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Sample records for soil moisture analysis

  1. Recent advances in (soil moisture) triple collocation analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To date, triple collocation (TC) analysis is one of the most important methods for the global scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method....

  2. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    PubMed

    Gaikwad, Pramod; Devendrachari, Mruthyunjayachari Chattanahalli; Thimmappa, Ravikumar; Paswan, Bhuneshwar; Raja Kottaichamy, Alagar; Makri Nimbegondi Kotresh, Harish; Thotiyl, Musthafa Ottakam

    2015-07-21

    Here we report the first potentiometric sensor for soil moisture analysis by bringing in the concept of Galvanic cells wherein the redox energies of Al and conducting polyaniline are exploited to design a battery type sensor. The sensor consists of only simple architectural components, and as such they are inexpensive and lightweight, making it suitable for on-site analysis. The sensing mechanism is proved to be identical to a battery type discharge reaction wherein polyaniline redox energy changes from the conducting to the nonconducting state with a resulting voltage shift in the presence of soil moisture. Unlike the state of the art soil moisture sensors, a signal derived from the proposed moisture sensor is probe size independent, as it is potentiometric in nature and, hence, can be fabricated in any shape or size and can provide a consistent output signal under the strong aberration conditions often encountered in soil moisture analysis. The sensor is regenerable by treating with 1 M HCl and can be used for multiple analysis with little read out hysteresis. Further, a portable sensor is fabricated which can provide warning signals to the end user when the moisture levels in the soil go below critically low levels, thereby functioning as a smart device. As the sensor is inexpensive, portable, and potentiometric, it opens up avenues for developing effective and energy efficient irrigation strategies, understanding the heat and water transfer at the atmosphere-land interface, understanding soil mechanics, forecasting the risk of natural calamities, and so on. PMID:26098202

  3. Long term analysis of PALS soil moisture campaign measurements for global soil moisture algorithm development

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An important component of satellite-based soil moisture algorithm development and validation is the comparison of coincident remote sensing and in situ observations that are typically provided by intensive field campaigns. The planned NASA Soil Moisture Active Passive (SMAP) mission has unique requi...

  4. Multivariate analysis of soil moisture and runoff dynamics for better understanding of catchment moisture state

    NASA Astrophysics Data System (ADS)

    Graeff, Thomas; Bronstert, Axel; Cunha Costa, Alexandre; Zehe, Erwin

    2010-05-01

    Soil moisture is a key state that controls runoff formation, infiltration and portioning of radiation into latent and sensible heat flux. The experimental characterisation of near surface soil moisture patterns and their controls on runoff formation is, however, still largely untapped. Using an intelligent sampling strategy of two TDR clusters installed in the head water of the Wilde Weißeritz catchment (Eastern Ore Mountains, Germany), we investigated how well "the catchment state" may be characterised by means of distributed soil moisture data observed at the field scale. A grassland site and a forested site both located on gentle slopes were instrumented with two Spatial TDR clusters (STDR) that consist of 39 and 32 coated TDR probes of 60 cm length. The interplay of soil moisture and runoff formation was interrogated using discharge data from three nested catchments: the Becherbach with a size of 2 km², the Rehefeld catchment (17 km²) and the superordinate Ammelsdorf catchment (49 km²). Multiple regression analysis and information theory including observations of groundwater levels, soil moisture and rainfall intensity were employed to predict stream flow. On the small scale we found a strong correlation between the average soil moisture and the runoff coefficients of rainfall-runoff events, which almost explains as much variability as the pre-event runoff. There was, furthermore, a strong correlation between surface soil moisture and subsurface wetness. With increasing catchment size, the explanatory power of soil moisture reduced, but it was still in a good accordance to the former results. Combining those results with a recession analysis of soil moisture and discharge we derived a first conceptual model of the dominant runoff mechanisms operating in these catchments, namely subsurface flow, but also by groundwater. The multivariate analysis indicated that the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore the soil moisture control on runoff generation and can be an important link between the scales. Long term monitoring of such sites could yield valuable information for flood warning and forecasting by identifying critical soil moisture conditions for the former and a better representation of the initial moisture conditions for the further.

  5. Rank Stability Analysis of Surface and Profile Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Although several studies have examined the spatial and rank stability of soil moisture at the surface layer (0-5cm) with the purpose of estimating large scale mean soil moisture, the integration of the rank stability of profile (0-60cm) soil moisture has not been fully considered. This research comb...

  6. Recent advances in (soil moisture) triple collocation analysis

    NASA Astrophysics Data System (ADS)

    Gruber, A.; Su, C.-H.; Zwieback, S.; Crow, W.; Dorigo, W.; Wagner, W.

    2016-03-01

    To date, triple collocation (TC) analysis is one of the most important methods for the global-scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method. Different notations that are used to formulate the TC problem are shown to be mathematically identical. While many studies have investigated issues related to possible violations of the underlying assumptions, only few TC modifications have been proposed to mitigate the impact of these violations. Moreover, assumptions, which are often understood as a limitation that is unique to TC analysis are shown to be common also to other conventional performance metrics. Noteworthy advances in TC analysis have been made in the way error estimates are being presented by moving from the investigation of absolute error variance estimates to the investigation of signal-to-noise ratio (SNR) metrics. Here we review existing error presentations and propose the combined investigation of the SNR (expressed in logarithmic units), the unscaled error variances, and the soil moisture sensitivities of the data sets as an optimal strategy for the evaluation of remotely-sensed soil moisture data sets.

  7. Microwave soil moisture measurements and analysis

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

    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.

  8. Soil Moisture Project Evaluation Workshop

    NASA Technical Reports Server (NTRS)

    Gilbert, R. H. (Editor)

    1980-01-01

    Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2013-04-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2012-12-01

    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.

  11. Analysis of soil moisture probability in a tree cropped watershed

    NASA Astrophysics Data System (ADS)

    Espejo-Perez, Antonio Jesus; Giraldez Cervera, Juan Vicente; Pedrera, Aura; Vanderlinden, Karl

    2015-04-01

    Probability density functions (pdfs) of soil moisture were estimated for an experimental watershed in Southern Spain, cropped with olive trees. Measurements were made using a capacitance sensors network from June 2011 until May 2013. The network consisted of 22 profiles of sensors, installed close to the tree trunk under the canopy and in the adjacent inter-row area, at 11 locations across the watershed to assess the influence of rain interception and root-water uptake on the soil moisture distribution. A bimodal pdf described the moisture dynamics at the 11 sites, both under and in-between the trees. Each mode represented the moisture status during either the dry or the wet period of the year. The observed histograms could be decomposed into a Lognormal pdf for dry period and a Gaussian pdf for the wet period. The pdfs showed a larger variation among the different locations at inter-row positions, as compared to under the canopy, reflecting the strict control of the vegetation on soil moisture. At both positions this variability was smaller during the wet season than during the dry period.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

  13. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using historical satellite surface soil moisture products, the 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 ground observations. In order to adapt...

  14. Remote soil moisture measurements

    NASA Technical Reports Server (NTRS)

    Stockhoff, E. H.; Frost, R. T.; Buerger, E. J.

    1973-01-01

    The degree of polarization of visible sunlight reflected from bare soils in agricultural test areas in the southwestern United States was measured by an airborne photopolarimeter. Surface soil specimens provided data concerning the surface moisture of the soil to which the polarization data were compared. The results indicate the feasibility of measuring soil surface moisture by airborne polarimeter instrumentation.

  15. Analysis of large scale spatial variability of soil moisture using a geostatistical method.

    PubMed

    Lakhankar, Tarendra; Jones, Andrew S; Combs, Cynthia L; Sengupta, Manajit; Vonder Haar, Thomas H; Khanbilvardi, Reza

    2010-01-01

    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 estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations. PMID:22315576

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

    PubMed Central

    Lakhankar, Tarendra; Jones, Andrew S.; Combs, Cynthia L.; Sengupta, Manajit; Vonder Haar, Thomas H.; Khanbilvardi, Reza

    2010-01-01

    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 estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations. PMID:22315576

  17. Understanding Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding soil moisture is critical for landscape irrigation management. This landscaep irrigation seminar will compare volumetric and matric potential soil-moisture sensors, discuss the relationship between their readings and demonstrate how to use these data. Soil water sensors attempt to sens...

  18. Spatio-temporal soil moisture patterns - A meta-analysis using plot to catchment scale data

    NASA Astrophysics Data System (ADS)

    Korres, W.; Reichenau, T. G.; Fiener, P.; Koyama, C. N.; Bogena, H. R.; Cornelissen, T.; Baatz, R.; Herbst, M.; Diekkrüger, B.; Vereecken, H.; Schneider, K.

    2015-01-01

    Soil moisture is a key variable in hydrology, meteorology and agriculture. It is influenced by many factors, such as topography, soil properties, vegetation type, management, and meteorological conditions. The role of these factors in controlling the spatial patterns and temporal dynamics is often not well known. The aim of the current study is to analyze spatio-temporal soil moisture patterns acquired across a variety of land use types, on different spatial scales (plot to meso-scale catchment) and with different methods (point measurements, remote sensing, and modeling). We apply a uniform set of tools to determine method specific effects, as well as site and scale specific controlling factors. Spatial patterns of soil moisture and their temporal development were analyzed using nine different datasets from the Rur catchment in Western Germany. For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture. For a forest sub-catchment compared to cropped areas, the offset of this relationship was larger, with generally larger variability at similar mean soil moisture values. Using a geostatistical analysis of the soil moisture patterns we identified three groups of datasets with similar values for sill and range of the theoretical variogram: (i) modeled and measured datasets from the forest sub-catchment (patterns mainly influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the Rur catchment (patterns mainly influenced by the land-use structure of the cropped area), and (iii) modeled datasets from the cropped part of the Rur catchment (patterns mainly influenced by large scale variability of soil properties). A fractal analysis revealed that all analyzed soil moisture patterns showed a multifractal behavior, with at least one scale break and generally high fractal dimensions. Corresponding scale breaks were found between different datasets. The factors causing these scale breaks are consistent with the findings of the geostatistical analysis. Furthermore, the joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at the upper and lower bounds of soil moisture (at maximum porosity and wilting point of the soils) can have a large influence on the soil moisture patterns and their autocorrelation structure. Depending on the prevalent type of land use and the time of year, vegetation causes a decrease or an increase of spatial variability in the soil moisture pattern.

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

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

    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.

  20. Soil moisture modeling review

    NASA Technical Reports Server (NTRS)

    Hildreth, W. W.

    1978-01-01

    A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.

  1. Analysis of the linearised observation operator in a soil moisture and temperature analysis scheme

    NASA Astrophysics Data System (ADS)

    Dharssi, I.; Candy, B.; Steinle, P.

    2015-06-01

    Several weather forecasting agencies have developed advanced land data assimilation systems that, in principle, can analyse any model land variable. Such systems can make use of a wide variety of observation types, such as screen level (2 m above the surface) observations and satellite based measurements of surface soil moisture and skin temperature. Indirect measurements can be used and information propagated from the surface into the deeper soil layers. A key component of the system is the calculation of the linearised observation operator matrix (Jacobian matrix) which describes the link between the observations and the land surface model variables. The elements of the Jacobian matrix (Jacobians) are estimated using finite difference by performing short model forecasts with perturbed initial conditions. The calculated Jacobians show that there can be strong coupling between the screen level and the soil. The coupling between the screen level and surface soil moisture is found to be due to a number of processes including bare soil evaporation, soil thermal conductivity as well as transpiration by plants. Therefore, there is significant coupling both during the day and at night. The coupling between the screen level and root-zone soil moisture is primarily through transpiration by plants. Therefore the coupling is only significant during the day and the vertical variation of the coupling is modulated by the vegetation root depths. The calculated Jacobians that link screen level temperature to model soil temperature are found to be largest for the topmost model soil layer and become very small for the lower soil layers. These values are largest during the night and generally positive in value. It is found that the Jacobians that link observations of surface soil moisture to model soil moisture are strongly affected by the soil hydraulic conductivity. Generally, for the Joint UK Land Environment Simulator (JULES) land surface model, the coupling between the surface and root zone soil moisture is weak. Finally, the Jacobians linking observations of skin temperature to model soil temperature and moisture are calculated. These Jacobians are found to have a similar spatial pattern to the Jacobians for observations of screen level temperature. Analysis is also performed of the sensitivity of the calculated Jacobians to the magnitude of the perturbations used.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Correcting rainfall using satellite-based surfae soil moisture retrievals: The soil moisture analysis rainfall tool(SMART)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work in 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 incorpor...

  5. Soil Moisture Workshop

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

    The Soil Moisture Workshop was held at the United States Department of Agriculture National Agricultural Library in Beltsville, Maryland on January 17-19, 1978. The objectives of the Workshop were to evaluate the state of the art of remote sensing of soil moisture; examine the needs of potential users; and make recommendations concerning the future of soil moisture research and development. To accomplish these objectives, small working groups were organized in advance of the Workshop to prepare position papers. These papers served as the basis for this report.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Gruber, A.; Su, C.-H.; Crow, W. T.; Zwieback, S.; Dorigo, W. A.; Wagner, W.

    2016-02-01

    Global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multisource soil moisture retrievals into a unified data set. However, this requires an appropriate parameterization of the error structures of the underlying data sets. While triple collocation (TC) analysis has been widely recognized as a powerful tool for estimating random error variances of coarse-resolution soil moisture data sets, the estimation of error cross covariances remains an unresolved challenge. Here we propose a method—referred to as extended collocation (EC) analysis—for estimating error cross-correlations by generalizing the TC method to an arbitrary number of data sets and relaxing the therein made assumption of zero error cross-correlation for certain data set combinations. A synthetic experiment shows that EC analysis is able to reliably recover true error cross-correlation levels. Applied to real soil moisture retrievals from Advanced Microwave Scanning Radiometer-EOS (AMSR-E) C-band and X-band observations together with advanced scatterometer (ASCAT) retrievals, modeled data from Global Land Data Assimilation System (GLDAS)-Noah and in situ measurements drawn from the International Soil Moisture Network, EC yields reasonable and strong nonzero error cross-correlations between the two AMSR-E products. Against expectation, nonzero error cross-correlations are also found between ASCAT and AMSR-E. We conclude that the proposed EC method represents an important step toward a fully parameterized error covariance matrix for coarse-resolution soil moisture data sets, which is vital for any rigorous data assimilation framework or data merging scheme.

  8. Evapotranspiration Controls Imposed by Soil Moisture: A Spatial Analysis across the United States

    NASA Astrophysics Data System (ADS)

    Rigden, A. J.; Tuttle, S. E.; Salvucci, G.

    2014-12-01

    We spatially analyze the control over evapotranspiration (ET) imposed by soil moisture across the United States using daily estimates of satellite-derived soil moisture and data-driven ET over a nine-year period (June 2002-June 2011) at 305 locations. The soil moisture data are developed using 0.25-degree resolution satellite observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), where the 9-year time series for each 0.25-degree pixel was selected from three potential algorithms (VUA-NASA, U. Montana, & NASA) based on the maximum mutual information between soil moisture and precipitation (Tuttle & Salvucci (2014), Remote Sens Environ, 114: 207-222). The ET data are developed independent of soil moisture using an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased ET rates, suggesting that land-atmosphere feedback processes minimize this variance (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from meteorological data measured at 305 common weather stations that are approximately uniformly distributed across the United States. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture. We fit evaporation efficiency curves across the United States at each of the 305 sites during the summertime (May-June-July-August-September). Spatial patterns are visualized by mapping optimal curve fitting coefficients across the Unites States. An analysis of efficiency curves and their spatial patterns will be presented.

  9. The Soil Moisture Analysis Rainfall Tool (SMART): Correcting satellite-based precipitation using land data assimilation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Despite the obvious physical connection between surface soil moisture conditions and antecedent rainfall, relatively little attention has been paid to date on integrating surface water balance information obtained from both spaceborne surface soil moisture and precipitation retrievals. Recently, Cr...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

  11. Observed soil moisture-atmosphere interactions in the contiguous US from the Soil Climate Analysis Network (SCAN)

    NASA Astrophysics Data System (ADS)

    Xu, R.; Sheffield, J.

    2013-12-01

    The interactions of water and energy between the land and atmosphere are important in many aspects such as understanding the role of the land in weather and climate, improving seasonal forecasts, and evaluating climate models and their projections. Past studies on land-atmosphere interactions over large regions have generally been carried out with reanalysis, satellite remote sensing and model data. This study focuses on observational data from the Soil Climate Analysis Network (SCAN) to investigate the coupling of air temperature, precipitation and soil moisture at different time scales across the contiguous United States. SCAN data from over 80 sites across the U.S. with data between 2002 and 2012 are quality controlled to remove measurement errors and spurious values. Two main hypotheses regarding land-atmosphere interactions are explored: 1) precipitation is the main driver of soil moisture variation with the strength of coupling dependent on location, soil depth and time scale; 2) lack of soil moisture is related to high temperatures through sensible heating with relationships also dependent on location and scale. The statistical correlation between precipitation and soil moisture at daily, sub-monthly, and monthly scales is examined, and a positive relationship is prominent. Daily and monthly air temperature and soil moisture observations suggest that a control of air temperature by soil moisture exists. Further analysis shows significant negative relationships between the number of hot days (NHD) in summer months and soil moisture. The extent of this relationship (quantified by the slope of linear regression) varies across the U.S., with stronger relationships moving from the humid east to the drier central U.S.. In order to differentiate the sources of temperature changes between local coupling and advection, temperature advection is estimated using data from the North American Land Data Assimilation System-2 (NLDAS-2). The results suggest that local feedbacks may account for up to about 50% of local temperature changes in dry periods. This study shows that coupling between the land and atmosphere can be seen in observations, and regions of strongest coupling between soil moisture and temperature extremes tend to occur in the drier central U.S..

  12. Soil Moisture Memory in Climate Models

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

  13. Analysis of Satellite Retreived Active-Passive Merged Soil Moisture Distribution: A Case Study Over India.

    NASA Astrophysics Data System (ADS)

    Chakravorty, A.; Chahar, B. R.; Sharma, O. P.; Dhanya, C. T.

    2014-12-01

    Soil moisture is the source of water for evapotranspiration over the continents and it participates in both energy and water balance of the earth. Soil moisture participates in the energy cycle by managing the partitioning of the energy budget into latent and sensible heat, there by influencing the hydrological cycle. But to better understand the influence of soil moisture on the hydrological cycle, large scale monitoring is required. The objective of this study is to qualitatively analyze the active-passive merged soil moisture distribution, prepared under the ESA_CCI programme, against two AMSR-E soil moisture distributions, AMSR-E/NSIDC (National Snow and Ice Data Center) and AMSR-E/VUA(Virje Universiet Amstradam) and GLDAS_NOAH model simulations. The ESA_CCI soil moisture distribution is also compared with the GPCC monthly precipitation distribution to observe the representativeness of the precipitation seasonality in the satellite retrieved soil moisture. India has been selected as the study area, esp. the Central Indian region, as it has shown to be a soil moisture hot-spot for land-surface atmosphere interaction. The preliminary study show that both ESA_CCI and AMSR-E/VUA soil moisture distributions capture similar seasonal patterns in addition to processes like rainfall events and inter-annual variations. In addition to this it was also observed that the soil moisture distribution of ESA_CCI and AMSR-E/VUA are linearly related to each other for more than 50% of the land points. In case of ESA_CCI and AMSR-E/NSIDC, the soil moisture distributions are able to capture similar seasonal patterns but not the random events and they also do not show a strong linear relationship. We also analyze the effect of topography and vegetation distribution on the error charactristics of the satellite retrieved soil moisture distributions.

  14. Evaluation of assumptions in soil moisture triple collocation analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually-independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and ort...

  15. Monte Carlo Analysis of the Commissioning Phase Maneuvers of the Soil Moisture Active Passive (SMAP) Mission

    NASA Technical Reports Server (NTRS)

    Williams, Jessica L.; Bhat, Ramachandra S.; You, Tung-Han

    2012-01-01

    The Soil Moisture Active Passive (SMAP) mission will perform soil moisture content and freeze/thaw state observations from a low-Earth orbit. The observatory is scheduled to launch in October 2014 and will perform observations from a near-polar, frozen, and sun-synchronous Science Orbit for a 3-year data collection mission. At launch, the observatory is delivered to an Injection Orbit that is biased below the Science Orbit; the spacecraft will maneuver to the Science Orbit during the mission Commissioning Phase. The delta V needed to maneuver from the Injection Orbit to the Science Orbit is computed statistically via a Monte Carlo simulation; the 99th percentile delta V (delta V99) is carried as a line item in the mission delta V budget. This paper details the simulation and analysis performed to compute this figure and the delta V99 computed per current mission parameters.

  16. In-situ soil composition and moisture measurement by surface neutron activation analysis

    NASA Astrophysics Data System (ADS)

    Waring, C.; Smith, C.; Marks, A.

    2009-04-01

    Neutron activation analysis is widely known as a laboratory technique dependent upon a nuclear reactor to provide the neutron flux and capable of precise elemental analysis. Less well known in-situ geochemical analysis is possible with isotopic (252Cf & 241Am) or compact accelerator (D-T, D-D fusion reaction) neutron sources. Prompt gamma neutron activation analysis (PGNAA) geophysical borehole logging has been applied to mining issues for >15 years (CSIRO) using isotopic neutron sources and more recently to environmental and hydro-geological applications by ANSTO. Similarly, sophisticated geophysical borehole logging equipment based on inelastic neutron scattering (INS) has been applied in the oil and gas industry by large oilfield services companies to measure oil saturation indices (carbon/oxygen) using accelerator neutron sources. Recent advances in scintillation detector spectral performance has enabled improved precision and detection limits for elements likely to be present in soil profiles (H, Si, Al, Fe, Cl) and possible detection of many minor to trace elements if sufficiently abundant (Na, K, Mg, Ca, S, N, + ). To measure carbon an accelerator neutron source is required to provide fast neutrons above 4.8 MeV. CSIRO and ANSTO propose building a soil geochemical analysis system based on experience gained from building and applying PGNA borehole logging equipment. A soil geochemical analysis system could effectively map the 2D geochemical composition of the top 50cm of soil by dragging the 1D logging equipment across the ground surface. Substituting an isotopic neutron source for a D-T accelerator neutron source would enable the additional measurement of elemental carbon. Many potential ambiguities with other geophysical proxies for soil moisture may be resolved by direct geochemical measurement of H. Many other applications may be possible including time series in-situ measurements of soil moisture for differential drainage, hydrology, land surface parameter models, fertiliser distribution, leaching and mobility characteristics and measuring carbon sequestration or loss from different land use practices.

  17. Error characterization of microwave satellite soil moisture data sets using fourier analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over meso to global scales used as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these processes. ...

  18. Error characterization of microwave satellite soil moisture data sets using fourier analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...

  19. Assessing representative soil moisture at watershed scale of Maqu catchment using spatio-temporal statistical analysis

    NASA Astrophysics Data System (ADS)

    Bhatti, H. A.; Rientjes, T. H. M.; Verhoef, W.

    2012-04-01

    In this study the temporal stability concept by Vachaud et al. (1985) is selected to evaluate a soil moisture measuring network in the Maqu catchment (3200 km2) in the north eastern part of the Tibetan plateau. The network serves for validation of coarse scale (25-50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. Besides identifying the Representative Mean Soil Moisture (RMSM) station for each respective probe depth, we applied the concept to a time series of satellite based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E) to evaluate if a RMSM pixel can be identified from the pixels that overlay the catchment. Analysis in this study serve to evaluate how well the satellite based moisture estimates match to observation at the RMSM stations for respective depths. We aim to evaluate if the RMSM can be estimated by the satellite product so to broaden the procedure to validate satellite images. We used moisture data for the year 2009 for which data is available at 15 minutes interval using ECH2O EC-TM probes. For each probe depth a Mean Relative Difference (MRD) plot is created to identify stations that are characterized by mean, wet and dry moisture conditions. The spearman non-parametric test and pearson's correlation coefficient test are used to analyze the temporal persistence of the ranks of the measuring stations. The analysis is applied to each probe depth to evaluate the effect of the measuring depth on determining the catchment RMSM. Similar analysis is carried out on the satellite soil moisture observations that cover a full hydrological year to identify a RMSM pixel. The result of the analysis on the network showed that the station that indicates RMSM changes for each probe depth and thus a single station that indicates the catchment RMSM cannot be identified. Results on identifying a RMSM pixel shows that such pixel can be identified, however in our case, a station is not available in the pixel footprint area to evaluate if a RMSM station coincides with the RMSM pixel. Therefore, the network may require optimization to represent catchment average moisture conditions. So to evaluate how well station based RMSM is represented by a satellite time series, we inter-compared the time series of the RMSM station at respective probe depths to the time series of the single pixels that overlay the station. We calculated the Root Mean Square Error and Bias for all probe depth and results indicate that satellite observations best match to observations indicating RMSM for probes installed at 20 cm depth. The study also showed that for selecting the RMSM station in the Maqu catchment a minimum observation period should cover an annual cycle with clear dry and wet seasons.

  20. Soil-moisture ground truth, Hand County, South Dakota

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

    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.

  1. Remote estimation of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

    Two methods under consideration for making remote estimates of soil moisture involve measurements made in electromagnetic spectral region of 0.4 to 14.0 micrometers: (1) spectral reflectance, (2) soil temperature.

  2. Geostatistical analysis of soil moisture distribution in a part of Solani River catchment

    NASA Astrophysics Data System (ADS)

    Kumar, Kamal; Arora, M. K.; Hariprasad, K. S.

    2016-03-01

    The aim of this paper is to estimate soil moisture at spatial level by applying geostatistical techniques on the point observations of soil moisture in parts of Solani River catchment in Haridwar district of India. Undisturbed soil samples were collected at 69 locations with soil core sampler at a depth of 0-10 cm from the soil surface. Out of these, discrete soil moisture observations at 49 locations were used to generate a spatial soil moisture distribution map of the region. Two geostatistical techniques, namely, moving average and kriging, were adopted. Root mean square error (RMSE) between observed and estimated soil moisture at remaining 20 locations was determined to assess the accuracy of the estimated soil moisture. Both techniques resulted in low RMSE at small limiting distance, which increased with the increase in the limiting distance. The root mean square error varied from 7.42 to 9.77 in moving average method, while in case of kriging it varied from 7.33 to 9.99 indicating similar performance of the two techniques.

  3. Soil moisture: Some fundamentals. [agriculture - soil mechanics

    NASA Technical Reports Server (NTRS)

    Milstead, B. W.

    1975-01-01

    A brief tutorial on soil moisture, as it applies to agriculture, is presented. Information was taken from books and papers considered freshman college level material, and is an attempt to briefly present the basic concept of soil moisture and a minimal understanding of how water interacts with soil.

  4. Assimilation of SMOS brightness temperatures in the ECMWF EKF for the analysis of soil moisture

    NASA Astrophysics Data System (ADS)

    Munoz-Sabater, Joaquin

    2012-07-01

    Since November 2nd 2009, the European Centre for Medium-Range Weather Forecasts (ECMWF) has being monitoring, in Near Real Time (NRT), L-band brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA). The main objective of the monitoring suite for SMOS data is to systematically monitor the difference between SMOS observed brightness temperatures and the corresponding model equivalent simulated by the Community Microwave Emission Model (CMEM), the so-called first guess departures. This is a crucial step, as first guess departures is the quantity used in the analysis. The ultimate goal is to investigate how the assimilation of SMOS brightness temperatures over land improves the weather forecast skill, through a more accurate initialization of the global soil moisture state. In this presentation, some significant results from the activities preparing for the assimilation of SMOS data are shown. Among these activities, an effective data thinning strategy, a practical approach to reduce noise from the observed brightness temperatures and a bias correction scheme are of special interest. Firstly, SMOS data needs to be significantly thinned as the data volume delivered for a single orbit is too large for the current operational capabilities in any Numerical Weather Prediction system. Different thinning strategies have been analysed and tested. The most suitable one is the assimilation of SMOS brightness temperatures which match the ECMWF T511 (~40 km) reduced Gaussian Grid. Secondly, SMOS observational noise is reduced significantly by averaging the data in angular bins. In addition, this methodology contributes to further thinning of the SMOS data before the analysis. Finally, a bias correction scheme based on a CDF matching is applied to the observations to ensure an unbiased dataset ready for assimilation in the ECMWF surface analysis system. The current ECMWF operational soil moisture analysis system is based on a point-wise Extended Kalman Filter (EKF). This system assimilates proxy surface observations, i.e., 2 m air temperature and relative humidity to analyse the soil moisture state. Recent developments have also made it possible to assimilate remote sensing data coming from active and passive instruments. In particular, the ECMWF EKF can also assimilate data from the Advanced Scatterometer (ASCAT) onboard METOP-A and, more recently, from SMOS brightness temperatures observations. The first preliminary assimilation results will be shown. The analysis fields will be evaluated through comparison to in-situ data from different regions.

  5. Analysis of soil moisture extraction algorithm using data from aircraft experiments

    NASA Technical Reports Server (NTRS)

    Burke, H. H. K.; Ho, J. H.

    1981-01-01

    A soil moisture extraction algorithm is developed using a statistical parameter inversion method. Data sets from two aircraft experiments are utilized for the test. Multifrequency microwave radiometric data surface temperature, and soil moisture information are contained in the data sets. The surface and near surface ( or = 5 cm) soil moisture content can be extracted with accuracy of approximately 5% to 6% for bare fields and fields with grass cover by using L, C, and X band radiometer data. This technique is used for handling large amounts of remote sensing data from space.

  6. Estimating soil properties from microwave measurements of soil moisture

    NASA Astrophysics Data System (ADS)

    Mattikalli, Nandish M.; Engman, Edwin T.; Ahuja, Laj; Jackson, Thomas J.

    1995-11-01

    This paper demonstrates that the soil physical properties can be estimated using temporal variation of surface soil moisture derived from remote sensing. Passive microwave remote sensing was employed to collect daily soil moisture data across the Little Washita watershed, Oklahoma, for the period between June 10-18, 1992. The ESTAR instrument operating at L band was flown on a NASA C-130 aircraft. Brightness temperature data collected at a ground resolution of 200 m were used to derive the spatial distribution of surface soil moisture. Analysis of temporal soil moisture information and soils data reveals a direct relationship between changes in soil moisture and soil texture. Areas identified by loam/silt loam soils are characterized by higher changes of total soil moisture and those of sand/sandy loam by remarkably lower amounts. Analysis suggests that two-day initial drainage of soil, measured from remote sensing, is related to saturated hydraulic conductivity (Ksat). A methodology has been developed to employ remotely sensed data for estimation of profile Ksat using a hydrologic model and a GIS. Model simulations have yielded good correlations between soil moisture change and Ksat. The results have potential applications to obtain quick estimates of spatial distributions of soil properties over large area for input to mesoscale hydrologic and global circulation models.

  7. Comparative analysis of surface soil moisture retrieval using VSWI and TVDI in karst areas

    NASA Astrophysics Data System (ADS)

    Yan, Hongbo; Zhou, Guoqing; Lu, Xianjian

    2015-12-01

    Vegetation Supply Water Index (VSWI) and Temperature Vegetation dryness Index (TVDI) are two most commonly used methods for surface soil moisture (SSM) retrieval using electromagnetic spectrum of visible, near infrared and thermal infrared band. Both of them take into account the effect of vegetation index (VI) and surface temperature (Ts) on SSM. A comparative analysis of the ability and effect of the two methods for SSM retrieval in karst areas was carried out, using the remote sensing data of Landsat 8 OLI_TIRS. The study area is located in Guilin, which is a typical karst area. The experimental results show that TVDI is more suitable for SSM retrieval in karst areas.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

    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.

  9. SMALT - Soil Moisture from Altimetry

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. DREAMS have been created over a number of arid and semi-arid deserts worldwide to produce historical SMALT timeseries over soil moisture variation. These products are available in two formats - a high resolution track product which utilises the altimeter's high frequency content alongtrack and a multi-looked 6" gridded product at facilitate easy comparison/integeration with other remote sensing techniques. An overview of the SMALT processing scheme, covering the progression of the data from altimeter sigma0 through to final soil moisture estimate, is included along with example SMALT products. Validation has been performed over a number of deserts by comparing SMALT products with other remote sensing techniques, results of the comparison between SMALT and Metop Warp 5.5 are presented here. Comparisons with other remote sensing techniques have been limited in scope due to differences in the operational aspects of the instruments, the restricted geographical coverage of the DREAMS and the low repeat temporal sampling rate of the altimeter. The potential to expand the SMALT technique into less arid areas has been investigated. Small-scale comparison with in-situ and GNSS-R data obtained by the LEiMON experimental campaign over Tuscany, where historical trends exist within both SMALT and SMC probe datasets. A qualitative analysis of unexpected backscatter characteristics in dedicated dry environments is performed with 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

  10. A Global Analysis of the Link between Soil Moisture Dynamics and Warm Extremes.

    NASA Astrophysics Data System (ADS)

    Casagrande, E.; Kondapalli, N. K.; Mueller, B.; Miralles, D. G.; Molini, A.

