysics Data System (ADS)

Soil water flow modeling has multiple applications. This modeling is based on simplifications stemming from both conceptual uncertainty and lack of detailed knowledge about parameters. Modern soil moisture sensors can provide detailed information about changes in soil water content in time and with depth. This information can be used for data assimilation in soil water flow modeling. The ensemble Kalman filter appears to be an appropriate method for that. Earlier we demonstrated ensemble simulations of soil water flow by using sets of pedotransfer functions (empirical relationships between soil hydraulic properties and soil basic properties, such as particle size distribution, bulk density, organic carbon content, etc.). The objective of this work was to apply the data assimilation with the ensemble Kalman filter to soil water flow modeling, using soil water content monitoring with TDR probes and an ensemble of soil water flow models parameterized with different pedotransfer functions. Experiments were carried out at the Bekkevoort site, Belgium. Sixty time domain reflectometry (TDR) probes with two rods) were installed along the trench in loamy soil at 12 locations with 50-cm horizontal spacing at five depths (15, 35, 55, 75, and 95 cm). Water content and weather parameters were monitored for one year with 15 min frequency. Soil water flow was simulated using the HYDRUS6 software. Mean daily means of water contents at the observation depths were the measurements used in data assimilation. Eighteen pedotransfer functions for water retention and one for hydraulic conductivity were applied to generate ensembles to evaluate the uncertainty in simulation results, whereas the replicated measurements at each of measurement depths were used to characterize the uncertainty in data. Data assimilation appeared to be very efficient. Even assimilating measurements at a single depth provided substantial improvement in simulations at other observation depths. Results on selecting one best depth or two best depths will be presented. Best depths appear to be different depending on whether simulations are carried out to estimate soil water dynamics in root zone or to estimate infiltration losses beyond this zone. Soil moisture sensor data assimilation in soil flow modeling allows one to avoid multiparametric calibration and correct simulation on the go which can be beneficial in many applications, Using pedotransfer functions in ensemble Kalman filter results in the effective data assimilation in soil water flow modeling.

Pachepsky, Y. A.; Guber, A.; Jacques, D.; Pan, F.; van Genuchten, M.; Cady, R. E.; Nicholson, T. J.

2010-12-01

185

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

NASA Astrophysics Data System (ADS)

Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.

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

2012-04-01

186

A nonlinear coupled soil moisture-vegetation model  

NASA Astrophysics Data System (ADS)

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.

Liu, Shikuo; Liu, Shida; Fu, Zuntao; Sun, Lan

2005-06-01

187

Examining the relationship between soil moisture and summer extreme temperatures in East China  

NASA Astrophysics Data System (ADS)

Soil moisture conditions affect energy partitioning between sensible and latent heat fluxes, resulting in a change in surface temperatures. In this study, relationship between antecedent soil moisture conditions (as indicated by the 6-month Standardized Precipitation Index (SPI)) and several temperature indices are statistically quantified using the quantile regression analysis across East China to investigate the influence of soil moisture on summer surface temperatures. These temperature indices include percentage of hot-degree days (%HD), hot wave duration (HWD), daily temperature range (DTR), and daily minimum temperature (Tmin). Our results demonstrate that soil moisture had a significant impact on %HD and HWD at higher quantiles in all regions except East, suggesting that drier soil moisture conditions tend to intensity summer hot extremes. It was also found that hot extremes (%HD and HWD at higher quantiles) had increased substantially from 1958 to 2010. Soil moisture also significantly affected the DTR in all regions, but tended to have more impacts on the DTR in soil moisture-limited regimes than in energy-limited regimes. This study provides observational evidence of soil moisture influences on hot extremes in East China.

Meng, Lei

2014-05-01

188

The role of surface vs. root-zone soil moisture variability for soil moisture-temperature coupling  

NASA Astrophysics Data System (ADS)

Hot extremes have been shown to be induced by antecedent surface moisture deficits in several regions. While most previous studies on this topic relied on modeling results or precipitation-based surface moisture information (particularly the standardized precipitation index, SPI), we use here a new merged remote sensing (RS) soil moisture product that combines active and passive microwave sensors to investigate the relation between the number of hot days (NHD) and preceding soil moisture deficits. Along with analyses of temporal variabilities of surface vs. root-zone soil moisture, this sheds light on the role of different soil depths for soil moisture-temperature coupling. The global patterns of soil moisture-NHD correlations from RS data and from SPI as used in previous studies are comparable. Nonetheless, the strength of the relationship appears underestimated with RS-based soil moisture compared to SPI-based estimates, particularly in regions of strong soil moisture-temperature coupling. This is mainly due to the fact that the temporal hydrological variability is less pronounced in the RS data than in the SPI estimates in these regions, and large dry/wet anomalies appear underestimated. Comparing temporal variabilities of surface and root-zone soil moisture in in-situ observations reveals a drop of surface-layer variability below that of root-zone when dry conditions are considered. This feature is a plausible explanation for the observed weaker relationship of RS-based soil moisture (representing the surface layer) with NHD as it leads to a gradual decoupling of the surface layer from temperature under dry conditions, while root-zone soil moisture sustains more of its temporal variability.

Hirschi, Martin; Mueller, Brigitte; Dorigo, Wouter; Seneviratne, Sonia I.

2014-05-01

189

Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part I-Bare Soil  

Microsoft Academic Search

This is the first in a series of two papers on the use of active microwave remote sensing for measuring the moisture content of bare (Part I) and vegetation-covered (Part II) soil. An experimental program was conducted to evaluate the response of the backscattering coefficient to soil moisture content as a means to specify radar system parameters for future airborne

FAWWAZ T. ULABY; Percy Batlivala; Myron Dobson

1978-01-01

190

A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole  

NASA Astrophysics Data System (ADS)

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatial/temporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we established a dense monitoring network on central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0, 0.3, 0.1 degree) and four soil depths (0~5cm, 10cm, 20cm, and 40cm). The experimental area is characterized by low biomass, large soil moisture dynamic range and typical freeze-thaw cycle. The network consists of 56 stations with their elevation varying over 4470 ~ 4950 m. Soil texture and soil organic matters are measured at each station, as auxiliary parameters of this network. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. As the highest soil moisture network in the world, our network meets the requirement for evaluating a variety of soil moisture products and for soil moisture scaling. It also directly contributes to the "water-ice-air-ecosystem-human" interaction theme of the "Third Pole Environment" Program. The data will be publicized via the International Soil Moisture Network. Publication: Zhao, L., K. Yang, J. Qin, Y-Y Chen, W-J Tang, C. Montzka, H. Wu, C-G Lin, M-L Han, and H. Vereecken., 2012: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology DOI: 10.1016/j.jhydrol.2012.12.033.

Yang, Kun; Qin, Jun; Zhao, Long; Chen, Yingying; Han, Menglei

2013-04-01

191

Preferential states in soil moisture and climate dynamics  

NASA Astrophysics Data System (ADS)

Summer precipitation in continental midlatitude regions is significantly contributed by local recycling, i.e., by moisture returning to the atmosphere through evapotranspiration from the same region. On the other hand, reduced soil moisture availability may limit evapotranspiration rates with effects on the planetary boundary layer dynamics through the partitioning between sensible and latent heat fluxes. Thus, a dependence may exist between precipitation and antecedent soil moisture conditions. Here we provide theoretical and experimental evidence in support of the hypothesis that in continental regions summer soil moisture anomalies affect the probability of occurrence of subsequent precipitation. Owing to these feedbacks, two preferential states may arise in summer soil moisture dynamics, which thus tend to remain locked either in a "dry" or a "wet" state, whereas intermediate conditions have low probability of occurrence. In this manner, such land-atmosphere interactions would explain the possible persistence of summer droughts sustained by positive feedbacks in response to initial (spring) surface moisture anomalies.

D'Odorico, Paolo; Porporato, Amilcare

2004-06-01

192

SMOS Soil moisture Cal val activities  

NASA Astrophysics Data System (ADS)

SMOS, successfully launched on November 2, 2009, uses an L Band radiometer with aperture synthesis to achieve a good spatial resolution.. It was developed and made under the leadership of the European Space Agency (ESA) as an Earth Explorer Opportunity mission. It is a joint program with the Centre National d'Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Tecnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L band 2D interferometric,radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the vegetation and with the atmosphere being almost transparent, it enables us to infer both soil moisture and vegetation water content. SMOS achieves an unprecedented spatial resolution of 50 km at L-band maximum (43 km on average) with multi angular-dual polarized (or fully polarized) brightness temperatures over the globe and with a revisit time smaller than 3 days. SMOS is now acquiring data and has undergone the commissioning phase. The data quality exceeds what was expected, showing very good sensitivity and stability. The data is however very much impaired by man made emission in the protected band, leading to degraded measurements in several areas including parts of Europe and China. Many different international teams are now performing cal val activities in various parts of the world, with notably large field campaigns either on the long time scale or over specific targets to address the specific issues. These campaigns take place in various parts of the world and in different environments, from the Antarctic plateau to the deserts, from rain forests to deep oceans. SMOS is a new sensor, making new measurements and paving the way for new applications. It requires a detailed analysis of the data so as to validate both the approach and the quality of the retrievals, and allow for monitoring and the evolution of the sensor. To achieve such goals it is very important to link efficiently ground measurement to satellite measurements through field campaigns and related airborne acquisitions. Comparison with models and other satellite products are necessary. It is in this framework that CESBIO has been involved with many groups to assess the data over many areas in close collaboration. This paper aims at summarising briefly the results (presented in detail in other presentations) to give a general overview and a general first taste of SMOS' performance, together with the identified gaps and next steps to be taken. This presentation could be the general introduction to Cal Val activities.

Kerr, Y.; Mialon, A.; Bitar, A. Al; Leroux, D.; Richaume, P.; Gruhier, C.; Berthon, L.; Novello, N.; Rudiger, C.; Bircher, S.; Wigneron, J. P.; Ferrazzoli, P.; Rahmoune, R.

2012-04-01

193

The Soil Moisture and Ocean Salinity Mission - An Overview  

Microsoft Academic Search

The Soil Moisture and Ocean Salinity (SMOS) mission is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the current lack of global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. The paper will give an overview on the

Susanne Mecklenburg; Yann Kerr; Achim Hahne

2008-01-01

194

Relationships between Climate Variability, Drought and Model Soil Moisture  

Microsoft Academic Search

This research investigates the interannual variability of soil moisture as related to large scale climate variability. A three layer hydrological model VIC -3L (Variable Infiltration Capacity Model - 3 layers) was used in the Colorado River Basin and Mississippi River Basin over a 50 year period. The simulation focuses on the soil moisture generation and simulation have been developed between

C. Tang; T. Piechota

2004-01-01

195

Spatial and temporal variability of soil moisture and climate variability  

Microsoft Academic Search

This research investigates the spatial and temporal variability of soil moisture as related to large scale climate variability. A three layer hydrological model VIC-3L (Variable Infiltration Capacity Model -C 3 layers) was used in the Colorado River Basin over a 50 year period. The simulation focused on the soil moisture generation between January 1950 and December 2002 at daily time

C. Tang; T. Piechota

2005-01-01

196

The Use of Multispectral Imagery to Detect Variations in Soil Moisture Associated Shallow Soil Slumps  

Microsoft Academic Search

Spatial variations in soil moisture have previously been linked to the process of soil aging and can contribute to mass wasting in slopes rich in clay. We use remote sensing imagery to assess variation in soil moisture. Our investigation includes compacted clay soils of the levees along the Mississippi River maintained by the Mississippi Levee Board. Shallow soil slumps are

J. S. Kuszmaul; J. A. Neuner; A. A. Hossain; G. L. Easson

2004-01-01

197

Microwave and gamma radiation observations of soil moisture  

NASA Technical Reports Server (NTRS)

The unique dielectric properties of water at microwave wavelengths afford the possibility for remotely sensing the moisture content in the surface layer of the soil. The surface emissivity and reflectivity for the soils at these wavelengths are strong functions of its moisture content. The changes in emissivity can be observed by passive microwave techniques (radiometry) and the change in reflectivity can be observed by active microwave techniques (radar). The difference in the natural terrestrial gamma ray flux measured for wet and dry soil may be used to determine soil moisture. The presence of water moisture in the soil causes an effective increase in soil density, resulting in an increased attenuation of the gamma flux for wet soil and a corresponding lower flux above the ground surface.

Schmugge, T. J.; Njoku, E. G.; Peck, E.; Ulaby, F. T.

1979-01-01

198

Soil moisture responses to vapour pressure deficit in polytunnel-grown tomato under soil moisture triggered irrigation control  

NASA Astrophysics Data System (ADS)

The aim of this work has been to investigate soil-to-atmosphere water transport in potted tomato plants by measuring and processing high-resolution soil moisture data against the environmental driver of vapour pressure deficit (VPD). Whilst many researchers have successfully employed sap flow sensors to determine water uptake by roots and transport through the canopy, the installation of sap flow sensors is non-trivial. This work presents an alternative method that can be integrated with irrigation controllers and data loggers that employ soil moisture feedback which can allow water uptake to be evaluated against environmental drivers such as VPD between irrigation events. In order to investigate water uptake against VPD, soil moisture measurements were taken with a resolution of 2 decimal places - and soil moisture, air temperature and relative humidity measurements were logged every 2 minutes. Data processing of the soil moisture was performed in an Excel spread sheet where changes in water transport were derived from the rate of change of soil moisture using the Slope function over 5 soil moisture readings. Results are presented from a small scale experiment using a GP2-based irrigation controller and data logger. Soil moisture feedback is provided from a single SM300 soil moisture sensor in order to regulate the soil moisture level and to assess the water flow from potted tomato plants between irrigation events. Soil moisture levels were set to avoid drainage water losses. By determining the rate of change in soil moisture between irrigation events, over a 16 day period whilst the tomato plant was in flower, it has been possible to observe very good correlation between soil water uptake and VPD - illustrating the link between plant physiology and environmental conditions. Further data is presented for a second potted tomato plant where the soil moisture level is switched between the level that avoids drainage losses and a significantly lower level. This data illustrates the possibility that rate-of-change of soil moisture and VPD measurement could be employed to highlight plant stress conditions.

Goodchild, Martin; Kühn, Karl; Jenkins, Dick

2014-05-01

199

Soil moisture determination study. [Guymon, Oklahoma  

NASA Technical Reports Server (NTRS)

Soil moisture data collected in conjunction with aircraft sensor and SEASAT SAR data taken near Guymon, Oklahoma are summarized. In order to minimize the effects of vegetation and roughness three bare and uniformly smooth fields were sampled 6 times at three day intervals on the flight days from August 2 through 17. Two fields remained unirrigated and dry. A similar pair of fields was irrigated at different times during the sample period. In addition, eighteen other fields were sampled on the nonflight days with no field being sampled more than 24 hours from a flight time. The aircraft sensors used included either black and white or color infrared photography, L and C band passive microwave radiometers, the 13.3, 4.75, 1.6 and .4 GHz scatterometers, the 11 channel modular microwave scanner, and the PRT5.

Blanchard, B. J.

1979-01-01

200

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations  

NASA Astrophysics Data System (ADS)

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

201

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints  

Microsoft Academic Search

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31cm) were measured in

Minha Choi; Jennifer M. Jacobs

2007-01-01

202

Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data  

NASA Astrophysics Data System (ADS)

Agricultural models, such as Decision Support System for Agrotechnology Transfer - Cropping Systems Model (DSSAT-CSM) (Tsuji, et al., 1994), have been developed to predict the yield of various crops at field and regional scales. The model simulations of crop yields provide essential information for water resources management. One key input of the agricultural models is soil moisture. So far there are no observed soil moisture data covering the entire US with adequate time (daily) and space (1 km or less) resolutions preferred for model simulation of crop yields. Spatially and temporally downscaled data from the upcoming Soil Moisture Active Passive (SMAP) mission can fill this data gap through the generation of fine resolution soil moisture maps that can be incorporated into DSSAT-CSM model. This study will explore the impact downscaled remotely-sensed soil moisture data can have on agricultural model forecasts of agricultural yield and irrigation demand using synthetically generated data sets exhibiting statistical characteristics (uncertainty) similar to the upcoming SMAP products. It is expected that incorporating this data into agricultural model will prove especially useful for cases in which soil water conductivity characteristics and/or precipitation amount at a specific site of interest are not fully known; furthermore, a proposed Bayesian analysis is expected to generate a soil moisture sequence that reduces the uncertainty in modeled yield and irrigation demand compared to using downscaled remotely-sensed soil moisture or precipitation data alone. References Tsuji, G., Uehara, G., and Balas, S. (1994). DSSAT V3, University of Hawaii, Honolulu.

El Sharif, H. A.; Wang, J.; Georgakakos, A. P.; Bras, R. L.

2013-12-01

203

The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations  

NASA Astrophysics Data System (ADS)

For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the modern Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and Windsat have been used to retrieve surface soil moisture using multi-channel observations obtained at higher microwave frequencies. While AMSR-E and Windsat lack an L-band channel, they are able to leverage multi-channel microwave observations to estimate additional land surface parameters. In particular, the availability of Ka-band observations allows AMSR-E and Windsat to obtain surface temperature estimates required for the retrieval of surface soil moisture. In contrast, SMOS and SMAP carry only a single frequency radiometer. Because of this, ancillary - and potentially less accurate - sources of surface temperature information (e.g. re-analysis data from operational weather prediction centers) must be sought to produce surface soil moisture retrievals. Here, two newly-developed, large-scale soil moisture evaluation techniques, the triple collocation (TC) approach and the R value data assimilation approach, are applied to quantify the global-scale impact of replacing Ka-band based surface temperature retrievals with Modern Era Retrospective-analysis for Research and Applications (MERRA) surface temperature predictions on the accuracy of Windsat and AMSR-E surface soil moisture retrievals. Results demonstrate that under sparsely vegetated conditions, the use of Ka-band radiometric land surface temperature leads to better soil moisture anomaly estimates compared to those retrieved using MERRA land surface temperature predictions. However the situation is reversed for highly vegetated conditions where soil moisture anomaly estimates retrieved using MERRA land surface temperature are superior. In addition, the surface temperature phase shifting approach is shown to generally enhance the value of MERRA surface temperature estimates for soil moisture retrieval. Finally, a high degree of consistency is noted between evaluation results produced by the TC and Rvalue soil moisture verification approaches.

Parinussa, R. M.; Holmes, T. R. H.; Crow, W. T.