    2014-12-01

    Under future climatic scenarios long-lasting warm extremes, such as heat waves, are expected to become more intense, persistent and frequent for both temperate and arid regions, resulting in diverse but nonetheless significant impacts for the human health, sustainable development and economy of these regions. As the underlying processes responsible for triggering and sustaining warm extremes are extremely variegate and yet not well understood, the occurrence of extreme events such heat waves and prolonged droughts results exceedingly difficult to predict and model. Major uncertainties arise from the fact that warm extremes mainly derive from the interplay of large-scale atmospheric processes and local feedbacks operating across very different spatial and temporal scales, and are characterized by several thresholds, limiting factors and non-linearities determining their deviation from the "classical" extreme-value theory.In this study we explore - from a global point of view - the role of local and synoptic dynamical components in initiating warm extremes and in determining their spatial and temporal clustering. Previous studies have already highlighted the role of large negative soil moisture anomalies in causing and sustaining long periods of dry and hot weather. For this reason we propose here a novel approach to the characterization of warm extremes, based on the conditioning of traditional air temperature quintile statistics to antecedent soil moisture conditions. Case studies from different climatic regimes are shown in order to prove the major and varied role of antecedent soil moisture conditions across the different regions of the world. In addition, we also investigate the connection between regional climate features and large-scale dynamics during warm extremes by the joint usage of classical diagnostic analysis and novel statistics for the detection of cross-scale interactions.

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

    PubMed Central

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

    2009-01-01

    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. PMID:22399996

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

    NASA Astrophysics Data System (ADS)

    Coopersmith, Evan J.; Bell, Jesse E.; Cosh, Michael H.

    2015-05-01

    Soil moisture estimates are valuable for hydrologic modeling, drought prediction and management, climate change analysis, and agricultural decision support. However, in situ measurements of soil moisture have only become available within the past few decades with additional sensors being installed each year. Comparing newer in situ resources with older resources, previously required a period of cross-calibration, often requiring several years of data collection. One new technique to improve this issue is to develop a methodology to extend the in situ record backwards in time using a soil moisture model and ancillary available data sets. This study will extend the soil moisture record of the U.S. Climate Reference Network (USCRN) by calibrating a precipitation-driven model during the most recent few years when soil moisture data are available and applying that model backwards temporally in years where precipitation data are available and soil moisture data are not. This approach is validated by applying the technique to the Soil Climate Analysis Network (SCAN) where the same model is calibrated in recent years and validated during preceding years at locations with a sufficiently long soil moisture record. Results suggest that if two or three years of concurrent precipitation and soil moisture time series data are available, the calibrated model's parameters can be applied historically to produce RMSE values less than 0.033 m3/m3. With this approach, in locations characterized by in situ sensors with short or intermittent data records, a model can now be used to fill the relevant gaps and improve the historical record as well.

  13. Multi-scale temporal stability analysis of surface and subsurface soil moisture within the Upper Cedar Creek Watershed, Indiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is a key state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Although soil...

  14. Parameter Estimation And Sensitivity Analysis for Root Zone Soil Moisture in SVAT Models.

    NASA Astrophysics Data System (ADS)

    Judge, J.; Agrawal, D.; Graham, W. D.

    2008-05-01

    Accurate knowledge of root zone soil moisture is crucial in hydrology, micrometeorology and agriculture for estimating energy and moisture fluxes at the land surface. Soil Vegetation Atmosphere Transfer (SVAT) models are typically used to simulate energy and moisture transport in soil and vegetation, and estimate these fluxes at the land surface and in the vadose zone. Coupling an SVAT model with a vegetation model allows inclusion of canopy effects on the fluxes, without relying on observations or empirical functions. An SVAT model, viz. Land Surface Process (LSP) model, has been coupled with a widely used crop-growth model, Decision Support System for Agrotechnology Transfer (DSSAT). The LSP-DSSAT was calibrated for a growing season of sweet corn in North Central Florida, using extensive field observations from the second Microwave Water and Energy Balance Experiment (MicroWEX-2). In this research, we address uncertainty of parameters in the LSP-DSSAT model, due to uncertainty in forcings and initial conditions, and due to accumulated errors from numerical computation. We also conduct sensitivity analyses to identify key model parameters to which the root zone soil moisture estimates are most sensitive. We will present a stochastic approach to estimate correlations between the parameters and root zone soil moisture.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...

  17. Spatio-temporal analysis of surface and subsurface soil moisture for remote sensing applications within the Upper Cedar Creek Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

  18. Refinement of SMOS multi-angular brightness temperature toward soil moisture retrieval and its analysis over reference targets

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) satellite is scheduled for launch in 2014. It will provide global measurements of soil moisture with a 3-day revisit time and accuracy of 0.04 m3/m3 at three spatial resolutions; 40 km, 10 km and 3 km. Of these, the 40 km resolution soil moisture product, whi...

  19. Method for evaluating moisture tensions of soils using spectral data

    NASA Technical Reports Server (NTRS)

    Peterson, John B. (Inventor)

    1982-01-01

    A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.

  20. Remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T.

    1976-01-01

    The surface emissivity and reflectivity of soil are strong functions of its moisture content. Changes in emissivity, observed by passive microwave techniques (radiometry), and changes in reflectivity, observed by active microwave techniques (radar), can provide information on the moisture content of the 0 to 5 cm surface layer. In addition, the thermal inertia of the surface layer, which can be remotely sensed by observing the diurnal range of surface temperature, is an indicator of soil moisture content. The thermal infrared approach to remote sensing of soil moisture has little utility in the presence of cloud cover, but provides soil moisture data at high spatial resolutions and thermal data which are a potentially useful indicator of crop status. Microwave techniques can penetrate cloud covers. The passive technique has been demonstrated by both aircraft and spacecraft instruments, but spatial resolution is limited by the size of the antenna which can be flown. Active microwave systems offer the possibility of better spatial resolution, but have yet to be demonstrated from aircraft or spacecraft platforms.

  1. Hydrologic applications of SAR derived soil moisture

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1992-01-01

    The MACHYDRO-90 was a multi-sensor aircraft campaign conducted to study drainage basin hydrology and the role of soil moisture in defining hydrologic characteristics and patterns. The results from the synthetic aperture radar (SAR) are presented. Data were collected over a period in which the soil conditions changed from dry to wet and then through a drying period which was close to ideal. Radar backscatter data are compared to detailed soil moisture samples taken to define soil moisture gradients within a watershed. The analysis also includes 40-MHz bandwidth SAR data, which provide very high spatial resolution. It is shown these data can be interpreted for hydrology and their application to hydrologic modeling is discussed.

  2. The determination of soil moisture by extraction and gas chromatography

    NASA Technical Reports Server (NTRS)

    Merek, E. L.; Carle, G. C.

    1974-01-01

    Soil moisture content was determined by extracting soil with methanol and subsequently analyzing the extract for water by gas chromatography. With air-dried mineral soils, this method gave slightly higher moisture content values than those obtained by the oven-dry method. Moisture content was determined quantitatively in soils to which various amounts of water had been added. The complete procedure, including extraction and analysis, requires less than one hour and gives results that closely compare to the oven-dry method.

  3. Soil Moisture Retrieval from Aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquarius observations over land offer an unprecedented opportunity to provide a value-added product, land surface soil moisture, which will contribute to a better understanding of the Earth’s climate and water cycle. Additionally, Aquarius will provide the first spaceborne data that can be used to a...

  4. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1994-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture... This Paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods.

  5. Soil residue analysis and degradation of saflufenacil as affected by moisture content and soil characteristics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objective of this study was to evaluate saflufenacil degradation and persistence in soils from rice regions under field capacity (non-flooded) and saturated (flooded) conditions. Saflufenacil dissolved in acetonitrile was added into pre-incubated samples at the rate of 2000 g ha-1. The amount of...

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

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  7. The Temperature in Microwave Soil Moisture Retrieval

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the near future two dedicated soil moisture satellites will be launched, the Soil Moisture and Ocean Salinity (SMOS) satellite and the Soil Moisture Active Passive (SMAP) satellite that are expected to contribute to our understanding of the global hydrological cycle. It is well known that microwa...

  8. Microstrip Ring Resonator for Soil Moisture Measurements

    NASA Technical Reports Server (NTRS)

    Sarabandi, Kamal; Li, Eric S.

    1993-01-01

    Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

  9. Role of soil moisture in maintaining droughts

    NASA Technical Reports Server (NTRS)

    Sud, Y. C.; Smith, W. E.

    1984-01-01

    The influence of soil moisture on the persistence of an ongoing drought was investigated. The case study of drought of the summer of 1980 was selected. The difference in the simulation of two identical twin runs: one with the climatological normal soil moisture and the other with anomalous soil moisture for drought conditions, were examined on the mean monthly circulation. It is found that a reduction in soil moisture did produce a corresponding reduction in precipitation. The pattern of the rainfall anomaly however, was not identical to the soil moisture (evapotranspiration) anomaly but had a good resemblance with observations.

  10. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Efendiev, Y. R.; Mohanty, B.

    2014-12-01

    Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily.

  11. Influence of soil moisture on soil respiration

    NASA Astrophysics Data System (ADS)

    Fer, Miroslav; Kodesova, Radka; Nikodem, Antonin; Klement, Ales; Jelenova, Klara

    2015-04-01

    The aim of this work was to describe an impact of soil moisture on soil respiration. Study was performed on soil samples from morphologically diverse study site in loess region of Southern Moravia, Czech Republic. The original soil type is Haplic Chernozem, which was due to erosion changed into Regosol (steep parts) and Colluvial soil (base slope and the tributary valley). Soil samples were collected from topsoils at 5 points of the selected elevation transect and also from the parent material (loess). Grab soil samples, undisturbed soil samples (small - 100 cm3, and large - 713 cm3) and undisturbed soil blocks were taken. Basic soil properties were determined on grab soil samples. Small undisturbed soil samples were used to determine the soil water retention curves and the hydraulic conductivity functions using the multiple outflow tests in Tempe cells and a numerical inversion with HYDRUS 1-D. During experiments performed in greenhouse dry large undisturbed soil samples were wetted from below using a kaolin tank and cumulative water inflow due to capillary rise was measured. Simultaneously net CO2 exchange rate and net H2O exchange rate were measured using LCi-SD portable photosynthesis system with Soil Respiration Chamber. Numerical inversion of the measured cumulative capillary rise data using the HYDRUS-1D program was applied to modify selected soil hydraulic parameters for particular conditions and to simulate actual soil water distribution within each soil column in selected times. Undisturbed soil blocks were used to prepare thin soil sections to study soil-pore structure. Results for all soil samples showed that at the beginning of soil samples wetting the CO2 emission increased because of improving condition for microbes' activity. The maximum values were reached for soil column average soil water content between 0.10 and 0.15 cm3/cm3. Next CO2 emission decreased since the pore system starts filling by water (i.e. aggravated conditions for microbes, closing soil gas pathways etc.). In the case of H2O exchange rate, values increased with increasing soil water contents (up to 0.15-0.20 cm3/cm3) and then remained approximately constant. Acknowledgement: Authors acknowledge the financial support of the Ministry of Agriculture of the Czech Republic No. QJ1230319

  12. An integrated GIS application system for soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

  13. Surface Soil Moisture Assimilation with SWAT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is one of the most critical state variables in hydrologic modeling. Certain studies have demonstrated that assimilating observed surface soil moisture into a hydrologic model results in improved predictions of profile soil water content. With the Soil and Water Assessment Tool (SWAT), ...

  14. Statistical analysis of soil moisture content changes in Central Europe using GLDAS database over three past decades

    NASA Astrophysics Data System (ADS)

    Zawadzki, Jarosław; Kȩdzior, Mateusz A.

    2014-09-01

    This paper examine soil moisture trends changes in inhomogeneous area of Central European countries — Poland, the Czech Republic and neighbouring territories. The area suffered from the lack of large-scale soil parameters research. Most of them are limited to ground measurements performed for a small part of land. Although there were extensive water conditions studies performed for the whole Europe, such as drought analysis, they were focused on Western European countries, neglecting situation in Central Europe (taking exception to Austria). The NOAH model of Global Land Data Assimilation System database has been used as a data source. It delivers one degree spatial resolution data and variables which describe soil moisture values for four depth levels (0-10 cm, 10-40 cm, 40-100 cm and 100-200 cm). Data covering years 1979-2011 has been averaged in order to analyse summer and winter terms separately. Descriptive statistics and regression analysis have been prepared on the software Statistica, Research reveals that area is losing water content. Due to promising results of water content trend analysis, the authors plan to run a large-scale analysis using other variables from the GLDAS database, especially concerning soil temperature and evapotranspiration.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  16. Analysis of spatial variability of near-surface soil moisture to increase rainfall-runoff modelling accuracy in SW Hungary

    NASA Astrophysics Data System (ADS)

    Hegedüs, P.; Czigány, S.; Pirkhoffer, E.; Balatonyi, L.; Hickey, R.

    2015-04-01

    Between September 5, 2008 and September 5, 2009, near-surface soil moisture time series were collected in the northern part of a 1.7 km2 watershed in SWHungary at 14 monitoring locations using a portable TDR-300 soil moisture sensor. The objectives of this study are to increase the accuracy of soil moisture measurement at watershed scale, to improve flood forecasting accuracy, and to optimize soil moisture sensor density. According to our results, in 10 of 13 cases, a strong correlation exists between the measured soil moisture data of Station 5 and all other monitoring stations; Station 5 is considered representative for the entire watershed. Logically, the selection of the location of the representative measurement point(s) is essential for obtaining representative and accurate soil moisture values for the given watershed. This could be done by (i) employing monitoring stations of higher number at the exploratory phase of the monitoring, (ii) mapping soil physical properties at watershed scale, and (iii) running cross-relational statistical analyses on the obtained data. Our findings indicate that increasing the number of soil moisture data points available for interpolation increases the accuracy of watershed-scale soil moisture estimation. The data set used for interpolation (and estimation of mean antecedent soil moisture values) could be improved (thus, having a higher number of data points) by selecting points of similar properties to the measurement points from the DEM and soil databases. By using a higher number of data points for interpolation, both interpolation accuracy and spatial resolution have increased for the measured soil moisture values for the Pósa Valley.

  17. New Approaches for Soil Moisture Analysis over Complex Arctic Environments with PALSAR/ALOS

    NASA Astrophysics Data System (ADS)

    Longépé, N.; Necsoiu, M.; Tadono, T.; Shimada, M.

    2010-12-01

    Frozen ground is a sensitive indicator of how our home planet is changing. In this study, the relevance of L-band Synthetic Aperture Radar (SAR) data for extracting information on frozen ground is presented. Specifically, the study focused on the characterization of a permafrost active layer using polarimetric ALOS PALSAR imagery in two locations in Alaska: the Kobuk river valley and the Arctic National Wildlife Refuge. The adequacy between polarimetric EM model and radar data has been studied for a long time, especially over bare agricultural fields (Oh et al., 1992). The assessment of residual liquid water can be realized by means of a bare soil EM backscattering model. Over natural wild land areas such as the Arctic tundra, new approaches have to be proposed in order to tackle the effect of the vegetation and other irrelevant effects (sensor calibration, multiple scattering terms, etc.). As a result, traditional soil moisture retrieval has shown limited accuracy for operational use, even though promising methods have been recently investigated (Mattia et al., 2006; Verhoest et al., 2007). Two methodologies based on multi-temporal acquisitions are proposed in this study. In regards to the uncertainties of the vegetation effect or other irrelevant mechanisms, a first methodology is proposed in this study. An optimization on the Oh’s weights (Oh, 2004) and full-polarimetric PALSAR data is carried out by using priori information provided by the Advanced Microwave Scanning Radiometer (AMSR-E) onboard the Aqua satellite. By tuning PALSAR data and Oh’s weights, the effects of vegetation are counterbalanced. This method was tested over the Arctic National Wildlife Refuge (ANWR). The optimization results are found to be in good agreement with theoretical aspects: vegetation induces an increase of cross-polarized channel (anisotropic effect) and a decrease of co-polarized channels (attenuation mechanism). The soil moisture variation can be then retrieved in a consistent manner. The second methodology does not use any priori information from AMSR-E sensor to reduce the uncertainties. Over the second test site, the Kobuk river valley, nine single-polarized HH PALSAR scenes were used, four being acquired during the thawing period and five during the frozen period. Since the soil moisture content during the frozen events is close to zero, the roughness was estimated through the inversion of Oh’s model, assuming also some effects (e.g., Fresnel refraction) due to the overlying snow cover. In this assessment, the uncertainties about the snow densities and the soil moistures were modeled and integrated into the retrieval approach. The retrieved soil roughness and its associated uncertainty estimates based on the data acquired during the frozen season were further used to derive moisture variation during the thawing period.

  18. Innovative sensing techniques and data analysis for characterizing the spatial and temporal dynamics of soil moisture patterns at the hillslope scale

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Soil moisture plays a critical role in every hydrological or meteorological model; nevertheless, it is still a great challenge to provide adequate information on soil moisture distribution beyond the point scale. Mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. The objective of this study was to characterize the spatio-temporal pattern of soil moisture at the hillslope scale and infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing the monitoring setup of a wireless sensor network for a grassland hillslope in the Schäfertal catchment, Central Germany. At the same site, we measured soil apparent electrical conductivity (ECa) using EMI devices. Hypothesizing a wet and a dry soil moisture state to be characteristic of the spatial pattern of soil moisture, we tested a new method of analysis based on the Spearman rank correlation coefficient for describing the spatial and temporal evolution of such patterns. Based on this approach, we described the persistence and switching mechanisms of the two characteristic states, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. The method showed to provide valuable insight into the persistence of characteristic states of soil moisture and the mechanisms of transition, and to be suitable for highlighting events for which specific hydrological processes occurred. The spatial organization of soil moisture was observed to be controlled by different processes in different soil horizons, with time-varying contribution, and the topsoil's moisture does not mirror processes that take place within the soil profile. The EMI investigation at the Schäfertal site appears to be suitable for mapping soil moisture at times when local soil properties control the spatial distribution of soil moisture, but not when topography has a major control on such pattern. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented areas.

  19. ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As part of our ongoing analysis of L-band radar mapping of soil moisture we are evaluating the role that ALOS PALSAR data can play in the development of radar retrieval algorithms for the future NASA Soil Moisture Active Passive (SMAP) satellite. Differences in configurations must be assessed to det...

  20. Soil-moisture sensors and irrigation management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This agricultural irrigation seminar will cover the major classes of soil-moisture sensors; their advantages and disadvantages; installing and reading soil-moisture sensors; and using their data for irrigation management. The soil water sensor classes include the resistance sensors (gypsum blocks, g...

  1. Analysis of soil moisture condition under different land uses in the arid region of Horqin sandy land, northern China

    NASA Astrophysics Data System (ADS)

    Niu, C. Y.; Musa, A.; Liu, Y.

    2015-10-01

    Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff and evapotranspiration, which is important to crop growth and vegetation restoration in semiarid environments, such as Horqin sandy land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil to infiltration under different land use types in semiarid area. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of 2 years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy soils. The higher soil moisture content among different land uses was exhibited by the grassland, followed by cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water at the surface, in the root zone and at the deep soil layer indicated statistical differences for different types of land cover. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in the deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80-120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

  2. Variations in soil moisture content in rangeland catchment

    SciTech Connect

    Salve, Rohit; Allen-Diaz, Barbara

    2000-01-02

    Soil water studies for California rangelands have focused on near-surface hydrologic processes, limiting our understanding of spatial-temporal dynamics of the water regime below the root zone. Soil moisture content and potential were monitored for 16 months in 12 locations in an annual grass dominated 20 ha catchment. The data collected were analyzed by ANOVA to determine significant spatial and temporal differences in soil moisture. Further analysis identified variables that influenced the amount of moisture present at a particular subsurface location. It was determined that there were significant differences in the amount of soil moisture present along the vertical profile of each site and between sites. Soil texture, type of vegetation cover, and elevation were the significant variables that influenced the soil moisture status.

  3. Analysis of soil moisture condition under different land uses in arid region of Horqin Sandy Land, northern China

    NASA Astrophysics Data System (ADS)

    Niu, C.; Musa, A.; Liu, Y.

    2015-07-01

    Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff, and evapotranspiration, which is substantive meaning to crop growth and vegetation restoration in semiarid environments, such as the Horqin Sandy Land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil water to precipitation infiltration under different land use types in this semiarid region. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of two years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy land. The order of soil moisture (from high to low) among different land uses was grassland, cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water in surface, root zone and deep soil layer indicated statistical difference for different land covers. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80-120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

  4. Comparison of soil moisture dynamics across different land covers

    NASA Astrophysics Data System (ADS)

    Mittelbach, Heidi; Henschel, Florian; Seneviratne, Sonia I.

    2013-04-01

    The spatial and temporal variability of soil moisture and its dependency on local or regional scale characteristics, such as soil texture, land cover and topography as well as weather and climate anomalies, is a fundamental feature for environmental applications. In a recent study based on a network of grassland stations in Switzerland (Mittelbach and Seneviratne 2012), it was shown that the spatio-temporal variability of absolute soil moisture is clearly distinct from the spatio-temporal variability of temporal soil moisture anomalies, and that regional-scale patterns of soil moisture dynamics could clearly be identified at the scale of Switzerland. However, it has not yet been investigated whether these conclusions apply across land cover types. In the current study, we investigate differences in soil moisture dynamics at paired grassland-forest sites and their dependency either on dynamic or static site properties. The analysis is based on three-year continuous soil moisture measurements at three paired grassland and nearby forest sites of the SwissSMEX (http://www.iac.ethz.ch/url/research/SwissSMEX) soil moisture network. The three paired sites are located in different climatic regions of Switzerland. They are characterized by similar meteorological conditions but within the pairs differences in topography (elevation, slope, aspect) and soil properties are found. At all sites continuous measurements of soil moisture are available in four different depths, from 5 cm to 50 cm. The analyses of daily mean soil moisture at the single depths and integrated over the 50 cm soil column reveal different behaviour with respect to absolute soil moisture levels and temporal soil moisture dynamics between grassland and forest sites during the whole three-year period. Focusing on the recession of soil moisture during precipitation-free periods, a seasonal dependency is observed with strongest recession in summer for both land covers. However, a different behaviour is found in spring and autumn. While stronger recession is found over grassland in spring, the forest sites indicate stronger recession in autumn, with most pronounced differences at deeper depths. This investigation thus suggests that differences in soil moisture dynamics across land cover types depend on the dynamics of the vegetation cover and less on static site properties. Reference: 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...

  7. Soil moisture by extraction and gas chromatography

    NASA Technical Reports Server (NTRS)

    Merek, E. L.; Carle, G. C.

    1973-01-01

    To determine moisture content of soils rapidly and conveniently extract moisture with methanol and determine water content of methanol extract by gas chromatography. Moisture content of sample is calculated from weight of water and methanol in aliquot and weight of methanol added to sample.

  8. Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

  9. Electrical methods of determining soil moisture content

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

    The electrical permittivity of soils is a useful indicator of soil moisture content. Two methods of determining the permittivity profile in soils are examined. A method due to Becher is found to be inapplicable to this situation. A method of Slichter, however, appears to be feasible. The results of Slichter's method are extended to the proposal of an instrument design that could measure available soil moisture profile (percent available soil moisture as a function of depth) from a surface measurement to an expected resolution of 10 to 20 cm.

  10. Survey of methods for soil moisture determination

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

    1979-01-01

    Existing and proposed methods for soil moisture determination are discussed. These include: (1) in situ investigations including gravimetric, nuclear, and electromagnetic techniques; (2) remote sensing approaches that use the reflected solar, thermal infrared, and microwave portions of the electromagnetic spectrum; and (3) soil physics models that track the behavior of water in the soil in response to meteorological inputs (precipitation) and demands (evapotranspiration). The capacities of these approaches to satisfy various user needs for soil moisture information vary from application to application, but a conceptual scheme for merging these approaches into integrated systems to provide soil moisture information is proposed that has the potential for meeting various application requirements.

  11. Evaluating ESA CCI soil moisture in East Africa

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA), Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP); however, these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM) over East Africa. Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we find substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies are well correlated (R > 0.5) with modeled soil moisture, and in some regions, NDVI. We use pixel-wise correlation analysis and qualitative comparisons of seasonal maps and time series to show that remotely sensed soil moisture can inform remote drought monitoring that has traditionally relied on rainfall and NDVI in moderately vegetated regions.

  12. Development of an Aquarius Soil Moisture Product

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  13. The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The contributions of precipitation and soil moisture observations to soil moisture skill in 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 derive...

  14. Measuring soil moisture with imaging radars

    NASA Technical Reports Server (NTRS)

    Dubois, Pascale C.; Vanzyl, Jakob; Engman, Ted

    1995-01-01

    An empirical model was developed to infer soil moisture and surface roughness from radar data. The accuracy of the inversion technique is assessed by comparing soil moisture obtained with the inversion technique to in situ measurements. The effect of vegetation on the inversion is studied and a method to eliminate the areas where vegetation impairs the algorithm is described.

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.

  16. Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

    NASA Astrophysics Data System (ADS)

    Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

    2016-02-01

    Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

  17. Soil Moisture Changes in the Russian Federation: In Situ Data

    NASA Astrophysics Data System (ADS)

    Speranskaya, N. A.

    2009-04-01

    Soil moisture observations in the USSR began the middle of 1950s. At the peak of the network extent (in the middle of 1980s) more than 2000 stations performed these observations operated over Russia. Since that time the number of stations in this network was significantly reduced, especially at soil plots with natural vegetation. Therefore, in this study soil moisture changes over Russia during 1970-2000 (2001) are presented using the data of only 120 long-term stations. For the European part of Russia, it is concluded that: (1) Soil moisture changes within the upper 0-10 and 0-20 cm have no systematic component. Only when the thicker layers (starting with the upper 50 cm) are used, systematic changes (trends) can be found. That is why soil moisture of the upper 20 cm layer cannot be considered as characteristic of a moistening regime of the active soil layer. (2) Over most of non-boreal European Russia, soil moisture increase is observed for layers 0-50 and 0-100 cm both in spring and during the summer (i.e., during the entire growing period). Moreover, trends in soil moisture for the upper meter of soil (layer 0-100 cm) are more apparent when compared to those in layer 0-50 cm. (3) Only in the zone of mixed and broad-leaved forest, areas of decreasing levels of soil moisture are observed during the entire growing period. For the Asian part of Russia (Southern Siberia and the southern part of Russian Far East) soil moisture changes within the upper 0-10 and 0-20 cm have no systematic component too. Changes in soil moisture within the thicker layers (the upper 50 cm and the upper 1 m) are currently under scrutiny and results of their analysis will be presented at the Session.

  18. Soil moisture variability within remote sensing pixels

    SciTech Connect

    Charpentier, M.A.; Groffman, P.M. )

    1992-11-30

    This work is part of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), an international land-surface-atmosphere experiment aimed at improving the way climate models represent energy, water, heat, and carbon exchanges, and improving the utilization of satellite based remote sensing to monitor such parameters. This paper addresses the question of soil moisture variation within the field of view of a remote sensing pixel. Remote sensing is the only practical way to sense soil moisture over large areas, but it is known that there can be large variations of soil moisture within the field of view of a pixel. The difficulty with this is that many processes, such as gas exchange between surface and atmosphere can vary dramatically with moisture content, and a small wet spot, for example, can have a dramatic impact on such processes, and thereby bias remote sensing data results. Here the authors looked at the impact of surface topography on the level of soil moisture, and the interaction of both on the variability of soil moisture sensed by a push broom microwave radiometer (PBMR). In addition the authors looked at the question of whether variations of soil moisture within pixel size areas could be used to assign errors to PBMR generated soil moisture data.

  19. Investigation of remote sensing techniques of measuring soil moisture

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

    Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

  20. SMALT - Soil Moisture from Altimetry project

    NASA Astrophysics Data System (ADS)

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

    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

  1. Retrieving pace in vegetation growth using precipitation and soil moisture

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  2. Soil moisture monitoring for crop management

    NASA Astrophysics Data System (ADS)

    Boyd, Dale

    2015-07-01

    The 'Risk management through soil moisture monitoring' project has demonstrated the capability of current technology to remotely monitor and communicate real time soil moisture data. The project investigated whether capacitance probes would assist making informed pre- and in-crop decisions. Crop potential and cropping inputs are increasingly being subject to greater instability and uncertainty due to seasonal variability. In a targeted survey of those who received regular correspondence from the Department of Primary Industries it was found that i) 50% of the audience found the information generated relevant for them and less than 10% indicted with was not relevant; ii) 85% have improved their knowledge/ability to assess soil moisture compared to prior to the project, with the most used indicator of soil moisture still being rain fall records; and iii) 100% have indicated they will continue to use some form of the technology to monitor soil moisture levels in the future. It is hoped that continued access to this information will assist informed input decisions. This will minimise inputs in low decile years with a low soil moisture base and maximise yield potential in more favourable conditions based on soil moisture and positive seasonal forecasts

  3. Sensitivity of Soil Respiration to Variability in Soil Moisture and Temperature in a Humid Tropical Forest

    PubMed Central

    Wood, Tana E.; Detto, Matteo; Silver, Whendee L.

    2013-01-01

    Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflux from a humid tropical forest in Puerto Rico. We measured hourly soil CO2 efflux, temperature and moisture in control and exclusion plots (n = 6) for 6-months. The variance of each time series was analyzed using orthonormal wavelet transformation and Haar-wavelet coherence. We found strong negative coherence between soil moisture and soil respiration in control plots corresponding to a two-day periodicity. Across all plots, there was a significant parabolic relationship between soil moisture and soil CO2 efflux with peak soil respiration occurring at volumetric soil moisture of approximately 0.375 m3/m3. We additionally found a weak positive coherence between CO2 and temperature at longer time-scales and a significant positive relationship between soil temperature and CO2 efflux when the analysis was limited to the control plots. The coherence between CO2 and both temperature and soil moisture were reduced in exclusion plots. The reduced CO2 response to temperature in exclusion plots suggests that the positive effect of temperature on CO2 is constrained by soil moisture availability. PMID:24312508

  4. Soil moisture mapping for aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquarius is the first satellite to provide both passive and active L-band observations of the Earth. In addition, the instruments on Satelite de Aplicaciones Cientificas-D (SAC-D) provide complementary information for analysis and retrieval algorithms. Our research focuses on the retrieval of soil m...

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

    In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill.

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

    PubMed Central

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

    2009-01-01

    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. PMID:22399956

  7. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  8. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

    Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  9. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1996-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

  10. Introducing a Soil Moisture Scaling Triangle

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2014-12-01

    Soil moisture measurement from space is yet, the only feasible way of procuring global moisture data. These global measurements typically result in spatial resolutions of ~ 9-56 km which are not always appropriate for direct use in various applications like agricultural yield predictions, weather and climate forecasting etc. The science for transferring soil moisture information between scales is still developing and no formal theory exists that describes the scaling relationship of soil moisture at remote sensing footprint scales. Based on past studies which describe the relationships between land surface based heterogeneity (typically determined by hydro-climate of a region) and soil moisture, we hypothesized that as opposed to the existence of a universal scaling relationship, there exist hydro-climate specific scaling relationships of soil moisture. To this effect, we have developed a hydro-climate specific soil moisture scaling triangle whose sides represent land surface heterogeneity, soil wetness and scale. The region enclosed within the triangle is divided into sub-regions corresponding to various combinations of the three sides of the triangle. Each sub-region defines a variogram of soil moisture. These variograms are a weighted sum of the variograms of the land surface based heterogeneity, namely soil, vegetation and topography observed at different support scales of measurement as represented by the particular sub-region. The weights for the variograms of soil, vegetation and topography differ for different wetness conditions, thus, also highlighting the dominant processes at different wetness conditions and their evolution across remote sensing footprint scales. The study has been conducted for three different hydro-climates i.e. semi-arid (Arizona), humid (Iowa) and sub-humid (Oklahoma).

  11. Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

    NASA Astrophysics Data System (ADS)

    Li, Fuqin; Crow, Wade T.; Kustas, William P.

    2010-02-01

    The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2-5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE 3) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m 3 m -3). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m 3 m -3) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R2 correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE 3 study site.

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

    NASA Astrophysics Data System (ADS)

    Lakshmi, Venkat; Fang, Bin

    2014-05-01

    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.

  13. Relating Soil Moisture to TRMMPR Backscatter in Southern United States

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    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 (σ°) 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). σ° 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 σ° 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.

  14. Soil Organic Matter Feedback to changes in soil moisture regimes

    NASA Astrophysics Data System (ADS)

    Kuhn, N. J.; Strunk, R.

    2012-04-01

    The reaction of the soil organic matter (SOM) pool to climate change is largely assessed based on simple models linking temperature and soil moisture, in more sophisticated models also Net Primary Productivity (NPP), to Carbon (C) stocks. Experiments on the sensitivity of vegetation growth and soil properties also mostly consider only temperature as a driver for NPP and thus SOM turnover in soils, while keeping moisture either constant or not distinguishing between moisture and temperature effects. All approaches ignore the feedback of secondary soil properties such aggregation and pore size distribution, to changes in rainfall regime and litter input. In this study, we present an experiment which is designed specifically to identifying the long-term effects of contrasting soil moisture regimes on NPP, soil C stocks and secondary soil properties such as aggregate stability and porosity. In addition, soil respiration as well as SOM quantity and quality are analyzed.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...

  16. Soil moisture estimation from radar altimetry

    NASA Astrophysics Data System (ADS)

    Mougin, E.; Frappart, F.; Famiglietti, J. S.

    2006-12-01

    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. Radar altimetry, initially developed to make accurate measurements of ocean topography, is commonly used for the survey of ice sheets and river stages. Several studies showed that changes in snow cover, soil water content and vegetation properties are responsible for variations of the backscatter response. Over the Sahel region, maxima of the backscatter coefficients are correlated to rain events. We present the results of an analysis of the backscatter coefficients from Topex/Poseidon and ENVISAT/RA-2 over the Gourma site (Mali) and compare them with in- situ and satellite measurements of precipitation, soil moisture and vegetation.

  17. Soil Moisture Patterns in a Small Forested Catchment: Hydropedological Investigations

    NASA Astrophysics Data System (ADS)

    Lin, H.

    2004-05-01

    Much effort by non-pedologists is hampered because soil distribution and processes are not well understood that site selection for sampling or monitoring and the design of modeling do not represent actual distribution and processes. To connect pedon and landscape phenomena, one of the keys lies in the distribution of various soils over the landscape (i.e., soil patterns). The fabric of soil over the landscape helps optimal sampling design as well as appropriate modeling of landscape hydrology. This strategy, reflected in hydropedological approaches, is important in understanding spatio-temporal dynamics of soil moisture over the landscape. We investigated surface and subsurface soil moisture patterns in a small forested catchment in central Pennsylvania through mapping and monitoring, and then explored the underlying mechanisms for such patterns. Soil distribution and topographic metrics were emphasized in correlating with the observed soil moisture patterns. The preliminary analysis indicated that the surface soil moisture acted as a signature of the hydrologic dynamics of this catchment, while the subsurface soil moisture was more spatio-temporally stable over the monitoring period.

  18. NASA's Soil Moisture Active Passive (SMAP) Observatory

    NASA Technical Reports Server (NTRS)

    Kellogg, Kent; Thurman, Sam; Edelstein, Wendy; Spencer, Michael; Chen, Gun-Shing; Underwood, Mark; Njoku, Eni; Goodman, Shawn; Jai, Benhan

    2013-01-01

    The SMAP mission 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.

  19. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1974-01-01

    The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4- to 8-GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-ft truck-mounted boom was used to measure the return at ten frequency points across the 4- to 8-GHz band, at eight different look angles (0 through 70 deg), and for all polarization combinations. A total of 17 sets of data were collected covering the range from 4 to 36% soil moisture content by weight. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear, however, over the range from 15 to 30% moisture content for all angles, frequencies, polarizations and surface conditions.

  20. Snow cover and soil moisture in mountains

    NASA Astrophysics Data System (ADS)

    Wever, N.; Lehning, M.

    2012-04-01

    Soil moisture is an important parameter of the climate system. It constrains evapotranspiration of plants and it functions as a storage of water, giving it an economic value, e.g. for agriculture. Furthermore, soil moisture is an important factor for predicting flood risk. In mountainous areas with a seasonal snow cover, the spatial distribution of snow depth is strongly influencing the spatial variation of soil moisture. To assess potential flooding situations during snow melt and rain on snow events in particular but for any heavy precipitation event in the mountains, it is important to understand the influence of the snow cover on soil status with respect to liquid and solid water. Only if this is known, the reaction of the soil i.e. amount of runoff, storage or melt, on additional water input can be assessed. For an operational assessment of the soil moisture state in the Swiss Alps at 140 measurement sites for snow and avalanche forecasting (IMIS network), the SNOWPACK model has been extended with a soil module, solving the Richards equation for the matrix flow. The modelling is validated with vertical profile measurements of soil moisture at meteorological stations in an Alpine catchment near Davos, Switzerland. It was found that the combination of a physical based snowpack model with a Richards equation solver seems to provide an adequate description of soil moisture fluctuations, especially in near surface layers. Soil moisture fluctuations, both measured and modelled, are strongly reduced when a snow cover is present. The measurements also revealed a strong increase in soil moisture, accompanied by a daily cycle in soil moisture during snow melt, extending down to 120cm depth. When soil properties from literature were assumed for the soil type in the vertical profile, the daily cycle in the model during snow melt was restricted mainly to the top layers, while observations show also a reaction in deeper layers. These observations are consistent with the assumption of the existence of preferential flow paths, which are not modelled by the Richards equation. This discrepancy between observations and model results during the melt phase may cause an underestimation of the soil storage capacity and an overestimation of the surface run-off in the model.

  1. Analysis of field-sampled, in-situ network, and PALS airborne soil moisture observations over SMAPVEX12

    NASA Astrophysics Data System (ADS)

    Adams, J. R.; Berg, A. A.; McNairn, H.; Cosh, M. H.

    2014-12-01

    The Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12) was conducted over an agricultural domain in southern Manitoba, Canada. The purpose of the campaign was to develop ground and airborne datasets for pre-launch validation of SMAP satellite soil moisture retrieval algorithms. Three key soil moisture datasets were collected in support of the campaign objectives: 1) intensive field sampling over (up to) 55 agricultural fields on 17 sampling days; 2) a continuously operated temporary in-situ network (> 30 stations) distributed over the domain; and 3) L-band microwave data from NASA's Passive Active L-band Sensor (PALS) onboard a Twin-Otter aircraft. This presentation addresses whether dense temporary in-situ networks can supplant intensive field-sampling during pre-/post-launch validation campaigns. SMAPVEX12 datasets are examined at the field and aircraft pixel (~800 m) scale, and at the domain scale. Preliminary results demonstrate that, at the field-scale, there is generally limited agreement between a single station and sampled data over its field. Over the duration of the campaign, the majority of temporary soil moisture stations have > 0.04 m3m-3 RMSE with sampled field data, suggesting that a single station has limited representativeness of an agricultural field. Furthermore, the in-situ stations and field-sampled data are compared with PALS generated soil moisture to assess differences in daily RMSE. For wet-periods, both ground datasets provide a comparable RMSE for the PALS estimate. Although for dry-periods, the difference in RMSE between the ground datasets becomes more significant (> 0.04 m3m-3). This is because the field-sampled data exhibit a sharper dry-down than the in-situ station measurements. However, at the domain scale there is strong agreement between the soil moisture datasets. Additional results describe the sources of variability affecting these soil moisture datasets and the statistical number of stations needed to represent the SMAPVEX12 domain. This research is of importance for the efficient allocation of ground resources during remote sensing validation campaigns for soil moisture.

  2. Evaluation of the Second Global Soil Wetness Project soil moisture simulations: 1. Intermodel comparison

    NASA Astrophysics Data System (ADS)

    Guo, Zhichang; Dirmeyer, Paul A.

    2006-11-01

    Driven with the meteorological data sets based on the reanalyses and gridded observational data archived by the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II, eleven different land surface models generated global soil moisture data sets for the 10-year period (1986-1995) for the Second Global Soil Wetness Project (GSWP-2). We evaluate these model simulations against in situ observations over grasslands and agricultural regions in the former Soviet Union, United States (Illinois), China, and Mongolia from the Global Soil Moisture Data Bank in terms of their ability to estimate the actual column plant-available soil moisture in the top 1-m soil layer, to simulate the phasing of the annual cycle, and to represent observed interannual variability. Results from these 11 land surface models show that they reproduce reasonably well the observed interannual variability and phasing of the annual cycle. Statistical analysis also shows that the median root mean square of errors among these models ranges from 4 to 8 cm of soil moisture. Similar to what has been found in soil moisture simulations for GSWP-1, the absolute values of soil moisture are poorly simulated by most models. However, the models do a good job of reproducing the soil moisture anomalies. This suggests that the global soil wetness data set produced by GSWP-2 can be used for analyzing climate variability and initializing GCMs by using transform strategies. This also has relevance to subseasonal to seasonal forecasts since soil moisture anomalies may potentially have impact on precipitation.

  3. Radar for Measuring Soil Moisture Under Vegetation

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    A two-frequency, polarimetric, spaceborne synthetic-aperture radar (SAR) system has been proposed for measuring the moisture content of soil as a function of depth, even in the presence of overlying vegetation. These measurements are needed because data on soil moisture under vegetation canopies are not available now and are necessary for completing mathematical models of global energy and water balance with major implications for global variations in weather and climate.

  4. Soil moisture estimation with limited soil characterization for decision making

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    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.

  5. Airborne gamma radiation soil moisture measurements over short flight lines

    NASA Technical Reports Server (NTRS)

    Peck, Eugene L.; Carrol, Thomas R.; Lipinski, Daniel M.

    1990-01-01

    Results are presented on airborne gamma radiation measurements of soil moisture condition, carried out along short flight lines as part of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE). Data were collected over an area in Kansas during the summers of 1987 and 1989. The airborne surveys, together with ground measurements, provide the most comprehensive set of airborne and ground truth data available in the U.S. for calibrating and evaluating airborne gamma flight lines. Analysis showed that, using standard National Weather Service weights for the K, Tl, and Gc radiation windows, the airborne soil moisture estimates for the FIFE lines had a root mean square error of no greater than 3.0 percent soil moisture. The soil moisture estimates for sections having acquisition time of at least 15 sec were found to be reliable.

  6. Soil Moisture Experiments 2004 (SMEX04)

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.; Lettenmaier, D. P.

    2004-05-01

    Soil Moisture Experiments 2004 (SMEX04) will be conducted during the summer of 2004 to address overlapping science issues of the North American Monsoon Experiment (NAME) and soil moisture remote sensing programs. Surface boundary conditions play an important role in initiation and maintenance of the system that controls summer precipitation over much of the NAME region. A working hypothesis of NAME is that among the land surface antecedent boundary conditions that control the onset and intensity of the precipitation is soil moisture in the southwestern U.S. and northern Mexico. Surface soil moisture can change dramatically after rain events. This increased soil moisture after precipitation can increase evapotranspiration between storm events, which may contribute to enhanced convection and further precipitation. Soil moisture can vary both spatially, due to topography, soil, vegetation and precipitation variability, and temporally, due to differences in soil physical characteristics that control drainage and accumulated evapotranspiration. SMEX04 will focus on providing these critical soil moisture products using the new generation of satellite sensors supported by insitu observations and high-resolution aircraft mapping. Intensive study regions will be established over 50 by 75 km domains in southeastern Arizona and northwestern Mexico. Insitu observations will be collected over an extended time frame. Aircraft mapping and intensive regional ground sampling will be performed between mid-July and mid-August. The field campaign will at the same time contribute to the validation of these satellite products, expand our knowledge of the effects of key land surface features, establish algorithms for future satellite sensors, and explore the potential of new technologies.

  7. Soil-moisture ground truth, Hand County, South Dakota

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

    Soil types were determined from the Soil Survey of Hand County, South Dakota. The soil types encountered on the soil moisture lines are summarized. The actual soil moisture data are presented. The data have been divided by range, township and section. The soil moisture data obtained in fields of winter wheat and spring wheat are briefly summarized.

  8. Soil moisture at local scale: Measurements and simulations

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio

    2014-08-01

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

  9. The prototype SMOS soil moisture Algorithm

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    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, floods, etc…), the making of data sets and validation verification exercises. During the presentation we will describe in more details the algorithm and accompanying work in particular decision tree principle and characteristics, the auxiliary data used and the special and "exotic" cases. We will also be more explicit on the algorithm validation and verification approaches together with the making of test data sets from existing and synthetic data. A glimpse of level 3 and 4 products will also be given.

  10. Microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

    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.

  11. Effect of soil moisture on chlorine deposition.

    PubMed

    Hearn, John; Eichler, Jeffery; Hare, Christopher; Henley, Michael

    2014-02-28

    The effect of soil moisture on chlorine (Cl(2)) deposition was examined in laboratory chamber experiments at high Cl(2) exposures by measuring the concentration of chloride (Cl(-)) in soil columns. Soil mixtures with varying amounts of clay, sand, and organic matter and with moisture contents up to 20% (w/w) were exposed to ≈3×10(4)ppm Cl(2) vapor. For low water content soils, additional water increased the reaction rate as evidenced by higher Cl(-) concentration at higher soil moisture content. Results also showed that the presence of water restricted transport of Cl(2) into the soil columns and caused lower overall deposition of Cl(2) in the top 0.48-cm layer of soil when water filled ≈60% or more of the void space in the column. Numerical solutions to partial differential equations of Fick's law of diffusion and a simple rate law for Cl(2) reaction corroborated conclusions derived from the data. For the soil mixtures and conditions of these experiments, moisture content that filled 30-50% of the available void space yielded the maximum amount of Cl(2) deposition in the top 0.48cm of soil. PMID:24434132

  12. Surface and Profile Soil Moisture Spatial Analysis During an Excessive Rainfall Period in the Southern Great Plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this work we analyze the temporal stability of soil moisture content across the 61,000 ha Little Washita River Experimental Watershed (LWREW) and at a field scale of 64 ha as part of the remote sensing Cloud and Land Surface Interaction Campaign (CLASIC07) during June 2007 in south-central Oklaho...

  13. Combined analysis of soil moisture measurements from roving and fixed cosmic ray neutron probes for multiscale real-time monitoring

    NASA Astrophysics Data System (ADS)

    Franz, Trenton E.; Wang, Tiejun; Avery, William; Finkenbiner, Catherine; Brocca, Luca

    2015-05-01

    Soil moisture partly controls land-atmosphere mass and energy exchanges and ecohydrological processes in natural and agricultural systems. Thus, many models and remote sensing products continue to improve their spatiotemporal resolution of soil moisture, with some land surface models reaching 1 km resolution. However, the reliability and accuracy of both modeled and remotely sensed soil moisture require comparison with ground measurements at the appropriate spatiotemporal scales. One promising technique is the cosmic ray neutron probe. Here we further assess the suitability of this technique for real-time monitoring across a large area by combining data from three fixed probes and roving surveys over a 12 km × 12 km area in eastern Nebraska. Regression analyses indicated linear relationships between the fixed probe averages and roving estimates of soil moisture for each grid cell, allowing us to derive an 8 h product at spatial resolutions of 1, 3, and 12 km, with root-mean-square error of 3%, 1.8%, and 0.9%.

  14. Soil moisture content estimation from passive temperature measurements

    NASA Astrophysics Data System (ADS)

    Halloran, Landon JS; Roshan, Hamid; Rau, Gabriel C.; Cuthbert, Mark O.; Andersen, Martin S.; Acworth, Ian

    2015-04-01

    Natural temperature variations have increasingly been used to study shallow groundwater; however, the vast majority of studies are limited to saturated conditions. Despite the greater complexity of the unsaturated zone due to the non-linear relationships between moisture content and other physical properties (such as effective thermal conductivity and heat capacity), estimating soil moisture from measurements of natural temperature variations is possible. We have developed fundamental relationships between soil moisture and the diel temperature amplitude ratio and phase-shift. Additionally, we have developed fully coupled thermodynamic and hydraulic finite element (FE) models of temperature and soil moisture response to various boundary conditions. The performance of novel inversion techniques based on existing empirical thermal conductivity models has been evaluated with these results. Two significant empirical models of thermal conductivity of unsaturated sediments were integrated into the approach and compared. We performed a sensitivity analysis of our soil moisture model and determined the feasibility of deriving moisture estimates from temperature data by analysing the required measurement precision for the involved parameters. Inversion of the temperature output from the FE models demonstrates the factors, such as homogeneity and rapidly changing boundary conditions, which may limit the performance of unsaturated zone heat tracing, as well as the benefits of the approach. The use of heat to determine soil moisture content offers the advantages of lower cost; applicability to zones of high pore-water salinity, where inductive electromagnetic measurement methods fail; and the option of high spatial resolution or wide coverage when combined with fibre optic temperature sensing.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...

  16. Passive Microwave Observations of Soil Moisture and Dew in Soil Moisture Experiments 2005

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microwave remote sensing can provide reliable measurements of surface soil moisture. However, there are a few land surface features that have a perturbing influence on the soil moisture retrievals. A lack of appropriate observations and physical characterization of target parameters contribute to re...

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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.

  18. Soil moisture - resistivity relation at the plot and catchment scale

    NASA Astrophysics Data System (ADS)

    Calamita, Giuseppe; Perrone, Angela; Satriani, Antonio; Brocca, Luca; Moramarco, Tommaso

    2010-05-01

    The key role played by soil moisture in both Global Hydrological Cycle and Earth Radiation Budget has been claimed by numerous authors during past decades. The importance of this environmental variable is evident in several natural processes operating in a wide range of spatial and temporal scales. At continental and regional scales soil moisture influences the evapotranspiration process and so acts indirectly on the climate processes; at middle scale is one of the major controls of the infiltration-runoff soil response during rainfall events; at small scales the knowledge of soil moisture evolution is crucial for precision agriculture and the associated site-specific management practices. However, soil moisture exhibits an high temporal and spatial variability and this is even more evident in the vadose zone. Thus, in order to better understand the soil moisture dynamics it is desirable to capture its behavior at different temporal and/or spatial scales. Traditional in situ methods to measure soil moisture like TDR can be very precise and allows an high temporal resolution. Recently, the application in field of geophysical methods for capturing soil moisture spatial and temporal variations has demonstrated to be a promising tool for hydro-geological studies. One of the major advantages relies on the capability to capture the soil moisture variability at larger scales, that is decametric or hectometric scale. In particular, this study is based on the simultaneous application of the electrical resistivity and the TDR methods. We present two study cases that differ from each other by both spatial and temporal resolution. For the first one, simultaneous measurements obtained during four different period of the year and carried out within a test catchment (~60 km2) in Umbria region (central Italy) were analyzed. The second case concerns almost three months of simultaneous measurements carried out in a small test site ( <200 m2), located in the garden of IMAA-CNR institute in Tito Scalo (south Italy). One measurement every two days were performed on average, in particular 44 sampling events during 80 days. In both case we present a correlation and a regression analysis conducted both on punctual measurements and on their spatial averages. The results show that the resistivity method can be conveniently applied for soil moisture retrieval with a fairly good accuracy. The capability of this technique to obtain information for the whole soil profile suggests its use to better investigate the role of soil moisture dynamics at catchment scale and its influence on the rainfall-runoff processes.

  19. Soil Moisture Characterization for Biogenic Emissions Modeling in Texas

    NASA Astrophysics Data System (ADS)

    McGaughey, G.; Sun, Y.; Kimura, Y.; Huang, L.; Fu, R.; McDonald-Buller, E.

    2014-12-01

    The role of isoprene and other biogenic volatile organic compounds (BVOCs) in the formation of tropospheric ozone has been recognized as critical for air quality planning in Texas. In the southwestern United States, drought has become a recurring phenomenon and, in addition to other extreme weather events, can impose profound and complex effects on human populations and the environment. Understanding these effects on vegetation and biogenic emissions is important as Texas concurrently faces requirements to achieve and maintain attainment with the National Ambient Air Quality Standard (NAAQS) for ozone in several large metropolitan areas. This research evaluated the impact of soil moisture through the use of simulated and observational datasets on emissions estimates of isoprene. Soil moisture measurements (e.g., Climate Reference Network, Soil Climate Analysis Network) at limited locations in eastern Texas during 2006-2011 showed spatial and temporal variability associated with environmental drivers such as meteorology and physical soil characteristics; low volumetric soil moisture values (< 0.05 m3/m3) were observed during 2011, a year characterized by all-time record drought over the majority of Texas. Comparisons of soil moisture observations in the upper one meter to predictions from the North American Land Data Assimilation System (NLDAS) indicated a tendency towards a dry bias for NLDAS especially at depths greater than 10 cm. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was used to explore the sensitivity of biogenic emissions estimates to alternative soil moisture representations for year 2011. A range of soil moisture inputs over eastern Texas informed by the observed to simulated comparisons demonstrated that the impact on predicted isoprene emissions was affected by both the soil moisture and specific wilting point datasets employed.

  20. Reconciling spatial and temporal soil moisture effects on afternoon rainfall

    PubMed Central

    Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I.

    2015-01-01

    Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks. PMID:25740589

  1. Reconciling spatial and temporal soil moisture effects on afternoon rainfall

    NASA Astrophysics Data System (ADS)

    Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I.

    2015-03-01

    Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks.

  2. Evaluation of soil moisture sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study evaluated the measurement accuracy and repeatability of the EC-5 and 5TM soil volumetric water content (SVWC) sensors, MPS-2 and 200SS soil water potential (SWP) sensors, and 200TS soil temperature sensor. Six 183cm x 183cm x 71cm wooden compartments were built inside a greenhouse, and e...

  3. Measuring soil moisture with imaging radars

    SciTech Connect

    Dubois, P.C.; Zyl, J. van; Engman, T.

    1995-07-01

    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.

  4. Detecting soil moisture impacts on convective initiation in Europe

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher M.

    2015-06-01

    Feedbacks between soil moisture and precipitation are important for understanding hydroclimatic variability in many regions. However, much uncertainty remains about how land surface fluxes influence the initiation of deep convection locally. While some studies consider only atmospheric and soil profiles, in a one-dimensional sense, others have argued that horizontal variability in fluxes plays an important role in convective triggering, via mesoscale circulations. This paper presents the first comprehensive observational analysis over Europe linking convective initiation to soil moisture, based on satellite observations of cloud top and land surface temperature, and soil moisture. The results show that convective initiations are favored on the downwind side of dry surfaces, close to wetter areas. The signal is clearest following dry periods and under light winds, consistent with forcing by a mesoscale circulation. Overall, the detected signal in Europe is weaker than in previous Sahelian analysis, but key spatial characteristics are essentially the same.

  5. Improving government decision making in response to floods using soil moisture observations from Soil Moisture Active Passive (SMAP) data

    NASA Astrophysics Data System (ADS)

    Escobar, V. M.; Schumann, G.; Torak, L. J.

    2014-12-01

    NASA's Soil Moisture Active Passive (SMAP) Mission, due to launch January 2015, will provide global observations of the Earth's surface soil moisture, providing high accuracy, resolution and continuous global coverage. This paper seeks to show how SMAP data can be used in flood applications to improve flood warning/planning operations for the Upper Mississippi River basin. The Mississippi River ranks as the fourth longest and tenth largest river in the world and is noted as one of the most altered rivers in the United States. The Mississippi River has a very long track record of flood events, with the 2011 event being a unique event due to large volumes of snow melt and heavy spring rain in the Upper Mississippi basin. Understanding and modeling these processes and combining them with relevant satellite observations such as soil moisture conditions could help alleviate some of the risk to flooding by identifying when infiltration to soils is cut off causing excessive runoff. The objective of the analysis is to improve our understanding of how satellite-derived soil moisture will impact basin scaled/multi state decision processes linked to emergency planning and preparedness, such as FEMA FloodSMART. Using the snow hydrology model SNOW-17 (NWS) coupled to a large-scale two-dimensional floodplain inundation model LISFLOOD-FP, the study evaluates how different soil moisture states can be captured by satellites to enable a multi-state decision process focused on flood risk and planning. The study develops a scenario that applies historical soil moisture data from past events to monitor basin soil moisture conditions and yields a percent value of the saturation status. Scenario analysis is particularly important for decision makers such as emergency responders and insurers as their operations depend on their ability to gauge and appropriately assess risk. This analysis will enables insurers to develop mitigation strategies and contingency plans for such events.

  6. Soil moisture in sessile oak forest gaps

    NASA Astrophysics Data System (ADS)

    Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter

    2015-04-01

    By social demands are being promoted the aspects of the natural forest management. In forestry the concept of continuous forest has been an accepted principle also in Hungary since the last decades. The first step from even-aged stand to continuous forest can be the forest regeneration based on gap cutting, so small openings are formed in a forest due to forestry interventions. This new stand structure modifies the hydrological conditions for the regrowth. Without canopy and due to the decreasing amounts of forest litter the interception is less significant so higher amount of precipitation reaching the soil. This research focuses on soil moisture patterns caused by gaps. The spatio-temporal variability of soil water content is measured in gaps and in surrounding sessile oak (Quercus petraea) forest stand. Soil moisture was determined with manual soil moisture meter which use Time-Domain Reflectometry (TDR) technology. The three different sizes gaps (G1: 10m, G2: 20m, G3: 30m) was opened next to Sopron on the Dalos Hill in Hungary. First, it was determined that there is difference in soil moisture between forest stand and gaps. Second, it was defined that how the gap size influences the soil moisture content. To explore the short term variability of soil moisture, two 24-hour (in growing season) and a 48-hour (in dormant season) field campaign were also performed in case of the medium-sized G2 gap along two/four transects. Subdaily changes of soil moisture were performed. The measured soil moisture pattern was compared with the radiation pattern. It was found that the non-illuminated areas were wetter and in the dormant season the subdaily changes cease. According to our measurements, in the gap there is more available water than under the forest stand due to the less evaporation and interception loss. Acknowledgements: The research was supported by TÁMOP-4.2.2.A-11/1/KONV-2012-0004 and AGRARKLIMA.2 VKSZ_12-1-2013-0034.

  7. Soil Moisture Estimation Using Inexpensive Radios

    NASA Astrophysics Data System (ADS)

    Niemeier, J. J.; Kruger, A.

    2011-12-01

    Technological advances and changes in licensing have made small, inexpensive radio modules commonplace. Today, these radios are used in a large number of wireless data- and control applications. A novel approach is to view such radio modules not only as communication devices, but also as small, inexpensive sources of radio frequency (RF) energy, which are useful for devising unconventional sensors. We have explored the possibility of using buried radios and the resulting RF links as distributed soil moisture sensors. We conducted a number of experiments that record the RF attenuation of the links over time. Estimating RF attenuation is straightforward, since the radio modules provide a received signal strength indication (RSSI). To provide reference data, we installed several time-domain reflectometry (TDR) soil moisture probes with accompanying temperature probes to monitor changes in soil moisture and soil temperature. We collocated tipping bucket rain gauges for monitoring rain events. We employed RF modules that operate at 900 MHz. Rather than burying the radios, we lowered the antennas into 2.5 cm PVC pipes that we drove into the ground to a depth of 60 cm. We seal both ends of the PVC pipe to prevent water from entering the tube. Our experimental data shows a clear relationship between soil moisture and RF attenuation. We developed a simple, yet effective, mathematical model to relate changes in RF attenuation to changes in soil moisture. One can easily achieve reliable links 2-3 m long, and we believe the technique holds promise as an economical method for distributed/integrated soil moisture estimation.

  8. Comparing soil moisture memory in satellite observations and models

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the 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.

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

    USGS Publications Warehouse

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

    2011-01-01

    The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture. ?? 2011 Taylor & Francis.

  10. Numerical studies on soil moisture distributions in heterogeneous catchments

    NASA Astrophysics Data System (ADS)

    Settin, T.; Botter, G.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2007-05-01

    The paper deals with numerical studies of basin-scale dynamics of soil moisture in arbitrarily heterogeneous conditions (i.e., in presence of heterogeneity of climate, soil, vegetation and land use). Its relevance stems from comparative analysis of the probabilistic structure of spatially averaged soil moisture fields with the corresponding exact solutions of the underlying simplified stochastic point processes. The probabilistic structure of coarse-grained soil moisture fields is largely controlled by temporal fluctuations of intermittent rainfall fields. Averaged properties are also affected by heterogeneous soil and vegetation features and by the spatial scale of aggregation. Here, we employ results from extended Montecarlo simulations of a continuous model of the hydrologic response that proved suitable to describe observed events. The comparison of numerically derived soil moisture probability density functions with exact simplified solutions suggests, somewhat unexpectedly, that the analytical model can reasonably describe the large-scale behavior of spatially-averaged hydrologic fluxes through physically meaningful, basin-scale soil and vegetation parameters. The application of a seasonally variable, stochastic climate model shows pronounced daily fluctuations in the relationship between water losses and soil moisture, related to the underlying climatic fluctuations. The resulting spatially averaged soil moisture probability density functions in heterogeneous catchments, however, do not show appreciable differences with respect to the ones obtained assuming constant mean climate conditions. We thus conclude that effective basin-scale states, which average highly heterogeneous (spatial/temporal) properties allowing exact probabilistic descriptions, indeed exist, with implications for large scale estimates of soil-atmosphere interactions.

  11. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1973-01-01

    The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system was used to measure the return at 10 frequency points across the 4-8 GHz band, at different look angles, and for all polarization combinations. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear over the range 15%-30% moisture content for all angles, frequencies, polarizations and surface conditions.

  12. Effects of soil moisture on the diurnal pattern of pesticide emission: Numerical simulation and sensitivity analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate prediction of pesticide volatilization is important for the protection of human and environmental health. Due to the complexity of the volatilization process, sophisticated predictive models are needed, especially for dry soil conditions. A mathematical model was developed to allow simulati...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

  14. Application of a soil moisture diagnostic equation for estimating root-zone soil moisture in arid and semi-arid regions

    NASA Astrophysics Data System (ADS)

    Pan, Feifei; Nieswiadomy, Michael; Qian, Shuan

    2015-05-01

    Knowledge of soil moisture in the root zone is critical for crop growth estimation and irrigation scheduling. In this study, a soil moisture diagnostic equation is applied to estimate soil moisture at depths of 0-100 cm (because the majority of crop roots are in the top 100 cm of soil) at four USDA Soil Climate Analysis Network (SCAN) sites in arid and semi-arid regions: TX2105 in northwest Texas, NM2015 and NM2108 in east New Mexico, and AZ2026 in southeast Arizona. At each site, a dataset of 5-6 years of records of daily soil moisture, daily mean air temperature, precipitation and downward solar radiation is compiled and processed. Both the sinusoidal wave function of day of year (DOY) and a linear function of the potential evapotranspiration (PET) are used to approximate the soil moisture loss coefficient. The first four years of data are used to derive the soil moisture loss function and the empirical parameters in the soil moisture diagnostic equation. The derived loss function and empirical parameters are then applied to estimate soil moisture in the last fifth or sixth year at each site. Root mean square errors (RMSEs) of the estimated volumetric soil moistures in five different soil columns (i.e., 5 cm, 10 cm, 20 or 30 cm, 50 cm, and 100 cm) are less than 3.2 (%V/V), and the accuracy of the estimated soil moistures using the sinusoidal soil moisture loss function is slightly better than the PET-based loss functions. In addition to the three advantages of this soil moisture diagnostic equation, i.e., (1) non-cumulative errors in the estimated soil moisture, (2) no regular recalibration is required to correct the cumulative errors, and (3) no numerical iteration and initial moisture inputs are needed since only precipitation data are required, this study also demonstrates that the soil moisture diagnostic equation not only can be used to estimate surface soil moisture, but also the entire root-zone soil moisture.

  15. Estimating rootzone soil moisture by assimilating both microwave based surface soil moisture and thermal based soil moisture proxy observations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A number of synthetic data assimilation experiments are carried out at the USDA Economic and Environmental Enhancement (OPE3) site in Beltsville, Maryland. As a first case, only surface soil moisture retrievals are assimilated into a land surface model using the Ensemble Kalman filter (EnKF). This...

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  17. Advanced microwave soil moisture studies. [Big Sioux River Basin, Iowa

    NASA Technical Reports Server (NTRS)

    Dalsted, K. J.; Harlan, J. C.

    1983-01-01

    Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: soil map and land cover data; direct soil moisture measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (soil features and land cover) hold promise for qualitative assessment of soil moisture and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.