2011-07-01

204

Geophysical mapping of variations in soil moisture  

NASA Astrophysics Data System (ADS)

The geophysical investigation of soil characteristics is a matter of great actuality for agricultural, hydrogeological, geotechnical or archaeological purposes. The geophysical mapping of soil quality is subject of a recently started scientific project in Romania: "Soil investigation and monitoring techniques - modern tools for implementing the precision agriculture in Romania - CNCSIS 998/2009". One of the first studied soil parameter is moisture content, in irrigated or non-irrigated agricultural areas. The geophysical techniques employed in two areas located within the Romanian Plain, Prahova and Buzau counties, are the following: - electromagnetic (EM), using the EM38B (Geonics) conductivity meter for getting areal distribution of electric conductivity and magnetic susceptibility; - electric resistivity tomography (ERT), using the SuperSting (AGI) multi-electrode instrument for getting in-depth distribution of electric resistivity. The electric conductivity mapping was carried out on irrigated cultivated land in a vegetable farm in the Buzau county, the distribution of conductivity being closely related to the soil water content due to irrigation works. The soil profile is represented by a chernozem with the following structure: Am (0 - 40 cm), Bt (40-150 cm), Bt/C (150-170 cm), C (starting at 170 cm). The electromagnetic measurements showed large variations of this geophysical parameter within different cultivated sectors, ranging from 40 mS/m to 85 mS/m. The close association between conductivity and water content in this area is illustrated by such geophysical measurements on profiles situated at ca 50 m on non-irrigated land, displaying a mean value of 15 mS/m. This low conductivity is due to quite long time interval, of about three weeks, without precipitations. The ERT measurements using multi-electrode acquisition systems for 2D and 3D results, showed by means of electric resistivity variations, the penetration of water along the cultivated rows from the drip system. The mean depth of water penetration is about 0.5 m, while the depth level where the irrigation water is accumulating in a continuous wet layer is about 0.7 m. Magnetic susceptibility measurements performed on the soil profile in this area showed highest values on the Am layer, an important decrease within the Bt layer, followed by a weak increase toward the C layer. Electric conductivity and magnetic susceptibility measurements were carried out on profiles crossing non-irrigated cultivated areas in the Prahova county. The variations of electric conductivity, ranging between 10 and 30 mS/m is considered to be related mainly to the moisture content. Highest values of electric conductivity, greater than 50 mS/m, correlated with anomalies of magnetic susceptibility, were recorded over buried metallic pipes of various sizes, the cultivated land being located between an oil refinery and green-houses.

Ioane, Dumitru; Scradeanu, Daniel; Chitea, Florina; Garbacea, George

2010-05-01

205

Impact of Soil Moisture-Atmosphere Interactions on Surface Temperature Distribution  

NASA Astrophysics Data System (ADS)

Land-atmosphere interactions are a key physical process in the climate system. One of the critical variables involved in these interactions is soil moisture, as it partly controls radiative and turbulent heat fluxes to the atmosphere. Through these processes, soil moisture variability has the potential to feed back on near-surface hydroclimate, in particular temperature. This study investigates simulations performed at GFDL in the frame of the GLACE-CMIP5 project to investigate soil moisture feedbacks : a coupled land-atmosphere model was run over 1950-2100 with transient forcings, prescribed SSTs (derived from the corresponding historical and future coupled CMIP5 simulations) and with either interactive soil moisture, or soil moisture prescribed to its 1971-2000 climatology. Here we compare in particular the two simulations over 1971-2000, isolating the effect of soil moisture dynamics (since soil moisture climatology is identical) on the simulated climate. We place the emphasis on the distribution of daily near-surface temperatures, and how the associated probability distribution function is shaped by soil moisture-atmosphere interactions. We show that soil moisture dynamics strongly enhance both temperature mean and variability over apparent regional 'hotspots'. Moreover, higher-order distribution moments such as skewness and kurtosis are also significantly impacted: in particular, skewness generally becomes more positive with interactive soil moisture, suggesting an asymmetric impact on hot and cold anomalies. We interpret these changes by considering changes in the distributions of the surface radiative and turbulent fluxes. Importantly, the different temperature pdf parameters are not all affected at the same time or in a similar way in different regions. These different behaviors underscore the importance of analyzing all distribution moments to fully characterize the impacts of soil moisture-atmosphere interactions on surface temperature. In addition, we show that soil moisture dynamics impact daily temperature variability at different time over different regions in the model. The impacts of soil moisture dynamics on the distribution of surface temperatures have implications for the analysis (attribution, projections) of extreme temperature events.

Berg, A. M.; Lintner, B. R.; Findell, K. L.; Gentine, P.; Malyshev, S.

2013-12-01

206

Evaluation of ECMWF's soil moisture analyses using observations on the Tibetan Plateau  

NASA Astrophysics Data System (ADS)

An analysis is carried out for two hydrologically contrasting but thermodynamically similar areas on the Tibetan Plateau, to evaluate soil moisture analysis based on the European Centre for Medium-Range Weather Forecasts (ECMWF) previous optimum interpolation scheme and the current point-wise extended Kalman filter scheme. To implement the analysis, this study used two regional soil moisture and soil temperature networks (i.e., Naqu and Maqu) on the Tibetan Plateau. For the cold-semiarid Naqu area, both ECMWF soil moisture analyses significantly overestimate the regional soil moisture in the monsoon seasons. For the cold-humid Maqu network area, the ECMWF products have comparable accuracy as reported by previous studies in the humid monsoon period. The comparisons were made among the liquid soil moisture analysis from ECMWF, the ground station's measurements and the satellite estimates from the Advanced Scatterometer sensor. The results show reasonable performances of the ECMWF soil moisture analyses (i.e., both optimum interpolation and extended Kalman filter products) and the Advanced Scatterometer level 2 products, when compared to the in situ measurements.

Su, Z.; Rosnay, P.; Wen, J.; Wang, L.; Zeng, Y.

2013-06-01

207

Development of New Hyperspectral Angle Index for Estimation of Soil Moisture Using in Situ Spectral Measurments  

NASA Astrophysics Data System (ADS)

Near-surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. On the other hand, information of distributed soil moisture at large scale with reasonable spatial and temporal resolution is required for improving climatic and hydrologic modeling and prediction. The advent of hyperspectral imagery has allowed examination of continuous spectra not possible with isolated bands in multispectral imagery. In addition to high spectral resolution for individual band analyses, the contiguous narrow bands show characteristics of related absorption features, such as effects of strong absorptions on the band depths of adjacent absorptions. Our objective in this study was to develop a new spectral angle index to estimate soil moisture based on spectral region (350 and 2500 nm). In this paper, using spectral observations made by ASD Spectroradiometer for predicting soil moisture content, two soil indices were also investigated involving the Perpendicular Drought Index (PDI), NMDI (Normalized Multi-band Drought Index) indices. Correlation and regression analysis showed a high relationship between PDI and the soil moisture percent (R2 = 0.9537) and NMDI (R2 = 0.9335). Furthermore, we also simulated these data according to the spectral range of some sensors such as MODIS, ASTER, ALI and ETM+. Indices relevant these sensors have high correlation with soil moisture data. Finally, we proposed a new angle index which shows significant relationship between new angle index and the soil moisture percentages (R2 = 0.9432).angle index relevant bands 3, 4, 5, 6, 7 MODIS also showing high accuracy in estimation of soil moisture (R2 = 0.719).

Mobasheri, M. R.; Bidkhan, N. G.

2013-10-01

208

Effects of soil moisture and temperature on overwintering survival of Curculio larvae (Coleoptera : Curculionidae)  

USGS Publications Warehouse

Few studies to date have investigated factors, other than mast crop size, that influence the dynamics of Curculio populations.W e examined the effects of varying levels of soil moisture (0.35, 0.4 and 0.5 g water/g soil) and temperature (8, 14 and 20 C) on over wintering survival of Curculio larvae collected from Quercus michauxii acorns. Survival of larvae, analyzed using log-linear analysis, was adversely affected by soil moisture but not by soil temperature. Larvae that overwinter in drier soil may have higher probabilities of successfully metamorphosing.

Ricca, M. A.; Weckerly, F. W.; Semlitsch, R. D.

1996-01-01

209

A Time Series Approach for Soil Moisture Estimation  

NASA Technical Reports Server (NTRS)

Soil moisture is a key parameter in understanding the global water cycle and in predicting natural hazards. Polarimetric radar measurements have been used for estimating soil moisture of bare surfaces. In order to estimate soil moisture accurately, the surface roughness effect must be compensated properly. In addition, these algorithms will not produce accurate results for vegetated surfaces. It is difficult to retrieve soil moisture of a vegetated surface since the radar backscattering cross section is sensitive to the vegetation structure and environmental conditions such as the ground slope. Therefore, it is necessary to develop a method to estimate the effect of the surface roughness and vegetation reliably. One way to remove the roughness effect and the vegetation contamination is to take advantage of the temporal variation of soil moisture. In order to understand the global hydrologic cycle, it is desirable to measure soil moisture with one- to two-days revisit. Using these frequent measurements, a time series approach can be implemented to improve the soil moisture retrieval accuracy.

Kim, Yunjin; vanZyl, Jakob

2006-01-01

210

Microwave remote sensing and its application to soil moisture detection  

NASA Technical Reports Server (NTRS)

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.

Newton, R. W. (principal investigator)

1977-01-01

211

Analysis of soil moisture patterns in forested and suburban catchments in Baltimore, Maryland, using high-resolution photogrammetric and LIDAR digital elevation datasets  

NASA Astrophysics Data System (ADS)

Field observations of near-surface soil moisture, collected over several seasons in a watershed in suburban Maryland, are compared with values of the topographic soil moisture index generated using digital elevation models (DEMs) at a range of grid cell sizes from photogrammetric and light detection and ranging (LIDAR) data sources. A companion set of near-surface soil moisture observations, DEMs and topographic index values are also presented for a nearby forested catchment. The degree to which topographic index values are an effective indicator of near-surface soil moisture conditions varies in the two environments. The urbanizing environment requires topographic index values from a DEM with a much finer grid cell resolution than the LIDAR data can provide, and the relationship is stronger in wetter conditions. In the forested environment, the DEM resolution required is considerably lower and adequately supported by the photogrammetric data, and the relationship is strong under all moisture conditions. These results provide some insights into the length scales of near-surface hydrological processes in the urbanizing environment, and the resolution of terrain data required to model those processes.

Tenenbaum, D. E.; Band, L. E.; Kenworthy, S. T.; Tague, C. L.

2006-02-01

212

Response of grassland ecosystems to prolonged soil moisture deficit  

NASA Astrophysics Data System (ADS)

Soil moisture is commonly used for predictions of plant response and productivity. Climate change is predicted to cause an increase in the frequency and duration of droughts over the next century, which will result in prolonged periods of below-normal soil moisture. This, in turn, is expected to impact regional plant production, erosion and air quality. In fact, the number of consecutive months of soil moisture content below the drought-period mean has recently been linked to regional tree and shrub mortality in the southwest United States. This study investigated the effects of extended periods of below average soil moisture on the response of grassland ANPP to precipitation. Grassland ecosystems were selected for this study because of their ecological sensitivity to precipitation patterns. It has been postulated that the quick ecological response of grasslands to droughts can provide insight to large scale functional responses of regions to predicted climate change. The study sites included 21 grassland biomes throughout arid-to-humid climates in the United States with continuous surface soil moisture records for 2-13 years during the drought period from 2000-2013. Annual net primary production (ANPP) was estimated from the 13-year record of NASA MODIS Enhanced Vegetation Index extracted for each site. Prolonged soil moisture deficit was defined as a period of at least 10 consecutive months during which soil moisture was below the drought-period mean. ANPP was monitored before, during and after prolonged soil moisture deficit to quantify shifts in the functional response of grasslands to precipitation, and in some cases, new species assemblages that included invasive species. Preliminary results indicated that when altered climatic conditions on grasslands led to an increase in the duration of soil water deficit, then the precipitation-to-ANPP relation became non-linear. Non-linearity was associated with extreme grassland dieback and changes in the historic species assemblage. The magnitude of change was related to the precipitation regime, where grasslands in hyper-arid and humid regimes were least likely to be affected by prolonged soil moisture deficit, and semiarid and mesic grasslands were most likely to be impacted, depending on the duration of the deficit. These results were applied to a large grassland region in Australia with soil moisture estimates from the European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) sensor to demonstrate the continental-scale potential of this application with satellite measurements. These results are even more relevant for application with the higher-resolution NASA Soil Moisture Active Passive (SMAP) products to be available in 2015.

Ross, Morgan A.; Ponce-Campos, Guillermo E.; Barnes, Mallory L.; Hottenstein, John D.; Moran, M. Susan

2014-05-01

213

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-Comparing Soil Moisture Data  

NASA Technical Reports Server (NTRS)

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.

Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih

2012-01-01

214

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

NASA Technical Reports Server (NTRS)

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

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

2011-01-01

215

Soil moisture tendencies into the next century for the conterminous United States  

USGS Publications Warehouse

A monthly snow-pack and soil- moisture accounting model is formulated for application to each of the climate divisions of the conterminous United States for use in climate impacts-assessment studies. Statistical downscaling and bias-adjustment components complement the model for the assimilation of large-scale global climate model data. Simulations of the formulated model driven by precipitation and temperature for the period 1931-1998 produce streamflows that are broadly consistent with observed data from several drainage basins in the US. Simulated historical soil moisture fields reproduce several features of the available observed soil moisture in the Midwest. The simulations produce large-scale coherent seasonal patterns of soil moisture field- moments over the conterminous US, with high soil moisture means over divisions in the Ohio Valley, the northeastern US and the Pacific Northwest, and with pronounced low means in most of the western US climate divisions. Characteristically low field-standard- deviations are produced for the Ohio Valley and northeastern US, and the Pacific Northwest in winter, and the southwestern US in summer. Differences in extreme standardized anomalies of soil moisture over the historical record range possess high values (2.5 - 3) in the central US where the available water capacity of the soils is high. An application of the model to exemplify the methodology for determining projected US monthly soil moisture fields under control and greenhouse gas forcing is also documented. Climate simulations of the coupled global climate model from the Canadian Centre for Climate Modeling and Analysis were used for these sensitivity examples. The climatology of the control-run soil moisture fields reproduces several characteristic features of the historical soil moisture climatology. Simulations with forcing by a 1% greenhouse-gas- increase scenario show that for at least the first few decades of the 21 st Century somewhat drier-than-present soil conditions are projected, with highest drying trends found in the southeastern US. The soil moisture deficits in most areas are of the same order of magnitude as the soil moisture field-standard- deviations aris ing from historical natural variability. In a companion paper (Brumbelow and A. Georgakakos, 2000), the monthly soil moisture fields for the historical, control and greenhouse-gas-increase runs are used to initialize a site-specific daily crop yield model at the start of the growing season. Assessments of potential impacts of climate variability and trends on irrigation requirements and crop yield across the conterminous US are made.

Georgakakos, Konstantine P.; Smith, Diane E.

2000-01-01

216

The Effects of Wildfire on Soil Moisture Dynamics  

NASA Astrophysics Data System (ADS)

Moisture dynamics in the critical zone have significant implications for a variety of hydrologic processes, from water availability to plants to infiltration and groundwater recharge rates. These processes are perturbed by events such as wildfires, which may have long-lasting impacts. In September 2011, the most destructive wildfire in Texas history occurred in and around Bastrop State Park, which was significantly affected; thus we take advantage of a rare opportunity to study soil moisture under such burned conditions. A 165 m long transect bridging burned and unburned areas was established within the 'Lost Pines' of the park. Soil moisture and soil temperature were monitored and estimated using a variety of methods, including 2D electrical resistivity imaging (using dipole-dipole and Schlumberger configurations), surface permittivity measurements (ThetaProbe), permittivity-based soil moisture profiling (PR2 profile probes), and installation of thermistors. Field measurements were collected at approximately one-month intervals to study temporal and seasonal effects on soil moisture and temperature in this area. Greater soil moisture and lower resistivity were found near the surface at the heavily burned end of the transect, where trees have been largely killed by the fire and grasses now dominate, and very low near-surface soil moisture and higher resistivity were found at the opposite end, which is still populated by pine trees. These variations can likely be attributed to the vegetative variations between the two ends of the transect, with trees consuming more water at one end and the ground cover of grasses and mosses consuming less water and helping reduce evaporation at the burned end. Higher clay content at the burned end of the transect could also be a factor in greater soil moisture retention there. Given the higher moisture content throughout the soil profile at the heavily burned end of the transect, this could be an indication of greater infiltration, and could increase recharge, at least in the short term.

Kanarek, M.; Cardenas, M.

2013-12-01

217

High-resolution soil moisture mapping in Afghanistan  

NASA Astrophysics Data System (ADS)

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.

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

2011-05-01

218

Is soil moisture initialization important for seasonal to decadal predictions?  

NASA Astrophysics Data System (ADS)

The state of soil moisture can can have a significant impact on regional climate conditions for short time scales up to several months. However, focusing on seasonal to decadal time scales, it is not clear whether the predictive skill of global a Earth System Model might be enhanced by assimilating soil moisture data or improving the initial soil moisture conditions with respect to observations. As a first attempt to provide answers to this question, we set up an experiment to investigate the life time (memory) of extreme soil moisture states in the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). This experiment consists of an ensemble of 3 years simulations which are initialized with extreme wet and dry soil moisture states for different seasons and years. Instead of using common thresholds like wilting point or critical soil moisture, the extreme states were extracted from a reference simulation to ensure that they are within the range of simulated climate variability. As a prerequisite for this experiment, the soil hydrology in JSBACH was improved by replacing the bucket-type soil hydrology scheme with a multi-layer scheme. This new scheme is a more realistic representation of the soil, including percolation and diffusion fluxes between up to five separate layers, the limitation of bare soil evaporation to the uppermost soil layer and the addition of a long term water storage below the root zone in regions with deep soil. While the hydrological cycle is not strongly affected by this new scheme, it has some impact on the simulated soil moisture memory which is mostly strengthened due to the additional deep layer water storage. Ensemble statistics of the initialization experiment indicate perturbation lengths between just a few days up to several seasons for some regions. In general, the strongest effects are seen for wet initialization during northern winter over cold and humid regions, while the shortest memory is found during northern spring. For most regions, the soil moisture memory is either sensitive to wet or to dry perturbations, indicating that soil moisture anomalies interact with the respective weather pattern for a given year and might be able to enhance or dampen extreme conditions. To further investigate this effect, the simulations will be repeated using JSBACH with prescribed meteorological forcing to better disentangle the direct effects of soil moisture initialization and the atmospheric response.

Stacke, Tobias; Hagemann, Stefan

2014-05-01

219

Remote monitoring of soil moisture using airborne microwave radiometers  

NASA Technical Reports Server (NTRS)

The current status of microwave radiometry is provided. The fundamentals of the microwave radiometer are reviewed with particular reference to airborne operations, and the interpretative procedures normally used for the modeling of the apparent temperature are presented. Airborne microwave radiometer measurements were made over selected flight lines in Chickasha, Oklahoma and Weslaco, Texas. Extensive ground measurements of soil moisture were made in support of the aircraft mission over the two locations. In addition, laboratory determination of the complex permittivities of soil samples taken from the flight lines were made with varying moisture contents. The data were analyzed to determine the degree of correlation between measured apparent temperatures and soil moisture content.

Kroll, C. L.

1973-01-01

220

Evaluation of multi-model simulated soil moisture in NLDAS-2  

NASA Astrophysics Data System (ADS)

The North American Land Data Assimilation System (NLDAS) phase 2 (NLDAS-2) has generated 31-years (1979-2008) of water and energy products from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC). The soil moisture data from these models have been used for operational drought monitoring activities, but so far have not yet been comprehensively evaluated. In this study, three available in situ soil moisture observation data sets in the United States were used to evaluate the model-simulated soil moisture for different time scales varying from daily to annual. First, we used the observed multiple layer monthly and annual mean soil moisture from the Illinois Climate Network to evaluate 20-years (January 1985-December 2004) of model-simulated soil moisture in terms of skill and analysis of error statistics. Second, we utilized 6-years (1 January 1997-31 December 2002) of daily soil moisture observed from 72 sites over the Oklahoma Mesonet network to assess daily and monthly simulation skill and errors for 3 model soil layers (0-10 cm, 10-40 cm, 40-100 cm). Third, we extended the daily assessment to sites over the continental United States using 8-years (1 January 2002-31 December 2009) of observations for 121 sites from the Soil Climate Analysis Network (SCAN). Overall, all models are able to capture wet and dry events and show high skill (in most cases, anomaly correlation is larger than 0.7), but display large biases when compared to in situ observations. These errors may come from model errors (i.e., model structure error, model parameter error), forcing data errors, and in situ soil moisture measurement errors. For example, all models simulate less soil moisture due to lack of modeled irrigation and ground water processes in Illinois, Oklahoma, and the other Midwest states.