  18. The role of biological soil crusts on soil moisture

    NASA Astrophysics Data System (ADS)

    Chamizo, S.; Cantón, Y.; Lázaro, R.; Rodriguez-Caballero, E.; Domingo, F.

    2012-04-01

    In water-limited ecosystems, water becomes the most important driver for plant productivity. In these systems, spatial distribution of water resources is not random but organized into a mosaic of water-depletion areas linked to water-accumulation areas. In other words, water is transferred from interplant patches that act as source areas to vegetation patches that act as sinks of this resource. Thus, structure and functioning of interplant patches have a decisive role in water redistribution and distribution patterns of vegetation. Soil surface in the interplant spaces of most arid and semiarid ecosystems is covered by biological soil crusts (BSCs). These organisms regulate water fluxes into and through soils and play major roles in local hydrological processes. In the last years, the role of these organisms in infiltration and runoff has gained increased importance and a better knowledge about their effects on these processes has been acquired. However, the role of BSCs in other important components of the water balance such as evaporation or soil moisture has been scarcely studied, so that their effects on these processes remain unknown. The objective of this work is to examine the influence of BSCs on soil moisture regimes in the top profile of the soil in two semiarid ecosystems of SE Spain with contrasting soil texture and where BSCs are well-represented. Soil moisture content at 0.03 and 0.10 m was monitored under two representative types of BSCs, a dark cyanobacteria-dominated BSC and a light-coloured lichen-dominated BSC, and in soils where these BSCs were removed by scraping, at both study sites. Our results show that, under high water conditions, removal of BSCs leads to a decrease in soil moisture compared to soils covered by BSCs. Decrease in soil moisture due to BSC removal namely affects moisture in the upper layer of the soil (0.03 m), but has little impact in deeper soil (0.10 m). Evaporation is also generally faster in soils with no BSCs than in soils covered by them. The type of BSC influences soil moisture in a different way depending on soil water conditions. Under high water content conditions, soil water loss is faster and soil moisture content lower under cyanobacterial than under lichen BSCs, due to higher infiltration promoted by lichens. On the contrary, under low water content conditions, lichen-crusted soils dry out faster and exhibit less moisture than cyanobacteria-crusted ones, attributed to the larger porosity and subsequent greater evaporative losses in lichen- than in cyanobacteria-crusted soils. We found higher moisture in coarse-textured soils than in fine-textured ones, despite the higher water retention capacity of the latter soils. More favourable conditions in the coarser soils, which had greater organic matter content, aggregate stability and were subject to less water stress due to its proximity to the coast, seems to contribute to this increased soil moisture content. BSCs therefore play an important role on the maintenance of water availability in the interplant spaces, thereby strongly affecting soil physical and biological processes, and the potential for emergence establishment and survival of plants in semiarid ecosystems.

  19. Freeze/thaw and soil moisture effects on wind erosion

    NASA Astrophysics Data System (ADS)

    Wang, L.; Shi, Z. H.; Wu, G. L.; Fang, N. F.

    2014-02-01

    Wind erosion is very pronounced in semiarid regions during late winter-early spring and has major impacts on regional desertification and agriculture. In order to identify the effects of freeze/thaw and soil moisture on wind erosion, wind tunnel experiments were conducted to compare wind erosion effects under various soil moisture gradients in frozen and thawed soil. The variation of surface soil moisture after wind erosion and the effective soil particle size distribution was tested to explain the differences. The results showed that surface soil moisture content decreased in thawed soil and increased in frozen soil after wind erosion. The mean weight diameter, which increased with increasing soil moisture, was smaller in thawed soil than in frozen soil. The wind-driven sediment flux of frozen and thawed soil both decreased with increasing moisture, owing to the heavier soil particle weight and stronger interparticle bonding forces. The critical soil moisture content for suppressing wind erosion was around 2.34% for frozen soil and around 2.61% for thawed soil. The wind-driven sediment flux of thawed soil was always larger than that of frozen soil at the same moisture content, but this difference became negligible at moisture contents above 3.38%. We may speculate that wind erosion will be more severe in the future because of the lower soil moisture content and fewer soil freezing days as a result of global warming.

  20. Spatiotemporal variations of soil moisture in the Tarim River basin, China

    NASA Astrophysics Data System (ADS)

    Su, Buda; Wang, Anqian; Wang, Guojie; Wang, Yanjun; Jiang, Tong

    2016-06-01

    Based on in situ soil moisture and river runoff records in the Tarim River basin, usability of the long term Essential Climate Variable (ECV) soil moisture dataset is validated in the arid climatic region of China. The spatio-temporal variation of soil moisture and its possible influencing factors in the 1988-2013 is also preliminary analyzed in the current paper. Results reveal that the ECV soil moisture can capture the large scale dynamics of regional water cycle quite satisfactorily, showing good agreement with in situ observations in their seasonal and interannual variability. In the period of 1988-2013, the ECV soil moisture shows obvious increasing trends in the northwest and the southwest parts of the Tarim River basin, particularly in spring (March-May) and autumn (September-November). Statistical analysis further suggests that the variations of soil moisture in the Tarim River basin are more controlled by precipitation, and temperature is less effective in controlling of soil moisture variations.

  1. Remote detection of soil surface moisture

    NASA Technical Reports Server (NTRS)

    Stockhoff, E. H.; Frost, R. T.

    1974-01-01

    Polarimetric data concerning soil surface moisture were obtained during a series of flights over the Imperial Valley, California, and Phoenix, Arizona, during March 1972. A polarimeter was installed in NASA's Convair-990 aircraft, Galileo, above a window in the floor of the aft cargo compartment in such a manner that it could view from 42 deg ahead of, to 42 deg to the rear of the nadir. It had a 3 deg field of view and a 10 nm bandwidth centered at 641 nm. The moisture content of the solid surface for fields viewed by the polarimeter was measured by determining the angle through which the light had been scattered by the soil and by observing the degree of polarization of this light produced during its interaction with the soil. The polarimeter measures this degree of polarization in terms of Stokes parameters. Ground-truth samples of soil were obtained at several depths along the flight path.

  2. Soil moisture - precipitation feedbacks in observations and models (Invited)

    NASA Astrophysics Data System (ADS)

    Taylor, C.

    2013-12-01

    There is considerable uncertainty about the strength, geographical extent, and even the sign of feedbacks between soil moisture and precipitation. Whilst precipitation trivially increases soil moisture, the impact of soil moisture, via surface fluxes, on convective rainfall is far from straight-forward, and likely depends on space and time scale, soil and synoptic conditions, and the nature of the convection itself. In considering how daytime convection responds to surface fluxes, large-scale models based on convective parameterisations may not necessarily provide reliable depictions, particularly given their long-standing inability to reproduce a realistic diurnal cycle of convection. On the other hand, long-term satellite data provide the potential to establish robust relationships between soil moisture and precipitation across the world, notwithstanding some fundamental weaknesses and uncertainties in the datasets. Here, results from regional and global satellite-based analyses are presented. Globally, using 3-hourly precipitation and daily soil moisture datasets, a methodology has been developed to compare the statistics of antecedent soil moisture in the region of localised afternoon rain events (Taylor et al 2012). Specifically the analysis tests whether there are any significant differences in pre-event soil moisture between rainfall maxima and nearby (50-100km) minima. The results reveal a clear signal across a number of semi-arid regions, most notably North Africa, indicating a preference for afternoon rain over drier soil. Analysis by continent and by climatic zone reveals that this signal (locally a negative feedback) is evident in other continents and climatic zones, but is somewhat weaker. This may be linked to the inherent geographical differences across the world, as detection of a feedback requires water-stressed surfaces coincident with frequent active convective initiations. The differences also reflect the quality and utility of the soil moisture datasets outside of sparsely-vegetated regions. No evidence is found for afternoon convection developing preferentially above locally moister soils. Higher resolution datasets are used to provide a clearer relationship between soil moisture patterns and convective initiation in both the Sahel (Taylor et al 2011) and Europe. The observations indicate a preference for convection to initiate on soil moisture gradients, consistent with many high resolution numerical studies. The ability of models to capture the observed relationships between soil moisture and rainfall in the Sahel has been evaluated. This focuses on models run at different resolutions, and with convective parameterisations switched on or off, and highlights issues associated with the parameterisation of convection. Taylor, C.M., Gounou, A., Guichard, F., Harris, P.P., Ellis, R.J.,Couvreux, F., and M. De Kauwe. 2011, Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns, Nature Geoscience, 4, 430-433, doi:10.1038/ngeo1173 Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P, and W.A. Dorigo. 2012, Afternoon rain more likely over drier soils, Nature, 489, 423-426, doi:10.1038/nature11377

  3. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

    Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

    2015-04-01

    Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

  4. Geostatistical Analysis of Surface Temperature and In-Situ Soil Moisture Using LST Time-Series from Modis

    NASA Astrophysics Data System (ADS)

    Sohrabinia, M.; Rack, W.; Zawar-Reza, P.

    2012-07-01

    The objective of this analysis is to provide a quantitative estimate of the fluctuations of land surface temperature (LST) with varying near surface soil moisture (SM) on different land-cover (LC) types. The study area is located in the Canterbury Plains in the South Island of New Zealand. Time series of LST from the MODerate resolution Imaging Spectro-radiometer (MODIS) have been analysed statistically to study the relationship between the surface skin temperature and near-surface SM. In-situ measurements of the skin temperature and surface SM with a quasi-experimental design over multiple LC types are used for validation. Correlations between MODIS LST and in-situ SM, as well as in-situ surface temperature and SM are calculated. The in-situ measurements and MODIS data are collected from various LC types. Pearson's r correlation coefficient and linear regression are used to fit the MODIS LST and surface skin temperature with near-surface SM. There was no significant correlation between time-series of MODIS LST and near-surface SM from the initial analysis, however, careful analysis of the data showed significant correlation between the two parameters. Night-time series of the in-situ surface temperature and SM from a 12 hour period over Irrigated-Crop, Mixed-Grass, Forest, Barren and Open- Grass showed inverse correlations of -0.47, -0.68, -0.74, -0.88 and -0.93, respectively. These results indicated that the relationship between near-surface SM and LST in short-terms (12 to 24 hours) is strong, however, remotely sensed LST with higher temporal resolution is required to establish this relationship in such time-scales. This method can be used to study near-surface SM using more frequent LST observations from a geostationary satellite over the study area.

  5. Soil Moisture From Satellite Radar Altimetry (SMALT)

    NASA Astrophysics Data System (ADS)

    Smith, R. G.; Salloway, M. K.; Berry, P. A. M.; Dowson, M.; Hahn, S.; Wagner, W.; Egibo, A.; Benveniste, J.

    2013-12-01

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. These DREAMS are complicated to build and require multiple stages of processing and manual intervention. However, this approach obviates the requirement for detailed ground truth to populate theoretical models, facilitating derivation of surface soil moisture estimates over arid regions, where detailed survey data are generally not available. DREAMS have been produced over a number of deserts worldwide and a selection are presented in this paper. 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. In order to validate these products comparisons with other remote sensing techniques and in-situ data have been performed over a number of desert regions. SMALT products are made freely available to the scientific community through the website http://tethys.eaprs.cse.dmu.ac.uk/SMALT

  6. Microwave soil moisture retrieval under trees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    During 2007 a field experiment was conducted with a goal of optimizing microwave soil moisture retrieval algorithms for small to medium deciduous trees. After initial field checkout in Fall 2006, the ComRAD microwave truck instrument system was deployed to a test site with several stands of deciduo...

  7. Estimating Subcanopy Soil Moisture with RADAR

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

    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.

  8. SOIL MOISTURE EXPERIMENTS 2003 (SMEX03)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A series of large-scale soil moisture field experiments have been conducted over the past decade. These have been successful at addressing a broad range of science question, focusing technology development and demonstration, and providing educational experiences for undergraduate and graduate studen...

  9. SMAP validation of soil moisture products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) satellite will be launched by the National Aeronautics and Space Administration in October 2014. SMAP will also incorporate a rigorous calibration and validation program that will support algorithm refinement and provide users with information on the accuracy ...

  10. Soil moisture and temperature algorithms and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Passive microwave remote sensing of soil moisture has matured over the past decade as a result of the Advanced Microwave Scanning Radiometer (AMSR) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...

  11. SOIL MOISTURE EXPERIMENTS IN 2002 AND 2003

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture field experiments have been very successful at addressing a broad range of science question, focusing technology development and demonstration, and providing educational experiences for undergraduate and graduate students. The data have been used in studies that went well beyond the a...

  12. Soil Moisture Active Passive Validation Experiment 2008

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil Moisture Active Passive Validation Experiment 2008 (SMAPVEX08) was conducted to address specific issues identified by the SMAP satellite mission (launch 2013). SMAP is currently addressing issues related to the development and selection of retrieval algorithms as well as refining the mission de...

  13. Impact of Soil Moisture Initialization on Seasonal Weather Prediction

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

    The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.

  14. The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts

    NASA Technical Reports Server (NTRS)

    Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)

    2002-01-01

    Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.

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

    NASA Technical Reports Server (NTRS)

    1980-01-01

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

  16. Preliminary assessment of soil moisture over vegetation

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1986-01-01

    Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.

  17. SMOS observations to evaluate SMAP soil moisture algorithms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One of the products of the proposed SMAP (Soil Moisture Active Passive) mission is soil moisture at a 40 km resolution based solely on the passive microwave radiometer measurements. In this paper we contribute to the development of this level 2 radiometer-only soil moisture algorithm by exploiting t...

  18. Soil moisture inferences from thermal infrared measurements of vegetation temperatures

    NASA Technical Reports Server (NTRS)

    Jackson, R. D. (Principal Investigator)

    1981-01-01

    Thermal infrared measurements of wheat (Triticum durum) canopy temperatures were used in a crop water stress index to infer root zone soil moisture. Results indicated that one time plant temperature measurement cannot produce precise estimates of root zone soil moisture due to complicating plant factors. Plant temperature measurements do yield useful qualitative information concerning soil moisture and plant condition.

  19. Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Validation is an important and particularly challenging task for remote sensing of soil moisture. The key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point wh...

  20. The impact of vertical measurement depth on the information content of soil moisture times series data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using a decade of high-quality ground-based soil moisture observations acquired from the United States Department of Agriculture’s Soil Climate Analysis Network (SCAN), we calculate the mutual information content between multiple soil moisture variables and near-future vegetation condition to examin...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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 freezing, snow cover and terrain effects." Geoscientific Model Development Discussions 6, no. 4 (2013): 6279-6341. Heathman, G. C., P. J. Starks, L. R. Ahuja, and T. J. Jackson. "Assimilation of surface soil moisture to estimate profile soil water content." Journal of Hydrology 279, no. 1 (2003): 1-17. Pasolli, L., C. Notarnicola, L. Bruzzone, G. Bertoldi, S. Della Chiesa, V. Hell, G. Niedrist. "Estimation of Soil Moisture in an Alpine catchment with RADARSAT2 Images." Applied and Environmental Soil Science 2011 (2011)

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1975-01-01

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

  4. Microwave soil moisture estimation in humid and semiarid watersheds

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

    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.

  5. Analysis of the TIR (8-13 ㎛) Emissivity Dependence on Soil Moisture in the Context of the SMOS Mission

    NASA Astrophysics Data System (ADS)

    Valor, E.; Mira, M.; Coll, C.; Caaselles, V.; Rubio, E.; Galve, J. M.; Niclos, R.; Sanchez, J. M.; Boluda, R.

    2010-12-01

    The influence of soil texture on emissivity is well known from experimental studies; however, up to now, few published works analyze the soil moisture (SM) effect on thermal emissivities. The SMOS mission is a good opportunity to address this study by combining data coming from different satellite-borne sensors: the MIRAS SM measurements and LSEs provided by instruments such as MODIS and ASTER. We conducted a laboratory experiment as a preparatory task before the availability of the first SMOS acquisitions. TIR emissivities of soils with different textures were measured for several SM contents under controlled conditions using the Box method and a high-precision multi-channel TIR radiometer. The results showed a common increase of emissivity with SM. The highest emissivity variations were observed in sandy soils, especially in 8-9 μm. A general and unique relationship were obtained considering several soil properties (i.e., organic matter, quartz, and carbonate contents), predicting TIR emissivities from SM with standard estimation errors less than ±0.008.

  6. Estimating Soil Moisture from Satellite Microwave Observations

    NASA Technical Reports Server (NTRS)

    Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

    1998-01-01

    Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data and used to derive the one-way canopy transmissivity. Using a simple radiative transfer model, this information was combined with horizontally polarized 6.6 GHz SMMR observations to derive a 9-year time series of soil moisture for all of Spain at a one quarter degree spatial scale. Both day and night SMMR observations were used independently, in order to check the consistency of the results. A first order Fourier Transform was performed on the mean monthly soil moisture values to identify major characteristics of time series such as trend, amplitude, and phase shift.

  7. Microwave Soil Moisture Retrieval Under Trees

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave 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.

  8. Towards an integrated soil moisture drought monitor for East Africa

    NASA Astrophysics Data System (ADS)

    Anderson, W. B.; Zaitchik, B. F.; Hain, C. R.; Anderson, M. C.; Yilmaz, M. T.; Mecikalski, J.; Schultz, L.

    2012-04-01

    Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010-2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

  9. Towards an integrated soil moisture drought monitor for East Africa

    NASA Astrophysics Data System (ADS)

    Anderson, W. B.; Zaitchik, B. F.; Hain, C. R.; Anderson, M. C.; Yilmaz, M. T.; Mecikalski, J.; Schultz, L.

    2012-08-01

    Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010-2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

  10. Investigating soil controls on soil moisture spatial variability: Numerical simulations and field observations

    NASA Astrophysics Data System (ADS)

    Wang, Tiejun; Franz, Trenton E.; Zlotnik, Vitaly A.; You, Jinsheng; Shulski, Martha D.

    2015-05-01

    Due to its complex interactions with various processes and factors, soil moisture exhibits significant spatial variability across different spatial scales. In this study, a modeling approach and field observations were used to examine the soil control on the relationship between mean (θ bar) and standard deviation (σθ) of soil moisture content. For the numerical experiments, a 1-D vadose zone model along with van Genuchten parameters generated by pedotransfer functions was used for simulating soil moisture dynamics under different climate and surface conditions. To force the model, hydrometeorological and physiological data that spanned over three years from five research sites within the continental US were used. The modeling results showed that under bare surface conditions, different forms of the θ bar -σθ relationship as observed in experimental studies were produced. For finer soils, a positive θ bar -σθ relationship gradually changed to an upward convex and a negative one from arid to humid conditions; whereas, a positive relationship existed for coarser soils, regardless of climatic conditions. The maximum σθ for finer soils was larger under semiarid conditions than under arid and humid conditions, while the maximum σθ for coarser soils increased with increasing precipitation. Moreover, vegetation tended to reduce θ bar and σθ, and thus affected the θ bar -σθ relationship. A sensitivity analysis was also conducted to examine the controls of different van Genuchten parameters on the θ bar -σθ relationship under bare surface conditions. It was found that the residual soil moisture content mainly affected σθ under dry conditions, while the saturated soil moisture content and the saturated hydraulic conductivity largely controlled σθ under wet conditions. Importantly, the upward convex θ bar -σθ relationship was mostly caused by the shape factor n that accounts for pore size distribution. Finally, measured soil moisture data from a semiarid region were retrieved from the Automated Weather Data Network. The observed moisture data showed that based on soil texture, a positive θ bar -σθ relationship existed for sandy soils, while an upward convex one was observed for silty soils. The difference in the observed θ bar -sigmaθ relationship can be attributed to the differences in water holding capacities between sand and silt, which is consistent with the modeling results. The field data also revealed that increasing spatial variability in soil texture led to increased variability in soil moisture (e.g., the maximum σθ). Therefore, the effect of soil texture for verifying remotely sensed soil moisture products should be considered.

  11. SMOS validation of soil moisture and ocen salinity (SMOS) soil moisture over watershed networks in the U.S.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must b...

  12. Application of triple collocation for the ground-based validation of soil moisture active/passive (SMAP) soil moisture products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The contrast in horizontal spatial support between ground-based soil moisture observations and satellite-derived soil moisture estimates represents a long-standing challenge for the validation of satellite soil moisture data products [Crow et al., 2014]. This challenge can be alleviated by limiting ...

  13. Synergies and complementarities between ASCAT and SMOS soil moisture products

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

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

    USGS Publications Warehouse

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

    2006-01-01

    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.

  15. A method for estimating soil moisture availability

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1985-01-01

    A method for estimating values of soil moisture based on measurements of infrared surface temperature is discussed. A central element in the method is a boundary layer model. Although it has been shown that soil moistures determined by this method using satellite measurements do correspond in a coarse fashion to the antecedent precipitation, the accuracy and exact physical interpretation (with respect to ground water amounts) are not well known. This area of ignorance, which currently impedes the practical application of the method to problems in hydrology, meteorology and agriculture, is largely due to the absence of corresponding surface measurements. Preliminary field measurements made over France have led to the development of a promising vegetation formulation (Taconet et al., 1985), which has been incorporated in the model. It is necessary, however, to test the vegetation component, and the entire method, over a wide variety of surface conditions and crop canopies.

  16. Development of a measurement operator for cosmic ray soil moisture observations

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Cosmic ray sensors measure neutron fluxes close to the earth surface. Effective absorption of energetic cosmic rays by hydrogen nuclei in the soil establishes a direct relationship between measured neutron flux and soil moisture content. Using this relationship, cosmic ray sensors are becoming increasingly popular for measuring soil moisture content at the field scale. The interesting aspect of the measurement is that the average soil moisture content (with diameter around 600 m and a vertical depth up to 70 cm) over a larger scale can be obtained (Zreda et al., 2008). However, the relation between the spatial distribution of soil moisture content in the footprint of a cosmic ray probe and the measured number of neutron counts is non-linear and the exact relationship is still subject to uncertainty. The soil moisture monitoring network SoilNet (Bogena et al. 2010) established in the framework of the TERENO project offers an excellent opportunity to compare soil moisture measurements and neutron counts and improve the calibration of cosmic ray probes. The established relation between the two methods is a non-linear measurement operator in a data assimilation framework. Here soil moisture contents measured in Rollesbroich (Eifel, Germany) at 83 locations and 3 depths (5, 20 and 50 cm) were used to calibrate a cosmic ray probe. First results of the analysis to illustrate the influence of soil moisture heterogeneity in the cosmic ray footprint, the relation between mean soil moisture content and vertical footprint, as well as the causes for deviations between soil moisture content measured by a cosmic ray probe and by SoilNet will be shown. It will be demonstrated that a good correspondence between measured soil moisture contents by TDR or FDR and soil moisture estimated with a cosmic ray probe for a period of a few months does not guarantee a good fit at other times of the year.

  17. NASA Soil Moisture Active Passive (SMAP) Applications

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  18. NASA's Soil Moisture Active Passive (SMAP) observatory

    NASA Astrophysics Data System (ADS)

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

    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.

  19. Methods of measuring soil moisture in the field

    USGS Publications Warehouse

    Johnson, A.I.

    1962-01-01

    For centuries, the amount of moisture in the soil has been of interest in agriculture. The subject of soil moisture is also of great importance to the hydrologist, forester, and soils engineer. Much equipment and many methods have been developed to measure soil moisture under field conditions. This report discusses and evaluates the various methods for measurement of soil moisture and describes the equipment needed for each method. The advantages and disadvantages of each method are discussed and an extensive list of references is provided for those desiring to study the subject in more detail. The gravimetric method is concluded to be the most satisfactory method for most problems requiring onetime moisture-content data. The radioactive method is normally best for obtaining repeated measurements of soil moisture in place. It is concluded that all methods have some limitations and that the ideal method for measurement of soil moisture under field conditions has yet to be perfected.

  20. NASA Soil Moisture Data Products and Their Incorporation in DREAM

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

    2005-01-01

    NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.

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

    NASA Technical Reports Server (NTRS)

    Bolten, John D.; Lakshmi, Venkat

    2009-01-01

    The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.

  2. Assimilation of Passive and Active Microwave Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.

  3. Estimation of soil moisture from diurnal surface temperature observations

    NASA Technical Reports Server (NTRS)

    Vandegriend, A. A.; Camillo, P. J.

    1986-01-01

    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 thermal conductivity and heat capacity to relate soil moisture and thermal inertia as a function of soil type. A sensitivity study of the surface roughness length and thermal inertia on diurnal surface temperature shows the necessity of focusing on the night time surface temperature rather than on the day time surface temperature, in order to estimate the soil moisture content of the top soil.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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 (m/m), 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 km). 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.

  5. Root-zone soil moisture estimation using data-driven methods

    NASA Astrophysics Data System (ADS)

    Kornelsen, Kurt C.; Coulibaly, Paulin

    2014-04-01

    The 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.

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

    USGS Publications Warehouse

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

    2008-01-01

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

  7. Evolution of physical controls for soil moisture in humid and subhumid watersheds

    NASA Astrophysics Data System (ADS)

    Gaur, Nandita; Mohanty, Binayak P.

    2013-03-01

    The covariability of soil moisture with soil, vegetation, topography, and precipitation is linked by physical relationships. The influence of each of these interdependent physical controls on soil moisture spatial distribution depends on the nature of heterogeneity present in the domain and evolves with time and scale. This paper investigates the effect of three physical controls, i.e., topography (slope), vegetation (type), and soil (texture), on soil moisture spatial distribution in the Little Washita and Walnut Creek watersheds in Oklahoma and Iowa, respectively, at two support scales. Point-support-scale data collected from four soil moisture campaigns (SMEX02, SMEX03, SMEX05, and CLASIC07) and airborne-scale data from three soil moisture campaigns (SGP97, SGP99, and SMEX02) were used in this analysis. The effect of different physical controls on the spatial mean and variability of soil moisture was assessed using Kruskal-Wallis and Shannon entropy respectively. It was found that at both (point and airborne) support scales, nonuniform precipitation (forcing) across the domain can mask the effect of the dominant physical controls on the soil moisture distribution. In order to isolate land-surface controls from the impact of forcing, the effect of precipitation variability was removed. After removing the effect of precipitation variability, it was found that for most soil moisture conditions, soil texture as opposed to vegetation and topography is the dominant physical control at both the point and airborne scales in Iowa and Oklahoma. During a very wet year (2007), however, the effect of topography on the soil moisture spatial variability overrides the effect of soil texture at the point support scale. These findings are valuable for developing any physically based scaling algorithms to upscale or downscale soil moisture between the point and watershed scales in the studied watersheds in humid and subhumid regions of the Great Plains of USA. These results may also be used in designing effective soil moisture field campaigns.

  8. Uncertainty in SMAP Soil Moisture Measurements Caused by Dew

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an important reservoir of the hydrologic cycle that regulates the exchange of moisture and energy between the land surface the atmosphere. Two satellite missions will soon make the first global measurements of soil moisture at the optimal microwave wavelength within L-band: ESA's So...

  9. Ultrasonic Velocity Variations with Soil Composition for Moisture Measurement

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Tang, Chunling; Piechota, Thomas C.

    2009-12-01

    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.

  11. The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne

    2015-04-01

    Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.

  12. Effect of soil hydraulic properties on the relationship between soil moisture variability and its mean value

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Knowledge of soil moisture and its variability is needed for many environmental applications. We analyzed dependencies of soil moisture variability on average soil moisture contents in bare soils using ensembles of non-stationary water flow simulations by varying soil hydraulic properties under diff...

  13. Research on Regional Spatial Variability of Soil Moisture Based on GIS

    NASA Astrophysics Data System (ADS)

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

    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.

  14. Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products

    NASA Astrophysics Data System (ADS)

    Rahmani, Abdolaziz; Golian, Saeed; Brocca, Luca

    2016-06-01

    Soil moisture (SM) plays a fundamental role for many hydrological applications including water resources, drought analysis, agriculture, and climate variability and extremes. SM is not measured in most parts of Iran and limited measurements do not meet sufficient temporal and spatial resolution. Hence, due to ease of operation, their global coverage and demonstrated accuracy, use of remote sensing SM products is almost the only way for deriving SM information in Iran. In the present research, surface SM (SSM) datasets at six subregions of Iran with different climate conditions were extracted from two satellite-based passive (SMOSL3) and active + passive (ESA CCI SM) microwave observations, and two reanalysis (ERA-Interim and ERA-Interim/Land) products. Time series of averaged monthly mean SSM products and in situ ground precipitation and temperature measurements were derived for each subregion. Results revealed that, generally, all SSM products were in good agreement with each other with correlation coefficients higher than 0.5. The better agreement was found in the Northeast and Southwest region with average correlation values equal to 0.88 and 0.91, respectively. It should be noted that the SSM datasets are characterized by different periods and lengths. Hence, results should be assessed with cautious. Moreover, most SSM products have strong correlations with maximum, minimum and average temperature as well as with total monthly precipitation. Also, trend analysis showed no trend for time series of monthly SSM over all subregions in the two periods 1980-1999 and 2000-2014. The only exceptions were the Southeast subregion for ERA-Interim and Center and Northwest subregions for the ESA CCI SM for which a negative trend was detected for the period 2000-2014. Finally, the Standardized Soil Moisture Index (SSI) calculated from ERA-Interim, ERA-I/Land and ESA CCI SM datasets showed that the Center and Southeast regions suffered from the most severe and longest-lasting drought events in the last decade.

  15. Detecting soil moisture impacts on convective initiation in Europe

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher

    2015-04-01

    Climate models suggest that soil moisture feedbacks on precipitation can play an important role in shaping the climate of some regions of the world. However, observational studies to evaluate models have produced a diverse range of conclusions, depending on scale, methodology, region etc. Our recent global study (Taylor et al, Nature 2012) showed that afternoon rain is more likely to develop over dry soils than nearby (50-100km) wetter areas. This is in contrast to typical global and regional models which favour a positive feedback. One key part of the feedback is the sensitivity of convective initiation to surface fluxes. Whilst some studies consider this in a purely one-dimensional sense, others have argued that spatial variability in fluxes plays an important role in convective triggering, via mesoscale circulations. In semi-arid Africa at least, there is an emerging observational and modelling consensus that it is the spatial heterogeneity of soil moisture which is the key to its influence on deep convective initiation. This study presents the first comprehensive observational analysis over Europe linking convective initiation to soil moisture, based on satellite observations. It builds on our previous global analysis, which indicated over Europe a weak but significant favouring of afternoon rain over locally drier soil at the 50 km scale. Higher space and time resolution satellite datasets are employed in the current study, which can shed light on the dominant mechanisms responsible. Afternoon convective initiations are defined by rapidly cooling cloud-tops using Meteosat images available every 15 minutes. To minimise the impact of fixed triggers such as mountains and coastlines, the analysis is restricted to flat inland regions, which means that most of the 2962 cases are located in central and eastern Europe. Land surface conditions preceding the initiation are characterised by MODIS land surface temperature and ASCAT soil moisture data, whilst wind conditions are taken from ERA-Interim reanalysis. The results show that convective initiations are favoured on the downwind side of dry surfaces, close to wetter areas. The signal is clearest following dry periods and under light winds, consistent with forcing by a mesoscale circulation. Overall, the detected signal in Europe is weaker than in previous African analysis, but key spatial characteristics are essentially the same. This implies that the previous observation of afternoon rain favoured over drier soil in Europe is associated with heterogeneous soil moisture, rather than dry soil per se.

  16. Passive Microwave Soil Moisture Downscaling Using Vegetation and Surface Temperatures

    NASA Astrophysics Data System (ADS)

    Fang, B.; Lakshmi, V.

    2012-12-01

    Soil moisture satellite estimates are available from a variety of passive microwave satellite missions, but their resolution is frequently too large for use by land managers and action agencies. In this article, a soil moisture downscaling algorithm based on look-up curves between daily temperature change and daily average soil moisture is presented and developed to bridge the scale. The algorithm was derived from 1/8o spatial resolution North American Land Data Assimilation System (NLDAS-2) surface temperature and soil moisture data, and also used 5 km Advanced Very High Resolution Radiometer (AVHRR) and 1km Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) as look-up dataset for different vegetation and surface temperature conditions. The differences between 1km MODIS temperature downscaled soil moisture values and Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture values were used to modify AMSR-E soil moistures. The 1km downscaled soil moisture maps display greater details on the spatial pattern of soil moisture distribution. Two sets of ground-based measurements, the Oklahoma Mesonet and the Little Washita Micronet were used to validate the algorithm. The Root Mean Square Error (RMSE) of the 1km downscaled soil moisture versus Oklahoma Mesonet observations for clear days ranges from 0.119~0.168, whereas the RMSE of 1km downscaled soil moisture versus the Little Washita Watershed observations ranges from 0.022~0.077. The results demonstrate that the 1 km downscaled soil moisture has better agreement with watershed in situ data compared to the other sources of soil moisture.

  17. Measurement of soil moisture using remote sensing multisensor radiation techniques

    NASA Technical Reports Server (NTRS)

    Waite, W. P. (Principal Investigator)

    1982-01-01

    Theoretical modeling as well as laboratory and field measurement were coupled with analysis of aircraft data obtained from controlled sites in an effort to enhance understanding of the microwave response due to soil moisture so as to specify sensor parameters and develop inversion algorithms. Models to predict the complex dielectric constant were produced which led to the interpretation of the results in terms of a matrix potential rather than simply moisture content. Similar advances were made in the development of coherent and incoherent radiative transfer models and rough surface scattering models.

  18. Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend

    NASA Astrophysics Data System (ADS)

    Qiu, Jianxiu; Gao, Quanzhou; Wang, Sheng; Su, Zhenrong

    2016-06-01

    In this study, soil moisture trend during 1996-2010 in China was analyzed based on three soil moisture data sets, namely microwave-based multi-satellite surface soil moisture product released from European Space Agency's Climate Change Initiative (ESA CCI), ERA-Interim/Land reanalysis, and in-situ measurements collected from the nationwide agro-meteorological network. Taking the in-situ soil moisture as reference, it is found that ESA CCI generally captured soil moisture trend more accurately than ERA-Interim/Land did. From the spatial distribution of trend analysis results, it is seen that significant decreasing trend for summer soil moisture in northwestern China and northern Inner Mongolia, as well as the significant increasing trend for autumn soil moisture in northern China were identified by both ESA CCI and ERA-Interim/Land. This is in alignment with results from gauge-based precipitation provided by Institute of Geographic Sciences and Natural Resources Research (IGSNRR) and satellite-based precipitation from Tropical Rainfall Measuring Mission (TRMM). However, disagreements in derived trends between ESA CCI, ERA-Interim/Land and IGSNRR were observed in the southwest and north of China, especially in major irrigation regions, such as the oases in northern Xinjiang and large areas in Sichuan province. Prominent difference between soil moisture and precipitation exhibited in the extensively irrigated Huang-Huai-Hai Plain. The spatial coincidence between significantly wetting areas (identified by ESA CCI) and heavily irrigated areas, as well as the grid-based Student's t-test sampling from various irrigation levels revealed that the observed discrepancy was caused by massive anthropogenic interference in this region. Results indicate that, for regions with great magnitude of human interference, modules considering actual irrigation practice are crucial for successful modeling of soil moisture and capturing the long-term trend. Furthermore, results could provide insights on hindcast of historical irrigation areas using satellite-based precipitation and soil moisture data sets.

  19. Concerning the relationship between evapotranspiration and soil moisture

    NASA Technical Reports Server (NTRS)

    Wetzel, Peter J.; Chang, Jy-Tai

    1987-01-01

    The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  1. Remote sensing of soil moisture with microwave radiometers

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

    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.

  2. Spatio-temporal variation of surface soil moisture over the Yellow River basin during 1961-2012

    NASA Astrophysics Data System (ADS)

    Tong, R.; Yang, X.; Ren, L.; Shen, H.; Shan, H.; Kong, H.; Lin, C.

    2015-05-01

    Soil moisture plays a significant role in agricultural and ecosystem development. However, in the real world soil moisture data are very limited due to many factors. VIC-3L model, as a semi-distribution hydrological model, can potentially provide valuable information regarding soil moisture. In this study, daily soil moisture contents in the surface soil layer (0-10 cm) of 1500 grids at 0.25 × 0.25 degree were simulated by the VIC-3L model. The Mann-Kendall trend test and Morlet wavelet analysis methods were used for the analysis of annual and monthly average surface soil moisture series. Results showed that the trend of surface soil moisture was not obvious on the basin scale, but it varied with spatial and temporal conditions. Different fluctuation amplitudes and periods of surface soil moisture were also discovered on the Yellow River basin during 1961 to 2012.

  3. 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)

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

    2012-01-01

    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.

  4. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.

  5. Soil Moisture Spatial Patterns in a Uniform Paulownia Tree Stand

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture spatial patterns have been studied at length in agricultural fields and pasture/rangelands as part of the USDA soil moisture satellite validation program, but recent research has begun to address the distribution of soil beneath a forest canopy. Forests cover a significant portion of ...

  6. Mesoscale Monitoring of Soil Moisture Across a Statewide Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an important component in many hydrologic and land-atmosphere interactions. Understanding the spatial and temporal nature of soil moisture on the mesoscale is vital to determine the influence that land surface processes have upon the atmosphere. Sensing devices to measure soil moi...

  7. Temporal dynamics and spatial heterogeneity of soil moisture in a northern temperate deciduous forest

    NASA Astrophysics Data System (ADS)

    He, L.; Ivanov, V. Y.; Vogel, C. S.; Bohrer, G.; Moghaddam, M.

    2010-12-01

    Soil moisture in forest environments is variable both in time and space, strongly influencing water and energy fluxes between the land surface and the atmosphere. However, few continuous, deep profile soil moisture datasets exist for temperate forest environments. Our study has initiated measurements of soil moisture in a heterogeneous deciduous forest environment of Northern Michigan in April 2009. Our research site is at the Forest Accelerated Succession ExperimenT (FASET) at the University of Michigan Biological Station (UMBS) where canopy structure was manipulated to represent a large disturbance and a successional phase shift by girdling all mid-successional canopy-dominant aspen and birch trees over 33 Ha. The nearby UMBS-AmeriFlux tower site serves as the un-manipulated control. In total, forty four sensors were deployed at four different locations. They provide half-hourly data on soil water content and temperature over the 3m-deep profiles at multiple depths ( 5, 15, 30, 60, 100, 200 and 300cm). In this study, we examine the temporal dynamics of deep-profile soil moisture and correlation between near-surface and deeper layer soil moisture. Through the analysis of data over the observational period we demonstrate that soil moisture was influenced by differences in canopy structure. Specifically, deep soil moisture (integrated over the root zone or deeper than 300 cm) has been consistently larger at the experimental than at the control site. Furthermore, correlation analysis between near-surface soil moisture and deeper layer soil moisture over the four sites provides inferences pointing to the non-uniqueness of the relationship that has an important implication for remotely sensed near-surface soil moisture. In addition to continuous point measurements, periodic observations of near-surface soil moisture during growing-season were conducted at two nested 50m X 50m plots and at long transects in the footprints of the AmeriFlux and FASET towers. This dataset was used to characterize the evolution of spatial heterogeneity of soil moisture states in the forest environment. By combining high resolution point-scale soil moisture profile data with periodic near-surface soil moisture measurements, this study has also examined the representativeness of point-scale measurement with regards to the spatially mean soil moisture state.

  8. Soil Moisture Experiments 2005 (SMEX05): Passive Microwave Polarimetric Signature Of Soil Moisture and Vegetation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microwave remote sensing provides a direct measurement of soil moisture; however, there have been many challenges in algorithm science and technology that we have faced on the path to providing global measurements. Field experiments, especially those involving both ground and aircraft measurements, ...

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

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

    Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

    Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

  11. Controlling Factors of Root-Zone Soil Moisture Spectra in Tropical and Temperate Forests

    NASA Astrophysics Data System (ADS)

    Nakai, T.; Katul, G. G.; Kotani, A.; Igarashi, Y.; Ohta, T.; Kumagai, T.

    2014-12-01

    Characteristics of root-zone soil moisture spectra in a subtropical monsoon forest in Thailand (Mae Moh) and two warm-temperate forests in the US (Duke) and Japan (Seto) were examined for time scales ranging from 30 minutes to multiple years. These forested areas have comparable maximum leaf area index but markedly different phase relations between evapotranspiration, net radiation, precipitation, and soil moisture. A hierarchy of models that sequentially introduce the spectrum of precipitation, net radiation, and nonlinearites in the damping originating from stomatal controls and drainage losses were used. If the precipitation is random, and the damping term by evapotranspiration and drainage is increased linearly with increasing soil moisture, the temporal variability of soil moisture simplifies to a first order Markov process commonly employed in the analysis of soil moisture in climate models. Its spectrum exhibits a Lorentz function with a white-noise behavior at low frequency and red-noise behavior at high frequency separated by a time-scale constant for intermediate frequencies. Such first order Markov process model with its time scale defined by the maximum wet surface evapotranspiration, soil porosity, and root-zone depth did not represent the observed soil moisture spectra at all three sites. Adding the effect of precipitation and net radiation variability were necessary for representing the actual soil moisture spectra. While the observed soil moisture spectra were satisfactorily reproduced by these additions, the relative importance of precipitation and net radiation to the soil moisture spectra differed between sites. The soil moisture memory, inferred from the observed soil moisture spectra (model decay time scale), was about 25-38 days, which was larger than that determined from maximum wet evapotranspiration and available pore space alone, except that these two time scales in Seto forest were nearly the same.

  12. Long-term trend and variability of soil moisture over East Asia

    NASA Astrophysics Data System (ADS)

    Cheng, Shanjun; Guan, Xiaodan; Huang, Jianping; Ji, Fei; Guo, Ruixia

    2015-09-01

    The variability of soil moisture over East Asia was analyzed using a long-term data set from the Global Land Data Assimilation System. Overall, a clear decreasing trend occurred over a period of 63 years, with pronounced drying over northeast China, north China, part of Mongolia, and Russia near lake Baikal. Statistical analyses show that decreasing precipitation and global warming have different effects on the decrease in soil moisture. The qualitative analysis and quantitative contributions illustrated that soil drying is driven primarily by decreasing precipitation and is enhanced almost twofold by increasing temperatures. As soil moisture decreases, the positive feedback between soil moisture and temperature may result in future water shortages. Following the Representative Concentration Pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) simulation scenarios of Coupled Model Intercomparison Project phase 5, the model-predicted soil moisture demonstrated a continuously decreasing trend during the 21st century.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An 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.

  14. BOREAS HYD-1 Volumetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

    Cuenca, Richard H.; Kelly, Shaun F.; Stangel, David E.; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-1 team made measurements of volumetric soil moisture at the Southern Study Area (SSA) and Northern Study Area (NSA) tower flux sites in 1994 and at selected tower flux sites in 1995-97. Different methods were used to collect these measurements, including neutron probe and manual and automated Time Domain Reflectometry (TDR). In 1994, the measurements were made every other day at the NSA-OJP (Old Jack Pine), NSA-YJP (Young Jack Pine), NSA-OBS (Old Black Spruce), NSA-Fen, SSA-OJP, SSA-YJP, SSA-Fen, SSA-YA (Young Aspen), and SSA-OBS sites. In 1995-97, when automated equipment was deployed at NSA-OJP, NSA-YJP, NSA-OBS, SSA-OBS, and SSA-OA (Old Aspen), the measurements were made as often as every hour. The data are stored in tabular ASCII files. The volumetric 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).

  15. Recent Enhancements in the North American Soil Moisture Database (NASMD)

    NASA Astrophysics Data System (ADS)

    Chavez, N.; Galvan, J., III; Quiring, S. M.; Ford, T.

    2014-12-01

    The North American Soil Moisture Database (soilmoisture.tamu.edu) is a high-quality observational soil moisture database that contains data from >1800 stations. In the last year we have enhanced the database by identifying sites in Mexico and expanding the database to also include soil temperature data. Here we provide an overview of how the in situ soil moisture and soil temperature observations are assembled, quality controlled and harmonized prior to being incorporated in the NASMD. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    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.

  17. High Latitude Soil Moisture Observations to Study Climate Variations and to Evaluate Climate Models

    NASA Astrophysics Data System (ADS)

    Robock, A.; Vinnikov, K. Y.; Luo, L.; Mu, M.

    2002-12-01

    Soil moisture is an important variable in the climate system. Understanding and predicting variations of surface temperature, drought, and flood depend critically on knowledge of soil moisture variations, as do impacts of climate change and seasonal climate forecasting. An observational data set of actual in situ measurements is crucial for model development and evaluation, and as ground truth for remote sensing. The Global Soil Moisture Data Bank is a web site (http://climate.envsci.rutgers.edu/soil_moisture) dedicated to collection, dissemination, and analysis of soil moisture data from around the globe, and is a resource for the remote sensing, climate modeling and climate analysis communities. We currently have soil moisture observations for over 400 stations from a large variety of global climates, including from the former Soviet Union, China, Mongolia, India, and the US, but not many from high latitude locations. We will describe two examples of different uses of these data sets. We have used the data to examine the impact of explicitly including frozen soil in land surface models on the partition of snow melt into runoff and infiltration, as a continuation of analysis of the PILPS Phase 2(d) experiment in Valdai, Russia, and to examine the role of soil moisture in serving as a memory for snow cover anomalies to influence the Asian summer monsoon. We find that inclusion of frozen soil is important for accurate simulations of soil temperature, but not as important for soil moisture in high latitudes, since the soil tends to be saturated and there is insufficient capacity for a large influence on infiltration. There is no evidence for soil moisture serving as snow cover memory.

  18. [Soil moisture dynamics of apple orchard in Loess Plateau dryland].

    PubMed

    Zhao, Gang; Fan, Ting-lu; Li, Shang-zhong; Zhang, Jian-jun; Wang, Yong; Dang, Yi; Wang, Lei

    2015-04-01

    The soil moisture of 0-500 cm soil layer in a dryland orchard at its full fruit period was measured from 2009 to 2013 to explore the soil moisture dynamics. Results indicated that soil water consumption mainly occurred in the soil layer of 0-300 cm in normal rainfall year and below the 300 cm soil layer when the annual rainfall was less than 400 mm. The soil moisture in the 200-300 cm soil layer fluctuated most and was affected by rainfall and apple consumption. Seasonal drought usually happened between April and late June, while the accumulation of soil moisture mainly occurred in the rainy season from July to mid-October to alleviate the drought effectively in next spring. PMID:26259464

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

    NASA Astrophysics Data System (ADS)

    Puri, Sumit; Stephen, Haroon; Ahmad, Sajjad

    2011-05-01

    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 ( σ°) 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.

  20. Development and Validation of Global Soil Moisture Data Products from GCOM-W1/AMSR2 and NESDIS SMOPS

    NASA Astrophysics Data System (ADS)

    Zhan, X.; Liu, J.; Fang, L.; Hain, C.

    2014-12-01

    Soil moisture is a critical component of the regional and global water and energy cycle. It controls the exchanges of water, energy and carbon between land surface and the atmosphere and has significant impact on the accuracy of numerical weather predictions (NWP). To meet the near real time soil moisture data needs, NOAA NESDIS has developed a soil moisture environmental data record (EDR) from the Advanced Microwave Scanning Radiometer 2 on board the 1st Global Climate Observation Mission for Water Cycle (GCOM-W1) of JAXA. The level2 soil moisture EDR is also merged with other satellite soil moisture observations via NESDIS Soil Moisture Operational Product System (SMOPS) so that users at NCEP could assimilate all the available satellite soil moisture observations for NWP model accuracy. This presentation will describe the AMSR2 soil moisture EDR and how it is merged with similar soil moisture retrievals from ESA's Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Scatterometer (ASCAT) on MetOp-A and MetOp-B satellites of EUMETSAT, and Naval Research Lab's WindSat satellite. Qualities of these merged and individual satellite soil moisture data sets are evaluated against the in situ soil moisture measurements of various ground observation networks such as NOAA's Climate Reference Network (CRN) and USDA's Soil Climate Analysis Network (SCAN). They are also compared with the Essential Climate Variable (ECV) soil moisture data set and the soil moisture simulations by the Noah land surface model of NCEP. Application of the AMSR2 and SMOPS data sets in NWP models has demonstrated positive impact of the satellite soil moisture products on NWP models.

  1. Soil Moisture derivation from the multi-frequency sensor AMSR-2

    NASA Astrophysics Data System (ADS)

    Parinussa, Robert; de Nijs, Anne; de Jeu, Richard; Holmes, Thomas; Dorigo, Wouter; Wanders, Niko; Schellekens, Jaap

    2015-04-01

    We present a method to derive soil moisture from the multi-frequency sensor Advanced Microwave Scanning Radiometer 2 (AMSR-2). Its predecessor, the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), has already provided Earth scientists with a consistent and continuous global soil moisture dataset. However, the AMSR-2 sensor has one big advantage in relation to the AMSR-E sensor; is has an additional channel in the C-band frequency (7.3 GHz). This channel creates the opportunity to have a better screening for Radio Frequency Interference (RFI) and could eventually lead to improved soil moisture retrievals. The soil moisture retrievals from AMSR-2 we present here use the Land Parameter Retrieval Model (LPRM) in combination with a new radio frequency interference masking method. We used observations of the multi-frequency microwave radiometer onboard the Tropical Rainfall Measuring Mission (TRMM) satellite to intercalibrate the brightness temperatures in order to improve consistency between AMSR-E and AMSR-2. Several scenarios to accomplish synergy between the AMSR-E and AMSR-2 soil moisture products were evaluated. A global comparison of soil moisture retrievals against ERA Interim re-analysis soil moisture demonstrates the need for an intercalibration procedure. Several different scenarios based on filtering were tested and the impact on the soil moisture retrievals was evaluated against two independent reference soil moisture datasets (reanalysis and in situ soil moisture) that cover the observation periods of the AMSR-E and AMSR-2 sensors. Results show a high degree of consistency between both satellite products and two independent reference products for the soil moisture products. In addition, the added value of an additional frequency for RFI detection is demonstrated within this study with a reduction of the total contaminated pixels in the 6.9 GHz of 66% for horizontal observations and even 85% for vertical observations when 7.3 and 10.7 GHz are used.

  2. Evaluation and Application of Remotely Sensed Soil Moisture Products

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    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.

  3. A nonlinear coupled soil moisture-vegetation model

    NASA Astrophysics Data System (ADS)

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

    2005-06-01

    Based on the physical analysis that the soil moisture and vegetation depend mainly on the precipitation and evaporation as well as the growth, decay and consumption of vegetation a nonlinear dynamic coupled system of soil moisture-vegetation is established. Using this model, the stabilities of the steady states of vegetation are analyzed. This paper focuses on the research of the vegetation catastrophe point which represents the transition between aridness and wetness to a great extent. It is shown that the catastrophe point of steady states of vegetation depends mainly on the rainfall P and saturation value v0, which is selected to balance the growth and decay of vegetation. In addition, when the consumption of vegetation remains constant, the analytic solution of the vegetation equation is obtained.

  4. Incorporation of Soil Moisture into Real-Time Hydrologic Simulation

    NASA Astrophysics Data System (ADS)

    Bosch, D. D.; Jackson, T.; Lakshmi, V.; Sheridan, J.; Arnold, J.

    2005-05-01

    Soil moisture data collected from an in situ network and from satellite measurements were used to enhance estimates of streamflow for the Suwannee River Basin in the Southeastern U.S. Coastal Plain. Soil Moisture data collected from the AMSR-E instrument as well as the in situ data were used. The Soil Water Assessment Tool (SWAT) was used for the hydrologic simulations. Simulated stream-flow characteristics were compared to observed data from the Basin. Simulations using the observed soil moisture data were compared to those obtained without the soil moisture observations. Improvements obtained through incorporation of the observed soil moisture, based upon peak flow and volume estimates, were quantified. If successful, the real time estimates will be used to improve drought, flood, and agronomic production forecasts.

  5. A microwave systems approach to measuring root zone soil moisture

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

    Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.

  6. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

    Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

  7. Impact of Surface Soil Moisture of Pesticide Volatilization Fluxes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Volatilization of pesticides can detrimentally affect the environment by contaminating soil and surface waters many kilometers from where the pesticides were applied and intended. To improve quantifying the effect of soil moisture and meteorological interactions on pesticides volatization, metolach...

  8. Remote sensing as a tool in assessing soil moisture

    NASA Technical Reports Server (NTRS)

    Carlson, C. W.

    1978-01-01

    The effects of soil moisture as it relates to agriculture is briefly discussed. The use of remote sensing to predict scheduling of irrigation, runoff and soil erosion which contributes to the prediction of crop yield is also discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  10. SMOS Soil moisture Cal val activities

    NASA Astrophysics Data System (ADS)

    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

    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.

  11. Joint microwave and infrared studies for soil moisture determination

    NASA Technical Reports Server (NTRS)

    Njoku, E. G.; Schieldge, J. P.; Kahle, A. B. (Principal Investigator)

    1980-01-01

    The feasibility of using a combined microwave-thermal infrared system to determine soil moisture content is addressed. Of particular concern are bare soils. The theoretical basis for microwave emission from soils and the transport of heat and moisture in soils is presented. Also, a description is given of the results of two field experiments held during vernal months in the San Joaquin Valley of California.

  12. Evaluation of a Soil Moisture Data Assimilation System Over West Africa

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

    A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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.

  14. Soil moisture determination study. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1979-01-01

    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.

  15. Estimation of Soil Moisture With Dual-Frequency-PALS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The purpose of this study is to evaluate whether the NASA/JPL dual frequency airborne system, Passive Active L-band and S-band (PALS), can provide a reliable soil moisture measurements so that they can be integrated to provide soil moisture data at the scales of the spaceborne coarse resolutions. Th...

  16. WindSat Soil Moisture Algorithm and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A WindSat land algorithm that retrieves global soil moisture and vegetation water content simultaneously using the physically-based multi-channel maximum-likelihood estimation was developed and evaluated. The retrievals agree well with soil moisture climatology, and in-situ data collected from a ser...

  17. Soil Moisture Active Passive Validation Experiment 2008 (SMAPVEX08)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive Mission (SMAP) is currently addressing issues related to the development and selection of soil moisture retrieval algorithms. Several forums have identified a number of specific questions that require supporting field experiments. Addressing these issues as soon as p...

  18. SMOS Soil Moisture Validation with Dense and Sparse Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Validation is an important but particularly challenging task for passive microwave remote sensing of soil moisture from Earth orbit. The key issue is spatial scale; conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value for a ...

  19. Timescales of Soil Moisture Anomalies: Results from Two GCMs

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Milly, P. C. D.; Schlosser, C. Adam; Suarez, Max J.

    1999-01-01

    Soil moisture anomalies dissipate over timescales that may span weeks to months. Characterizing the geographical and seasonal variations in these timescales can have important practical benefit; significant soil moisture "memory" allows long-lead forecasts of soil moisture, which have been found in recent studies to be essential for useful Ion--lead forecasts of precipitation in many regions. In this talk, we will present and compare the soil moisture timescales derived in two separate general circulation model (GCM) studies. Both studies employ multiple ensembles of short-term climate simulations. Timescales at a given point are effectively estimated by determining how quickly the soil moisture distribution generated in one ensemble of simulations (characterized by a unique set of initial soil moisture conditions) approaches that produced by another ensemble (characterized by a different set of initial soil moisture conditions). The talk will include a discussion of why the timescales produced by the two GCMs differ in some regions, and it will also describe the impact of soil moisture memory on simulated precipitation.

  20. Enhancing agricultural forecasting using SMOS surface soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the onset of data availability from the ESA Soil Moisture and Ocean Salinity (SMOS) mission (Kerr and Levine, 2008) and the expected 2015 launch of the NASA Soil Moisture Active and Passive (SMAP) mission (Entekhabi et al., 2010), the next five years should see a significant expansion in our ab...

  1. Global Evaluation of Remotely-Sensed Soil Moisture Retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To date, limitations in the availability of ground based soil moisture observations have hampered the large-scale evaluation of remotely-sensed surface soil moisture retrievals. Recently developed evaluation techniques offer the potential to greatly expand the geographic domain over which such retri...

  2. Long term observation and validation of windsat soil moisture data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The surface soil moisture controls surface energy budget. It is a key environmental variable in the coupled atmospheric and hydrological processes that are related to drought, heat waves and monsoon formation. Satellite remote sensing of soil moisture provides information that can contribute to unde...

  3. The Soil Moisture Active/Passive Mission (SMAP)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active/Passive (SMAP) mission will deliver global views of soil moisture content and its freeze/thaw state that are critical terrestrial water cycle state variables. Polarized measurements obtained with a shared antenna L-band radar and radiometer system will allow accurate estima...

  4. Soil Moisture Retrieval Using the Aquarius/SAC-D Instruments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquarius/SAC-D will share common elements with several current and future satellite missions that provide soil moisture. Passive microwave soil moisture retrieval using low frequencies is currently performed using Aqua Advanced Microwave Scanning Radiometer-E (AMSR-E) (C/X-band). This will extended ...

  5. Summer soil moisture spatiotemporal variability in southeastern Arizona

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is important for many applications, but its measurements are lacking globally and even regionally. The Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona has measured nearsurface 5-cm soil moisture with 19 in situ probes since 2002 within its 150km2 area. Using various ...

  6. Filtration and assimilation of soil moisture satellite data

    NASA Astrophysics Data System (ADS)

    Bogoslovskiy, Nikolay N.; Erin, Sergei I.; Borodina, Irina A.; Kizhner, Lubov I.

    2015-11-01

    This paper presents two data filtration methods. These methods are used for filtration of satellite soil moisture measurement data. A comparison with in-situ soil moisture measurement data shows an improvement in data quality after application of the filters. First results of satellite data assimilation with a global model of numerical weather forecasting are given.

  7. Large Scale Field Campaign Contributions to Soil Moisture Remote Sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Large-scale field experiments have been an essential component of soil moisture remote sensing for over two decades. They have provided test beds for both the technology and science necessary to develop and refine satellite mission concepts. The high degree of spatial variability of soil moisture an...

  8. Diurnal variation of diazinon volatilization: Soil moisture effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A field study was conducted to measure the effect of soil moisture on diazinon volatilization under typical semi-arid field conditions. The study comprised three experiments performed with differing soil moisture conditions. Over the course of each three day experiment, diurnal changes in volatiliz...

  9. 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)

    Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

    2014-06-01

    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.

  10. Microwave and gamma radiation observations of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

    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.

  11. Creation and destruction of soil moisture variability by vegetation

    NASA Astrophysics Data System (ADS)

    Guswa, A. J.

    2011-12-01

    Vegetation canopies introduce spatial variability into soil moisture by localizing and concentrating throughfall and stemflow. In the soil, the self-limiting process of plant uptake acts to undo this variability and homogenize soil moisture. Root compensation (increased uptake from wetter regions) and hydraulic redistribution (movement of water from wetter to drier soils via plant roots) enhance this homogenization process. This work investigates the interplay between these processes that create and destroy soil moisture variability via a stochastic modeling framework for both wet and dry climates. Precipitation events arrive as a Poisson process in time, and spatial patterns of throughfall are taken to be temporally persistent. Plant uptake is represented with an electric circuit analog that captures the effects of root compensation as well as hydraulic redistribution. Effects of vegetation on soil-moisture variability and partitioning of hydrologic fluxes are depend on the magnitude of heterogeneity introduced via throughfall, the strength of root processes, and other climate, plant, and soil characteristics.

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

    NASA Astrophysics Data System (ADS)

    Goodchild, Martin; Kühn, Karl; Jenkins, Dick

    2014-05-01

    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.

  13. Using similarity of soil texture and hydroclimate to enhance soil moisture estimation

    NASA Astrophysics Data System (ADS)

    Coopersmith, E. J.; Minsker, B. S.; Sivapalan, M.

    2014-08-01

    Estimating soil moisture typically involves calibrating models to sparse networks of in situ sensors, which introduces considerable error in locations where sensors are not available. We address this issue by calibrating parameters of a parsimonious soil moisture model, which requires only antecedent precipitation information, at gauged locations and then extrapolating these values to ungauged locations via a hydroclimatic classification system. Fifteen sites within the Soil Climate Analysis Network (SCAN) containing multiyear time series data for precipitation and soil moisture are used to calibrate the model. By calibrating at 1 of these 15 sites and validating at another, we observe that the best results are obtained where calibration and validation occur within the same hydroclimatic class. Additionally, soil texture data are tested for their importance in improving predictions between calibration and validation sites. Results have the largest errors when calibration-validation pairs differ hydroclimatically and edaphically, improve when one of these two characteristics are aligned, and are strongest when the calibration and validation sites are hydroclimatically and edaphically similar. These findings indicate considerable promise for improving soil moisture estimation in ungauged locations by considering these similarities.

  14. The moisture response of soil heterotrophic respiration: Interaction with soil properties.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy

  16. SOIL MOISTURE EFFECTS ON ENERGY REQUIREMENTS AND SOIL DISRUPTION OF SUBSOILING A COASTAL PLAIN SOIL

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An experiment was conducted to determine the optimum moisture content to subsoil based on tillage forces and soil disruption. Two different shanks, a straight shank and a "minimum- tillage" shank, were tested in a Coastal Plain soil in the soil bins of the National Soil Dynamics Laboratory in Aubur...

  17. Tree species specific soil moisture patterns and dynamics through the seasons

    NASA Astrophysics Data System (ADS)

    Heidbüchel, Ingo; Dreibrodt, Janek; Simard, Sonia; Güntner, Andreas; Blume, Theresa

    2015-04-01

    Soil moisture patterns in the landscape are largely controlled by soil types (pore size distributions) and landscape position. But how strong is the influence of vegetation on patterns within a single soil type? While we would envision a clear difference in soil moisture patterns and responses between for example bare soil, a pasture and a forest, our conceptual images start to become less clear when we move on to different forest stands. Do different tree species cause different moisture patterns to emerge? Could it be possible to identify the dominant tree species of a site by classifying its soil moisture pattern? To investigate this question we analyzed data from 15 sensor clusters in the lowlands of north-eastern Germany (within the TERENO observatory) which were instrumented with soil moisture sensors (5 profiles per site), tensiometers, sap flow sensors, throughfall and stemflow gages. Data has been collected at these sites since May 2014. While the summer data has already been analyzed, the analysis of the winter data and thus the possible seasonal shifts in patterns will be carried out in the coming months. Throughout the last summer we found different dynamics of soil moisture patterns under pine trees compared to beech trees. While the soils under beech trees were more often relatively wet and more often relatively dry, the soils under pine trees showed less variability and more often average soil moisture. These differences are most likely due to differences in both throughfall patterns as well as root water uptake. Further analysis includes the use of throughfall and stemflow data as well as stable water isotope samples that were taken at different depths in the soil, in the groundwater and from the sapwood. The manifestation of tree species differences in soil moisture patterns and dynamics is likely to have implications for groundwater recharge, transit times and hydrologic partitioning.

  18. The GLOBE Soil Moisture Campaign's Light Bulb Oven

    NASA Astrophysics Data System (ADS)

    Whitaker, M. P.; Tietema, D.; Ferre, T. P.; Nijssen, B.; Washburne, J.

    2003-12-01

    The GLOBE Soil Moisture Campaign (SMC) (www.hwr.arizona.edu/globe/sci/SM/SMC) has developed a light bulb oven to provide a low budget, low-technology method for drying soil samples. Three different soils were used to compare the ability of the light bulb oven to dry soils against a standard laboratory convection oven. The soils were: 1) a very fine sandy loam (the "Gila" soil); 2) a silty clay (the "Pima" soil); and 3) a sandy soil (the "Sonoran" soil). A large batch of each soil was wetted uniformly in the laboratory. Twelve samples of each soil were placed in the light bulb oven and twelve samples were placed in the standard oven. The average gravimetric soil moisture of the Gila soil was 0.214 g/cm3 for both ovens; the average Pima soil moisture was 0.332 g/cm3 and 0.331 g/cm3 for the traditional and light bulb ovens, respectively; and the Sonoran soil moisture was 0.077 g/cm3 for both ovens. These results demonstrate that the low technology light-bulb oven was able to dry the soil samples as well as a standard laboratory oven, offering the ability to make gravimetric water content measurements when a relatively expensive drying oven is not available.

  19. USING SOIL MOISTURE TO DETERMINE WHEN TO SUBSOIL

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An experiment was conducted to determine the optimum moisture content to subsoil based on tillage forces and on soil disruption. Two different shanks, a straight shank and a "minimum-tillage" shank, were tested in a Coastal Plains soil in the soil bins of the National Soil Dynamics Laboratory in Au...

  20. Estimating root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, the vertical support of microwave-based surface soil moistur...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions suc...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...

  3. Degradation and persistence of metolachlor in soil: effects of concentration, soil moisture, soil depth, and sterilization.