Xia, Youlong; Sheffield, Justin; Ek, Michael B.; Dong, Jiarui; Chaney, Nathaniel; Wei, Helin; Meng, Jesse; Wood, Eric F.

2014-05-01

221

Validation of soil moisture and surface fluxes in EURO-CORDEX simulations as part of a land-atmosphere coupling analysis  

NASA Astrophysics Data System (ADS)

Land-atmosphere coupling is highly important to understand e.g. many of the processes involved in regional climate change and its impacts. A main science question is in which way the land surface influences the atmosphere and how the strength of this coupling may be quantified. Such complex land-atmosphere interactions are e.g. sensitive to small scale surface heterogeneities that are better captured by higher resolution regional climate model runs that are supposed to provide an added value when it comes to the reproduction of extremes and associated impacts. As part of a land-atmosphere coupling analysis, where we investigate the coupling strength and its spatial and temporal variability based on ERA-Interim re-analysis driven multiscale EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) validation runs, the present study shows, how well the spatial patterns and temporal evolutions of surface moisture and surface energy fluxes are reproduced in these simulations. The analysis is done on a subset of eight WRF RCM simulations that are part of the EURO-CORDEX ensemble. We evaluate daily model results from 1990 to 2008 at spatial resolutions of about 48 km (EUR-44) and 12 km (EUR-11) for the complete European model domain. The model simulations are compared to the Essential Climate Variables (ECV) Soil Moisture satellite data product of the ESA Climate Change Initiative regridded with a nearest neighbor resampling to the EUR-44 and the EUR-11 grid, respectively. Due to data coverage, the data intercomparison is done on a grid-cell-basis for all individual days with a matching satellite observation for annual and seasonal time spans. Related to the soil moisture-temperature feedback this quantity is highly important for flux partitioning. In order to evaluate those fluxes and thereby the reproduction of boundary layer processes by the models, latent and sensible heat fluxes are compared for individual locations against flux tower measurements of the FLUXNET dataset. An important prerequisite for a valid intercomparison is e.g. a match of the dominant land use as used by the land surface schemes in the RCMs with the station site. As most RCMs in the intercomparison use the NOAH LSM with MODIS land use and USGS GTOPO topographic data, our intercomparison does not necessarily give an information on the quality of the LSM but is rather intended to investigate the overall effects of the complex interplay of several processes.

Knist, Sebastian; Goergen, Klaus; Keune, Jessica; Poorthuis, Lukas; Colette, Augustin; Margarida Cardoso, Rita; Fealy, Rowan; Fernandez, Jesus; Garcia-Diez, Markel; Katragkou, Eleni; Mayer, Stephanie; Soares, Pedro; Sobolowski, Stefan; Vautard, Robert; Sarrach-Wagi, Kirsten; Wulfmeyer, Volker; Simmer, Clemens

2014-05-01

222

The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations  

NASA Astrophysics Data System (ADS)

For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the current Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and WindSat have been used to retrieve surface soil moisture using multi-channel observations obtained at higher microwave frequencies. While AMSR-E and WindSat lack an L-band channel, they are able to leverage multi-channel microwave observations to estimate additional land surface parameters. In particular, the availability of Ka-band observations allows AMSR-E and WindSat to obtain coincident surface temperature estimates required for the retrieval of surface soil moisture. In contrast, SMOS and SMAP carry only a single frequency radiometer and therefore lack an instrument suited to estimate the physical temperature of the Earth. Instead, soil moisture algorithms from these new generation satellites rely on ancillary sources of surface temperature (e.g. re-analysis or near real time data from weather prediction centres). A consequence of relying on such ancillary data is the need for temporal and spatial interpolation, which may introduce uncertainties. Here, two newly-developed, large-scale soil moisture evaluation techniques, the triple collocation (TC) approach and the Rvalue data assimilation approach, are applied to quantify the global-scale impact of replacing Ka-band based surface temperature retrievals with Modern Era Retrospective-analysis for Research and Applications (MERRA) surface temperature output on the accuracy of WindSat and AMSR-E based surface soil moisture retrievals. Results demonstrate that under sparsely vegetated conditions, the use of MERRA land surface temperature instead of Ka-band radiometric land surface temperature leads to a relative decrease in skill (on average 9.7%) of soil moisture anomaly estimates. However the situation is reversed for highly vegetated conditions where soil moisture anomaly estimates show a relative increase in skill (on average 13.7%) when using MERRA land surface temperature. In addition, a pre-processing technique to shift phase of the modelled surface temperature is shown to generally enhance the value of MERRA surface temperature estimates for soil moisture retrieval. Finally, a very high correlation (R2 = 0.95) and consistency between the two evaluation techniques lends further credibility to the obtained results.

Parinussa, R. M.; Holmes, T. R. H.; Yilmaz, M. T.; Crow, W. T.

2011-10-01

223

The Soil Moisture Active and Passive (SMAP) Mission  

NASA Technical Reports Server (NTRS)

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

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; Kimball, John; Piepmeier, Jeffrey R.; Koster, Randal D.; McDonald, Kyle C.; Moghaddam, Mahta; Moran, Susan; Reichle, Rolf; Shi, J. C.; Spencer, Michael W.; Thurman, Samuel W.; Tsang, Leung; VanZyl, Jakob

2009-01-01

224

Long-term soil moisture variability from a new P-E water budget method  

NASA Astrophysics Data System (ADS)

Basin-scale soil moisture is traditionally estimated using either land-surface model forced by observed meteorological variables or atmospheric moisture convergence from atmospheric analysis and observed runoff. Interannual variability from such methods suffer from major uncertainties due to the sensitivity to small imperfections in the land-surface model or the atmospheric analysis. Here we introduce a novel P-E method in estimating basin-scale soil moisture, or more precisely apparent land water storage (AWS). The key input variables are observed precipitation and runoff, and reconstructed evaporation. We show the results for the tropics using the example of the Amazon basin. The seasonal cycle of diagnosed soil moisture over the Amazon is about 200mm, compares favorably with satellite estimate from the GRACE mission, thus lending confidence both in this method and the usefulness of space gravity based large-scale soil moisture estimate. This is about twice as large as estimates from several traditional methods, suggesting that current models tend to under estimate the soil moisture variability. One of the advantage of the P-E method is to retrive long-term variability of the basin-scale soil moisture (including interannual and decadal time scales), which can provide valuable information to understand climate variability and to predict future climate condition. However, validation on reconstructed evaporation is very difficult due to lack of observation. The interannual variability in AWS in the Amazon basin is about 150mm, also consistent with GRACE data, but much larger than model results. We also apply this P-E method to the midlatitude Mississippi basin and discuss the impact of major 20th century droughts such as the dust bowl period on the long-term soil moisture variability. The results suggest the existence of soil moisture memories on decadal time scales, significantly longer than typically assumed seasonal timescales.

Zeng, N.; Yoon, J.; Mariotti, A.; Swenson, S. C.

2006-05-01

225

Derivation of soil moisture retrieval uncertainties associated to the simplification of the dynamic vegetation signal.  

NASA Astrophysics Data System (ADS)

Satellite-based microwave remote sensing has proven to provide reliable soil moisture observations on a global scale over the last decades. In microwave remote sensing of soil moisture the satellite signal holds information on both soil moisture and vegetation. Separating these components from each other is not straightforward. In the last years the importance of a robust and reliable vegetation parameterization within the soil moisture retrieval algorithms has become evident. In the TU-Wien soil moisture retrieval algorithm, developed by the Vienna University of Technology, the backscatter observations are corrected for vegetation effects by way of the slope and curvature. The slope and curvature are derivates of noisy backscatter measurements in relation to incidence angle and hence have a high level of noise. Therefore, they are averaged over several years resulting in a fixed seasonal vegetation correction, where no inter-annual variability is present in the characterisation of vegetation. This study assesses the strengths and weaknesses of the fixed seasonal vegetation correction in the TU-Wien soil moisture retrieval algorithm. The Vegetation Optical Depth (VOD) retrieved from AMSR-E passive microwave observations with the VUA-NASA retrieval algorithm is analysed to identify regions with high inter-annual variability in vegetation. For these regions the effect of a fixed seasonal correction on the soil moisture retrieval is investigated. First, the TU-Wien soil moisture products before and after the application of the vegetation correction, the TU-Wien normalised backscatter and TU-Wien soil moisture respectively, are compared to modelled soil moisture from ECMWFs ERA-Interim. With this analysis regions where the vegetation correction decreases the quality of the TU-Wien soil moisture product with regard to modeled soil moisture can be identified. Secondly, the vegetation correction within the TU-Wien retrieval algorithm is replaced by the VOD to simulate an inter-annually dynamic vegetation correction. The VOD is like the slope and curvature an indicator of vegetation water content. This new soil moisture product based on VOD is then also compared to modeled soil moisture from ERA-Interim. Results show that in areas of high inter-annual variability, like the Sahel, the TU-Wien vegetation correction is suboptimal and decreases the quality of the TU-Wien soil moisture product when compared to ERA-Interim. Spearman R with ERA-Interim soil moisture can decrease with as much as 0.4 after applying the vegetation correction. Using the VOD in these regions increases the quality of the TU-Wien soil moisture product. This study demonstrates that a fixed seasonal vegetation correction is not able to account for high inter-annual vegetation variability and leads to an inaccurate soil moisture signal, emphasizing the need for a dynamic vegetation correction.

Vreugdenhil, Mariette; Dorigo, Wouter; de Jeu, Richard; Hahn, Sebastian; Salinas, Jose Luis; Wagner, Wolfgang

2014-05-01

226

Improved understanding of hillslope-scale hydrological processes using high-resolution soil moisture measurements  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable that controls e.g. matter and energy fluxes, slope stability, occurence of flood events and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the non-linearity of hillslope response to rainfall due to local soil moisture dynamics. Characterizing this variability is one of the major challenges in hillslope hydrology. Long-term monitoring of surface and subsurfce soil moisture at various depths can provide a comprehensive picture of the spatial and temporal pattern of soil moisture dynamics, and facilitate understanding the controlling factors of underlying hydrological processes. In the Schäfertal catchment (located in the Harz Mountains, in Central Germany) a 2.5 ha hillslope area was permanently instrumented with a wireless soil moisture and soil temperature monitoring network. Ground-based electromagnetic induction (EMI) measurements and topographic data were included into a geostatistical sampling strategy in order to optimize the placement of the network nodes. In total, 240 sensors were distributed to create 40 pairs of instrumented soil profiles, providing hourly measurements of soil water content and soil temperature at 5, 25 and 50 cm depth. The soil spatial variability was mapped and the soil texture was determined for each node location and each soil horizon. For the selected monitoring period of 14 months, the soil moisture pattern and its variability through time were analyzed. Seasonal and event-based analysis shows the varying relevance of topography and soil properties in determining several near-surface processes such as preferential flow, subsurface lateral flow and dynamics of the groundwater table.

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

2014-05-01

227

Geophysical Investigations of Soil Moisture in North Mississippi Loams  

Microsoft Academic Search

Geophysical and remote sensing technologies are being increasingly used to investigate the properties of shallow soils. To provide a facility for detailed study of soil geophysical interactions, we have constructed a Soil Moisture Observatory (SMO) at the University of Mississippi (UM). The 5 acre SMO is located in a former agricultural field at the UM Field Station, a 740 acre

R. M. Holt; C. J. Hickey; M. S. Aufman

2006-01-01

228

The added value of spaceborne passive microwave soil moisture retrievals for forecasting rainfall-runoff partitioning  

Microsoft Academic Search

Using existing data sets of spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios. The predictive ability of

W. T. Crow; R. Bindlish; T. J. Jackson

2005-01-01

229

Generation of an empirical soil moisture initialization and its potential impact on subseasonal forecasting skill of continental precipitation and air temperature  

Microsoft Academic Search

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

Marie A. Boisserie

2010-01-01

230

Field Observations of Soil Moisture Variability across Scales  

NASA Technical Reports Server (NTRS)

In this study, over 36,000 ground-based soil moisture measurements collected during the SGP97, SGP99, SMEX02, and SMEX03 field campaigns were analyzed to characterize the behavior of soil moisture variability across scales. The field campaigns were conducted in Oklahoma and Iowa in the central USA. The Oklahoma study region is sub-humid with moderately rolling topography, while the Iowa study region is humid with low-relief topography. The relationship of soil moisture standard deviation, skewness and the coefficient of variation versus mean moisture content was explored at six distinct extent scales, ranging from 2.5 m to 50 km. Results showed that variability generally increases with extent scale. The standard deviation increased from 0.036 cm3/cm3 at the 2.5-m scale to 0.071 cm3/cm3 at the 50-km scale. The log standard deviation of soil moisture increased linearly with the log extent scale, from 16 m to 1.6 km, indicative of fractal scaling. The soil moisture standard deviation versus mean moisture content exhibited a convex upward relationship at the 800-m and 50-km scales, with maximum values at mean moisture contents of roughly 0.17 cm3/cm3 and 0.19 cm3/cm3, respectively. An empirical model derived from the observed behavior of soil moisture variability was used to estimate uncertainty in the mean moisture content for a fixed number of samples at the 800-m and 50-km scales, as well as the number of ground-truth samples needed to achieve 0.05 cm3/cm3 and 0.03 cm3/cm3 accuracies. The empirical relationships can also be used to parameterize surface soil moisture variations in land surface and hydrological models across a range of scales. To our knowledge, this is the first study to document the behavior of soil moisture variability over this range of extent scales using ground-based measurements. Our results will contribute not only to efficient and reliable satellite validation, but also to better utilization of remotely sensed soil moisture products for enhanced modeling and prediction.

Famiglietti, James S.; Ryu, Dongryeol; Berg, Aaron A.; Rodell, Matthew; Jackson, Thomas J.

2008-01-01

231

Exploring spatiotemporal patterns and physical controls of soil moisture at various spatial scales  

NASA Astrophysics Data System (ADS)

Soil moisture variability of various spatial scales is analyzed based on empirical orthogonal function (EOF) method using soil moisture datasets with various spatial resolutions: 1 km eco-hydrological model simulation, 0.25° passive microwave (Advanced Microwave Scanning Radiometer for the Earth Observing System, AMSR-E) dataset, and 0.5° land surface model simulation from Climate Predictor Center (CPC). All three datasets generate EOFs that explain similar variances with those generated from in situ observations from agro-meteorological network. Using AMSR-E product and eco-hydrological model simulation, it is found that the primary spatial pattern of soil moisture obtained from watershed scale has a strong connection to topographic attributes, followed by soil texture and rainfall variability, as suggested by the correlation between the primary EOF mode (EOF1) of soil moisture and landscape attributes. However, the EOF analysis of both AMSR-E and CPC datasets at regional scale reaches the conclusion that soil texture indices, such as sand and clay content, is of higher importance to soil moisture EOF1 spatial pattern (explaining 61 % variance) than topography is. Furthermore, correlation between soil moisture EOF1 and soil property is higher in spring than in autumn, which indicates that soil water-holding and drainage capabilities are more important under dry conditions. At national scale, the combined effects of topographic feature and soil property are clearly exhibited in EOF1. The study results reveal that different emphases should be placed on accurate acquisition of landscape attributes for soil moisture estimation according to various spatial scales.

Qiu, Jianxiu; Mo, Xingguo; Liu, Suxia; Lin, Zhonghui

2013-12-01

232

Soil moisture from temperature measurements at the Earth's surface, update  

NASA Technical Reports Server (NTRS)

Soil moisture budgets at the Earth's surface were investigated based on soil and atmospheric temperature variations. A number of data sets were plotted and statistically analyzed in order to accentuate the existence and the characteristics of mesoscale soil temperature extrema variations and their relations to other parameters. The correlations between diurnal temperature extrema for air and soil in drought and non-drought periods appear to follow different characteristic patterns, allowing an inference of soil moisture content from temperature data. The recovery of temperature extrema after a precipitation event also follows a characteristic power curve rise between two limiting values which is an indicator of evaporation rates. If these indicators are applied universally to regional temperature data, soil moisture content or drought conditions can be inferred directly from temperature measurements.

Welker, J. E.

1984-01-01

233

A New International Network for in Situ Soil Moisture Data  

NASA Astrophysics Data System (ADS)

The International Soil Moisture Network (ISMN) is a new data-hosting center where globally available ground-based soil moisture measurements are collected, harmonized, and made available to users through a Web interface (http://www.ipf.tuwien.ac.at/insitu). As the first international initiative of its kind, the ISMN will play a crucial role in globally assessing the quality of soil moisture estimates from spaceborne microwave sensors and land surface models; in uncovering how the hydrological cycle integrates with land, the atmosphere, and the ocean; and in studying climate change. The ISMN is fully operational and currently hosts soil moisture data from more than 500 stations spanning 18 different networks. For scientific use, access to the data is free of charge.

Dorigo, Wouter; van Oevelen, Peter; Wagner, Wolfgang; Drusch, Matthias; Mecklenburg, Susanne; Robock, Alan; Jackson, Thomas

2011-04-01

234

Moisture Content: Unit Weight Relationship of Soils. Second Edition (Revised).  

National Technical Information Service (NTIS)

This manual is designed to help the reader learn or review the basic principles of the moisture content-unit weight relationships of soils used for construction purposes. New or reassigned Bureau of Reclamation employees (laboratory technicians, inspector...

A. K. Howard V. D. Goldsmith

1989-01-01

235

A Microwave Systems Approach to Measuring Root Zone Soil Moisture.  

National Technical Information Service (NTIS)

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...

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

1983-01-01

236

The NASA Soil Moisture Active Passive (SMAP) Mission: Overview  

NASA Technical Reports Server (NTRS)

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.

O'Neill, Peggy; Entekhabi, Dara; Njoku, Eni; Kellogg, Kent

2011-01-01

237

A quantitative comparison of soil moisture inversion algorithms  

NASA Technical Reports Server (NTRS)

This paper compares the performance of four bare surface radar soil moisture inversion algorithms in the presence of measurement errors. The particular errors considered include calibration errors, system thermal noise, local topography and vegetation cover.

Zyl, J. J. van; Kim, Y.

2001-01-01

238

Measurement of soil moisture trends with airborne scatterometers  

NASA Technical Reports Server (NTRS)

The author had identified the following significant results. Repeated looks at surfaces that maintain constant roughness can provide an estimate of soil moisture in the surface, when appropriate radar look angles are used. Significant influence due to differences in soil moisture can be detected in the 13.3 GHz and 1.6 GHz scatterometer returns. Effects of normal crop densities have little influence on the surface soil moisture estimate, when appropriate look angles are used. It appears that different look angles are optimum for different frequencies to avoid effects from vegetation. Considering the frequency and look angles used on the Seasat-A imaging radar, differences in soil moisture should produce as much as 9 db difference in return on that system.

Blanchard, B. J. (principal investigator)

1978-01-01

239

Soil moisture and evapotranspiration predictions using Skylab data  

NASA Technical Reports Server (NTRS)

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.

Myers, V. I. (principal investigator); Moore, D. G.; Horton, M. L.; Russell, M. J.

1975-01-01

240

Inverse Method for Estimating the Spatial Variability of Soil Particle Size Distribution from Observed Soil Moisture  

SciTech Connect

Soil particle size distribution (PSD) (i.e., clay, silt, sand, and rock contents) information is one of critical factors for understanding water cycle since it affects almost all of water cycle processes, e.g., drainage, runoff, soil moisture, evaporation, and evapotranspiration. With information about soil PSD, we can estimate almost all soil hydraulic properties (e.g., saturated soil moisture, field capacity, wilting point, residual soil moisture, saturated hydraulic conductivity, pore-size distribution index, and bubbling capillary pressure) based on published empirical relationships. Therefore, a regional or global soil PSD database is essential for studying water cycle regionally or globally. At the present stage, three soil geographic databases are commonly used, i.e., the Soil Survey Geographic database, the State Soil Geographic database, and the National Soil Geographic database. Those soil data are map unit based and associated with great uncertainty. Ground soil surveys are a way to reduce this uncertainty. However, ground surveys are time consuming and labor intensive. In this study, an inverse method for estimating mean and standard deviation of soil PSD from observed soil moisture is proposed and applied to Throughfall Displacement Experiment sites in Walker Branch Watershed in eastern Tennessee. This method is based on the relationship between spatial mean and standard deviation of soil moisture. The results indicate that the suggested method is feasible and has potential for retrieving soil PSD information globally from remotely sensed soil moisture data.

Pan, Feifei [University of Texas; Peters-lidard, Christa D. [NASA Goddard Space Flight Center; King, Anthony Wayne [ORNL

2010-11-01

241

Soil moisture under contrasted atmospheric conditions in Eastern Spain  

NASA Astrophysics Data System (ADS)

Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at p<0.01) with the amount of measured precipitation. In this study we analyze the role of other crucial atmospheric parameters (i.e., temperature, relative humidity, global solar radiation, and wind speed and wind direction) in the intraanual evolution of soil moisture; focussing our analyses on the soil moisture discharge episodes. Here we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). Key Words: Soil Moisture Discharges, Intraannual changes, Atmospheric parameters, Eastern Spain Acknowledgements The research projects GL2008-02879/BTE, LEDDRA 243857 and RECARE FP7 project 603498 supported this research. References: Azorin-Molina, C., Connell, B.H., Baena-Calatrava, R. 2009. Sea-breeze convergence zones from AVHRR over the Iberian Mediterranean Area and the Isle of Mallorca, Spain. Journal of Applied Meteorology and Climatology 48 (10), 2069-2085. Azorin-Molina, C., Vicente-Serrano, S. M., Cerdà, A. 2013. Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming. EGU, Geophysical Research Abstracts, EGU2013-13286. Bodí, M.B., Mataix-Solera, J., Doerr, S.H. & Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments, 52, 319-337. García-Fayos, P. García-Ventoso, B. Cerdà, A. 2000. Limitations to Plant establishment on eroded slopes in Southeastern Spain. Journal of Vegetation Science, 11- 77- 86. Ghafoor, A., Murtaza, G., Rehman, M. Z., Saifullah Sabir, M. 2012. Reclamation and salt leaching efficiency for tile drained saline-sodic soil using marginal quality water for irrigating rice and wheat crops. Land Degradation & Development, 23: 1 -9. DOI 10.1002/ldr.1033 Johnston, C. R., Vance, G. F., Ganjegunte, G. K. 2013. Soil properties changes following irrigation with coalbed natural gas water: role of water treatments, soil amendments and land suitability.

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

2014-05-01

242

SMOS CATDS Level 3 products, Soil Moisture and Brightness Temperature  

NASA Astrophysics Data System (ADS)

The ESA's (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission, operating since november 2009, is the first satellite dedicated to measuring the surface soil moisture and the ocean salinity. The CNES (Centre National d'Etudes Spatiales) has developed the CATDS (Centre Aval de Traitement des Données SMOS) ground segment. The CATDS provides temporal synthesis products (referred to as level 3) of soil moisture, which are now covering the whole SMOS period, i.e. since January 2010. These products have different time resolutions: daily products, 3-day global products (insuring a complete coverage of the Earth surface), 10-day composite products, and monthly averaged products. Moreover, a new product provides brightness temperatures at H and V polarizations which are computed at fixed incidence angles every 5 degrees. As the instrument measures L-band brightness temperatures at the antenna frame (X/Y polarizations), a rotation is applied to transform the observations to V/H polarizations. All the CATDS products are presented in the NetCDF format and on the EASE grid (Equal Area Scalable Earth grid) with a spatial resolution of ~ 25*25 km2 The soil moisture level 3 algorithm is based on ESA's (European Space Agency) level 2 retrieval scheme with the improvement of using several overpasses (3 at most) over a 7-day window. The use of many revisits is expected to improve the retrieved soil moisture. This communication aims at presenting the soil moisture and brightness temperature products from the CATDS as well as the other geophysical parameters retrieved, such as the vegetation optical depth or the dielectric constant of the surface. SMOS Level 3 soil moisture. 3-days aggregation product, the best estimation of soil moisture is chosen.

Berthon, L.; Mialon, A.; Al Bitar, A.; Cabot, F.; Kerr, Y. H.

2012-12-01

243

Effects of climate change on soil moisture over China from 1960-2006  

USGS Publications Warehouse

Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

Zhu, Q.; Jiang, H.; Liu, J.

2009-01-01

244

Validation of the SMOS L2 Soil Moisture Data in the REMEDHUS Network (Spain)  

Microsoft Academic Search

The Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission have been released. The data must be validated under different scenarios of biophysical and climatic conditions. For the current study, the data from January to December 2010 from 20 in situ soil moisture stations from the REMEDHUS soil moisture measurement station network (Spain) were used.

Nilda Sanchez; José Martinez-Fernandez; Anna Scaini; Carlos Perez-Gutierrez

2012-01-01

245

Temporal and spatial scales of observed soil moisture variations in the extratropics  

Microsoft Academic Search

Scales of soil moisture variations are important for understanding patterns of climate change, for developing and evaluating land surface models, for designing surface soil moisture observation networks, and for determining the appropriate resolution for satellite-based remote sensing instruments for soil moisture. Here we take advantage of a new archive of in situ soil moisture observations from Illinois and Iowa in

Jared K. Entin; Alan Robock; Konstantin Y. Vinnikov; Steven E. Hollinger; Suxia Liu; A. Namkhai

2000-01-01

246

Soil Moisture Measurements and their Applications at the Savannah River Site  

Microsoft Academic Search

Soil moisture is a very important component of the land-atmosphere exchange. Practically, it is valuable in both the agricultural and meteorological industries. Farmers require soil moisture for crop yields, while the atmospheric numerical modeling community has found soil moisture to be extremely important in generating realistic forecasts. Physically, the soil moisture not only provides water vapor for precipitation through evapotranspiration

Buckley

2000-01-01

247

The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations  

Microsoft Academic Search

For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the modern Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors

R. M. Parinussa; T. R. H. Holmes; W. T. Crow

2011-01-01

248

The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations  

Microsoft Academic Search

For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the current Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors

R. M. Parinussa; T. R. H. Holmes; M. T. Yilmaz; W. T. Crow

2011-01-01

249

Validation of SMOS soil moisture products over the Maqu and Twente regions.  

PubMed

The validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture products is a crucial step in the investigation of their inaccuracies and limitations, before planning further refinements of the retrieval algorithm. Therefore, this study intended to contribute to the validation of the SMOS soil moisture products, by comparing them with the data collected in situ in the Maqu (China) and Twente (The Netherlands) regions in 2010. The seasonal behavior of the SMOS soil moisture products is generally in agreement with the in situ measurements for both regions. However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data. Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m(3)/m(3) for the Maqu region and 0.17 m(3)/m(3) for the Twente region for ascending pass data. Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter. Improving the RFI filtering method and the quality of the retrieval algorithm inputs, such as land surface temperature and land cover, would certainly improve the accuracy of the retrieved soil moisture. PMID:23112582

Dente, Laura; Su, Zhongbo; Wen, Jun

2012-01-01

250

Estimating surface soil moisture using ENVISAT RA-2 altimetry measurements  

NASA Astrophysics Data System (ADS)

The climate of West African Sahel is controlled by a complex system of interactions between the atmosphere, biosphere and hydrosphere, known as the West African monsoon. The rainfall dynamics at various spatial and temporal scales, which have a strong impact on human activities, are mainly governed by surface conditions, vegetation cover and soil moisture. This important parameter of the hydrological cycle is poorly described at regional, continental or global scale. Space-borne sensors exhibit a strong potential for the study of continental surfaces. Satellite altimetry, initially designed to make accurate measurements of the sea surface topography, has recently demonstrated a strong capability to provide valuable information for land hydrology. It exhibited abilities for measuring water level variations of lakes, rivers, and floodplains. The radar altimetry backscattering coefficient was also related to surface properties, especially soil moisture and surface roughness, and their temporal evolution. We analyzed 8 years of backscattering coefficients variations from Envisat in Ku and S bands over the AMMA meso-scale site in Gourma, Sahel, and related them to the nature of the soil and its hydrological status (presence of moisture, open water, ...). Comparisons were made with in situ superficial soil moisture measurements and satellite-derived soil moisture estimates. Good correlations were found especially over sandy surfaces, showing the ability of radar altimetry for detecting soil moisture in semi-arid regions.

Frappart, F.; Fatras, C.; Mougin, E.; Grippa, M.

2011-12-01

251

Evaluating Electromagnetic Induction Techniques for Predicting Soil Moisture in Loamy Soils  

Microsoft Academic Search

We are conducting a study to evaluate usefulness of electromagnetic induction (EM) methods for predicting soil moisture in loamy soils present at the University of Mississippi (UM) Soil Moisture Observatory (SMO). The 5 acre SMO is located in a former agricultural field at the UM Field Station, a 740 acre tract of land located 11 miles from the UM campus

M. S. Aufman; R. M. Holt; C. J. Hickey

2006-01-01

252

Variation Of Soil Moisture Patterns In Response To Anthropogenic Land Disturbances In A Semiarid Regional Landscape  

NASA Astrophysics Data System (ADS)

This project focuses on examination of the effects of various land management practices on soil moisture for semiarid regional landscapes. The project is at the Wellhausen Ranch Research Station located near Laredo, TX. This ranch has undergone various land disturbances such as root plowing and cattle overgrazing that have caused damage to the vegetation and natural communities. Two research sites were chosen within the ranch, one disturbed by root plowing and one undisturbed, to represent various land use environment. Soil moisture analysis was performed, using the WatchDog Irrigation System, to identify the effects of temperature, vegetation, diurnal, and seasonal effect on the soil moisture patterns. In addition, three soil moisture probes were placed on the same location at three different depths, 3, 5, and 8 inches, below the surface, to evaluate the soil moisture profile in vertical direction. Statistical analysis such as ANOVA, Friedman's test, and the sign test was conducted and the results suggested that soil moisture is influenced by land disturbances significantly in a semiarid regional landscape.

Camarena, C.; Ren, J.; Jones, K.; Hempel, A.

2005-12-01

253

The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates  

NASA Astrophysics Data System (ADS)

This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.

Seyyedi, H.; Anagnostou, E. N.

2011-12-01

254

Preliminary results of SAR soil moisture experiment, November 1975  

NASA Technical Reports Server (NTRS)

The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

Choudhury, B. J.; Chang, A. T. C.; Schmugge, T. J.; Salomonson, V. V.; Wang, J. R.

1979-01-01

255

Large scale evaluation of soil moisture retrievals from passive microwave observations  

NASA Astrophysics Data System (ADS)

For several years passive microwave observations have been used to retrieve surface soil moisture from the Earth's surface. Several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and WindSat have been used for this purpose using multi-channel observations. Large scale validation of these retrievals is generally hampered by a lack of ground-based observation networks with sufficient spatial density to be accurately up-scaled to the resolution of satellite-based soil moisture retrievals. In response to this challenge, two new global evaluation techniques have been proposed which circumvent the need for extensive ground-based soil moisture observations. The first technique (Rvalue) is based on calculating the correlation coefficient between known rainfall errors and Kalman filter analysis increments realized during the assimilation of remotely sensed soil moisture into an antecedent precipitation index. The second technique is based on a so-called Triple Collocation (TC) analysis, which is a statistical tool for estimating the root mean square error (RMSE) of a set of three linearly related data sources with independent error structures. These two newly-developed, large-scale soil moisture evaluation techniques are applied for cross-verification on a global scale. Both techniques are also used to determine the sensitivity of soil moisture retrievals to land surface temperature estimates by artificially degrading the satellite signal used for the retrieval of this important parameter. Instead of coincident land surface temperature observations from the same satellite, external sources for land surface temperature are also evaluated using the same evaluation techniques. Finally, both day- and night-time observations are evaluated separately to determine the impact of the different physical conditions during day- and night-time. The evaluation results produced by the Rvalue and TC soil moisture verification approaches show a high mutual consistency (R2 = 0.95), which lends confidence to their interpretation as robust evaluation techniques. They show that the quality of soil moisture retrievals has a strong link with density of the vegetation cover of the observed area. This link was also found when evaluating the different scenarios for the land surface temperature input and when comparing soil moisture retrievals from day- and night-time observations. This study could be used as a framework to evaluate retrievals from the recent Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) missions.

Parinussa, R.; Holmes, T. R.; Crow, W. T.; De Jeu, R. A.

2011-12-01

256

The role of vegetation and soil properties on the spatio-temporal variability of the surface soil moisture in a maize-cropped field  

NASA Astrophysics Data System (ADS)

Soil moisture dynamics are affected by complex interactions among several factors. Understanding the relative importance of these factors is still an important challenge in the study of water fluxes and solute transport in unsaturated media. In this study, the spatio-temporal variability of surface soil moisture was investigated in a 10 ha flat cropped field located in northern Italy. Soil moisture was measured on a regular 50 × 50 m grid on seven dates during the growing season. For each measurement campaign, the spatial variability of the soil moisture was compared with the spatial variability of the soil texture and crop properties. In particular, to better understand the role of the vegetation, the spatio-temporal variability of two different parameters - leaf area index and crop height - was monitored on eight dates at different crop development stages. Statistical and geostatistical analysis was then applied to explore the interactions between these variables. In agreement with other studies, the results show that the soil moisture variability changes according to the average value within the field, with the standard deviation reaching a maximum value under intermediate mean soil moisture conditions and the coefficient of variation decreasing exponentially with increasing mean soil moisture. The controls of soil moisture variability change according to the average soil moisture within the field. Under wet conditions, the spatial distribution of the soil moisture reflects the variability of the soil texture. Under dry conditions, the spatial distribution of the soil moisture is affected mostly by the spatial variability of the vegetation. The interaction between these two factors is more important under intermediate soil moisture conditions. These results confirm the importance of considering the average soil moisture conditions within a field when investigating the controls affecting the spatial variability of soil moisture. This study highlights the importance of considering the spatio-temporal variability of the vegetation in investigating soil moisture dynamics, especially under intermediate and dry soil moisture conditions. The results of this study have important implications in different hydrological applications, such as for sampling design, ranking stability application, indirect measurements of soil properties and model parameterisation.

Baroni, G.; Ortuani, B.; Facchi, A.; Gandolfi, C.

2013-05-01

257

Assimilation of Satellite Based Soil Moisture Data in the National Weather Service's Flash Flood Guidance System  

NASA Astrophysics Data System (ADS)

Climate change and variability increases the probability of frequency, timing, intensity, and duration of flood events. After rainfall, soil moisture is the most important factor dictating flash flooding, since rainfall infiltration and runoff are based on the saturation of the soil. It is difficult to conduct ground-based measurements of soil moisture consistently and regionally. As such, soil moisture is often derived from models and agencies such as the National Oceanic and Atmospheric Administration's National Weather Service (NOAA/NWS) use proxy estimates of soil moisture at the surface in order support operational flood forecasting. In particular, a daily national map of Flash Flood Guidance (FFG) is produced that is based on surface soil moisture deficit and threshold runoff estimates. Flash flood warnings are issued by Weather Forecast Offices (WFOs) and are underpinned by information from the Flash Flood Guidance (FFG) system operated by the River Forecast Centers (RFCs). This study analyzes the accuracy and limitations of the FFG system using reported flash flood cases in 2010 and 2011. The flash flood reports were obtained from the NWS Storm Event database for the Arkansas-Red Basin RFC (ABRFC). The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) System using the NWS Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers. Comparison of the GFFG and real-time Multi-sensor Precipitation Estimator derived Quantitative Precipitation Estimate (QPE) for the same duration and location were used to analyze the success of the system. Improved flash flood forecasting requires accurate and high resolution soil surface information. The remote sensing observations of soil moisture can improve the flood forecasting accuracy. The Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellites are two potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. In order to determine the value of the satellite data to NWS operations, the streamflow generated by HL-RDHM with and without soil moisture assimilation will be compared to USGS gauge data. Furthermore, we will apply the satellite-based soil moisture data with the FFG algorithm to evaluate how many hits, misses and false alarms are generated. This study will evaluate the value of remote sensing data in constraining the state of the system for main-stem and flash flood forecasting.

Seo, D.; Lakhankar, T.; Cosgrove, B.; Khanbilvardi, R.

2012-12-01

258

[Spatial variation of soil moisture/salinity and the relationship with vegetation under natural conditions in Yancheng coastal wetland].  