    PubMed

    Rice, Pamela J; Anderson, Todd A; Coats, Joel R

    2002-12-01

    The present study evaluated the influence of soil depth, soil moisture, and concentration on the persistence and degradation of metolachlor in soil. Greater percentages of metolachlor persisted in subsurface soils than in surface soil regardless of the soil moisture or initial herbicide concentration. Larger quantities of bound residues and extractable degradation products were found in the surface soils as a result of the increased soil sorption and biodegradation of metolachlor associated with the surface soil, which had more organic matter. Saturated soil favored the dissipation of metolachlor and the formation of soil-bound residues. Significantly greater quantities of a dechlorinated metabolite were measured in the saturated surface soil compared to the unsaturated soil. Mineralization of metolachlor to CO2 and volatilization of metolachlor or metolachlor degradates was minimal in surface and subsurface soils at both soil moistures and herbicide concentrations. Increased metolachlor concentrations did not inhibit microbial activity; however, the greater rate of application did result in the reduced percentage of applied [14C]metolachlor that was bound to surface or subsurface soil. A significant reduction in the quantity of extractable metolachlor degradates and unextractable soil-bound residues in sterile soil revealed the significance of biodegradation to the dissipation of metolachlor in soil. PMID:12463559

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

  5. Remotely sensed soil moisture input to a hydrologic model

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

    The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  7. On the effects of hydrological model structure on soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Corato, Giovanni; Matgen, Patrick; Giustarini, Laura; Fenicia, Fabrizio

    2013-04-01

    Nowadays, satellite sensors allow obtaining soil moisture estimates at global scale with an adequate temporal and spatial resolution, thereby offering a theoretical chance to improve flood-forecasting systems based on rainfall-runoff models. In fact, the knowledge of antecedent soil moisture conditions plays a crucial role in predicting catchment response to rainfall events. In the literature, several studies have focused on the assimilation of soil moisture data into hydrological models. The results of these studies tend to show that an improvement in discharge and soil moisture forecasts can be obtained when the assimilated information originates from accurate in situ measurements. When dealing with the assimilation of remote sensing-derived soil moisture data, the reported results are more controversial. There is no doubt that the performances of soil moisture data assimilation studies depend on many factors: data assimilation scheme, hydrological model structure, accuracy and resolution of soil moisture data. As of today, these dependences are not well understood and the disparity of outcomes in past studies arguably reflects the differences in the design of the experiments. In this general context, the aim of this study is to investigate the effects of hydrological model structures on soil moisture data assimilation performance. The analysis focuses on the vertical "stratification" of the soil column in a conceptual hydrological model. We consider multiple structures that differ by the number of soil reservoirs and their respective sizes. The recently introduced SUPERFLEX hydrological modelling framework is used to this end. In fact, this framework allows building and modifying multiple hydrological models by combining three basic building blocks: reservoirs, lag functions and junctions. As a data assimilation scheme, the particle filter was considered. The area of interest is the Alzette catchment (1200 km2), located in Luxembourg, while the analysed period spans from 2005 to 2011. The results of our study provide some insights on model structure requirements supporting an optimal usage of in situ measured and remotely sensed soil moisture data for operational hydrology.

  8. Soil moisture and the persistence of North American drought

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

    Numerical sensitivity experiments on the effects of soil moisture on North American summertime climate are performed using a 12-layer global atmospheric general circulation model. Consideration is given to the hypothesis that reduced soil moisture may induce and amplify warm, dry summers of midlatitude continental interiors. The simulations resemble the conditions of the summer of 1988, including an extensive drought over much of North America. It is found that a reduction in soil moisture leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. It is shown that low-level moisture advection from the Gulf of Mexico is important in the maintenance of persistent soil moisture deficits.

  9. Is Regional Root Reinforcement Controlled by Soil Moisture Variability?

    NASA Astrophysics Data System (ADS)

    Hales, T.; Ford, C. R.

    2011-12-01

    Climate change will alter the amount, type (i.e., snow vs. rain), and timing of precipitation that controls many hazardous Earth surface processes, including debris flows. Most GCMs agree that as climate warms the frequency of extreme precipitation will increase across the globe. Debris flow events triggered by heavy precipitation will likely also increase. Precipitation also affects the resistance to debris flow initiation by controlling belowground plant hydraulic architecture (e.g. root frequency, diameter distribution, tensile strength). Quantifying the links between precipitation, below ground properties, and the processes that initiate debris flows are therefore critical to understanding future hazard. To explore these links, we conducted a field experiment in the Coweeta Hydrologic Laboratory by excavating 12 soil pits (~1 m3), from two topographies (noses, hollows), and two tree species (Liriodendron tulipifera and Betula lenta). For each species and topography, we collected all biomass from five soil depths and measured soil moisture at 30, 60, and 90cm depth. For each depth we also measured root tensile strength, root cellulose content. Where we collected soil moisture data, we also measured root and soil hydraulic conductivity. Our data show a link between soil moisture content and root biomass distribution; root biomass is more evenly distributed through the soil column in hollows compared to noses. This relationship is consistent with the hypothesis that more consistent soil moisture in hollows allows plant roots to access resources from deeper within the soil column. This physiologic control has a significant effect on root cohesion, with trees on noses (or lower average soil moisture) providing greater root cohesion close to the surface, but considerably less cohesion at depth. Root tensile strength correlated with local daily soil moisture rather than the long term differences represented by noses and hollows. Daily soil moisture affected the amount of "bound water" (water present in the cell wall), which in turn affected the strength of the cellulose fibrils that provide tensile strength. This phenomenon, which is the reason any wet wood is weaker than dry wood, results in a 50% difference in root tensile strength within the range of soil moisture measured in the field. We used a one-dimensional finite difference model to explore the effects of soil moisture on root cohesion. Our model shows that changes in the distribution of root biomass represent the primary control on root cohesion (representing up to 50% of intra-specific variability in root cohesion). Local changes in soil moisture result in ~20% change in the overall root cohesion. Our work suggest a feed-forward process in precipitation (and thus soil moisture), root strength changes, and debris flow hazard.

  10. The Sodankylä in situ soil moisture observation network: an example application of ESA CCI soil moisture product evaluation

    NASA Astrophysics Data System (ADS)

    Ikonen, Jaakko; Vehviläinen, Juho; Rautiainen, Kimmo; Smolander, Tuomo; Lemmetyinen, Juha; Bircher, Simone; Pulliainen, Jouni

    2016-04-01

    During the last decade there has been considerable development in remote sensing techniques relating to soil moisture retrievals over large areas. Within the framework of the European Space Agency's (ESA) Climate Change Initiative (CCI) a new soil moisture product has been generated, merging different satellite-based surface soil moisture based products. Such remotely sensed data need to be validated by means of in situ observations in different climatic regions. In that context, a comprehensive, distributed network of in situ measurement stations gathering information on soil moisture, as well as soil temperature, has been set up in recent years at the Finnish Meteorological Institute's (FMI) Sodankylä Arctic research station. The network forms a calibration and validation (CAL-VAL) reference site and is used as a tool to evaluate the validity of satellite retrievals of soil properties. In this paper we present the Sodankylä CAL-VAL reference site soil moisture observation network, its instrumentation as well as its areal representativeness over the study area and the region in general as a whole. As an example of data utilization, comparisons of spatially weighted average top-layer soil moisture observations between the years 2012 and 2014 against ESA CCI soil moisture data product estimates are presented and discussed. The comparisons were made against a single ESA CCI data product pixel encapsulating most of the Sodankylä CAL-VAL network sites. Comparisons are made with daily averaged and running weekly averaged soil moisture data as well as through application of an exponential soil moisture filter. The overall achieved correlation between the ESA CCI data product and in situ observations varies considerably (from 0.479 to 0.637) depending on the applied comparison perspective. Similarly, depending on the comparison perspective used, inter-annual correlation comparison results exhibit even more pronounced variation, ranging from 0.166 to 0.840.

  11. Evaluation of GSWP-2 Soil Moisture Simulations and its Implication for Seasonal Prediction

    NASA Astrophysics Data System (ADS)

    Guo, Z.; Dirmeyer, P. A.

    2006-05-01

    Driven with the meteorological data sets based on the reanalyses and gridded observational data archived by the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II, eleven different land surface models generated global soil moisture data sets for the 10-year period (1986-1995) for the Second Global Soil Wetness Project (GSWP-2). We also integrate one land model with a dozen different combinations of meteorological forcing data and vegetation parameters. We evaluate these model simulations against in situ observations over grasslands and agricultural regions in the former Soviet Union, United States (Illinois), China, and Mongolia from the Global Soil Moisture Data Bank in terms of their ability to estimate the actual column plant-available soil moisture in the top 1m soil layer, to simulate the phasing of the annual cycle, and to represent observed interannual variability. Comparison of the eleven land surface models show that they reproduce reasonably well the observed interannual variability and phasing of the annual cycle. Statistical analysis also shows that the median root mean square of errors ranges from 4-8 cm among these models. Similar to what has been found in soil moisture simulations for GSWP-1, the absolute values of soil moisture are poorly simulated by most models. However, the models do a fairly good job of reproducing the soil moisture anomalies. This suggests that the global soil wetness data set produced by GSWP-2 can be used for analyzing climate variability and initializing GCMs by using certain transform strategies. This also has relevance to sub-seasonal to seasonal forecasts since simulation of soil moisture anomalies might be more important than that for actual monthly mean values due to the persistence of soil moisture anomalies and its potential impact on future precipitation. Sensitivity of soil moisture simulations to different external data show that the skill of soil moisture simulations is very sensitive to the quality of meteorological forcing, and hybridization of reanalysis products with observational data substantially improves soil moisture simulations. The soil moisture simulations are most sensitive to the quality in products of precipitation, radiation, and vegetation class. The range of skill changes is as large as that resulting from different land surface models driven with the same meteorological forcing. If differences among versions of meteorological forcing fields are representative of uncertainties in our knowledge of these drivers of the land surface climate, then impact of that uncertainty on land surface hydrology is as large as that resulting from the uncertainty in land surface models itself.

  12. Microwave remote sensing and its application to soil moisture detection

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.

  13. Response of grassland ecosystems to prolonged soil moisture deficit

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  14. High-resolution soil moisture mapping in Afghanistan

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

    Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

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

    USGS Publications Warehouse

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

    1996-01-01

    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.

  17. Coupling rainfall observations and satellite soil moisture for predicting event soil loss in Central Italy

    NASA Astrophysics Data System (ADS)

    Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang

    2015-04-01

    The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the λ = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, θ, and powered to an exponent α > 0 (α =1: linear model; α ≠ 1: power model). Both soil moisture data the satellite retrieved (θ = θsat) and the estimates (θ = θest) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was always the lowest; the accuracy in estimating the event soil loss of a models with erosivity factor that includes the estimated runoff is always overcome by at least one model that uses the antecedent soil moisture θ in the erosivity index; the power models generally, at Masse, work better than the linear. The more accurate models are that with the estimated antecedent soil moisture, θest, when all the database is used and with the satellite retrieved soil moisture, θsat, when only the wet periods' events are considered. In fact it was also verified that much of the inaccuracy of the tested models is due to summer rainfall events, probably because of the particular characteristics that the soil assumes in the dry period (superficial crusts causing higher runoff): in this cases, high soil losses are observed in association to low values of soil moisture, while the simulated runoff assume low values too, since they are based on the antecedent wetness conditions. Thus, the analyses were repeated excluding the summer events. As expected, the performance of all the models increases, but still the use of θ provides the best results. The results of the analysis open interesting scenarios in the use of USLE-derived models for the unit event soil loss estimation at large scale. In particular the use of the soil moisture to correct the rainfall erosivity factor acquires a great practical importance, since it is a relatively simple measurable data and moreover because remote sensing soil moisture data are widely available and useful in large-scale erosion assessment. Bagarello, V., Di Piazza, G. V., Ferro, V., Giordano, G., 2008. Predicting unit soil loss in Sicily, south Italy. Hydrol. Process. 22, 586-595. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Todisco, F., Vergni, L., 2013. Predicting event soil loss form bare plots at two Italian sites. Catena 109, 96-102. Brocca, L., Melone, F., Moramarco, T., 2011. Distributed rainfall-runoff modeling for flood frequency estimation and flood forecasting. Hydrol. Process. 25, 2801-2813. Kinnell, P. I. A., Risse, L. M., 1998. USLE-M: empirical modeling rainfall erosion through runoff and sediment concentration. Soil Sci. Soc. Am. J. 62, 1667-1672. Todisco, F., Vergni, L., Mannocchi, F., Bomba, C., 2012. Calibration of the soil loss measurement at the Masse experimental station. Catena 91, 4-9. Wischmeier, W. H., Smith, D. D., 1978. Predicting rainfall-erosion losses - A guide to conservation planning. Agriculture Handbook 537, United Stated Department of Agriculture.

  18. Conditional dependence of evaporative fraction on surface and root-zone soil moisture and its application to soil moisture retrieval

    NASA Astrophysics Data System (ADS)

    Ryu, D.; Akuraju, V.

    2013-12-01

    Thermal infrared (TIR) or evapotranspiration (ET) estimates from space have been gaining growing attention as an input to retrieve root-zone soil moisture. The rationale behind the approach is that i) there exists a strong causal link between the evapotranspiration and the vegetation canopy temperature and ii) under water-limited conditions soil water available for transpiration controls the evaporative fraction (EF) or the actual evapotranspiration (AET) to potential evapotranspiration (PET) ratio of vegetated surfaces. In this work, we examine the relationship between EF and surface to root-zone soil moisture content collected from two study sites (wheat and pasture fields) at the Dookie research farm site in Victoria, Australia. EF estimated from the eddy covariance system is compared with soil moisture content under various ranges of soil depths (5 depths from surface to 120 cm), net radiation, soil wetness and biomass. In both wheat and pasture fields, EF is highly correlated with surface (0-8 cm) soil moisture when the soil surface is bare-to-lightly vegetated, but the correlation decreases as vegetation grows or as the net radiation decreases. On the other hand, EF shows strong correlation with root-zone soil moisture during the growing seasons of the fields. Under similar ranges of soil moisture and net radiation, EF can have different ranges depending on the vegetation height and density. These results indicate the importance of biophysical parameters and processes in estimating surface and root-zone soil moisture contents using surface energy flux. We propose an exponential and a spherical model to fit EF versus soil moisture and show how their uncertainty changes with biophysical parameters.

  19. Evaluation of NLDAS-2 Multi-Model Simulated Soil Moisture Using the Observations from North American Soil Moisture Dataset (NASMD)

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    The North American Land Data Assimilation System phase 2 (NLDAS-2, http://www.emc.ncep.noaa.gov/mmb/nldas/) has generated 35-years (1979-2013) of hydrometeorological products from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC). These products include energy fluxes, water fluxes, and state variables. Soil moisture is one of the most important state variables in NLDAS-2 as it plays a key role in land-atmosphere interaction, regional climate and ecological model simulation, water resource management, and other study areas. The soil moisture data from these models have been used for US operational drought monitoring activities, water resources management and planning, initialization of regional weather and climate models, and other meteorological and hydrological research purposes. However, these data have not yet been comprehensively evaluated due to the lack of extensive soil moisture observations. In this study, observations from over 1200 sites in the North America compiled from 27 observational networks in the North American Soil Moisture Database (NASMD, http://soilmoisture.tamu.edu/) were used to evaluate the model-simulated daily soil moisture for different vegetation cover varying from grassland to forest, and different soil texture varying from sand to clay. Seven states in the United States from NASMD were selected based on known measurement error estimates for the evaluation. Statistical metrics, such as anomaly correlation, root-mean-square errors (RMSE), and bias are computed to assess NLDAS-2 soil moisture products. Three sensitivity tests were performed using the Noah model to examine the effect of soil texture and vegetation type mismatch on NLDAS-2 soil moisture simulation. In the first test, site observed soil texture was used. In the second test, site observed vegetation type/land cover was used. In the third test, both site observed soil texture and vegetation type were used. The results from three sensitivity tests will be compared with NLDAS-2 Noah and observed soil moisture. This presentation reports major results from this evaluation.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  1. A comparison of methods for a priori bias correction in soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

    Data assimilation is increasingly being 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: (1) parameter estimation to calibrate the land model to the climatology of the soil moisture observations and (2) 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.

  2. Improvement of hydrologic model soil moisture predictions using SEBAL evapotranspiration estimates

    NASA Astrophysics Data System (ADS)

    Hendrickx, Jan M. H.; Pradhan, Nawa R.; Hong, Sung-ho; Ogden, Fred L.; Byrd, Aaron R.; Toll, David

    2009-05-01

    Soil moisture conditions influence practically all aspects of Army activities and are increasingly affecting its systems and operations. Regional distributions of high resolution soil moisture data will provide critical information on operational mobility, penetration, and performance of landmine and UXO sensors. The US Army Corps of Engineers (USACE) developed the Gridded Surface/Subsurface Hydrologic Analysis (GSSHA), which is a grid-based two-dimensional hydrologic model that has been effectively applied to predict soil moisture conditions. GSSHA computes evapotranspiration (ET) using the Penman-Monteith equation. However, lack of reliable spatially-distributed meteorological data, particularly in denied areas, makes it difficult to reliably predict regional ET and soil moisture distributions. SEBAL is a remote sensing algorithm that computes spatio-temporal patterns of ET using a surface energy balance approach. SEBAL has been widely accepted and tested throughout the world against lysimeter, eddy-covariance and other field measurements. SEBAL estimated ET has shown good consistency and agreement for irrigated fields, rangelands and arid riparian areas. The main objective of this research is to demonstrate improved GSSHA soil moisture and hydrological predictions using SEBAL estimates of ET. Initial results show that the use of SEBAL ET and soil moisture estimates improves the ability of GSSHA to predict regional soil moisture distributions, and reduces uncertainty in runoff predictions.

  3. Uncertainties of seasonal surface climate predictions induced by soil moisture biases in the La Plata Basin

    NASA Astrophysics Data System (ADS)

    Sorensson, Anna; Berbery, E. Hugo

    2015-04-01

    This work examines the evolution of soil moisture initialization biases and their effects on seasonal forecasts depending on the season and vegetation type for a regional model over the La Plata Basin in South America. WRF/Noah model simulations covering multiple cases during a two-year period are designed to emphasize the conceptual nature of the simulations at the expense of statistical significance of the results. Analysis of the surface climate shows that the seasonal predictive skill is higher when the model is initialized during the wet season and the initial soil moisture differences are small. Large soil moisture biases introduce large surface temperature biases, particularly for Savanna, Grassland and Cropland vegetation covers at any time of the year, thus introducing uncertainty in the surface climate. Regions with Evergreen Broadleaf Forest have roots that extend to the deep layer whose moisture content affects the surface temperature through changes in the partitioning of the surface fluxes. The uncertainties of monthly maximum temperature can reach several degrees during the dry season in cases when: (a) the soil is much wetter in the reanalysis than in the WRF/Noah equilibrium soil moisture, and (b) the memory of the initial value is long due to scarce rainfall and low temperatures. This study suggests that responses of the atmosphere to soil moisture initialization depend on how the initial wet and dry conditions are defined, stressing the need to take into account the characteristics of a particular region and season when defining soil moisture initialization experiments.

  4. Optimal averaging of soil moisture predictions from ensemble land surface model simulations

    NASA Astrophysics Data System (ADS)

    Crow, Wade T.; Su, Chun-Hsu; Ryu, Dongryeol; Tugrul Yilmaz, M.

    2015-04-01

    The correct interpretation of ensemble 3 soil moisture information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble's mutual error covariance. Here we propose a new technique for obtaining such information using an instrumental variable (IV) regression approach and comparisons against a long-term surface soil moisture dataset obtained from satellite remote sensing. Application of the approach to multi-model ensemble soil moisture output from the North American Land Data Assimilation System (NLDAS-2), and multi-satellite European Space Agency (ESA) Soil Moisture (SM) Essential Climate Variable (ECV) dataset, allows for the calculation of optimal weighting coefficients for individual members of a the NLDAS-2 ensemble and a biased-minimized estimate of uncertainty in a deterministic soil moisture analysis derived via such optimal weighted averaging. As such, it provides key information required to accurately condition soil moisture expectations using information gleaned from a multi-model LSM ensemble. However, existing continuity and rescaling concerns surrounding the generation of long-term, satellite-based soil moisture products must likely be resolved before the proposed approach can be applied with full confidence.

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

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

    Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data (e.g., precipitation). An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. The latter relationships are particularly important for applications users, for whom the continuity of soil moisture data, from whatever source, is critical. A recent example was provided by the sudden demise of EOS Aqua AMSR-E and the end of its soil moisture data production, as well as the end of other soil moisture products that had used the AMSR-E brightness temperature data. The purpose of the current effort is to create an environment, as part of the NASA Giovanni family of portals, that facilitates inter-comparisons of soil moisture algorithms and their derived data products.

  7. Remote monitoring of soil moisture using airborne microwave radiometers

    NASA Technical Reports Server (NTRS)

    Kroll, C. L.

    1973-01-01

    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.

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

    USGS Publications Warehouse

    Georgakakos, Konstantine P.; Smith, Diane E.

    2000-01-01

    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.

  9. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

    Bircher, Simone; Andreasen, Mie; Vuollet, Johanna; Vehviläinen, Juho; Rautiainen, Kimmo; Jonard, François; Weihermüller, Lutz; Zakharova, Elena; Wigneron, Jean-Pierre; Kerr, Yann H.

    2016-04-01

    This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the here-proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.

  10. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

    Bircher, S.; Andreasen, M.; Vuollet, J.; Vehviläinen, J.; Rautiainen, K.; Jonard, F.; Weihermüller, L.; Zakharova, E.; Wigneron, J.-P.; Kerr, Y. H.

    2015-12-01

    This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology HOBE. For the Decagon 5TE sensor such a function is currently not reported in literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified: for the Decagon 5TE apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger non-linearity in the sensor response and signal saturation in the high level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the here proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but in that case proof of value for the acquisition of instantaneous large-scale soil moisture estimates.

  11. The Soil Moisture Active and Passive (SMAP) Mission

    NASA Technical Reports Server (NTRS)

    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

    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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  13. ANALYSIS AND MAPPING OF FIELD-SCALE SOIL MOISTURE VARIABILITY USING HIGH-RESOLUTION, GROUND-BASED DATA DURING THE SOUTHERN GREAT PLAINS 1997 (SGP97) HYDROLOGY EXPERIMENT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an important state variable in the hydrologic cycle, and its spatiotemporal distribution depends on many geophysical processes operating at different spatial and temporal scales. To achieve a better accounting of the water and energy budgets at the land-atmosphere boundary, it is n...

  14. Soil Albedo in Relation to Soil Color, Moisture and Roughness

    NASA Astrophysics Data System (ADS)

    Fontes, Adan Fimbres

    Land surface albedo is the ratio of reflected to incident solar radiation. It is a function of several surface parameters including soil color, moisture, roughness and vegetation cover. A better understanding of albedo and how it changes in relation to variations in these parameters is important in order to help improve our ability to model the effects of land surface modifications on climate. The objectives of this study were (1) To determine empirical relationships between smooth bare soil albedo and soil color, (2) To develop statistical relationships between albedo and ground-based thematic mapper (TM) measurements of spectral reflectances, (3) To determine how increased surface roughness caused by tillage reduces bare soil albedo and (4) To empirically relate albedo with TM data and other physical characteristics of mixed grass/shrubland sites at Walnut Gulch Watershed. Albedos, colors and spectral reflectances were measured by Eppley pyranometer, Chroma Meter CR-200 and a Spectron SE-590, respectively. Measurements were made on two field soils (Gila and Pima) at the Campus Agricultural Center (CAC), Tucson, AZ. Soil surface roughness was measured by a profile meter developed by the USDA/ARS. Additional measurements were made at the Maricopa Agricultural Center (MAC) for statistical model testing. Albedos of the 15 smooth, bare soils (plus silica sand) were determined by linear regression to be highly correlated (r^2 = 0.93, p > 0.01) with color values for both wet and dry soil conditions. Albedos of the same smooth bare soils were also highly correlated (r^2>=q 0.86, p > 0.01) with spectral reflectances. Testing of the linear regression equations relating albedo to soil color and spectral reflectances using the data from MAC showed a high correlation. A general nonlinear relationship given by y = 8.366ln(x) + 37.802 r^2 = 0.71 was determined between percent reduction in albedo (y) and surface roughness index (x) for wet and dry Pima and Gila field soils. Measurements of albedo, color and spectral reflectance at the Walnut Gulch Watershed indicated that albedo values were highly correlated with percent rock & gravel, color value and reflectance data (TM bands 1-4).

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    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.

  16. Field Observations of Soil Moisture Variability across Scales

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    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.

  17. Measurement and utilization of on-site soil moisture data

    NASA Astrophysics Data System (ADS)

    Georgakakos, Konstantine P.; Baumer, Otto W.

    1996-10-01

    Programs for the on-site measurement of soil moisture in the USA are reviewed. These are regional and national measurement programs that may be useful for the verification of remotely sensed soil moisture estimates and for hydroclimatic studies. Location and type of measurement are described. A technique for the utilization of on-site data of soil moisture and discharge together with remotely sensed data of the surface soil moisture is proposed for the estimation of soil water content aggregated over large areas. The technique is based on large-scale conceptual hydrologic models and on state estimation techniques that allow explicit account to be taken of measurement uncertainty. The proposed approach is explored in an example formulation applied to a 40 year record of monthly data from a 4672 km 2 natural catchment in Illinois. This study shows the ability of simple conceptual hydrologic models to simulate well both flow and soil water in humid areas and with monthly data. It is further shown that, even when the remotely sensed measurements of the surface soil moisture carry substantial measurement errors, inference of lower soil water and of total soil water is possible with an expected error that is smaller than that achieved without the use of the remotely sensed data.

  18. Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

    NASA Technical Reports Server (NTRS)

    Reichle, R. H.

    2010-01-01

    Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

  19. The Soil Moisture Active and Passive (SMAP) Mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 f...

  20. Soil moisture active/passive (SMAP) mission concept

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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. ...

  1. Preparing for NASA's Soil Moisture Active Passive (SMAP) mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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. ...

  2. Soil moisture variation patterns observed in Hand County, South Dakota

    NASA Technical Reports Server (NTRS)

    Jones, E. B.; Owe, M.; Schmugge, T. J. (Principal Investigator)

    1981-01-01

    Soil moisture data were taken during 1976 (April, June, October), 1977 (April, May, June), and 1978 (May, June, July) Hand County, South Dakota as part of the ground truth used in NASA's aircraft experiments to study the use of microwave radiometers for the remote sensing of soil moisture. The spatial variability observed on the ground during each of the sampling events was studied. The data reported are the mean gravimetric soil moisture contained in three surface horizon depths: 0 to 2.5, 0 to 5 and 0 to 10 cm. The overall moisture levels ranged from extremely dry conditions in June 1976 to very wet in May 1978, with a relatively even distribution of values within that range. It is indicated that well drained sites have to be partitioned from imperfectly drained areas when attempting to characterize the general moisture profile throughout an area of varying soil and cover type conditions. It is also found that the variability in moisture content is greatest in the 0 to 2.5 cm measurements and decreases as the measurements are integrated over a greater depth. It is also determined that the sampling intensity of 10 measurements per km is adequate to estimate the mean moisture with an uncertainty of + or - 3 percent under average moisture conditions in areas of moderate to good drainage.

  3. Using magnetic susceptibility to discriminate between soil moisture regimes in selected loess and loess-like soils in northern Iran

    NASA Astrophysics Data System (ADS)

    Valaee, Morteza; Ayoubi, Shamsollah; Khormali, Farhad; Lu, Sheng Gao; Karimzadeh, Hamid Reza

    2016-04-01

    This study used discriminant analysis to determine the efficacy of magnetic measures for discriminating between four soil moisture regimes in northern Iran. The study area was located on loess deposits and loess-like soils containing similar parent material. Four soil moisture regimes including aridic, xeric, udic, and aquic were selected. A total of 25 soil profiles were drug from each regime and composite soil samples were collected within the moisture control section. A set of magnetic measures including magnetic susceptibility at low (χlf) and high (χhf) frequencies, frequency-dependent magnetic susceptibility (χfd), saturation isothermal remnant magnetization (SIRM), and isothermal remnant magnetization (IRM100 mT, IRM 20 mT) were measured in the laboratory. Dithionite citrate bicarbonate (Fed) and acid oxalate (Feo) contents of all soil samples were also determined. The lowest and highest χlf and χhf were observed in aquic and udic moisture regimes, respectively. A similar trend was obtained for Fed and Fed-Feo. The significant positive correlation between Fed and SIRM (r = 0.60; P < 0.01) suggested the formation of stable single domains (SSD) due to pedogenic processes. The results of discriminant analysis indicated that a combination of magnetic measures could successfully discriminate between the selected moisture regimes in the study area (average accuracy = 80%). It can thus be concluded that magnetic measures could be applied as a powerful indicator for differentiation of soil moisture regimes in the study area.

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

    NASA Technical Reports Server (NTRS)

    Welker, J. E.

    1984-01-01

    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.

  5. Soil moisture and evapotranspiration predictions using Skylab data

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

    The author has identified the following significant results. Multispectral reflectance and emittance data from the Skylab workshop were evaluated for prediction of evapotranspiration and soil moisture for an irrigated region of southern Texas. Wavelengths greater than 2.1 microns were required to spectrally distinguish between wet and dry fallow surfaces. Thermal data provided a better estimate of soil moisture than did data from the reflective bands. Thermal data were dependent on soil moisture but not on the type of agricultural land use. The emittance map, when used in conjunction with existing models, did provide an estimate of evapotranspiration rates. Surveys of areas of high soil moisture can be accomplished with space altitude thermal data. Thermal data will provide a reliable input into irrigation scheduling.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council?s Decadal Survey [1]. Its mission design consists of L-band radiometer and radar instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every 2-3 days. The combined active/passive microwave soil moisture product will have a spatial resolution of 10 km and a mean latency of 24 hours. In addition, the SMAP surface observations will be combined with advanced modeling and data assimilation to provide deeper root zone soil moisture and net ecosystem exchange of carbon. SMAP is expected to launch in the late 2014 - early 2015 time frame.

  7. Measurement of soil moisture trends with airborne scatterometers

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J. (Principal Investigator)

    1978-01-01

    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.

  8. Sensitivity of seasonal weather prediction and extreme precipitation events to soil moisture initialization uncertainty using SMOS soil moisture products

    NASA Astrophysics Data System (ADS)

    Khodayar-Pardo, Samiro; Lopez-Baeza, Ernesto; Coll Pajaron, M. Amparo

    Sensitivity of seasonal weather prediction and extreme precipitation events to soil moisture initialization uncertainty using SMOS soil moisture products (1) S. Khodayar, (2) A. Coll, (2) E. Lopez-Baeza (1) Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe Germany (2) University of Valencia. Earth Physics and Thermodynamics Department. Climatology from Satellites Group Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area and/or state of the art products such as the soil moisture measurements from the SMOS (Soil Moisture and Ocean Salinity) space mission may be also convenient. The potential role of soil moisture initialization and associated uncertainty in numerical weather prediction is illustrated in this study through sensitivity numerical experiments using the SVAT SURFEX model and the non-hydrostatic COSMO model. The aim of this investigation is twofold, (a) to demonstrate the sensitivity of model simulations of convective precipitation to soil moisture initial uncertainty, as well as the impact on the representation of extreme precipitation events, and (b) to assess the usefulness of SMOS soil moisture products to improve the simulation of water cycle components and heavy precipitation events. Simulated soil moisture and precipitation fields are compared with observations and with level-1(~1km), level-2(~15 km) and level-3(~35 km) soil moisture maps generated from SMOS over the Iberian Peninsula, the SMOS validation area (50 km x 50 km, eastern Spain) and selected stations, where in situ measurements are available covering different vegetation cover and soil types. Additionally, measurements from an L-band radiometer from ESA (European Space Agency), ELBARA-II, installed in the area to monitor SMOS validation conditions over a vineyard crop are available. Furthermore, MODIS, LANDSAF and SMOS products are used to define realistic initial conditions for sensitivity simulations. The results of these simulations are investigated, compared and conclusions drawn. The investigation covers the autumn period of 2012, September to November, and we will particularly focus on selected stages where extreme rain events occurred in our study area.