PubMed

Taking the core part of Yancheng national nature reserve as the study area, according to soil sampling analysis of coastal wetlands in April and May 2011 land the 2011 ETM + remote sensing image, the spatial difference characteristic of coastal wetlands soil moisture and salinity, and the relationship with vegetation under natural conditions, were investigated with the model of correspondence analysis (CCA), linear regression simulation and geo-statistical method. The results showed: Firstly, the average level of the soil moisture was fluctuating between 36.820% and 46.333% , and the soil salinity was between 0.347% and 1.328% , in a more detailed sense, the Spartina swamp was the highest, followed by the mudflats swamp, the Suaeda salsa swamp, and the Reed marsh. Secondly, the spatial variation of soil moisture was consistent with that of the salinity, and the degree of variation in the east-west direction was greater than that in the north-south. The maximum soil moisture and salinity were found in the southwest Spartina swamp. The minimum was in the Reed swamp. The soil moisture and salinity were divided into 5 levels, from I to V. Level IV occupied the highest proportion, which were 36.156% and 28.531% , respectively. Finally, different landscape types with the combination of soil moisture and salinity showed a common feature that the moisture and salinity were from both high to low. The soil moisture value of Reed marshes was lower than 40.116% and the salinity value was lower than 0. 676% . The soil moisture value of Suaeda salsa marshes was between 38. 162% and 46. 403% and the salinity value was between 0.417% and 1.295%. The soil moisture value of Spartina swamp was higher than 43.214% and the salinity was higher than 1.090%. The soil moisture value of beach was higher than 43.214% and the salinity was higher than 0.677%. PMID:23668120

Zhang, Hua-Bing; Liu, Hong-Yu; Li, Yu-Feng; An, Jing; Xue, Xing-Yu; Hou, Ming-Hang

2013-02-01

259

Evaluation of Soil Moisture Downscaling Algorithms for the SMAP Mission  

NASA Astrophysics Data System (ADS)

The Soil Moisture Active Passive (SMAP) satellite is scheduled for launch by NASA in November 2014, with the aim to provide a medium-resolution soil moisture product at the global scale and with 2-3 days revisit frequency. The rationale behind this mission is that the synergy between 3 km resolution active (radar) and 36 km resolution passive (radiometer) observations can be used in a downscaling approach to overcome the individual limitations of each observation, ultimately providing soil moisture data at a resolution suitable for hydro-meteorological applications, on the order of ~9 km. Two soil moisture downscaling approaches were tested in this study: i) the baseline downscaling algorithm proposed for SMAP, which is based on an assumption of linear relationship between radiometer and radar observations, with the downscaled radiometer data then converted to a soil moisture product using the passive microwave retrieval method; ii) the optional downscaling algorithm for SMAP, which is based on an assumption of a directly linear relationship between soil moisture and the radar observations. Data used to evaluate these two approaches were collected from the Soil Moisture Active Passive Experiments (SMAPEx) in south-eastern Australia, which closely simulate the SMAP data stream using airborne observations for a single SMAP radiometer pixel over a 3-week interval. Both approaches were compared to a reference soil moisture map retrieved from 1 km resolution radiometer data. Results indicated that radar observations at vv-polarization had the best correlation with radiometer observations or soil moisture data than hh- or hv-polarization, thus having best performance during downscaling procedure. These two downscaling approaches showed similar performance in terms of accuracy, with a Root-Mean-Square Error (RMSE) in downscaled soil moisture data around 0.02 cm3/cm3, when downscaled to 9 km resolution. This increased to 0.043 cm3/cm3 when applied at 1 km resolution. Results indicated both downscaling methods had the ability to fulfill the error target of SMAP, with a RMSE less than 0.04 cm3/cm3 at 9 km resolution.

Wu, Xiaoling; Walker, Jeffrey; Rüdiger, Christoph; Panciera, Rocco

2014-05-01

260

A physically based approach for the estimation of root-zone soil moisture from surface measurements  

NASA Astrophysics Data System (ADS)

In the present work, we developed a new formulation for the estimation of the soil moisture in the root zone based on the measured value of soil moisture at the surface. It was derived from a simplified soil water balance equation for semiarid environments that provides a closed form of the relationship between the root zone and the surface soil moisture with a limited number of physically consistent parameters. The method sheds lights on the mentioned relationship with possible applications in the use of satellite remote sensing retrievals of soil moisture. The proposed approach was used on soil moisture measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases. The AMMA network was designed with the aim to monitor three so-called mesoscale sites (super sites) located in Benin, Mali, and Niger using point measurements at different locations. Thereafter the new formulation was tested on three additional stations of SCAN in the state of New Mexico (US). Both databases are ideal for the application of such method, because they provide a good description of the soil moisture dynamics at the surface and the root zone using probes installed at different depths. The model was first applied with parameters assigned based on the physical characteristics of several sites. These results highlighted the potential of the methodology, providing a good description of the root-zone soil moisture. In the second part of the paper, the model performances were compared with those of the well-known exponential filter. Results show that this new approach provides good performances after calibration with a set of parameters consistent with the physical characteristics of the investigated areas. The limited number of parameters and their physical interpretation makes the procedure appealing for further applications to other regions.

Manfreda, S.; Brocca, L.; Moramarco, T.; Melone, F.; Sheffield, J.

2014-03-01

261

Does soil moisture overrule temperature dependency of soil respiration in Mediterranean riparian forests?  

NASA Astrophysics Data System (ADS)

Soil respiration (SR) is a major component of ecosystem's carbon cycle and represents the second largest CO2 flux of the terrestrial biosphere. Soil temperature is considered to be the primary control on SR whereas soil moisture as the secondary control factor. However, soil moisture can become the dominant control on SR in very wet or dry conditions. Determining the trigger that switches-on soil moisture as the primary control factor of SR will provide a deeper understanding on how SR changes under projected future increased droughts. Specific objectives of this study were (1) to investigate the seasonal variations and the relationship between SR and both soil temperature and moisture in a Mediterranean riparian forest along a groundwater level gradient; (2) to determine soil moisture thresholds at which SR is rather controlled by soil moisture than by temperature; (3) to compare SR responses under different tree species present in a Mediterranean riparian forest (Alnus, glutinosa, Populus nigra and Fraxinus excelsior). Results showed that the heterotrophic soil respiration rate, groundwater level and 30 cm integral soil moisture (SM30) decreased significantly from riverside to uphill and showed a pronounced seasonality. SR rates showed significant differences among tree species, with higher SR for P. nigra and lower SR for A. glutinosa. The lower threshold of soil moisture was 20 and 17% for heterotrophic and total SR respectively. Daily mean SR rate was positively correlated with soil temperature when soil moisture exceeded the threshold, with Q10 values ranging from 1.19 to 2.14; nevertheless, SR became decoupled from soil temperature when soil moisture dropped below these thresholds.

Chang, C.-T.; Sabaté, S.; Sperlich, D.; Poblador, S.; Sabater, F.; Gracia, C.

2014-06-01

262

The impact of different soil texture datasets on soil moisture and evapotranspiration simulated by CLM4  

NASA Astrophysics Data System (ADS)

Evapotranspiration (ET) is both a moisture flux and an energy flux. It has a substantial impact on climate. Community Land Model Version 4 (CLM4) is a widely used land surface model that simulates moisture, energy and momentum exchange between land and atmosphere. However, ET from CLM4 suffers from relatively low accuracy, especially for ground evaporation. In the parameterization of CLM4, soil texture, by determining soil hydraulic properties, affects the evolution of soil moisture and consequently ET. The three components of ET in climate models can more readily be improved after an evaluation of soil texture dataset's impact on ET simulations. Besides the IGBP-DIS (International Geosphere-Biosphere Programme Data and Information System) dataset used in CLM4, another two US multi-layer soil particle content datasets, Soil Database for the Conterminous United States (CONUS-SOIL) and Global Soil Texture and Derived Water-Holding Capacities (Webb2000), are also used. The latter two show a consistent substantial reduction of both sand and clay contents in Mississippi River Basin. CLM4 is run off line over the US with the three different soil texture datasets (Control Run, CONUS SOIL and Webb2000). Comparisons of simulated soil moisture with NCEP (National Centers for Environmental Prediction) reanalysis data show a higher agreement between CONUS SOIL and NCEP over Mississippi River Basin. Compared with Control Run, soil moisture from the other two runs increases in Western US and decreases in Eastern US, which produces a stronger west-east soil moisture gradient. The response of ET to soil moisture change differs in different climate regimes. In Mississippi River Basin, the change of ET is negligible even if soil moisture increases substantially. On the other hand, in eastern US and US Central Great Plains, ET is very sensitive to soil moisture during the warm seasons, with the change of up to 10 W/m2.

Yan, B.; Dickinson, R. E.

2012-12-01

263

Can the ASAR Global Monitoring Mode Product Adequately Capture Spatial Soil Moisture Variability?  

NASA Astrophysics Data System (ADS)

Global soil moisture (SM) monitoring in the past several decades has been undertaken mainly at coarse spatial resolution, which is not adequate for addressing small-scale phenomena and processes. The currently operational Advanced Microwave Scanning Radiometer (NASA) and future planned missions such as the Soil Moisture and Ocean Salinity (ESA) and the Soil Moisture Active Passive (NASA) will remain resolution limited. Finer scale soil moisture estimates can be achieved either by down-scaling the available coarse resolution radiometer and scatterometer (i.e. ERS1/2, ASCAT) observations or by using high resolution active microwave SAR type systems (typical resolution is in the order of meters). Considering the complex land surface - backscatter signal interaction, soil moisture inversion utilizing active microwave observations is difficult and generally needs supplementary data. Algorithms based on temporal change detection offer an alternative less complex approach for deriving (and disaggregating coarse) soil moisture estimates. Frequent monitoring and low frequency range along with a high pixel resolution are essential preconditions when characterizing spatial and temporal soil moisture variability. An alternative active system that meets these requirements is the Advance Synthetic Aperture Radar (ASAR) on ENVISAT [C-band, global, 1 km in Global Monitoring (GM) Mode]. The Vienna University of Technology (TU Wien) has developed a 1 km soil moisture product using the temporal change detection approach and the ASAR GM. The TU Wien SM product sensitivity was evaluated at two scales: point (using in situ data from permanent soil moisture stations) and regional [using ground measured data and aircraft estimates derived from the Polarimetric L-band Microwave Radiometer (PLMR)] over the National Airborne Field Experiment (NAFE'05) area located in the Goulburn catchment, SE Australia. The month long (November 2005) campaign was undertaken in a region predominantly covered by grasslands and partly by forests and croplands. Point scale analysis revealed high ASAR sensitivity and adequate response to changes in moisture conditions (R = 0.69 and RMSE = 0.08 v/v). Regional analysis was performed at several different spatial resolutions (1 km to 25 km). ASAR exhibited high noise level and significant wet bias. Increase in pixel size resulted in improving R and RMSE from R = 0.59 and RMSE = 0.14 to R = 0.91 and RMSE = 0.05 at 1 km and 25 km respectively; however, despite the reasonable statistical agreement at 1 km, the soil moisture spatial patterns clearly visible in the PLMR images, the later were verified with ground data, were lacking in the ASAR product.

Mladenova, I.; Lakshmi, V.; Walker, J.; Panciera, R.; Wagner, W.; Doubkova, M.

2008-12-01

264

Cross evaluation of in-situ, synthetic and remotely sensed surface soil moisture in southwestern France  

NASA Astrophysics Data System (ADS)

A long term data acquisition effort of profile soil moisture is currently underway at 12 automatic weather stations located in southwestern France. The SMOSMANIA profile soil moisture network has several objectives including: (i) the validation of the operational soil moisture products of Météo-France, produced by the hydrometeorological model SIM, (ii) the validation of new versions of the land surface model of Météo-France (ISBA), and (iii) ground-truthing of future airborne Cal/Val campaigns in support of the SMOS mission and in a more general way the verification of remotely sensed soil moisture products. Soil moisture observed at SMOSMANIA constitutes a unique data set as for the first time in Europe, automatic measurements of soil moisture are integrated in an operational meteorological network. Twelve stations of the existing automatic weather station network of Météo-France (RADOME) in southwestern France were upgraded to measure soil moisture at different depths (5, 10, 20, 30 cm) with a twelve minute time step. The network is operational since January 2007. These data permit to evaluate the surface soil moisture (SSM) from the operational SIM suite of model (SAFRAN-ISBA-MODCOU) used at Météo-France and also remotely sensed METOP/ASCAT (Advanced SCATterometer) surface soil moisture estimates over a two year period (2007-2008). In-situ SSM measurements are necessary to validate remotely sensed SSM estimates. Land surface models can be used to upscale the in situ SSM observations and complete the evaluation of satellite products. The comparison of the SIM and SMOSMANIA data shows a good temporal correlation with an average of r = 0.70 for the twelve stations with a positive mean bias = 0.031 m3m-3 and a mean error RMSE = 0.085 m3m-3. The good correlation shows that the SIM predictions may be used as a credible SSM data set to evaluate the seasonal and interannual variability of the remotely sensed SSM. Regarding the comparison between rescaled in-situ (or SIM) and ASCAT SSM, an average error of the soil moisture retrieval is about 0.06 m3m-3. However, the correlation for each station is always better for SIM. A new ASCAT SSM data set downscaled at one km scale is also presented in this study. Finally, a last SSM data set is evaluated, the ECMWF soil moisture analysis system updated with an Extended Kalman Filter (EKF) permits to assimilate the METOP/ASCAT SSM into the Integrated Forecasting System (IFS). Over a 6 month period in 2008, the IFS SSM correlates very well with the in situ observations (r = 0.84).

Albergel, Clement; Calvet, Jean-Christophe; Martin, Eric; Hasenauer, Stefan; Vahid, Naemi; Wagner, Wolfgang; de Rosnay, Patricia

2010-05-01

265

What perspective in remote sensing of soil moisture for hydrological applications by coarse-resolution sensors  

NASA Astrophysics Data System (ADS)

Soil moisture is a key state variable in hydrology, it controls the proportion of rainfall that infiltrates, runoff and evaporates from the land. For hydrological applications, soil moisture monitoring at catchment scale is required and, for that, microwave remote sensing sensors might be used. However, due to their coarse-spatial resolution, the skepticism on the suitability to retrieve the soil moisture at catchment scale takes still place. This work attempts to bring out if coarse resolution sensors for soil moisture monitoring can have some perspectives for hydrological applications. Two soil moisture products derived from the Advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) are used for this purpose. The analysis is addressed by investigating: (i) the reliability of product data in the estimation of the wetness conditions of a catchment antecedent to rainfall events, and (ii) the benefit on runoff prediction if data are assimilated into a rainfall-runoff model. Rainfall-runoff observations are taken from several catchments in Italy and Luxembourg for testing. Results reveal that ASCAT and AMSR-E soil moisture products can be conveniently used to improve runoff prediction thus opening new important challenges and opportunities for the use of this new sources of data in the operational hydrology.

Brocca, Luca; Melone, Florisa; Moramarco, Tommaso; Wagner, Wolfgang

2011-10-01

266

Evaluation of Assumptions in Soil Moisture Triple Collocation Studies  

NASA Astrophysics Data System (ADS)

Error variance information of different products that observe the same geophysical parameter can be obtained using Triple Collocation Analysis (TCA). However, the TCA system of equations has more unknowns than available equations, hence the system is underdetermined. To be able to obtain a solution for the error variance, several assumptions are made; in particular errors are orthogonal with respect to the truth and cross-correlations of errors vanish, while the accuracy of TCA-based errors depend on the degree that the available datasets fit these assumptions. Heavy majority of TCA-based hydrological applications commonly make these assumptions, yet no study has specifically investigated the degree that available soil moisture datasets fit these assumptions. Here we evaluate these assumptions both analytically and numerically using soil moisture data (station-based observations, Noah and API hydrological model simulations, and LPRM and ASCAT retrievals) obtained over four US Department of Agriculture watersheds. In addition to the non-orthogonal and cross-correlated errors, another type of error (leaked signal) is identified, while magnitudes of all error types (non-orthogonal, cross-correlated, leaked signal, true random, and TCA-based errors) are all numerically estimated. Results show widely assumed non-orthogonal and cross-correlated error components are not zero. On the other hand it is analytically shown that the impacts of non-orthogonal and leaked signal errors are largely dampened while error cross-correlations impose a negative bias on the TCA-based error estimates.

Yilmaz, M.; Crow, W. T.

2013-12-01

267

Advances, experiences, and prospects of the International Soil Moisture Network  

NASA Astrophysics Data System (ADS)

In 2009, the International Soil Moisture Network (ISMN; http:www.ipf.tuwien.ac.at) was initiated as a platform to support calibration and validation of soil moisture products from remote sensing and land surface models, and to advance studies on the behavior of soil moisture over space and time. This international initiative is fruit of continuing coordinative efforts of the Global Energy and Water Cycle Experiment (GEWEX) in cooperation with the Group of Earth Observation (GEO) and the Committee on Earth Observation Satellites (CEOS). The decisive financial incentive was given by the European Space Agency (ESA) who considered the establishment of the network critical for optimizing the soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. The ISMN collects and harmonizes ground-based soil moisture data sets from a large variety of individually operating networks and makes them available through a centralized data portal. Meanwhile, almost 6000 soil moisture data sets from over 1300 sites, distributed among 34 networks worldwide, are contained in the database. The steadily increasing number of organizations voluntarily contributing to the ISMN, and the rapidly increasing number of studies based on the network show that the portal has been successful in reaching its primary goal to promote easy data accessibility to a wide variety of users. Recently, several updates of the system were performed to keep up with the increasing data amount and traffic, and to meet the requirements of many advanced users. Many datasets from operational networks (e.g., SCAN, the US Climate Reference Network, COSMOS, and ARM) are now assimilated and processed in the ISMN on a fully automated basis in near-real time. In addition, a new enhanced quality control system is currently being implemented. This presentation gives an overview of these recent developments, presents some examples of important scientific results based on the ISMN, and sketches an outlook for mid- to long-term operation.

Dorigo, W.; van Oevelen, P. J.; Drusch, M.; Wagner, W.; Scipal, K.; Mecklenburg, S.

2012-12-01

268

Simulation of Soil Moisture Development in Flood Protecting Earth Dams  

Microsoft Academic Search

Extreme floods represent an increased risk for urban areas and agriculture. Time to time the protective earth dams are destroyed by a suddenly increased amount of water with destroing or even cathastrophic consequences. A numerical study of the soil moisture development within the earth body during the flood is simulated under a selection of boundary conditions. Several soil materials are

M. Cislerova; D. Zumr; J. Dusek; T. Vogel

2007-01-01

269

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

NASA Technical Reports Server (NTRS)

Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

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

2011-01-01

270

Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters  

NASA Technical Reports Server (NTRS)

A hypothesis is presented that many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture. The specific hydrologic processes that may be detected include groundwater recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential evapotranspiration (ET), and information about the hydrologic properties of soils. In basin and hillslope hydrology, soil moisture is the interface between surface and ground waters.

Engman, Edwin T.

1997-01-01

271

Moisture modulates rhizosphere effects on C decomposition in two different soil types  

Microsoft Academic Search

While it is well known that soil moisture directly affects microbial activity and soil organic matter (SOM) decomposition, it is unclear if the presence of plants alters these effects through rhizosphere processes. We studied soil moisture effects on SOM decomposition with and without sunflower and soybean. Plants were grown in two different soil types with soil moisture contents of 45%

Feike A. Dijkstra; Weixin Cheng

2007-01-01

272

Determination of chemical availability of cadmium and zinc in soils using inert soil moisture samplers  

Microsoft Academic Search

A rapid method for extracting soil solutions using porous plastic soil-moisture samplers was combined with a cation resin equilibration based speciation technique to look at the chemical availability of metals in soil. Industrially polluted, metal sulphate amended and sewage sludge treated soils were used in our study. Cadmium sulphate amended and industrially contaminated soils all had > 65% of the

Bruce P. Knight; Amar M. Chaudri; Steve P. McGrath; Kenneth E. Giller

1998-01-01

273

Soil electromagnetic parameters as functions of frequency, soil density, and soil moisture  

Microsoft Academic Search

Measurements are made to determine the conductivity and dielectric constants of a gray clay loam and a reddish-brown clay loam. The measurements are made as a function of soil density (from 1.2 g\\/cm3to 1.8 g\\/cm3), soil moisture (from 0 percent to 20 percent of the dry soil weight), and excitation frequency (from 30 MHz to 4 GHz), using standard transmission

J. E. Hipp

1974-01-01

274

Sensitivity of Severe Convective Storms to Soil Moisture and Lower Atmospheric Water Vapor  

NASA Astrophysics Data System (ADS)

Numerous studies have examined the sensitivity of the atmospheric state to soil moisture on time scales of up to a day. Dry line intensity, lower tropospheric water vapor content, and precipitation have all been shown through modeling studies to be affected by modest perturbations to upstream soil moisture content and subsequent lower atmospheric water vapor. Since all of these aspects could be associated with convection, a high-impact forecast event that exhibits rapid nonlinear error growth, it is reasonable to expect that irrigation practices might influence severe convective storms. Understanding the link between soil moisture and specific convective elements could have broad implications for severe weather forecasting, and could reveal the degree to which irrigation-induced storm-scale inadvertent weather modification exists. This work examines the sensitivity to soil moisture and lower atmospheric water vapor content of a severe convective storm that struck Moore, Oklahoma, USA on May 20th, 2013, killing 24 people. While adjoint sensitivity analysis that employs the tangent linear version of a numerical weather prediction model might be used to examine convective sensitivities to soil moisture, the strong nonlinearity associated with these events likely renders this technique inaccurate. Alternatively, the approach here utilizes backward trajectory analysis to identify the regions up to a day prior to which the storm might be sensitive. Once the regions are identified, an ensemble of model forecasts is created by varying initial soil moisture to reveal the degree to which perturbations must be made to influence the downstream storm. Subsequent comparisons are made between the required soil moisture perturbations and realistic soil water values added through irrigation.