  9. Sensitivity of the soil moisture initialization in the genesis of two simulated mesoscale convective systems

    NASA Astrophysics Data System (ADS)

    Cheng, William Yau Yin

    This study examines the sensitivity of the horizontal heterogeneities of the soil moisture initialization (SMI) in the cloud-resolving grid of two real-data mesoscale convective system (MCS) simulations during their genesis phase. We used a nested grid setup similar to some of the current realtime forecast models. Both systems were quasi-stationary. One system (Case 980726) formed in the Texas/Oklahoma border with a lifetime of 9h. The second system (Case 990802), with origins in western Oklahoma, also had a lifetime of 9h. Soil moisture for the cloud-resolving grid was derived from the Antecedent Precipitation Index (API) using 4-km grid spacing precipitation data for a three-month period. In order to test the sensitivity of the heterogeneities of the SMI in the cloud-resolving grid, (i) Barnes objective analysis was used to alter the resolution of the SMI, (ii) the amplitude of the soil moisture field was reduced by 50%, (iii) the position of a soil moisture anomaly was altered, and (iv) two experiments with homogeneous soil moisture (31% and 50% saturation) were performed. Large-scale forcing provided the favorable environment for convection to develop, but the distribution of the soil moisture determined where convection was likely to occur. The soil moisture anomalies generated physiographic-induced mesoscale systems (PIMSs), analogous to sea breeze, due to differential surface heating, and they assisted in organizing the convection as the MCS was developing. The larger soil moisture anomalies were more influential in initiating and/or interacting with convection. As the initial soil moisture was smoothed, the PIMSs associated with the larger soil moisture anomalies started to strengthen, but as the smoothing reached a cutoff wavelength of 80 km, the PIMSs began to weaken. Although the effects of the smaller soil moisture anomalies were not negligible in initiating and/or enhancing convective precipitation, they tended to lose their signatures with the smoothing operation. In the experiments, a negative feedback existed between wet soil and convective precipitation which tended to suppress convection over wet soil but favored convection at the periphery of the wet soil.

  10. Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover

    NASA Astrophysics Data System (ADS)

    Ochsner, T.; Venterea, R. T.

    2009-12-01

    Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching will also be examined.

  11. Multi-frequency SAR data for soil surface moisture estimation over agricultural fields

    NASA Astrophysics Data System (ADS)

    Zribi, Mehrez; Baghdadi, Nicolas

    2015-04-01

    Soil moisture plays a crucial role in the continental water cycle, in particular through its influence on the distribution of precipitation between surface runoff and infiltration, which is the main driver behind most hydrological and geomorphologic processes. Although there is now a good understanding of soil hydrodynamics and water transfer in porous media, the development of reliable techniques allowing field heterogeneities to be fully analyzed in space and time remains a key issue. In recent decades, various inversion models have been proposed for the retrieval of surface parameters (mainly soil moisture and surface roughness) from Synthetic Aperture Radar (SAR) high resolution measurements. The proposed techniques depend particularly on two instrumental parameters: the radar system's spatial resolution and the number of configurations measured during satellite acquisitions (mainly incidence angle and polarization). In this paper, our objective is to illustrate different applications of SAR data to estimate soil moisture over bare soil and vegetation cover areas (wheat, olive groves, meadows ...). Potential of very high resolution data, with the availability of TerraSAR-X and COSMO-SkyMed constellations is also discussed. This study is based on different experimental campaigns organized over different sites in humid and semi-arid regions. Ground measurements (soil moisture, soil roughness, vegetation description) over test fields were carried out simultaneously to SAR measurements. Effect of vegetation attenuation on radar signal is considered through a synergy with optical remote sensing. Soil moisture precision for all proposed applications is generally ranged between 3 and 5% of volumetric moisture. These methodologies are developed in the context of the preparation for having a high soil moisture operational product, with SENTINEL and/or the other planned constellations. After an analysis of radar data sensitivity (C and X bands) to surface parameters, different inversion approaches are developed to estimate soil moisture (change detection, neural network, and physical or semi-empirical model inversion).

  12. Derivation of soil moisture sensing depth from microwave satellite sensors

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Holmes, Thomas

    2015-04-01

    Soil moisture retrievals from low frequency passive microwave satellite sensors (e.g. ESAs current Soil Moisture Ocean Salinity mission (SMOS)) are assumed to estimate spatially explicit soil moisture content of the first centimeters. However, the exact microwave sensing depth and the dynamic nature of the sensing depth at satellite grid scale is still to a large degree unknown. A more reliable estimation of the sensing depth would greatly improve the utility of microwave soil moisture retrievals. Validation activities could be fine-tuned, algorithms could be improved, and modeling applications could match observations to more optimal model depth. In addition to all this, soil moisture sensing depth information is essential for the development of a consistent fundamental soil moisture climate data record. With the availability of multiple polar orbiting satellites with multi-frequency microwave radiometers it has now become possible to study the microwave sensing depth as it manifests itself at observational scales. The approach uses the differences in timing between the diurnal temperature cycle (DTC) of microwave observations and thermal infrared observations as a basis to calculate the sensing depth. Using an intercalibrated multi sensor microwave data set and geostationary thermal infrared observations this approach is used to evaluate sensing depth at several microwave frequencies relevant for soil moisture retrieval. Field data in combination with an integrated thermodynamic hydrological microwave model are then used to develop guidelines for a dynamic sensing depth algorithm. The key advantage of this approach is its global applicability, providing timely and consistent information on sensing depth for different satellite soil moisture datasets.

  13. Validation and trend analysis of ECV soil moisture data on cropland in North China Plain during 1981-2010

    NASA Astrophysics Data System (ADS)

    Wang, Sisi; Mo, Xingguo; Liu, Suxia; Lin, Zhonghui; Hu, Shi

    2016-06-01

    Global time series of the Essential Climate Variable (ECV) soil mositure (SM) is being developed from passive and active satellite microwave sensors at a coarse spatial resolution with Climate Change Initiative program funded by European Space Agency. This study aims to validate the reliability of ECV SM dataset, and attempts are made to analyze SM trends in cropland. Firstly, in-situ SM measurements during crop growing seasons from 1992 to 2010 for 228 stations across China and 21 stations over cropland of North China Plain (NCP) were employed to validate ECV SM product. Then, the spatiotemporal variations of ECV SM were analyzed during growing period of winter wheat (April-June) and summer maize (July-September) from 1981 to 2010 in NCP. Finally, the possible relationship between SM, precipitation, evapotranspiration and NDVI were explored. Results showed that ECV SM could generally capture the seasonal SM dynamics. The average triple collocation random error of ECV SM in China was 0.052 m3 m-3 while the error in cropland ranged from 0.003 to 0.156 m3 m-3. The averaged Spearman correlation coefficient between ECV SM and all in-situ observations was 0.42 (p < 0.01) in China and 0.43 (p < 0.01) for cropland over NCP. Spatially, ECV SM was decreasing in most areas during wheat season, whereas the trends of ECV SM were positive in south and negative in north during maize season in NCP, being consistent with the precipitation fluctuation. Overall, ECV SM is potentially suitable for trend analysis in NCP and its validations and analysis will be helpful for further enhancement of the ECV SM product.

  14. Validation of the ESA CCI soil moisture product in China

    NASA Astrophysics Data System (ADS)

    An, Ru; Zhang, Ling; Wang, Zhe; Quaye-Ballard, Jonathan Arthur; You, Jiajun; Shen, Xiaoji; Gao, Wei; Huang, LiJun; Zhao, Yinghui; Ke, Zunyou

    2016-06-01

    The quality of a newly merged soil moisture product (ECV_SM v0.1) from active and passive microwave sensors has attracted widespread international attention. The performance evaluation of this product will benefit studies on climate, meteorology, agriculture, hydrology, ecology and the environment. In this study, meteorological station data and the Noah soil moisture product were used to validate the ECV_SM product in China. First, some conventional statistical measures, such as correlation coefficients, bias, root mean square difference (RMSD) and mean relative error (MRE), were computed to describe the level of agreement between the meteorological station data and ECV_SM values. The accuracy was moderately high (the correlation was significant at the 0.05 level), although the two datasets differed slightly for various types of land cover. Compared with cropland and urban and built-up areas, the performance of ECV_SM was best in grassland regions. Second, the triple collocation technique was used to assess the random error in the meteorological station data, Noah soil moisture product and ECV_SM product. The mean errors in these three datasets were 0.108, 0.079 and 0.075 m3 m-3, respectively, on July 8, 2010 and 0.099, 0.061 and 0.059 m3 m-3, respectively, on October 8, 2010. Only two days of data were used for the triple collocation test as a representative, but this cannot precisely indicate that the test results on any other day correspond with the test results on these two days. Additionally, a trend analysis of ECV_SM during 2003-2010 was carried out using the Mann-Kendall trend test.

  15. [Response of nitrification/denitrification and their associated microbes to soil moisture change in paddy soil].

    PubMed

    Liu, Ruo-Xuan; He, Ji-Zheng; Zhang, Li-Mei

    2014-11-01

    To investigate the effect of moisture change on nitrification and denitrification and their corresponding functional microbes, an acidic paddy soil from Taoyuan, Hunan Province was selected as the study object, and soil microcosm experiment containing 4 different water holding capacity (WHC) levels (30% WHC, 60% WHC, 90% WHC, and waterlog) was set up in this study. Results showed that no active nitrification and denitrification occurred in 30% WHC treatment as there were no obvious ammonia consumption and nitrate accumulation, while nitrification was active in 60% WHC and 90% WHC treatments as indicated by the obvious accumulation of nitrate in those two treatments. Meanwhile, significant ammonia consumption and N2O emission were only observed in 90% WHC treatment, implying that a much stronger nitrification in 90% WHC treatment than in 60% WHC treatment and the co-occurrence of nitrification and denitrification in 90% WHC treatment. In waterlog treatment, relatively lower N2O emission was detected and no obvious nitrification was detected, corresponding to a significant lower soil Eh in this treatment than in the other three non-waterlog treatments. Except the early stage of incubation (7 d), the abundance of nirS, nirK and ammonia-oxidizing bacteria (AOB) amoA genes showed similar responses to soil moisture change over time. Except the slight decrease in waterlog treatment, the abundances of the three genes increased significantly as the soil moisture increased, and the highest abundances of nirS, nirK, and amoA gene were observed in 90% WHC treatment in which the highest nitrification and denitrification activity was detected. T-RFLP analysis showed that the community composition of nirS gene-containing denitrifiers changed significantly in response to soil moisture change after two weeks, and soil Eh and C(w) were the main factors affecting the community composition of denitrifiers. PMID:25639106

  16. Passive Microwave Observation of Diurnal Surface Soil Moisture

    NASA Technical Reports Server (NTRS)

    Jackson, Thomas J.; ONeill, Peggy E.; Swift, Calvin T.

    1997-01-01

    Microwave radiometers operating at low frequencies are sensitive to surface soil moisture changes. Few studies have been conducted that have involved multifrequency observations at frequencies low enough to measure a significant soil depth and not be attenuated by the vegetation cover. Another unexplored aspect of microwave observations at low frequencies has been the impact of diurnal variations of the soil moisture and temperature on brightness temperature. In this investigation, observations were made using a dual frequency radiometer (1.4 and 2.65 GHz) over bare soil and corn for extended periods in 1994. Comparisons of emissivity and volumetric soil moisture at four depths for bare soils showed that there was a clear correspondence between the 1 cm soil moisture and the 2.65-GHz emissivity and between the 3-5 cm soil moisture and the 1.4-GHZ emissivity, which confirms previous studies. Observations during drying and rainfall demonstrate that new and unique information for hydrologic and energy balance studies can be extracted from these data.

  17. Predicting root zone soil moisture using surface data

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    In recent years, much effort has been given to monitoring of soil moisture from satellite remote sensing. These tools represent an extraordinary source of information for hydrological applications, but they only provide information on near-surface soil moisture. 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. The method derives from a simplified form of the soil water balance equation and for this reason all parameters adopted are physically consistent. The formulation provides a closed form of the relationship between the root zone soil moisture and the surface soil moisture with a limited number of parameters, such as: the ratio between the depth of the surface layer and the deeper layer, the water loss coefficient, and the field capacity. The method has been tested using modeled soil moisture obtained from the North American Land Data Assimilation System (NLDAS). The NLDAS is a multi-institution partnership aimed at developing a retrospective data set, using available atmospheric and land surface meteorological observations to compute the land surface hydrological budget. The NLDAS database was extremely useful for the scope of the present research since it provides simulated data over an extended area with different climatic and physical condition and moreover it provides soil moisture data averaged over different depths. In particular, we used values in the top 10 cm and 100 cm layers. One year of simulation was used to test the ability of the developed method to describe soil moisture fluctuation in the 100cm layer over the entire NLDAS domain. The method was adopted by calibrating one of its three parameters and defining the remaining two based on physical characteristics of the site (using the potential evapotranspiration and ratio between the first and the second soil layer depth). In general, the method performed better than traditional low pass filters and its performance increased especially in dry areas. The skill of the method is therefore encouraging and there is potential to use the method to derive root zone soil moisture from satellite retrievals.

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

    SciTech Connect

    Pan, Feifei; Peters-lidard, Christa D.; King, Anthony Wayne

    2010-11-01

    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.

  19. The NASA Soil Moisture Active Passive (SMAP) Mission Status

    NASA Astrophysics Data System (ADS)

    Entekhabi, D.; Yueh, S. H.; O'Neill, P. E.; Entin, J. K.; Kellogg, K.; Njoku, E. G.

    2014-12-01

    NASA's Soil Moisture Active Passive (SMAP) mission, the first planned Tier 1 Earth Science Decadal Survey flight, will provide high-resolution, frequent-revisit global mapping of soil moisture and freeze/thaw state. The mission will use low-frequency microwave radar and radiometer measurements (L-band) to produce high resolution global maps of surface soil moisture. The radiometer provides greater sensitivity to soil moisture but at low resolution (40 km). The radar provides higher resolution information with lower sensitivity. The SMAP active-passive surface soil moisture product is a combination of the two measurements with 9 km resolution that is refreshed every 2 to 3 days globally. The SMAP project will also provide root-zone soil moisture and Net Ecosystem Exchange (NEE) information produced by merging observations with models. The status of the satellite observatory and plans for the calibration and validation of SMAP products are presented. The schedule for data release is shown and planned science and applications analyses are outlined.

  20. Estimating surface soil moisture using ENVISAT RA-2 altimetry measurements

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    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.

  1. Satellite based estimates of soil moisture over the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Su, Z.; Wang, L.; Dente, L.; van der Velde, R.; Wen, J.; Ofwono, M.

    2010-05-01

    Soil moisture plays essential role in water cycle and climate. In particular, over the Tibetan plateau, its importance is particularly pronounced in directly influencing the Monsoon systems and its precipitation patterns. The feasibility of retrieving top layer soil moisture from satellite data has been demonstrated and several techniques hold promise for extensive observation of soil moisture (Jackson et al., 1999; De Jeu and Owe, 2003; Njoku, 2004; Paloscia, et al., 2003; Su et al., 2003; Wagner et al., 2007; Wen et al., 2003; Wen and Su 2003). The consistency among the products derived using different algorithms and their uncertainties have not been yet documented. The launch of the SMOS satellite has, however, promoted renewed science interests in the production of consistent soil moisture products and use of these in water cycle and climate research (Kerr, 2007). This requires corresponding validation on the basis of extensive in-situ soil moisture measurements (Robock et al., 2000), before the consistency and uncertainties of such products can be quantified. We present recent progresses for better estimation of soil moisture at plateau and sub-continental scales by using available coarse active and passive microwave observations (SSM/I, WSC and ASCAT data in particular) and validation of the developed methodologies using in-situ measurements from dedicated SMOS cal/val sites. Preliminary validations for SMOS data will also be presented subject to data availability.

  2. New insights in catchment processes via distributed soil moisture measurements and 3D hydrological modeling

    NASA Astrophysics Data System (ADS)

    Bogena, H. R.; Sciuto, G.; Rosenbaum, U.; Herbst, M.; Huisman, J. A.; Vereecken, H.; Diekkrueger, B.

    2010-12-01

    Hydrological analysis is often limited by the number of data available. Usually, discharge data and only little point information concerning soil moisture status are available. This might give a good representation of the temporal variability of runoff, but it does not provide insights into the spatial dynamics of soil moisture and water fluxes within the catchment. The small forested Wüstebach catchment (~27 ha) has been instrumented with a wireless sensor network consisting of 150 nodes and more than 1200 soil moisture sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [1]. This unique data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution. We present first results of a geostatistical analysis of the data and an application of the integrated surface/subsurface 3D finite element model HydroGeoSphere model to investigate the scale dependency of the temporal dynamics of soil moisture patterns. A variogram analysis showed that the sum of the sub-scale variability and the measurement error is close to time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil moisture, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to root water uptake, lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. The temporal patterns of runoff discharge were reproduced by the HydroGeoSphere model in a satisfying way. The observed soil moisture patterns were used to analyze the simulation quality. Generally, the model accuracy increased with decreasing spatial discretisation. The spatial discretisation of the model also had a larger effect on the water balance than the scaling of soil properties, which was attributed to the model equation describing transpiration dependency on water status and was not considered to be related to the scale dependency of hydrological processes. These findings demonstrate that the conceptual model (deciding on equations) is as important as the perceptual model (deciding on the processes). References: [1] Bogena, H.R., M. Herbst, J.A. Huisman, U. Rosenbaum, A. Weuthen, and H. Vereecken (2010): Potential of wireless sensor networks for measuring soil water content variability. Vadose Zone J., doi:10.2136/vzj2009.0173.

  3. Operational Soil Moisture Estimation for the Midwestern United States.

    NASA Astrophysics Data System (ADS)

    Kunkel, Kenneth E.

    1990-11-01

    An operational soil moisture monitoring capability for the midwestern United States is developed using a multilayer soil water balance model which incorporates daily weather data to calculate precipitation, soil evaporation, plant transpiration, runoff, and drainage through the soil profile. The effects of vegetation on soil evaporation and plant transpiration are incorporated through the use of a model for the growth and development of corn. Data requirements include daily observations of maximum temperature, minimum temperature, and precipitation and hourly observations of cloud cover, humidity, and wind speed; these data are collected in real time and aggregated on a climate division scale. The average characteristics of the dominant soils in each climate division are used as representative of that climate division. Using these weather and soils data, the model makes estimates of the current soil moisture status on a climate division basis updated daily. Historical soil moisture estimates using this same model were generated for the period 1949-89 to provide an historical perspective on current soil moisture estimates. This information is accessible to the public through a dial-up computer information system.

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

    USGS Publications Warehouse

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

    2009-01-01

    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.

  5. The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates

    NASA Astrophysics Data System (ADS)

    Seyyedi, H.; Anagnostou, E. N.

    2011-12-01

    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.

  6. Preliminary results of SAR soil moisture experiment, November 1975

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

    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.

  7. Validation of SMOS Soil Moisture Products over the Maqu and Twente Regions

    PubMed Central

    Dente, Laura; Su, Zhongbo; Wen, Jun

    2012-01-01

    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 m3/m3 for the Maqu region and 0.17 m3/m3 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

  8. Application of observation operators for field scale soil moisture averages and variances in agricultural landscapes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is a key variable in understanding hydrologic processes and energy fluxes at the land surface. In spite of developing technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations ...

  9. Soil moisture sensor intercomparisons at the SMAP marena in situ testbed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In May 2010, a soil moisture sensor intercomparison study was begun in Marena, Oklahoma. This effort is designed to serve as a foundation for incorporating diverse soil moisture networks into the Soil Moisture Active Passive (SMAP) Calibration and Validation program. Various soil moisture sensors, w...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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) ...

  11. Comparison of soil moisture products obtained from active and passive microwave data

    NASA Astrophysics Data System (ADS)

    Dente, L.; Vekerdy, Z.; de Jeu, R.

    2009-04-01

    Forty years of research on passive and active microwave observations have led so far to a better understanding of the sensitivity of satellite microwave observations to soil moisture and to a higher confidence in the possibility to retrieve reliable soil moisture from these sensors at small as well as large scale. This research forms the basis of two important new satellite missions: ESA's Soil Moisture and Ocean Salinity mission (SMOS) and NASA's Soil Moisture Active and Passive mission (SMAP) whose main goal is the retrieval of soil moisture at global scale. In view of these missions, the research has been recently focussed more on the development of soil moisture retrieval methods which can be applied at global scale and on their application over the existing scatterometer (ERS scatterometer and Metop ASCAT) and radiometer (SMMR and AMSR-E) data to obtain long time series of global products. In this work, two global soil moisture products, one obtained from radiometer data and the other from scatterometer data, have been compared. The main objective of this comparison is to better understand the potential and limitations for soil moisture retrieval of both the data and the applied method and to investigate the possible complementarity of the different datasets. The two surface soil moisture datasets employed in this study are: the product obtained from AQUA AMSR-E data by the Department of Hydrology and Geo-Environmental Sciences of the Vrije Universiteit of Amsterdam and the product retrieved from ERS-2 scatterometer data by the Institute of Photogrammetry and Remote Sensing of the Vienna University of Technology. The temporal variability from 2003 to 2007, the seasonal trends, the anomalies, the autocorrelations and the correlation between the two global datasets have been analysed. Two in-situ datasets collected by large soil moisture monitoring networks in Oklahoma (Oklahoma Mesonet) and in Australia (OzNet) have been also included in this comparison. However the analysis has been also extended to other areas characterised by different vegetation cover. In these cases, temporal variability and trends have been compared with GPCC precipitation data. The analysis shows a general good agreement between the two global soil moisture datasets and with in-situ and precipitation data. Comparable temporal variability, trends and autocorrelations have been observed between AMSR-E and ERS soil moisture products over OzNet test site, confirmed also by the analysis of the soil moisture measured in-situ at a depth of 5 cm. As expected, the soil moisture measured at deeper layer shows trends shifted in time and longer autocorrelation than the satellite products. The obtained results can support the possibility to integrate the two soil moisture products and to synergistically use active and passive microwave data for soil moisture monitoring at global scale.

  12. NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

    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.

  14. Desert shrub stemflow and its significance in soil moisture replenishment

    NASA Astrophysics Data System (ADS)

    Wang, X.-P.; Wang, Z.-N.; Berndtsson, R.; Zhang, Y.-F.; Pan, Y.-X.

    2011-02-01

    Stemflow of xerophytic shrubs represents a significant component of water replenishment to the soil-root system influencing water utilization of plant roots at the stand scale, especially in water scarce desert ecosystems. In this study, stemflow of Caragana korshinskii was quantified by an aluminum foil collar collection method on re-vegetated sand dunes of the Shapotou restored desert ecosystem in northwestern China. Time domain reflectometry probes were inserted horizontally at 20 different soil profile depths under the C. korshinskii shrub to monitor soil moisture variation at hourly intervals. Results indicated that 2.2 mm precipitation was necessary for the generation of stemflow for C. korshinskii. Stemflow averaged 8% of the gross precipitation and the average funnelling ratio was as high as 90. The soil moisture in the uppermost soil profile was strongly correlated with individual rainfall and the stemflow strengthened this relationship. Therefore, it is favourable for the infiltrated water redistribution in the deeper soil profile of the root zone. Consequently, stemflow contributes significantly to a positive soil moisture balance in the root zone and the replenishment of soil moisture at deeper soil layers. This plays an important role in plant survival and the general ecology of arid desert environments.

  15. Evaluation of polarimetric SAR parameters for soil moisture retrieval

    NASA Technical Reports Server (NTRS)

    Shi, Jian-Cheng; Vanzyl, Jakob J.; Engman, Edwin T.

    1992-01-01

    Results of ongoing efforts to develop an algorithm for soil moisture retrieval from Synthetic Aperture Radar (SAR) imagery are reported. Estimates of soil moisture are of great importance in numerous environmental studies, including hydrology, meteorology, and agriculture. Previous studies using extensive scatterometer measurements have established the optimum parameters for moisture retrieval as C-band HH radar operating at incidence angles between 10 to 15 deg. However, these parameters were not tested or verified with imaging radar systems. The results from different investigators showed considerable variability in the relationship between soil moisture and radar backscattering. This variability suggests that those algorithms are site-specific. Furthermore, the small incidence angle requirement limits the spatial application, especially for airborne radar systems.

  16. Aircraft scatterometer observations of soil moisture on rangeland watersheds

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; Oneill, P. E.

    1983-01-01

    Extensive studies conducted by several researchers using truck-mounted active microwave sensors have shown the sensitivity of these sensors to soil moisture variations. The logical extension of these results is the evaluation of similar systems at lower resolutions typical of operational systems. Data collected during a series of aircraft flights in 1978 and 1980 over four rangeland watersheds located near Chickasha, Oklahoma, were analyzed in this study. These data included scatterometer measurements made at 1.6 and 4.75 GHz using a NASA aircraft and ground observations of soil moisture for a wide range of moisture conditions. Data were analyzed for consistency and compared to previous truck and aircraft results. Results indicate that the sensor system is capable of providing consistent estimates of soil moisture under the conditions tested.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  18. Soil moisture monitoring methods: Strengths and limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    All soil water content sensors require soil-specific calibration but calibration of capacitance sensors, whether in the laboratory or in the field, doesnt ensure accuracy in the field. EM fields from capacitance sensors do not uniformly interrogate the soil and are influenced by soil structure ...

  19. Bulk Density and Soil Moisture Sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil bulk density is a good indicator of problems of root penetration, soil aeration, and water infiltration. Knowledge of soil water content is important to understand crop water use, leaching of chemicals, and soil trafficability. The purpose of this presentation is to detail step-by-step how to m...

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    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.

  1. Estimating soil moisture and soil thermal and hydraulic properties by assimilating soil temperatures using a particle batch smoother

    NASA Astrophysics Data System (ADS)

    Dong, Jianzhi; Steele-Dunne, Susan C.; Ochsner, Tyson E.; Giesen, Nick van de

    2016-05-01

    This study investigates the potential of estimating the soil moisture profile and the soil thermal and hydraulic properties by assimilating soil temperature at shallow depths using a particle batch smoother (PBS) using synthetic tests. Soil hydraulic properties influence the redistribution of soil moisture within the soil profile. Soil moisture, in turn, influences the soil thermal properties and surface energy balance through evaporation, and hence the soil heat transfer. Synthetic experiments were used to test the hypothesis that assimilating soil temperature observations could lead to improved estimates of soil hydraulic properties. We also compared different data assimilation strategies to investigate the added value of jointly estimating soil thermal and hydraulic properties in soil moisture profile estimation. Results show that both soil thermal and hydraulic properties can be estimated using shallow soil temperatures. Jointly updating soil hydraulic properties and soil states yields robust and accurate soil moisture estimates. Further improvement is observed when soil thermal properties were also estimated together with the soil hydraulic properties and soil states. Finally, we show that the inclusion of a tuning factor to prevent rapid fluctuations of parameter estimation, yields improved soil moisture, temperature, and thermal and hydraulic properties.

  2. Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

    NASA Astrophysics Data System (ADS)

    Cumbrera, Ramiro; Tarquis, Ana M.; Gascó, Gabriel; Millán, Humberto

    2012-07-01

    SummaryImage analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates.

  3. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    NASA Astrophysics Data System (ADS)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

  4. Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment

    SciTech Connect

    Luo, Yan; Houser, Paul; Anantharaj, Valentine G; Fan, Xingang; De Lannoy, Gabrielle; Zhan, Xiwu

    2013-01-01

    Using an observing system simulation experiment (OSSE), we investigate the potential soil moisture retrieval capability of the National Aeronautics and Space Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) and scatterometer (L-band, 1.260 GHz). We estimate potential errors in soil moisture retrievals and identify the sources that could cause those errors. The OSSE system includes (i) a land surface model in the NASA Land Information System, (ii) a radiative transfer and backscatter model, (iii) a realistic orbital sampling model, and (iv) an inverse soil moisture retrieval model. We execute the OSSE over a 1000 2200 km2 region in the central United States, including the Red and Arkansas river basins. Spatial distributions of soil moisture retrieved from the radiometer and scatterometer are close to the synthetic truth. High root mean square errors (RMSEs) of radiometer retrievals are found over the heavily vegetated regions, while large RMSEs of scatterometer retrievals are scattered over the entire domain. The temporal variations of soil moisture are realistically captured over a sparely vegetated region with correlations 0.98 and 0.63, and RMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer, respectively. Over the densely vegetated region, soil moisture exhibits larger temporal variation than the truth, leading to correlation 0.70 and 0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. The domain-averaged correlations and RMSEs suggest that radiometer is more accurate than scatterometer in retrieving soil moisture. The analysis also demonstrates that the accuracy of the retrieved soil moisture is affected by vegetation coverage and spatial aggregation.

  5. Influence of Soil Moisture on Soil Gas Vapor Concentration for Vapor Intrusion

    PubMed Central

    Shen, Rui; Pennell, Kelly G.; Suuberg, Eric M.

    2013-01-01

    Abstract Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The “open field” soil gas vapor concentration profile is observed to be sensitive to the soil moisture distribution. The van Genuchten relations can be used for describing the soil moisture retention curve, and give results consistent with the results from a previous experimental study. Other modeling methods that account for soil moisture are evaluated. These modeling results are also compared with the measured subsurface concentration profiles in the U.S. EPA vapor intrusion database. PMID:24170970

  6. Application of the Preisach Model to Soil-moisture Hysteresis

    NASA Astrophysics Data System (ADS)

    O'Kane, J.; Pokrovskii, A.; Krejci, P.; Haverkamp, R.

    2003-12-01

    An examination of the physics of the land phase of the hydrological cycle shows that the most important non-linearities occur in the unsaturated zone of the soil. These have been studied using switched boundary conditions applied to the one-dimensional form of Richards differential equation, modelling the wetting and drying of a column of bare or vegetated soil, at a scale of roughly one meter. However, the strongly non-linear hysteretic property of the soil moisture characteristic is usually ignored. Smooth non-linear differential, or integro-differential, operators cannot reproduce soil-moisture hysteresis. The classical Preisach Model is presented and applied to the quantitative description of soil-moisture scanning curves. The Preisach model is a deterministic, rate independent non-linear operator with return-point memory and congruent loops. Special, one parameter, classes of Preisach operators are proposed as models of soil-moisture hysteresis for particular soils. The results of fitting these operators to laboratory and field data, taken from the Grenoble GRIZZLY Soil Database, are presented and discussed.

  7. SOIL MOISTURE MONITORING TO ASSIST IRRIGATION SCHEDULING FOR POTATO CROPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Potato production in the Columbia Basin region of the Pacific Northwest is primarily dependent on irrigation. The soils of the region are sandy and continuous monitoring of soil moisture content within and below the root zone can facilitate optimal irrigation scheduling aimed at minimizing both the ...

  8. ESTIMATING CORN GRAIN YIELD FROM TEMPORAL VARIATIONS OF SOIL MOISTURE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is often sited as the principal factor controlling yield response in rain-fed agricultural production systems. During the past two decades, a great deal of research has been conducted that attempts to describe the spatial and temporal variability of crop yield as a function of soil pr...

  9. Using data assimilation techniques to calibrate soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Traditional efforts to quantify the value of remotely-sensed soil moisture retrievals via comparison to ground-based measurements have been hindered by inconsistencies in spatial and temporal scales between the two products. A new method was developed to assess the "skill" of remotely-sensed soil mo...

  10. Dependence of soil respiration on soil temperature and soil moisture in successional forests in Southern China

    USGS Publications Warehouse

    Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, J.; Zhou, C.-Y.

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (?? SD) soil respiration rate in the DNR forests was (9.0 ?? 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ?? 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ?? 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities. ?? 2006 Institute of Botany, Chinese Academy of Sciences.

  11. Warm-season soil moisture-temperature coupling in historical and future climate projections

    NASA Astrophysics Data System (ADS)

    Williams, I. N.

    2014-12-01

    Anomalously dry soil moisture can lead to reduced evapotranspiration and increased surface temperatures. These higher temperatures have been hypothesized to further reduce soil moisture, enhance temperature variability, and prolong dry extremes, particularly in warmer climates. Historical and future climate projections from the Coupled Model Inter-comparison Project (CMIP5) were investigated in this study to identify climate trends attributable to soil moisture-temperature coupling and feedback processes. It was found that the probability of temperature extremes (departures from seasonal averages) increases under global warming, and the time taken to return toward average warm-season temperatures following temperature extremes (i.e. persistence) increases by more than 25% over many land regions. An analysis of changes in surface energy balance suggests that this increased persistence of warm temperature extremes results from decreased surface longwave radiative cooling at warm temperature extremes under global warming. This process was also found in radiative forcing experiments using a single-column climate model having a realistic radiation scheme and a simplified land surface model, where the sensitivity of extremes to the relationship between soil moisture and transpiration was further investigated. The persistence of warm extremes depends on the soil moisture content at stomatal closure (wilting point), where higher wilting points lead to larger reductions in surface longwave emission at warm extremes and increased persistence of extremes. These results highlight the importance of surface radiation regime and vegetation in soil moisture-temperature feedbacks.

  12. Optimal averaging of soil moisture predictions from ensemble land surface model simulations

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Su, C.-H.; Ryu, D.; Yilmaz, M. T.