Ancell, Brian; Nauert, Christian

2014-05-01

275

Active and passive microwave remote sensing of soil moisture  

NASA Astrophysics Data System (ADS)

This study focuses on the development of a consistent methodology for soil moisture inversion from Synthetic Aperture Radar (SAR) data using the Integral Equation Model (Fung et al., 1992) without the need to prescribe time-varying land-surface attributes as constraining parameters. Specifically, the dependence of backscatter coefficient on the soil dielectric constant, surface roughness height and correlation length was investigated. The IEM was used in conjunction with an inversion model to retrieve soil moisture using multi-frequency and multi-polarization data (L, C and X-Bands) simultaneously. The results were cross-validated with gravimetric observations obtained during the Washita '94 field experiment in the Little Washita Watershed, Oklahoma. The average error in the estimated soil moisture was of the order of 3.4%, which is comparable to that expected due to noise in the SAR data. The retrieval algorithm performed very well for low incidence angles and over bare soil fields, and it deteriorated slightly for vegetated areas, and overall for very dry soil conditions. The IEM was originally developed for scattering from a bare soil surface, and therefore the vegetation effects are not explicitly incorporated in the model. We coupled a semi-empirical vegetation scattering parameterization to our multi-frequency soil moisture inversion algorithm. This approach allows for the explicit representation of vegetation backscattering effects without the need to specify a large number of parameters. The retrieval algorithm performed well for vegetated conditions when a land-use based vegetation parameterization was used. The explicit incorporation of land-use in the parameterization scheme is equivalent to incorporating the effect of vegetation structure in the soil moisture estimates obtained using the SAR observations. ESTAR images of brightness temperature obtained during the same period were inverted independently for soil moisture. The results at individual sampling sites were first compared against gravimetric soil moisture observations for Washita '94, and the RMS errors for both applications were between 3% and 4%. Subsequently, we investigated the use of high resolution SAR-derived soil moisture fields to estimate sub-pixel variability in ESTAR derived fields. The effect of sub-pixel variability of various land surface properties (namely soil moisture, soil texture, soil temperature, and vegetation). The results demonstrated the linear scaling behavior of ESTAR based soil moisture estimates. We also investigated the problem of consistency between the two systems. Estimated and observed brightness temperature fields were compared and analyzed to establish the aggregation kernel inherent to ESTAR, i.e., how the instrument actually processes/integrates sub-pixel variability. The scaling properties of both SAR and ESTAR at all frequencies were investigated and the results indicated that both sensors demonstrated fractal behavior. The results suggested that the two systems can be used to complement each other, and there is a potential to downscale ESTAR observations for high resolution soil moisture estimation, using only one SAR frequency (e.g. L-band).

Bindlish, Rajat

2000-10-01

276

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

NASA Technical Reports Server (NTRS)

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

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

1995-01-01

277

Soil moisture retrieval by active/passive microwave remote sensing data  

NASA Astrophysics Data System (ADS)

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 between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

Wu, Shengli; Yang, Lijuan

2012-09-01

278

A spatially coherent global soil moisture product with improved temporal resolution  

NASA Astrophysics Data System (ADS)

Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11 km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures. The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN). The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

de Jeu, Richard A. M.; Holmes, Thomas R. H.; Parinussa, Robert M.; Owe, Manfred

2014-08-01

279

On the Disaggregation of Passive Microwave Soil Moisture Data Using A Priori Knowledge of Temporally Persistent Soil Moisture Fields  

Microsoft Academic Search

Water and energy fluxes at the interface between the land surface and atmosphere are affected by the surface water content of the soil, which is highly variable in space and time. The sensitivity of active and passive microwave remote sensing data to surface soil moisture content has been investigated in numerous studies. Recent satellite mission concepts as, for example, the

Alexander Loew; Wolfram Mauser

2008-01-01

280

Application of atmospheric neutrons to soil moisture measurement  

SciTech Connect

This paper describes the possibility of continuous remote sensing of the moisture content of soil using atmospheric neutrons produced by cosmic radiations near the ground surface. Using polyethylene-moderated BF3 neutron counters at several different underground depths, the authors measured time variations of the neutron fluxes, to examine their responses to soil moisture changes quantitatively. From the close correlations between neutron fluxes and soil moisture contents, they show that the fluxes of the underground neutrons with energies from the cadmium threshold of 0.025 eV to about 10W eV, measured at a depth of 20 cm, are affected most sensitively by the moisture content of the soil near the same depth. Their fractional change is represented by a regression coefficient of 1% per unit percent of soil moisture change for a range from 33% (approx.2.8 pF) to 52% (approx.1.9 pF) at the 20-cm depth. This neutron technique promises to be a simple and reliable measurement that depends on the counting statistics of neutrons.

Kodama, M.; Kudo, S.; Kosuge, T.

1985-10-01

281

The Multi-Level and Multi-Scale Factor Analysis for Soil Moisture Information Extraction by Multi-Source Remote Sensing Data  

NASA Astrophysics Data System (ADS)

The research on coupling both data source is very important for improving the accuracy of Image information interpretation and target recognition. In this paper a classifier is presented, which is based on integration of both active and passive remote sensing data and the Maximum Likelihood classification for inversion of soil moisture and this method is tested in Heihe river basin, a semi-arid area in the north-west of china. In the algorithm the wavelet transform and IHS are combined to integrate TM3, TM4, TM5 and ASAR data. The method of maximum distance substitution in local region is adopted as the fusion rule for prominent expression of the detailed information in the fusion image, as well as the spectral information of TM can be retained. Then the new R, G, B components in the fusion image and the TM6 is taken as the input to the Maximum Likelihood classification, and the output corresponds to five different categories according to different grades of soil moisture. The field measurements are carried out for validation of the method. The results show that the accuracy of completely correct classification is 66.3%, and if the discrepancy within one grade was considered to be acceptable, the precision is as high as 92.6%. Therefore the classifier can effectively be used to reflect the distribution of soil moisture in the study area.

Yu, F.; Li, H. T.; Jia, Y.; Han, Y. S.; Gu, H. Y.

2013-07-01

282

Radiative Transfer Parameter Estimation for SMOS Soil Moisture Retrieval  

NASA Astrophysics Data System (ADS)

The SMOS Level-2 Processor is an operational routine to calculate the SMOS Level-2 product soil moisture from the radiometer brightness temperature (Tb). But, the radiative transfer from measured Tb into soil moisture is influenced by several conditions such as soil surface roughness and vegetation opacity, which are parameterized in a general way only. Surface soil roughness and vegetation opacity cannot be easily measured at the scale of SMOS observation of 30 - 50 km. The absolute values of these parameters for different land surfaces are uncertain, and the degree of this uncertainty is unknown as well. In addition, recent studies found that SMOS overestimates the Tb. In this paper, we present a method to enhance the accuracy of the SMOS soil moisture product by parameter estimation using a data assimilation technique (Sampling Importance Resampling Particle Filter - SIR-PF) with in situ soil moisture observations. Therefore, we developed an approach to analyze the ability of the system to track the temporal evolution of parameters such as vegetation opacity and soil surface roughness. Based on observed soil moisture and soil temperature, the L-MEB forward model was run and perturbed according to the measurement accuracy. L-MEB was integrated into a data assimilation framework using the SIR-PF, which is able to concurrently update L-MEB states and parameters. In addition, we investigate the ability of the proposed approach to account for the SMOS observation bias by introducing a bias factor in L-MEB. The overall advantage of the proposed sequential approach is its ability to be integrated into the operational near real time processing of the Level-2 product. The objectives of this study are: (i) to retrieve radiative transfer parameters and their temporal changes and (ii) to account for a bias and uncertainty in SMOS measurements.

Montzka, C.; Hendricks Franssen, H.; Drusch, M.; Moradkhani, H.; Weihermueller, L.; Bogena, H. R.; Vanderborght, J.; Vereecken, H.

2011-12-01

283

Impact of the soil hydrology scheme on simulated soil moisture memory in a GCM  

NASA Astrophysics Data System (ADS)

Soil moisture-atmosphere feedback effects play an important role in several regions of the globe. For some of these regions, soil moisture memory may contribute significantly to the development of the regional climate. Identifying those regions can help to improve predictability in seasonal to decadal climate forecasts. The present study investigates how different setups of the soil hydrology scheme affect soil moisture memory simulated by the global climate model of the Max Planck Institute for Meteorology (MPI-M), ECHAM6/JSBACH. First, the standard setup applied for the CMIP5 exercise is used, in which soil water is represented by a single soil moisture reservoir. Second, a new five soil layer hydrology scheme is utilized where the previous bucket soil moisture now corresponds to the root zone soil moisture. In the standard setup, transpiration may access the whole soil moisture that is exceeding the wilting point over vegetated areas. However, in the five layer scheme, soil water below the root zone cannot be accessed by transpiration directly, but only be transported upwards into the root zone by diffusion following the Richard's equation. Thus, this below the root zone, which is not present in the standard setup, can act as buffer in the transition between wet and dry periods. A second notable difference between the two setups is the formulation of bare soil evaporation. In the standard setup, it may only occur if the whole soil moisture bucket is almost completely saturated, while in the new setup, it depends only on the saturation of the upper most soil layer. As the latter is much thinner than the root zone (bucket), bare soil evaporation can occur more frequently, especially after rainfall events. For the second setup, two further variants are considered: one where the bare soil evaporation was modified and one where a new parameter dataset of soil water holding capacities was used. Soil moisture memory of the different setups will be analysed from global ECHAM6/JSBACH simulations forced by AMIP2 SST. Areas will be highlighted where the regional climate seems to be sensitive to the improved representation of soil hydrology in the new setup and its variants. First results indicate that soil moisture memory effects play a role in regions where a soil moisture buffer is present below the root zone.

Hagemann, Stefan; Stacke, Tobias

2013-04-01

284

NASA Soil Moisture Active Passive (SMAP) Mission Formulation  

NASA Technical Reports Server (NTRS)

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 ground processing designs.

Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared

2011-01-01

285

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska  

NASA Astrophysics Data System (ADS)

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

286

A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data  

Microsoft Academic Search

The potential of using ERS Scatterometer data for soil moisture monitoring over the Ukraine is investigated. The ERS Scatterometer is a C-band radar with a spatial resolution of 50 km and a high temporal sampling rate. An algorithm for estimating the surface soil moisture content is applied to 6 years of data. A qualitative comparison with meteorological observations and auxiliary

Wolfgang Wagner; Guido Lemoine; Helmut Rott

1999-01-01

287

Soil temperature error propagation in passive microwave retrieval of soil moisture  

Microsoft Academic Search

In the near future two dedicated soil moisture satellites will be launched (SMOS and SMAP), both carrying an L-band radiometer. It is well known that microwave soil moisture retrieval algorithms must account for the physical temperature of the emitting surface. One proposed approach is the use of temperature output from numerical weather prediction (NWP) models. A radiative transfer model, as

T. Holmes; T. Jackson

2010-01-01

288

ASCAT soil wetness index validation through in situ and modeled soil moisture data in central Italy  

Microsoft Academic Search

Reliable measurements of soil moisture at global scale might greatly improve many practical issues in hydrology, meteorology, climatology or agriculture such as water management, quantitative precipitation forecasting, irrigation scheduling, etc. Remote sensing offers the unique capability to monitor soil moisture over large areas but, nowadays, the spatio-temporal resolution and accuracy required for some hydrological applications (e.g., flood forecasting in medium

L. Brocca; F. Melone; T. Moramarco; W. Wagner; S. Hasenauer

2010-01-01

289

Soil Moisture Extremes Observed by METOP ASCAT: Was 2012 an Exceptional Year?  

NASA Astrophysics Data System (ADS)

In summer 2012 the international press reported widely about the severe drought that had befallen large parts of the United States. Yet, the US drought was only one of several major droughts that occurred in 2012: Southeastern Europe, Central Asia, Brazil, India, Southern Australia and several other regions suffered from similarly dry soil conditions. This raises the question whether 2012 was an exceptionally dry year? In this presentation we will address this question by analyzing global soil moisture patterns as observed by the Advanced Scatterometer (ASCAT) flown on board of the METOP-A satellite. We firstly compare the 2012 ASCAT soil moisture data to all available ASCAT measurements acquired by the instrument since the launch of METOP-A in November 2006. Secondly, we compare the 2012 data to a long-term soil moisture data set derived by merging the ASCAT soil moisture data with other active and passive microwave soil moisture retrievals as described by Liu et al. (2012) and Wagner et al. (2012) (see also http://www.esa-soilmoisture-cci.org/). A first trend analysis of the latter long-term soil moisture data set carried out by Dorigo et al. (2012) has revealed that over the period 1988-2010 significant trends were observed over 27 % of the area covered by the data set, of which 73 % were negative (soil drying) and only 27 % were positive (soil wetting). In this presentation we will show how the inclusion of the years 2011 and 2012 affects the areal extent and strengths of these significant trends. REFERENCES Dorigo, W., R. de Jeu, D. Chung, R. Parinussa, Y. Liu, W. Wagner, D. Fernández-Prieto (2012) Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7. Liu, Y.Y., W.A. Dorigo, R.M. Parinussa, R.A.M. de Jeu, W. Wagner, M.F. McCabe, J.P. Evans, A.I.J.M. van Dijk (2012) Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.

Wagner, Wolfgang; Paulik, Christoph; Hahn, Sebastian; Melzer, Thomas; Parinussa, Robert; de Jeu, Richard; Dorigo, Wouter; Chung, Daniel; Enenkel, Markus

2013-04-01

290

Transient soil moisture profile of a water-shedding soil cover in north Queensland, Australia  

NASA Astrophysics Data System (ADS)

In current agricultural and industrial applications, soil moisture determination is limited to point-wise measurements and remote sensing technologies. The former has limitations on spatial resolution while the latter, although has greater coverage in three dimensions, but may not be representative of real-time hydrologic conditions of the substrate. This conference paper discusses the use of elongated soil moisture probes to describe the transient soil moisture profile of water-shedding soil cover trial plots in north Queensland, Australia. Three-metre long flat ribbon cables were installed at designed depths across a soil cover with substrate materials from mining activities comprising of waste rocks and blended tailings. The soil moisture measurement is analysed using spatial time domain reflectometry (STDR) (Scheuermann et al., 2009) Calibration of the flat ribbon cable's soil moisture measurement in waste rocks is undertaken in a glasshouse setting. Soil moisture retention and outflows are monitored at specific time interval by mass balance and water potential measurements. These data sets together with the soil hydrologic properties derived from laboratory and field measurements are used as input in the numerical code on unsaturated flow, Hydrus2D. The soil moisture calculations of the glasshouse calibration using this numerical method are compared with results from the STDR soil moisture data sets. In context, the purpose of the soil cover is to isolate sulphide-rich mine wastes from atmospheric interaction as oxidation and leaching of these materials may result to acid and metalliferous drainage. The long term performance of a soil cover will be described in terms of the quantities and physico-chemical characteristics of its outflows. With the soil moisture probes set at automated and pre-determined measurement time intervals, it is expected to distinguish between macropore and soil moisture flows during high intensity rainfall events and, also continuously update data sets on soil moisture retention, especially during long periods of drought. As such, description of the soil cover water balance will be more elaborate as the soil moisture profile will be described in terms of temporal and spatial variability. Moreover, this field data set can lend support on the evaluation of the potential use of mine wastes as cover materials with respect to their hydrologic and geochemical properties.

Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

2014-05-01

291

Agricultural Decision Support Through Robust Assimilation of Satellite Derived Soil Moisture Estimates  

NASA Astrophysics Data System (ADS)

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 correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.

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

2012-12-01

292

Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry  

NASA Astrophysics Data System (ADS)

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 regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.

Tawfik, Ahmed B.

293

Contribution of soil moisture retrievals to land data assimilation products  

NASA Astrophysics Data System (ADS)

Satellite measurements (retrievals) of surface soil moisture are subject to errors and cannot provide complete space-time coverage. Data assimilation systems merge available retrievals with information from land surface models and antecedent meteorological data, information that is spatio-temporally complete but likewise uncertain. For the design of new satellite missions it is critical to understand just how uncertain retrievals can be and still be useful. Here, we present a synthetic data assimilation experiment that determines the contribution of retrievals to the skill of land assimilation products (soil moisture and evapotranspiration) as a function of retrieval and land model skill. As expected, the skill of the assimilation products increases with the skill of the model and that of the retrievals. The skill of the soil moisture assimilation products always exceeds that of the model acting alone; even retrievals of low quality contribute information to the assimilation product, particularly if model skill is modest.

Reichle, R. H.; Crow, W. T.; Koster, R. D.; Sharif, H. O.; Mahanama, S. P. P.

2008-01-01

294

Radar estimates of soil moisture over the Konza Prairie  

NASA Technical Reports Server (NTRS)

Radar-backscatter measurements were made to estimate soil moisture. The helicopter-mounted radar was flown along selected transects that coincided with soil-moisture measurements. The radar operated at microwave frequencies of 5.3 and 9.6 GHz and at selected incidence angles between 0 and 60 degrees. Vertical polarization was used for two days and horizontal polarization was used for three days. The scattering-coefficient data from different days were grouped by frequency and antenna angles and then related to soil moisture along the flight paths using linear regression. A measure of linearity for the regression ranged between 0.9 and 0.5. The larger coefficients were for X-band measurements made at large antenna-incidence angles, and the smaller coefficients were for C-band measurements made at incidences angles near vertical.

Gogineni, S.; Ampe, J.; Budihardjo, A.

1991-01-01

295

BOREAS HYD-6 Ground Gravimetric Soil Moisture Data  

NASA Technical Reports Server (NTRS)

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).

Carroll, Thomas; Knapp, David E. (Editor); Hall, Forrest G. (Editor); Peck, Eugene L.; Smith, David E. (Technical Monitor)

2000-01-01

296

Design of a global soil moisture initialization procedure for the simple biosphere model  

NASA Technical Reports Server (NTRS)

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.

Liston, G. E.; Sud, Y. C.; Walker, G. K.

1993-01-01

297

Sensitivity of Microwave Backscatter to Soil Moisture under Bare Soil Conditions  

NASA Astrophysics Data System (ADS)

Soil water content is one of the most important governing factors for evapotranspiration, infiltration, runoff, and recharge. Soil moisture information can be used for improving hydrologic models and understanding the effects of water stress on crops. NASA Soil Moisture Active Passive (SMAP) is a satellite-based mission that will use active and passive microwave sensors at L-band to provide soil moisture data every 2-3 days, globally. This project is in support of the pre-launch activities of the SMAP mission. The goal of this research is to understand the sensitivity of active measurements at L-band to soil moisture under bare soil conditions with varying surface roughness. Specific objectives are to evaluate the RADAR's sensitivity to soil moisture at different polarizations, azimuth angles, and roughness conditions using observations from a two-week period during the eleventh Microwave, Water and Energy Balance Experiment (MicroWEX-11). Every 15-minute observations of backscatter were conducted at HH,VV, HV, and VH polarizations, at 21 azimuth angles for smooth and a freshly ploughed field. We found that backscattering coefficients (?0) at co-pols (VV and HH) are more sensitive to soil moisture changes than those at cross-pol coefficients. In addition, ?0 at VV polarization are the most sensitive to changes in soil moisture. The backscatter had a strong azimuthal dependence for the rough surface, with highest sensitivity at angles perpendicular to the row direction.

Luke, A.; Liu, P.; De Roo, R. D.; Judge, J.

2012-12-01

298

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

NASA Technical Reports Server (NTRS)

The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.

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

1982-01-01

299

Influence of land use on soil moisture spatial-temporal variability and monitoring  

NASA Astrophysics Data System (ADS)

In this study, the influence of land use on soil moisture dynamics is investigated for monitoring purposes. To this end, 23 measurement campaigns were carried out during a period of 8 months at 5 sites located in central Italy, within a catchment of ?6 km2. The sites are characterized by different land uses: grassland, woodland (holm oak and hornbeam) olive grove and cropland. Soil moisture was measured with a portable Time Domain Reflectometer for a layer depth of 15 cm under the soil surface. The optimization of the monitoring scheme was addressed through a statistical and temporal stability analysis. Notwithstanding the significant differences in the land use, the temporal patterns of the field-mean soil moisture of the different sites were very similar while the spatial variability, expressed through the coefficient of variation, was found slightly higher (average value equal to 0.27) than that obtained from previous sampling campaigns on the same area but on sites characterized by a homogeneous soil use. The maximum number of required samples, to estimate the areal mean soil moisture within an accuracy of 2% vol/vol, was found ranging between 7 and 11 at the field scale and equal to 20 at the catchment scale. The temporal stability analysis allowed to identify the grassland site as the most representative of the catchment-mean soil moisture behavior (coefficient of determination, R2 = 0.96). Therefore, even though the heterogeneity of the land use increases the spatial variability (as expected), soil moisture exhibits a significant temporal stability and its large scale monitoring from few observations is still feasible.

Zucco, G.; Brocca, L.; Moramarco, T.; Morbidelli, R.

2014-08-01

300

Soil Moisture Response to a Changing Climate in Arctic Regions  

NASA Astrophysics Data System (ADS)

Soil moisture is the land surface hydrologic variable that most strongly affects land-atmosphere moisture and energy fluxes. In Arctic regions, these interactions are complicated by the role of permafrost. Especially in northern regions, soil moisture therefore is important not only as a hydrological storage component, also as a result of its strong influence on the hydrological cycle through controls on energy fluxes such as evaporative heat flux, phase change in thawing of permafrost, and effects on thermal conductivity. With projected increases in surface temperature and decreases in surface moisture levels that may be associated with global warming, it is likely that the active layer thickness will increase, leading to subtle but predictable ecosystem responses such as vegetation changes. Field measurements of soil moisture have been collected on the North Slope of Alaska, with emphasis upon establishing macro and micro-topographic influences. Sites were installed in the foothill regions and on the coastal plain of the Kuparuk River basin. Spatially distributed model simulations are being conducted across a range of scales. Preliminary results indicate macro-topographic gradients greatly impact the importance of lateral versus vertical fluxes. Micro-topographic differences affect the small spatial scale differences in soil moisture, but have less impact upon flux direction. Permafrost in arctic regions exerts a significant influence on soil moisture through controls on vegetation and drainage. In relatively flat areas where the frozen layer is near the surface, the soil moisture contents are usually quite high. These areas have relatively high evapotranspiration and sensible heat transfer, but quite low conductive heat transfers due to the insulative properties of thick organic soils. As in more temperate regions, watershed morphology exerts strong controls on hydrological processes; however unique to arctic watersheds are complications arising from the short-term active layer dynamics and longer-term permafrost dynamics. As the active layer becomes thicker throughout the summer, it has a greater capacity to store water, resulting in a time-varying basin response to storm events. As the season progresses, the stream recession rates increase as more hillslope water flows through the soil rather than as overland flow. Peak flows are also more attenuated as the active layer increases in thickness or as permafrost areal extent decreases.

Hinzman, L. D.; Kane, D. L.; Lettenmaier, D.; Yang, D.; Zhao, Y.

2002-12-01

301

Significance of soil surface moisture with respect to daily bare soil evaporation  

Microsoft Academic Search

The significance of the soil surface moisture (thetas) with respect to daily bare soil evaporation (Ed) is analyzed using data from numerical simulations. This was performed by running a mechanistic model of heat and water flows in the soil. The mechanistic model was calibrated and validated on three different soils with contrasted hydraulic properties. Results show that thetas does not

A. Chanzy; L. Bruckler

1993-01-01

302

Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate  

NASA Astrophysics Data System (ADS)

Soil moisture is one of the important variables in hydrological modelling, which is now possible to be measured with remote sensing. This study is an attempt to evaluate the Soil Moisture and Ocean Salinity (SMOS) satellite derived soil moisture for hydrological applications at a catchment scale. The Soil Moisture Deficit (SMD) derived from a Probability Distribution Model is used as a benchmark for all comparisons. Three approaches are used for the evaluation of SMOS soil moisture. The first approach is based on ROSETTA pedotransfer functions (PTFs), while second and the third are based on linear/non-linear and seasonal algorithms particularly for growing and non-growing seasons respectively. The field capacity and permanent wilting point estimated from the simulated Water Retention Curve (WRC) through ROSETTA are used for the transformation of SMOS data into SMD. The growing seasons used in this study belong to the months from March to November, while the non-growing seasons comprise of months from December to February. The highest performance is given by a combined growing and non-growing season algorithms with the Nash Sutcliffe Efficiencies (NSEs) of 0.75 and RMSE = 0.01 m3/m3 followed by the linear and non-linear algorithms (NSE = 0.40-0.42; RMSE = 0.02 m3/m3). The worst performance is revealed by the PTFs indicating that it should be used with caution for direct coarse scale SMOS applications (NSE = -24.98 to -40.23) and need more treatments regarding the spatial and depth wise mismatch. The overall analysis reveals that SMOS soil moisture is of reasonable quality in estimating Soil Moisture Deficit at a catchment level with a local adjustment algorithm combining growing and non-growing seasons.

Srivastava, Prashant K.; Han, Dawei; Rico Ramirez, Miguel A.; Islam, Tanvir

2013-08-01

303

The Effects of Landscape Heterogeneity on Brightness Temperature and Soil Moisture Retrieval  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable to describe energy-water budgets at land surface. Passive remote sensing has played a crucial role in monitoring soil moisture from space. However, due to technical constrains and gaps in scientific understanding, the goal of 4% soil moisture accuracy are not obtained yet. With the advancement of technology and integration of radar/radiometer measurements, some of the measurement errors can be reduced. Nevertheless, the scientific understanding of the effects of landscape heterogeneity and its error contribution to soil moisture retrieval is lacking. In this paper, we have performed a synthetic study using tau-omega model, to understand the effects of within pixel heterogeneity in terms of different land cover types. This work focuses on understanding the effects of land cover type such as fresh/saline, vegetation density and type, percentage of clay on accuracy of soil moisture retrieval. Heterogeneous pixels cannot be characterized through simple averaging of contributing parameters, as these parameters exhibit non-linear behavior. For example, the brightness temperature observed for total VWC < 4.5 kg/m2 of mixed pixel with different vegetation types is far less than the average brightness temperature observed for individual vegetation types summing to total VWC. Such analysis is extended to different landcover types, to better address the effects of heterogeneity on soil moisture retrieval. Thus an attempt to develop an effective averaging technique to address the effect of nonlinear behavior on brightness temperature is made. The technique is tested by determining soil moisture accuracy obtained using retrieval algorithm.

Neelam, M.; Mohanty, B.

2013-12-01

304

The Use of Multispectral Imagery to Detect Variations in Soil Moisture Associated Shallow Soil Slumps  

NASA Astrophysics Data System (ADS)

Spatial variations in soil moisture have previously been linked to the process of soil aging and can contribute to mass wasting in slopes rich in clay. We use remote sensing imagery to assess variation in soil moisture. Our investigation includes compacted clay soils of the levees along the Mississippi River maintained by the Mississippi Levee Board. Shallow soil slumps are associated with aging of levee soils composed of clay of high plasticity. Continued exposure to seasonal fluctuations in groundwater conditions has contributed to this aging process, causing the soils to become increasingly fissured and stiff. This aging process also alters the moisture retention characteristics of the soil, providing a property contrast that we identified using multispectral imagery. Airborne multispectral imagery was collected along sites with limited vegetation cover (almost bare soil) along with direct measurements of soil water content. Moderate correlations, with correlation coefficients ranging from -0.62 to -0.80, were found between soil moisture and both the red and infrared reflectance bands of the imagery. Strong correlations, with correlation coefficients of 0.88 and 0.90, were found between soil moisture and the imagery indices known as simple ratio and Normalized Difference Vegetation Index (NDVI). Spaceborne multispectral imagery (IKONOS) was used in more heavily vegetated sites to detect variations in moisture content using Tasseled Cap transformation and imagery classification algorithms. We use this algorithm to provide a map of relative moisture content across the levee surface. We demonstrate how detecting variations in soil moisture is useful in detecting shallow surficial slides using both airborne and spaceborne multispectral images along with image processing tools.

Kuszmaul, J. S.; Neuner, J. A.; Hossain, A. A.; Easson, G. L.

2004-05-01

305

Scatterometer-Derived Soil Moisture Calibrated for Soil Texture With a One-Dimensional WaterFlow Model  

Microsoft Academic Search

Current global satellite scatterometer-based soil moisture retrieval algorithms do not take soil characteristics into account. In this paper, the characteristic time length of the soil water index has been calibrated for ten sampling frequencies and for different soil conductivity associated with 12 soil texture classes. The calibration experiment was independently performed from satellite observations. The reference soil moisture data set

Remko de Lange; Rob Beck; Nick van de Giesen; Jan Friesen; Allard de Wit; Wolfgang Wagner

2008-01-01

306

Alberta Soil Moisture Analyses using CaLDAS  

NASA Astrophysics Data System (ADS)

In order to improve soil moisture analyses, used to initialize numerical prediction systems, Environment Canada has developed the new Canadian Land Data Assimilation System (CaLDAS). CaLDAS uses the Global Environment Multi-scale (GEM) off-line land surface model and has been configured to assimilate Soil Moisture Ocean Salinity (SMOS) L-band soil moisture brightness temperatures using an Ensemble Kalman Filter framework and the Community Microwave Emission Modelling Platform as the radiative transfer forward model. One of the biggest challenges so far has been to correct the systematic dry bias of the off-line land surface model in order to provide an accurate first guess in which to assimilate SMOS brightness temperatures. Using a network of soil moisture stations in Alberta [Alberta Agriculture and Rural Development] we have improved and validated parameterizations using the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme. Results will be presented for the off-line model both alone and with the assimilation of bias corrected SMOS brightness temperatures for the summers of 2010 and 2012.

Dyck, S.; Carrera, M. L.; Belair, S.; Abrahamowicz, M.; Husain, S.; Bilodeau, B.; Gauthier, N.

2012-12-01

307

[Investigation of polarization characteristics of soil surface with low vegetation cover and different soil moisture].  

PubMed

Compared with the spectral detection method, polarization detection could obtain more information of the target. For example, the polarization detection could be applied to interpret the refractive index and the surface roughness of the object, or retrieve the soil moisture, etc. Polarization detection provides a new approach to quantitative retrieval of soil moisture, and this is very important in agriculture, hydrology, meteorology and ecology. The polarization characteristics of soil surface with low vegetation cover,which is a example of mixed pixel in remote sensing, were researched with experiments, and the relationship between the polarization characteristics and soil moisture was also explored. The results showed that the polarization characteristics of soil surface with low vegetation cover are mainly determined by the area of bare soil, and are strongly relevant with the soil moisture. For the results of experiments in this paper, the IDOLP of soil surface with low vegetation cover increased with increasing soil moisture when the viewing angle of instrument was between 20 degree and 60 degree, while the incident angle of light source was fixed at 40 degree. This paper offered a new method to retrieve moisture content of soil with low vegetation cover. PMID:21284189

Zhang, Qiao; Sun, Xiao-bing; Hong, Jin

2010-11-01

308

Macrofauna assemblage composition and soil moisture interact to affect soil ecosystem functions  

NASA Astrophysics Data System (ADS)

Changing climatic conditions and habitat fragmentation are predicted to alter the soil moisture conditions of temperate forests. It is not well understood how the soil macrofauna community will respond to changes in soil moisture, and how changes to species diversity and community composition may affect ecosystem functions, such as litter decomposition and soil fluxes. Moreover, few studies have considered the interactions between the abiotic and biotic factors that regulate soil processes. Here we attempt to disentangle the interactive effects of two of the main factors that regulate soil processes at small scales - moisture and macrofauna assemblage composition. The response of assemblages of three common temperate soil invertebrates (Glomeris marginata Villers, Porcellio scaber Latreille and Philoscia muscorum Scopoli) to two contrasting soil moisture levels was examined in a series of laboratory mesocosm experiments. The contribution of the invertebrates to the leaf litter mass loss of two common temperate tree species of contrasting litter quality (easily decomposing Fraxinus excelsior L. and recalcitrant Quercus robur L.) and to soil CO2 fluxes were measured. Both moisture conditions and litter type influenced the functioning of the invertebrate assemblages, which was greater in high moisture conditions compared with low moisture conditions and on good quality vs. recalcitrant litter. In high moisture conditions, all macrofauna assemblages functioned at equal rates, whereas in low moisture conditions there were pronounced differences in litter mass loss among the assemblages. This indicates that species identity and assemblage composition are more important when moisture is limited. We suggest that complementarity between macrofauna species may mitigate the reduced functioning of some species, highlighting the importance of maintaining macrofauna species richness.

Collison, E. J.; Riutta, T.; Slade, E. M.

2013-02-01

309

Snow cover dynamics, soil moisture variability and vegetation ecology in high mountain catchments of central Norway  

Microsoft Academic Search

The influence of water balance on vegetation was investigated by measurements of snow cover dynamics and soil moisture variability within small high mountain catchments of central Norway. The challenge of this study is to explain vegetation patterns by means of a functional ecosystem analysis as a basis for regionalization approaches. Results of a process-oriented analysis of factors determining vegetation were

Jörg Löffler

2005-01-01

310

Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China  

NASA Astrophysics Data System (ADS)

Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, -0.08% and 0.27%, accounting for 7.26%, -3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land cover change on soil moisture alternation and promoting effective management of water resources.

Feng, Huihui; Liu, Yuanbo

2014-06-01

311

Multifrequency Measurements of the Effects of Soil Moisture, Soil Texture, And Surface Roughness  

Microsoft Academic Search

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4, 5, and 10.7 GHz, during July-September of 1981. Three bare fields with different surface roughnesses and soil textures were prepared for the experiment. Ground-truth acquisition of soil temperatures and moisture contents for 5 layers down to the depths

James R. Wang; Peggy E. O'Neill; Thomas J. Jackson; Edwin T. Engman

1983-01-01

312

Soil moisture applications of the heat capacity mapping mission  

NASA Technical Reports Server (NTRS)

Results are presented of ground, aircraft and satellite investigations conducted to evaluate the potential of the Heat Capacity Mapping Mission (HCMM) to monitor soil moisture and the depth of shallow ground water. The investigations were carried out over eastern South Dakota to evaluate the relation between directly measured soil temperatures and water content at various stages of canopy development, aircraft thermal scanner measurements of apparent canopy temperature and the reliability of actual HCMM data. The results demonstrate the possibility of evaluating soil moisture on the basis of HCMM apparent canopy temperature and day-night soil temperature difference measurements. Limitations on the use of thermal data posed by environmental factors which influence energy balance interactions, including phase transformations, wind patterns, topographic variations and atmospheric constituents are pointed out.

Heilman, J. L.; Moore, D. G.

1981-01-01

313

Moisture Controls on Trace Gas Fluxes in Semiarid Riparian Soils  

Microsoft Academic Search

Variability in seasonal soil moisture (SM) and temperature (T) can alter ecosystem\\/atmosphere exchange of the trace gases carbon di- oxide (CO2), nitrous oxide (N2O), and methane (CH4). This study re- ports the impact of year-round SM status on trace gas fluxes in three semiarid vegetation zones, mesquite (30 g organic C kg 21 soil), open\\/ forb (6 g organic C

Jean E. T. McLain; Dean A. Martens

2006-01-01

314

Soil moisture assessments for brown locust Locustana pardalina breeding potential using synthetic aperture radar  

NASA Astrophysics Data System (ADS)

Synthetic aperture radar (SAR) imagery was collected over a brown locust Locustana pardalina outbreak area to estimate soil moisture relevant to egg development. ERS-2/RadarSat overpasses and field studies enabled parameterization of surface roughness, volumetric soil moisture, soil texture, and vegetation cover. Data were analyzed both when the target area was assessed as nonvegetated and when treated as vegetated. For the former, using the integral equation model (IEM) and soil surface data combined with the sensitivity of the IEM to changes in surface roughness introduced an error of ˜±0.06 cm3 cm-3 in volumetric soil moisture. Comparison of the IEM modeling results with backscatter responses from the ERS-2/RadarSat imagery revealed errors as high as ±0.14 cm3 cm-3, mostly due to IEM calibration problems and the impact of vegetation. Two modified versions of the water cloud model (WCM) were parameterized, one based on measurements of vegetation moisture and the other on vegetation biomass. A sensitivity analysis of the resulting model revealed a positive relationship between increases in both vegetation biomass and vegetation moisture and the backscatter responses from the ERS-2 and RadarSat sensors. The WCM was able to explain up to 80% of the variability found when the IEM was used alone.

Crooks, William T. S.; Cheke, Robert A.

2014-01-01

315

Methodology for Predicting Near Surface Soil Moisture.  

National Technical Information Service (NTIS)

A comprehensive model of soil-water dynamics, a 'wetting front' model, was developed and tested. The model represents a variety of flow processes including infiltration, redistribution, drainage and evaporation. The accuracy of the model was tested by com...

G. M. Hornberger R. B. Clapp B. J. Cosby

1984-01-01

316

Assessment of SAR-retrieved soil moisture uncertainty induced by uncertainty on modeled soil surface roughness  

NASA Astrophysics Data System (ADS)

The Integral Equation Model (IEM) is frequently used to retrieve moisture content of bare soils from synthetic aperture radar (SAR) images. This physically-based backscatter model requires surface roughness parameters, generally obtained by in situ measurements, which unfortunately often result in inaccurately retrieved soil moisture contents. Furthermore, when the retrieved soil moisture contents need to be used in data assimilation applications, it is important to also assess the retrieval uncertainty. Therefore, in this paper a regression-based method is developed that allows for the parameterization of roughness and that provides an estimation of its uncertainty by means of a probability distribution. By further propagating this distribution through the inversion of the IEM, a probability distribution of soil moisture content is obtained. It was found that 70% of the thus obtained distributions are skewed and non-normal. Furthermore, it is shown that their interquartile range varies depending on soil moisture conditions. Comparison of soil moisture measurements with the retrieved median values of the soil moisture histograms results in a root mean square error (RMSE) of approximately 3.5 vol%.

De Keyser, E.; Vernieuwe, H.; Lievens, H.; Álvarez-Mozos, J.; De Baets, B.; Verhoest, N. E. C.

2012-08-01

317

Multi-scale analysis of the impact of increased spatial resolution of soil moisture and atmospheric water vapour on convective precipitation  

NASA Astrophysics Data System (ADS)

The distribution of water vapour in the planetary boundary layer (PBL) and its development over time is one of the most important factors affecting precipitation processes. Despite the dense radiosonde network deployed during the Convective and Orographically-induced Precipitation Study (COPS), the high spatial variability of the water vapour field was not well resolved with respect to the detection of the initiation of convection. The first part of this investigation focuses on the impact of an increased resolution of the thermodynamics and dynamics of the PBL on the detection of the initiation of convection. The high spatial resolution was obtained using the synergy effect of data from the networks of radiosondes, automatic weather stations, synoptic stations, and especially Global Positioning Systems (GPSs). A method is introduced to combine GPS and radiosonde data to obtain a higher resolution representation of atmospheric water vapour. The gained spatial resolution successfully improved the representations of the areas where deep convection likelihood was high. Location and timing of the initiation of convection were critically influenced by the structure of the humidity field in the boundary-layer. The availability of moisture for precipitation is controlled by a number of processes including land surface processes, the latter are strongly influenced by spatially variable fields of soil moisture (SM) and land use. Therefore, an improved representation of both fields in regional model systems can be expected to produce better agreement between modelled and measured surface energy fluxes, boundary layer structure and precipitation. SM is currently one of the least assessed quantities with almost no data from operational monitoring networks available. However, during COPS an innovative measurement approach using a very high number of different SM sensors was introduced. The network consisted of newly developed low-cost SM sensors installed at 43 stations. Each station was equipped with sensors at three different depth (5, 20 and 50cm) simultaneously measuring SM and soil temperature. Within the framework of this work, a strategy to study the effects of SM, evapotranspiration and water vapour in the PBL on convective precipitation is applied on different scales, from local to regional. The SM and atmospheric fields are compared to their related representation within the COSMO-CLM, high-resolution regional model applied in the climate mode. The optimized fields are used for initialization of the model runs to study the impact of surface and PBL processes on convective precipitation. The combination of dense observations with COSMO-CLM simulations permits a rigorous analysis of the water transfer process chain from SM and fluxes to convective initiation and precipitation. This work constitutes a central part of the overall COPS strategy by thorough analysis of the measurement and model data and aims to improve the QPF by better process representation in the regional model COSMO-CLM.

Khodayar, S.; Schaedler, G.; Kalthoff, N.

2010-09-01

318

Improving agricultural drought monitoring in West Africa using root zone soil moisture estimates derived from NDVI  

NASA Astrophysics Data System (ADS)

The Famine Early Warning Systems Network (FEWS NET) relies heavily on remotely sensed rainfall and vegetation data to monitor agricultural drought in Sub-Saharan Africa and other places around the world. Analysts use satellite rainfall to calculate rainy season statistics and force crop water accounting models that show how the magnitude and timing of rainfall might lead to above or below average harvest. The Normalized Difference Vegetation Index (NDVI) is also an important indicator of growing season progress and is given more weight over regions where, for example, lack of rain gauges increases error in satellite rainfall estimates. Currently, however, near-real time NDVI is not integrated into a modeling framework that informs growing season predictions. To meet this need for our drought monitoring system a land surface model (LSM) is a critical component. We are currently enhancing the FEWS NET monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System. Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following questions: What is the relationship between NDVI and in-situ soil moisture measurements over the West Africa Sahel? How can we use this relationship to improve modeled water and energy fluxes over the West Africa Sahel? We investigate soil moisture and NDVI cross-correlation in the time and frequency domain to develop a transfer function model to predict soil moisture from NDVI. This work compares sites in southwest Niger, Benin, Burkina Faso, and Mali to test the generality of the transfer function. For several sites with fallow and millet vegetation in the Wankama catchment in southwest Niger we developed a non-parametric frequency response model, using NDVI inputs and soil moisture outputs, that accurately estimates root zone soil moisture (40-70cm). We extend this analysis by developing a low order parametric transfer function that is appropriate for estimating soil moisture across the West Africa Sahel. Frequency domain analysis allows us to evaluate how phase shifts (lags) and gains (changes in amplitude) vary across sites depending on soil and vegetation characteristics (e.g. from Food and Agriculture Organization (FAO) soil and University of Maryland (UMD) vegetation parameter maps). We compare observed and NDVI estimated soil moisture to outputs from the LIS-Noah LSM to assess the potential for data assimilation and use of the NDVI estimated soil moisture for model validation at the regional scale.

McNally, A.; Funk, C. C.; Yatheendradas, S.; Michaelsen, J.; Cappelarere, B.; Peters-Lidard, C. D.; Verdin, J. P.

2012-12-01

319

Inter-Comparison of Retrieved and Modelled Soil Moisture and Coherency of Remotely Sensed Hydrology Data  

NASA Astrophysics Data System (ADS)

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 hydrological processes. In addition, a regional analysis was conducted over several large river basins, including a detailed analysis of the time-lagged correlations between the three datasets and the spatial propagation of observed signals. Results appear consistent with the knowledge of the hydrological processes governing the individual basins. References Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, and P. Arkin (2003), The Version 2 Global Precipita- tion Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present).J. Hydrometeor., 4,1147-1167. Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. and Scipa,l K. (2009) A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrol., 10, 623-643 Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T. (2011), The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675-1698 Kolassa, J., Aires, F., Polcher, J., Prigent, C., and Pereira, J. (2012), Soil moisture Retrieval from Multi-instrument Observations: Information Content Analysis and Retrieval Methodology (2012), J. Geophys. Res., Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.(2011), Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425-436. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews (2007), Global inundation dy- namics inferred from multiple satellite observations, 1993-2000, J. Geophys. Res., 112, D12107, doi:10.1029/2006JD007847.

Kolassa, Jana; Aires, Filipe

2013-04-01

320

Solar dimming and CO2 effects on soil moisture trends  

Microsoft Academic Search

Summer soil moisture increased significantly from 1958 to the mid 1990s in Ukraine and Russia. This trend cannot be explained by changes in precipitation and temperature alone. To investigate the possible contribution from solar dimming and upward CO2 trends, we conducted experiments with a sophisticated land surface model. We demonstrate, by imposing a downward trend in incoming shortwave radiation forcing

Alan Robock; Haibin Li

2006-01-01

321

A comparison of soil moisture sensors for space flight applications  

NASA Technical Reports Server (NTRS)

Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

Norikane, J. H.; Prenger, J. J.; Rouzan-Wheeldon, D. T.; Levine, H. G.

2005-01-01

322

Experiments of Soil Moisture Retrieval based on Extended Kalman Filter  

Microsoft Academic Search

This paper is intended to investigate the sensing of surface parameters by microwave radiometry. A extended Kalman filter(EKF) is developed to manage the nonlinear relationship between surface parameters and radiometric signatures. Its performance of retrieving plant water content (PWC) and soil moisture content (SMC) from brightness temperatures is examined by using both predictions from model simulations and measurements from field

Ruofei Zhong; Qin Li; Wenji Zhao

2009-01-01

323

Future Soil Moisture Satellite Missions and Research Needs  

Microsoft Academic Search

During the coming decade, launches of a number of satellite microwave sensors will provide new and unique opportunities for acquiring global information on the amount and distribution of surface soil moisture and its frozen\\/thawed state. This new information will provide potentially significant enhancements to the predictive capabilities of numerical weather and climate models as well as improved capabilities for monitoring

E. G. Njoku; T. J. Jackson; P. E. O'Neill

2001-01-01

324

Modeling soil moisture patterns in a microscale forest catchment  

Microsoft Academic Search

The study investigates the spatial variability of the soil moisture on the microscale forest Wüstebach (27 ha) basin. A fully-integrated surface-subsurface flow model is applied to the Wüstebach headwater catchment in Germany which is a tributary to the Erkensruhr river and has a catchment size of about 27 ha. The catchment which is part of the Eifel national park is

G. Sciuto; B. Diekkrüger; H. Bogena; U. Rosenbaum; D. Dwersteg

2010-01-01

325

Algorithms to Estimate Soil Moisture Storage from Microwave Measurements.  

National Technical Information Service (NTIS)

An algorithm was devised to estimate the amount of water stored in the top 21 cm of the soil profile from L-band emissivity. It is valid over a range of moisture contents from near-saturation to approximately the wilting point. The algorithm also has a fe...

B. J. Blanchard W. Bausch

1979-01-01

326

Toward Global Soil Moisture Estimation By Satellite Precipitation Radars  

NASA Astrophysics Data System (ADS)

A soil moisture estimation algorithm using Tropical Rainfall Measuring Mission (TRMM) / Precipitation Radar (PR) is developed to be applied at global scale. In our algorithm, the backscattering coefficients at land surface (denoted as 0) observed by PR is used. As 0 is attenuated by strong rainfall, the data observed during rainfall is not included in our calculation (the percentage if observation is done while it is raining is as small as 5 percent in global average). Soil moisture estimation algorithms by active microwave sensors have been proposed by other researches, though, they are mainly applied to Synthetic Aperture Radars (SAR). TRMM/PR has poor spatial resolution compared with SAR, but the observation frequency (temporal resolution) is as high as passive microwave sensors. On behalf of such high observation frequency, our algorithm can be applied at daily scale which is suitable to analyze soil mois- ture variation. Though TRMM/PR observes by different incident angles from 0 to 18 degree, our algorithm is basically designed for 0(12) (0 observed by 12 degree). Assuming that observed 0 is composed of s (the backscattering at bare soil) and v 0 0 (the backscattering at vegetation layer), it is shown that the sensitivity of 0 to soil moisture is higher by smaller incident angle and the sensitivity of 0 to vegetation cover ratio is lower when observed by 12 degree. If the temporal change of vegetation is not significant, 0 observed by among 3 to 18 degree is well correlated with 0(12). In such case, 0 is converted to 0(12) by linear regression to increase the number of sample per day. The algorithm is firstly applied to Oklahoma in central United States and validated using in-situ soil moisture data. In Oklahoma, the effect of vegetation growth is not significant, then the soil moisture estimates well correspond with in-situ data. Contrastedly, in the Sahel of Africa which shows strong seasonal vegetation cy- cle, 0 obseved by only around 12 degree can be employed, therefore our algorithm should be improved to give estimates almost every day. We are planning to produce 3-year soil moisutre data set (1998-2000, daily, 0.25 degree grids) and also hope to apply the algorithm to future satelite precipitation radars developed under Global Pre- cipitation Measurement (GPM) mission for global soil moisture estimation.

Seto, S.; Oki, T.; Musiake, K.

327

Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment.  

National Technical Information Service (NTIS)

Soil moisture is a critical variable for many Army activities including mobility assessments. Several methods can be used to produce soil moisture patterns at an intermediate resolution (grid cells with approximately 1 km linear dimension). However, mobil...

J. D. Niemann M. L. Coleman

2011-01-01

328

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data  

NASA Technical Reports Server (NTRS)

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.

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

329

The International Soil Moisture Network - A data hosting facility for in situ soil moisture measurements in support of SMOS cal/val  

NASA Astrophysics Data System (ADS)

In situ soil moisture observations are crucial for validating SMOS and other satellite based soil moisture products. In order to support valid conclusions about the accuracy of such products the in situ soil moisture observations used need to be available for many locations worldwide and have to be intercomparable. So far, the latter requirement is usually not met as the different locally and regionally operating networks apply neither a standard measurement technique nor a standard protocol. The need for international cooperation in constructing centralized and homogenized global soil moisture data sets has been recognized by the international community. To support the validation of satellite soil moisture products the International Soil Moisture Working Group (ISMWG) has suggested constructing a standardized global data base of in-situ soil moisture measurements. Further, the creation of multi-source soil moisture datasets, including in situ observations, was included in the GEO 2009-2011 Work Plan under sub-task WA-08-01a led by GEWEX (Global Energy and Water Cycle Experiment) and ESA (European Space Agency). As fruit of this initiative and in support of SMOS calibration and validation activities, ESA decided to support the development of the International Soil Moisture Network. The International Soil Moisture Network is a web based data hosting facility for collecting and redistributing in situ soil moisture measurements from existing soil moisture networks. Incoming data are carefully checked for their quality and homogenized before being stored in the database. A web interface allows the user to easily query and download the data. Special care has been taken to make downloads compliant with international data and metadata standards such as GEWEX CEOP, ISO 19115, and INPIRE of the European Commission. This presentation provides insight in the design considerations, implementation, functionalities and outputs of the data hosting facility. The International Soil Moisture Network can be accessed at: http://www.ipf.tuwien.ac.at/insitu

Dorigo, Wouter; Hahn, Sebastian; Hohensinn, Roland; Paulik, Christoph; Wagner, Wolfgang; Drusch, Matthias; van Oevelen, Peter

2010-05-01

330

Analysis of surface moisture variations within large field sites  

NASA Technical Reports Server (NTRS)

A statistical analysis was made on ground soils to define the general relationship and ranges of values of the field moisture relative to both the variance and coefficient of variation for a given test site and depth increment. The results of the variability study show that: (1) moisture variations within any given large field area are inherent and can either be controlled nor reduced; (2) neither a single value of the standard deviation nor coefficient of variation uniquely define the variability over the complete range of mean field moisture contents examined; and (3) using an upper bound standard deviation parameter clearly defines the maximum range of anticipated moisture variability. 87 percent of all large field moisture content standard deviations were less than 3 percent while about 96 percent of all the computed values had an upper bound of sigma=4 percent for these intensively sampled fields. The limit of accuracy curves of mean soil moisture measurements for large field sites relative to the required number of samples were determined.

Bell, K. R.; Blanchard, B. J.; Witczak, M. W.; Schmugge, T. J.

1979-01-01

331

Global Soil Moisture from Satellite Observations, Land Surface Models, and Ground Data: Implications for Data Assimilation  

Microsoft Academic Search

Three independent surface soil moisture datasets for the period 1979-87 are compared: 1) global retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), 2) global soil moisture derived from observed meteorological forcing using the NASA Catchment Land Surface Model, and 3) ground-based measurements in Eurasia and North America from the Global Soil Moisture Data Bank. Time-average soil moisture fields from the

Rolf H. Reichle; Randal D. Koster; Jiarui Dong; Aaron A. Berg

2004-01-01

332

Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.  

PubMed

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. PMID:24743980

Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören

2014-07-01

333

Modeling Soil Moisture in the Mojave Desert  

USGS Publications Warehouse

The Mojave Desert is an arid region of southeastern California and parts of Nevada, Arizona, and Utah; the desert occupies more than 25,000 square miles (fig. 1). Ranging from below sea level to over 5,000 feet (1,524 m) in elevation, the Mojave Desert is considered a ?high desert.? On the west and southwest it is bounded by the Sierra Nevada, the San Gabriel, and the San Bernardino Mountains. These imposing mountains intercept moisture traveling inland from the Pacific Ocean, producing arid conditions characterized by extreme fluctuations in daily temperatures, strong seasonal winds, and an average annual precipitation of less than six inches. The Mojave Desert lies farther south and at a lower elevation than the cooler Great Basin Desert and grades southward into the even lower and hotter Sonoran Desert.

Miller, David M.; Hughson, Debra; Schmidt, Kevin M.

2008-01-01

334

Cross evaluation of in-situ, synthetic and remotely sensed surface soil moisture in southwestern France  

Microsoft Academic Search

A long term data acquisition effort of profile soil moisture is currently underway at 12 automatic weather stations located in southwestern France. The SMOSMANIA profile soil moisture network has several objectives including: (i) the validation of the operational soil moisture products of Météo-France, produced by the hydrometeorological model SIM, (ii) the validation of new versions of the land surface model

Clement Albergel; Jean-Christophe Calvet; Eric Martin; Stefan Hasenauer; Naemi Vahid; Wolfgang Wagner; Patricia de Rosnay

2010-01-01

335

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data.  

National Technical Information Service (NTIS)

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-d...

A. Colliander E. Njoku J. C. Shi M. Cosh P. O'Neill R. Bindlish S. Chan T. Zhao T. J. Jackson Y. Kerr

2011-01-01

336

Dynamic soil moisture monitoring in shendong mining area using Temperature Vegetation Dryness Index  

Microsoft Academic Search

As a method to analyze the soil moisture, the NDVI-Ts space has aroused much attention. The paper uses the method of TVDI which calculated from the NDVI-Ts space to monitor the soil moisture status of Shendong mining area which is located in arid and semiarid area in Northwest China from 6 September to 8 November. The soil moisture status come

Ying Liu; Weiyu Ma; Hui Yue; Hu Zhao

2011-01-01

337

Validation of the ASAR Global Monitoring Mode Soil Moisture Product Using the NAFE'05 Data Set  

Microsoft Academic Search

The Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) mode offers an opportunity for global soil moisture (SM) monitoring at much finer spatial resolution than that provided by the currently operational Advanced Microwave Scanning Radiometer for the Earth Observing System and future planned missions such as Soil Moisture and Ocean Salinity and Soil Moisture Active Passive. Considering the difficulties in

Iliana Mladenova; Venkat Lakshmi; Jeffrey P. Walker; Rocco Panciera; Wolfgang Wagner; Marcela Doubkova

2010-01-01

338

Performance of soil moisture retrieval algorithms using multiangular L band brightness temperatures  

Microsoft Academic Search

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency was successfully launched in November 2009 to provide global surface soil moisture and sea surface salinity maps. The SMOS single payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS), an L band two-dimensional aperture synthesis interferometric radiometer with multiangular and polarimetric imaging capabilities. SMOS-derived soil moisture

M. Piles; A. Camps; M. Vall-llossera; A. Monerris; M. Talone; J. M. Sabater

2010-01-01

339

Probabilistic modelling of soil moisture dynamics of irrigated cropland in the North China Plain  

Microsoft Academic Search

A probabilistic soil moisture dynamic model is used to estimate the soil moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic

Xingyao Pan; Lu Zhang; Nicholas J. Potter; Jun Xia; Yongqiang Zhang

2011-01-01

340

Improvement of soil moisture prediction through AMSR-E data assimilation  

Microsoft Academic Search

This dissertation is aimed at evaluating the soil moisture estimation from satellites as well as land surface models and improving it using a data assimilation technique. The entire study was conducted over the Little River Experimental Watershed, Georgia for the year 2003; one of the four selected watersheds to validate the current AMSR-E satellite soil moisture data. Soil moisture data

Alok K. Sahoo

2008-01-01