    2015-11-01

    The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble's mutual error covariance. Here we propose a technique for obtaining such information using an instrumental variable (IV) regression approach and comparisons against a long-term surface soil moisture data set acquired from satellite remote sensing. Application of the approach to multimodel ensemble soil moisture output from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) and European Space Agency (ESA) Soil Moisture (SM) Essential Climate Variable (ECV) data set allows for the calculation of optimal weighting coefficients for individual members of the NLDAS-2 LSM ensemble and a biased-minimized estimate of uncertainty in a deterministic soil moisture analysis derived via optimal averaging. As such, it provides key information required to accurately condition soil moisture expectations using information gleaned from a multimodel LSM ensemble. However, existing continuity and rescaling concerns surrounding the generation of long-term, satellite-based soil moisture products must likely be resolved before the proposed approach can be applied with full confidence.

  13. Correction of real-time satellite precipitation with satellite soil moisture observations

    NASA Astrophysics Data System (ADS)

    Zhan, W.; Pan, M.; Wanders, N.; Wood, E. F.

    2015-06-01

    Rainfall and soil moisture are two key elements in modeling the interactions between the land surface and the atmosphere. Accurate and high-resolution real-time precipitation is crucial for monitoring and predicting the on-set of floods, and allows for alert and warning before the impact becomes a disaster. Assimilation of remote sensing data into a flood-forecasting model has the potential to improve monitoring accuracy. Space-borne microwave observations are especially interesting because of their sensitivity to surface soil moisture and its change. In this study, we assimilate satellite soil moisture retrievals using the Variable Infiltration Capacity (VIC) land surface model, and a dynamic assimilation technique, a particle filter, to adjust the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) real-time precipitation estimates. We compare updated precipitation with real-time precipitation before and after adjustment and with NLDAS gauge-radar observations. Results show that satellite soil moisture retrievals provide additional information by correcting errors in rainfall bias. High accuracy soil moisture retrievals, when merged with precipitation, generally increase both rainfall frequency and intensity, and are most effective in the correction of rainfall under dry to normal surface condition while limited/negative improvement is seen over wet/saturated surfaces. Errors from soil moisture, mixed among the real signal, may generate a false rainfall signal approximately 2 mm day-1 and thus lower the precipitation accuracy after adjustment.

  14. Correction of real-time satellite precipitation with satellite soil moisture observations

    NASA Astrophysics Data System (ADS)

    Zhan, W.; Pan, M.; Wanders, N.; Wood, E. F.

    2015-10-01

    Rainfall and soil moisture are two key elements in modeling the interactions between the land surface and the atmosphere. Accurate and high-resolution real-time precipitation is crucial for monitoring and predicting the onset of floods, and allows for alert and warning before the impact becomes a disaster. Assimilation of remote sensing data into a flood-forecasting model has the potential to improve monitoring accuracy. Space-borne microwave observations are especially interesting because of their sensitivity to surface soil moisture and its change. In this study, we assimilate satellite soil moisture retrievals using the Variable Infiltration Capacity (VIC) land surface model, and a dynamic assimilation technique, a particle filter, to adjust the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) real-time precipitation estimates. We compare updated precipitation with real-time precipitation before and after adjustment and with NLDAS gauge-radar observations. Results show that satellite soil moisture retrievals provide additional information by correcting errors in rainfall bias. The assimilation is most effective in the correction of medium rainfall under dry to normal surface conditions, while limited/negative improvement is seen over wet/saturated surfaces. On the other hand, high-frequency noises in satellite soil moisture impact the assimilation by increasing rainfall frequency. The noise causes larger uncertainty in the false-alarmed rainfall over wet regions. A threshold of 2 mm day-1 soil moisture change is identified and applied to the assimilation, which masked out most of the noise.

  15. Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

    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.

  16. Soil Moisture Estimation under Vegetation Applying Polarimetric Decomposition Techniques

    NASA Astrophysics Data System (ADS)

    Jagdhuber, T.; Schön, H.; Hajnsek, I.; Papathanassiou, K. P.

    2009-04-01

    Polarimetric decomposition techniques and inversion algorithms are developed and applied on the OPAQUE data set acquired in spring 2007 to investigate their potential and limitations for soil moisture estimation. A three component model-based decomposition is used together with an eigenvalue decomposition in a combined approach to invert for soil moisture over bare and vegetated soils at L-band. The applied approach indicates a feasible capability to invert soil moisture after decomposing volume and ground scattering components over agricultural land surfaces. But there are still deficiencies in modeling the volume disturbance. The results show a root mean square error below 8.5vol.-% for the winter crop fields (winter wheat, winter triticale and winter barley) and below 11.5Vol-% for the summer crop field (summer barley) whereas all fields have a distinct volume layer of 55-85cm height.

  17. Rainfall estimation from soil moisture data: crash test for SM2RAIN algorithm

    NASA Astrophysics Data System (ADS)

    Brocca, Luca; Albergel, Clement; Massari, Christian; Ciabatta, Luca; Moramarco, Tommaso; de Rosnay, Patricia

    2015-04-01

    Soil moisture governs the partitioning of mass and energy fluxes between the land surface and the atmosphere and, hence, it represents a key variable for many applications in hydrology and earth science. In recent years, it was demonstrated that soil moisture observations from ground and satellite sensors contain important information useful for improving rainfall estimation. Indeed, soil moisture data have been used for correcting rainfall estimates from state-of-the-art satellite sensors (e.g. Crow et al., 2011), and also for improving flood prediction through a dual data assimilation approach (e.g. Massari et al., 2014; Chen et al., 2014). Brocca et al. (2013; 2014) developed a simple algorithm, called SM2RAIN, which allows estimating rainfall directly from soil moisture data. SM2RAIN has been applied successfully to in situ and satellite observations. Specifically, by using three satellite soil moisture products from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation) and SMOS (Soil Moisture and Ocean Salinity); it was found that the SM2RAIN-derived rainfall products are as accurate as state-of-the-art products, e.g., the real-time version of the TRMM (Tropical Rainfall Measuring Mission) product. Notwithstanding these promising results, a detailed study investigating the physical basis of the SM2RAIN algorithm, its range of applicability and its limitations on a global scale has still to be carried out. In this study, we carried out a crash test for SM2RAIN algorithm on a global scale by performing a synthetic experiment. Specifically, modelled soil moisture data are obtained from HTESSEL model (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced by ERA-Interim near-surface meteorology. Afterwards, the modelled soil moisture data are used as input into SM2RAIN algorithm for testing weather or not the resulting rainfall estimates are able to reproduce ERA-Interim rainfall data. Correlation, root mean square differences and categorical scores were used to evaluate the goodness of the results. This analysis wants to draw global picture of the performance of SM2RAIN algorithm in absence of errors in soil moisture and rainfall data. First preliminary results over Europe have shown that SM2RAIN performs particularly well over southern Europe (e.g., Spain, Italy and Greece) while its performances diminish by moving towards Northern latitudes (Scandinavia) and over Alps. The results on a global scale will be shown and discussed at the conference session. REFERENCES Brocca, L., Melone, F., Moramarco, T., Wagner, W. (2013). A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters, 40(5), 853-858. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141. Chen F, Crow WT, Ryu D. (2014) Dual forcing and state correction via soil moisture assimilation for improved rainfall-runoff modeling. J Hydrometeor, 15, 1832-1848. Crow, W.T., van den Berg, M.J., Huffman, G.J., Pellarin, T. (2011). Correcting rainfall using satellite-based surface soil moisture retrievals: the soil moisture analysis rainfall tool (SMART). Water Resour Res, 47, W08521. Dee, D. P.,et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteorol. Soc., 137, 553-597 Massari, C., Brocca, L., Moramarco, T., Tramblay, Y., Didon Lescot, J.-F. (2014). Potential of soil moisture observations in flood modelling: estimating initial conditions and correcting rainfall. Advances in Water Resources, 74, 44-53.

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

    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.

  19. Poor Soil Wettability: Does moisture alter measurement results?

    NASA Astrophysics Data System (ADS)

    Dragila, M. I.; Woolverton, P.; Horneck, D.; Kleber, M.

    2013-12-01

    Poor soil wettability is a global problem, creating challenges to agriculture by plant drought stress and to soil stability in natural environments. Events that lead to poor soil wettability are varied, including natural and manmade events such as forest fires, hot dry environments, poor soil management or the application of post-consumer materials. Even though options offered in the literature for amelioration of the symptoms of hydrophobicity greatly differ, the basic techniques used to identify hydrophobic soil have changed very little over the past half-century. Recently, however, scientists have begun to question what these traditional techniques are actually measuring. One of the areas of interest is the relationship of hydrophobicity to moisture content, also termed reversible or seasonal hydrophobicity. Many studies suggest that changes in the organic matter structure as it is exposed to soil moisture leads to a reduction of the surface energy of particle surfaces. This study further complements that work by investigating how testing methods and soil-sample treatment impact water sorption of hydrophobic media, so as to make it appear that the surface energy has changed. The understanding of this phenomenon can lead to improved techniques for testing of hydrophobicity soil and also for soil management in agricultural areas by understanding the impact of soil moisture regimes on wettability.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  1. Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

    NASA Astrophysics Data System (ADS)

    Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

    2014-12-01

    Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  3. Determination of soil moisture distribution from impedance and gravimetric measurements

    NASA Technical Reports Server (NTRS)

    Ungar, Stephen G.; Layman, Robert; Campbell, Jeffrey E.; Walsh, John; Mckim, Harlan J.

    1992-01-01

    Daily measurements of the soil dielectric properties at 5 and 10 cm were obtained at five locations throughout the First ISLSCP Field Experiment (FIFE) test site during the 1987 intensive field campaigns (IFCs). An automated vector voltmeter was used to monitor the complex electrical impedance, at 10 MHz, of cylindrical volumes of soil delineated by specially designed soil moisture probes buried at these locations. The objective of this exercise was to test the hypothesis that the soil impedance is sensitive to the moisture content of the soil and that the imaginary part (that is, capacitive reactance) can be used to calculate the volumetric water content of the soil. These measurements were compared with gravimetric samples collected at these locations by the FIFE staff science team.

  4. Spatiotemporal analyses of soil moisture from point to footprint scale in two different hydroclimatic regions

    NASA Astrophysics Data System (ADS)

    Joshi, Champa; Mohanty, Binayak P.; Jacobs, Jennifer M.; Ines, Amor V. M.

    2011-01-01

    This paper presents time stability analyses of soil moisture at different spatial measurement support scales (point scale and airborne remote sensing (RS) footprint scale 800 m × 800 m) in two different hydroclimatic regions. The data used in the analyses consist of in situ and passive microwave remotely sensed soil moisture data from the Southern Great Plains Hydrology Experiments 1997 and 1999 (SGP97 and SGP99) conducted in the Little Washita (LW) watershed, Oklahoma, and the Soil Moisture Experiments 2002 and 2005 (SMEX02 and SMEX05) in the Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percent silt, percent sand, and soil texture) and topography (elevation and slope) are significant physical controls jointly affecting the spatiotemporal evolution and time stability of soil moisture at both point and footprint scales. In Iowa, using point-scale soil moisture measurements, the WC11 field was found to be more time stable (TS) than the WC12 field. The common TS points using data across the 3 year period (2002-2005) were mostly located at moderate to high elevations in both the fields. Furthermore, the soil texture at these locations consists of either loam or clay loam soil. Drainage features and cropping practices also affected the field-scale soil moisture variability in the WC fields. In Oklahoma, the field having a flat topography (LW21) showed the worst TS features compared to the fields having gently rolling topography (LW03 and LW13). The LW13 field (silt loam) exhibited better time stability than the LW03 field (sandy loam) and the LW21 field (silt loam). At the RS footprint scale, in Iowa, the analysis of variance (ANOVA) tests show that the percent clay and percent sand are better able to discern the TS features of the footprints compared to the soil texture. The best soil indicator of soil moisture time stability is the loam soil texture. Furthermore, the hilltops (slope ˜0%-0.45%) exhibited the best TS characteristics in Iowa. On the other hand, in Oklahoma, ANOVA results show that the footprints with sandy loam and loam soil texture are better indicators of the time stability phenomena. In terms of the hillslope position, footprints with mild slope (0.93%-1.85%) are the best indicators of TS footprints. Also, at both point and footprint scales in both the regions, land use-land cover type does not influence soil moisture time stability.

  5. Longwall Coal Mining and Soil Moisture Changes in Southwestern Pennsylvania

    NASA Astrophysics Data System (ADS)

    Pfeil-McCullough, E. K.; Bain, D.

    2014-12-01

    Subsidence from longwall coal mining impacts the surface and sub-surface hydrology in overlying areas. During longwall mining, coal is completely removed in large rectangular panels and the overlying rock collapses into the void. Though the hydrologic effects of longwall mining subsidence have been studied in arid systems, in humid-temperate regions these effects are not well understood. In particular, it is not clear how longwall mining will impact soil moisture patterns. Utilizing simple soil water modeling frameworks (ArcGIS-based Water Balance Toolbox) and the locations of recent long wall mining, potential impacts on soil water availability were predicted at the landscape scale. For example, in areas overlying panel edges, soil available water capacities (AWC) were altered based on several scenarios of AWC change and interactions between aspect driven soil moisture regimes and the mining perturbation were explored over a five year period (2008-2013). The regular patterns of soil moisture arising from insolation contrasts, when interacting with broad-scale longwall mining impacts, are predicted to cause complicated patterns of soil moisture change. These predictions serve as a means to guide field campaigns necessary to understand longwall mining's hydrologic impacts in wetter climates

  6. Hydrological connectivity drives microbial responses to soil moisture (Invited)

    NASA Astrophysics Data System (ADS)

    Schimel, J.

    2013-12-01

    Biogeochemical models generally fit microbial responses to moisture with smooth functions--as soils dry, processes slow. Microbial physiology, in contrast, has focused on how cells synthesize organic solutes to remain hydrated. Increasingly, however, we recognize that drying affects soil processes through resource constraints that develop when hydrological connection breaks down and organisms and resources become isolated in disconnected water pockets. Thus, microbial activity is regulated by abrupt breaks in connectivity and resources become unavailable to synthesize organic osmolytes; i.e. both biogeochemical models and pure-culture physiology perspectives are flawed. Hydrological connectivity fails before microbes become substantially stressed and before extracellular enzymes become inactive. Thus, resources can accumulate in dry soils, even as microbial activity shuts down because of resource limitation. The differential moisture responses of enzymes, organisms, and transport explains why microbial biomass and extractable C pools increase through the dry summer in California annual grasslands, why the size of the respiration pulse on rewetting increases with the length of drought, and even why soils from a wide range of biomes show the same relative response to soil moisture. I will discuss the evidence that supports the hydrological connectivity hypothesis for soil microbial moisture responses, how it affects a range of ecosystem processes, and how we can use it to develop simple, yet mechanistically rich, models of soil dynamics.

  7. SIMULTANEOUS SOIL MOISTURE AND CONE INDEX MEASUREMENT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil compaction can restrict root growth and water infiltration resulting in yield reduction. Maps of yield monitor data aid in visualization of variations in yield without identifying underlying factors for these variations. Soil penetration resistance can help identify areas where soil physical ch...

  8. An evaluation of the spatial resolution of soil moisture information

    NASA Technical Reports Server (NTRS)

    Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.

    1981-01-01

    Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

  9. Soil moisture and strength index for earthwork construction quality control

    NASA Astrophysics Data System (ADS)

    Sawangsuriya, A.; Wachiraporn, S.; Sramoon, W.

    2015-09-01

    This paper presents the implementation of soil moisture and strength index measurements for earthwork construction quality control as well as a link between the in situ testing and structural property of earthen materials. Use of the convenient Dynamic Cone Penetrometer (DCP) in conjunction with conventional moisture-density measurements enhances quality control by achieving acceptable level of compaction, more uniform structural properties, and aids developing a controlled design parameter during the earthwork construction. Soil strength in term of DCP index normalized by the deviation of compaction moisture content from the optimum moisture content is proposed as performance criteria for a variety of engineered earth fills and special engineering assessment, prevention, and mitigation of geohazards e.g. earthen flood defense embankments.

  10. Small-scale soil moisture determination with GPR

    NASA Astrophysics Data System (ADS)

    Igel, Jan; Preetz, Holger

    2010-05-01

    The knowledge of topsoil moisture distribution is an important input for modelling water flow and evapotranspiration which are essential processes in hydrology, meteorology, and agriculture. All these processes involve non-linear effects and thus the small-scale variability of input parameters play an important role. Using smoothed interpolations instead can cause significant biases. Lateral soil moisture distribution can be sensed by different techniques at various scales whereby geophysical methods provide spatial information which closes the gap between point measurements by classical soil scientific methods and measurements on the field or regional scale by remote sensing. Ground-penetrating radar (GPR) can be used to explore soil moisture on the field scale as propagation of electromagnetic waves is correlated to soil water content. By determining the velocity of the ground wave, which is a guided wave travelling along the soil surface, we can sense soil water content. This method has been applied to determine topsoil moisture for several years. We present a new groundwave technique which determines the velocity in between two receiving antennas which enables a higher lateral resolution (approx. 10 cm) compared to classical groundwave technique (half meter and more). We present synthetic data from finite-differences (FD) calculations as well as data from a sandbox experiment carried out under controlled conditions to demonstrate the performance of this method. Further, we carried out field measurements on two sites on a sandy soil which is used as grassland. The measurements were carried out in late summer at dry soil conditions. Soil moisture on the first site shows an isotropic pattern with correlation lengths of approx. 35 cm. We think this natural pattern is governed by rout distribution within the soil and the water uptake of vegetation. On the second site, soil moisture distribution shows a regular stripe pattern. As the land has been used as agricultural crop land until two years before the measurements were carried out, this anisotropy is obviously caused by the former cultivation of the land. Finally, we present a second technique to determine moisture of the topsoil by GPR using the same principle as remote sensing: the reflection of electromagnetic waves at the soil surface and determination of reflection amplitude. We use a 1 GHz horn antenna that is operated 0.5 m above the ground surface. As this method is based on a completely different physical principle than the first one, it provides an independent revision of our results. Even though, lateral resolution is not that high as when using the groundwave technique and the depth of investigation is not exactly the same, we get similar results showing the same pattern and characteristics at both sites.

  11. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    NASA Astrophysics Data System (ADS)

    Castillo, A.; Castelli, F.; Entekhabi, D.

    2015-04-01

    Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101-103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10-3-10-1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-pixel version of a distributed catchment hydrologic model and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

  12. NASA Soil Moisture Active Passive (SMAP) Mission Formulation

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and ground processing designs.

  13. A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Tibetan Plateau and Its Applications

    NASA Astrophysics Data System (ADS)

    Yang, K.

    2013-12-01

    In situ measurements are required to support the calibration and validation of satellite remote sensing of soil moisture. 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. The data is being publicized via the International Soil Moisture Network. Based on the soil moisture data, we have conducted studies to evaluate GLDAS output and remotes sensing products, and to develop soil moisture upscaling and data assimilation algorithms. References: Yang, K., J. Qin, L. Zhao, Y. Y. Chen, W. J. Tang, M. L. Han, Lazhu, Z. Q. Chen, N. Lv, B. H. Ding, H. Wu, C. G. Lin, 2013: A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole, Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-12-00203.1, in press Chen, Y. Y., K. Yang, J. Qin, L. Zhao, W. J. Tang and M. L. Han, 2013: Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau, J. Geophys. Res. Atmos., 118, doi:10.1002/jgrd.50301. 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., 2013: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology, 482, 92-104 doi:10.1016/j.jhydrol.2012.12.033.

  14. Soil moisture retrieval by active/passive microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Wu, Shengli; Yang, Lijuan

    2012-09-01

    This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship 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.

  15. Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data

    NASA Astrophysics Data System (ADS)

    Zawadzki, Jaroslaw; Kędzior, Mateusz

    2016-03-01

    Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band, radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission, which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavorable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries - Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118,861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe. This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012. This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of a large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, Centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual comparisons. The results obtained using various statistical tools unveil high scientific potential of CATDS SMOS data to study soil moisture over the Odra river watershed. This was also confirmed by reasonable agreement between results derived from CATDS SMOS Ascending and GLDAS data sets. This agreement was achieved mainly by using these data spatially averaged over the whole watershed area, and for observations performed in the period longer than three-day averaging time. Comparisons of separate three-day data in a given pixel position, or at smaller areas would be difficult because of data gaps. Hence, the results of the work suggest that despite of RFI interferences, SMOS observations can provide effective input for analysis of soil moisture at regional scales. Moreover, it was shown that CATDS SMOS soil moisture data are better correlated with rainfall rate than GLDAS ones.

  16. A Spatially Coherent Global Soil Moisture Product with Improved Temporal Resolution

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    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.

  17. A spatially coherent global soil moisture product with improved temporal resolution

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Stacke, Tobias

    2013-04-01

    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.

  19. Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

    NASA Astrophysics Data System (ADS)

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

    1999-01-01

    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

  20. Results of soil moisture flights during April 1974

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Blanchard, B. J.; Burke, W. J.; Paris, J. F.; Swang, J. R.

    1976-01-01

    The results presented here are derived from measurements made during the April 5 and 6, 1974 flights of the NASA P-3A aircraft over the Phoenix, Arizona agricultural test site. The purpose of the mission was to study the use of microwave techniques for the remote sensing of soil moisture. These results include infrared (10-to 12 micrometers) 2.8-cm and 21-cm brightness temperatures for approximately 90 bare fields. These brightness temperatures are compared with surface measurements of the soil moisture made at the time of the overflights. These data indicate that the combination of the sum and difference of the vertically and the horizontally polarized brightness temperatures yield information on both the soil moisture and surface roughness conditions.

  1. BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  2. Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States

    NASA Astrophysics Data System (ADS)

    Bolten, J. D.; Crow, W. T.; Zhan, X.; Reynolds, C. A.; Jackson, T. J.

    2008-12-01

    A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each model simulation over the conterminous United States, as well as statistical assessments for each simulation over various land cover types.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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.

  4. Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System

    SciTech Connect

    Buckley, R.

    2001-06-27

    Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

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

    NASA Astrophysics Data System (ADS)

    Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

    2014-05-01

    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.

  6. Variability of soil moisture memory for wet and dry basins

    NASA Astrophysics Data System (ADS)

    Rahman, Mohammad Mahfuzur; Lu, Minjiao; Kyi, Khin Htay

    2015-04-01

    Soil moisture memory (SMM) is not only important for atmospheric weather/climate forecasting, but may also be useful in flood and drought prediction. Despite their importance, SMM studies are restricted in certain regions due to the scarcity of soil moisture data. To overcome this limitation, this study explains the variability of SMM in wet and dry basins, and shows an alternative way to predict the basin scale SMM using observed precipitation and potential evapotranspiration information only. This study presents the basin average SMM in the form of a timescale that indicates the duration of significant autocorrelations at 95% confidence intervals. The soil moisture autocorrelations were calculated using observed precipitation, potential evapotranspiration, streamflow and soil moisture data sets simulated using the XinAnJiang (XAJ) model, for 26 river basins across the USA. The XAJ model's capability to simulate seasonal cycles (temporal anomalies) of soil moisture was validated against cycles from the observed data set of the Spoon River basin of Illinois State, USA. Based on the validation experience, the XAJ model was thereafter used to simulate soil moisture data for the analysed basins. Basin scale SMM timescale ranges were computed from 11 to 133 days. The SMM timescale is highly influenced by precipitation variability and exhibits strong seasonality. Dry basins tend to show the highest memory during the winter months (December to February) and lowest in late spring (May). In contrast, wet basins have the lowest memory during winter and early spring (December to April) and highest in the late summer and early autumn (July to September). The SMM timescale displayed an exponential relationship with the basin aridity index, with an r2 value of 0.9. This relationship could be a cheap source of basin scale SMM prediction from widely available observed data sets (actual precipitation and potential evapotranspiration), and thus, could afford some knowledge of SMM under no knowledge conditions.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

  9. ESTAR - A synthetic aperture microwave radiometer for measuring soil moisture

    NASA Technical Reports Server (NTRS)

    Le Vine, D. M.; Griffis, A.; Swift, C. T.; Jackson, T. J.

    1992-01-01

    The measurement of soil moisture from space requires putting relatively large microwave antennas in orbit. Aperture synthesis, an interferometric technique for reducing the antenna aperture needed in space, offers the potential for a practical means of meeting these requirements. An aircraft prototype, electronically steered thinned array L-band radiometer (ESTAR), has been built to develop this concept and to demonstrate its suitability for the measurement of soil moisture. Recent flights over the Walnut Gulch Watershed in Arizona show good agreement with ground truth and with measurements with the Pushbroom Microwave Radiometer (PBMR).

  10. Regions of strong coupling between soil moisture and precipitation.

    PubMed

    Koster, Randal D; Dirmeyer, Paul A; Guo, Zhichang; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C T; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David; Liu, Ping; Lu, Cheng-Hsuan; Malyshev, Sergey; McAvaney, Bryant; Mitchell, Ken; Mocko, David; Oki, Taikan; Oleson, Keith; Pitman, Andrew; Sud, Y C; Taylor, Christopher M; Verseghy, Diana; Vasic, Ratko; Xue, Yongkang; Yamada, Tomohito

    2004-08-20

    Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts. PMID:15326351

  11. Implications of complete watershed soil moisture measurements to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

    1983-01-01

    A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

    Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.

  13. Soil sample moisture content as a function of time during oven drying for gamma-ray spectroscopic measurements

    NASA Astrophysics Data System (ADS)

    Benke, R. R.; Kearfott, K. J.

    1999-02-01

    In routine gamma-ray spectroscopic analysis of collected soil samples, procedure often calls to remove soil moisture by oven drying overnight at a temperature of 100°C [1]. Oven drying not only minimizes the gamma-ray self-attenuation of soil samples due to the absence of water during the gamma-ray spectroscopic analysis, but also allows for a straightforward calculation of the specific activity of radionuclides in soil, historically based on the sample dry weight. Because radon exhalation is strongly dependent on moisture [2, 3], knowledge of the oven-drying time dependence of the soil moisture content, combined with radon exhalation measurements during oven drying and at room temperature for varying soil moisture contents, would allow conclusions to be made on how the oven-drying radon exhalation rate depends on soil moisture content. Determinations of the oven-drying radon exhalation from soil samples allow corrections to be made for the immediate laboratory gamma-ray spectroscopy of radionuclides in the natural uranium decay chain. This paper presents the results of soil moisture content measurements during oven drying and suggests useful empirical fits to the moisture data.

  14. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at p<0.01) with the amount of measured precipitation. In this study we analyze the role of other crucial atmospheric parameters (i.e., temperature, relative humidity, global solar radiation, and wind speed and wind direction) in the intraanual evolution of soil moisture; focussing our analyses on the soil moisture discharge episodes. Here we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). Key Words: Soil Moisture Discharges, Intraannual changes, Atmospheric parameters, Eastern Spain Acknowledgements The research projects GL2008-02879/BTE, LEDDRA 243857 and RECARE FP7 project 603498 supported this research. References: Azorin-Molina, C., Connell, B.H., Baena-Calatrava, R. 2009. Sea-breeze convergence zones from AVHRR over the Iberian Mediterranean Area and the Isle of Mallorca, Spain. Journal of Applied Meteorology and Climatology 48 (10), 2069-2085. Azorin-Molina, C., Vicente-Serrano, S. M., Cerdà, A. 2013. Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming. EGU, Geophysical Research Abstracts, EGU2013-13286. Bodí, M.B., Mataix-Solera, J., Doerr, S.H. & Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments, 52, 319-337. García-Fayos, P. García-Ventoso, B. Cerdà, A. 2000. Limitations to Plant establishment on eroded slopes in Southeastern Spain. Journal of Vegetation Science, 11- 77- 86. Ghafoor, A., Murtaza, G., Rehman, M. Z., Saifullah Sabir, M. 2012. Reclamation and salt leaching efficiency for tile drained saline-sodic soil using marginal quality water for irrigating rice and wheat crops. Land Degradation & Development, 23: 1 -9. DOI 10.1002/ldr.1033 Johnston, C. R., Vance, G. F., Ganjegunte, G. K. 2013. Soil properties changes following irrigation with coalbed natural gas water: role of water treatments, soil amendments and land suitability. Land Degradation & Development, 24: 350- 362. DOI 10.1002/ldr.1132 Qadir, M., Noble, A. D., Chartres, C. 2013. Adapting to climate change by improving water productivity of soil in dry areas. Land Degradation & Development, 24: 12- 21. DOI 10.1002/ldr.1091 Ziadat, F. M., and Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

  15. Prediction of runoff and soil moistures at the watershed scale: Effects of model complexity and parameter assignment

    NASA Astrophysics Data System (ADS)

    Downer, Charles W.; Ogden, Fred L.

    2003-03-01

    The application of physically based hydrologic models implies they properly simulate processes at the computational scale. A chief criticism is that model predictions are compared only to discharge data. The physically based, hydrologic model CASC2D is reformulated such that soil moistures and fluxes can be computed using Richards' equation. The gridded surface subsurface hydrologic analysis (GSSHA) model is calibrated and verified against outlet discharge measurements during the growing season. The verified model is used to simulate an extended period during which measurements of soil moisture are available. Though soil moisture data are not used in the calibration and verification efforts, the model reproduces both the trends and the magnitude of soil moisture during the growing season. With additional formulation enhancements, soil moistures during the nongrowing season are also reproduced within a root-mean-square error of 0.1. However, more work is needed to understand the underprediction of runoff during the nongrowing season.

  16. Effect of Soil Moisture on Fumigant Emissions from a Loam Soil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Emissions of soil fumigants must be minimized in order to protect air quality in California. Soil moisture is an important factor that can be managed at a relatively low cost prior to soil fumigation to reduce emissions. A previous study indicated that increasing soil water content up to field capac...

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Neelam, M.; Mohanty, B.

    2013-12-01

    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.

  19. De-noising of microwave satellite soil moisture time series

    NASA Astrophysics Data System (ADS)

    Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew; Wagner, Wolfgang

    2013-04-01

    The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of Technology) ASCAT data sets to identify two types of errors that are spectrally distinct. Based on a semi-empirical model of soil moisture dynamics, we consider possible digital filter designs to improve the accuracy of their soil moisture products by reducing systematic periodic errors and stochastic noise. We describe a methodology to design bandstop filters to remove artificial resonances, and a Wiener filter to remove stochastic white noise present in the satellite data. Utility of these filters is demonstrated by comparing de-noised data against in-situ observations from ground monitoring stations in the Murrumbidgee Catchment (Smith et al., 2012), southeast Australia. Albergel, C., de Rosnay, P., Gruhier, C., Muñoz Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y. H., & Wagner, W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226. Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters, 35, L24403. Smith, A. B., Walker, J. P., Western, A. W., Young, R. I., Ellett, K. M., Pipunic, R. C., Grayson, R. B., Siriwardena, L., Chiew, F. H. S., & Richter, H. (2012). The Murrumbidgee soil moisture network data set. Water Resources Research, 48, W07701. Su, C.-H., Ryu, D., Young, R., Western, A. W., & Wagner, W. (2012). Inter-comparison of microwave satellite soil moisture retrievals over Australia. Submitted to Remote Sensing of Environment.

  20. [Characteristics of soil moisture in artificial impermeable layers].

    PubMed

    Suo, Gai-Di; Xie, Yong-Sheng; Tian, Fei; Chuai, Jun-Feng; Jing, Min-Xiao

    2014-09-01

    For the problem of low water and fertilizer use efficiency caused by nitrate nitrogen lea- ching into deep soil layer and soil desiccation in dryland apple orchard, characteristics of soil moisture were investigated by means of hand tamping in order to find a new approach in improving the water and fertilizer use efficiency in the apple orchard. Two artificial impermeable layers of red clay and dark loessial soil were built in soil, with a thickness of 3 or 5 cm. Results showed that artificial impermeable layers with the two different thicknesses were effective in reducing or blocking water infiltration into soil and had higher seepage controlling efficiency. Seepage controlling efficiency for the red clay impermeable layer was better than that for the dark loessial soil impermeable layer. Among all the treatments, the red clay impermeable layer of 5 cm thickness had the highest bulk density, the lowest initial infiltration rate (0.033 mm · min(-1)) and stable infiltration rate (0.018 mm · min(-1)) among all treatments. After dry-wet alternation in summer and freezing-thawing cycle in winter, its physiochemical properties changed little. Increase in years did not affect stable infiltration rate of soil water. The red clay impermeable layer of 5 cm thickness could effectively increase soil moisture content in upper soil layer which was conducive to raise the water and nutrient use efficiency. The approach could be applied to the apple production of dryland orchard. PMID:25757307

  1. 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)

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

    2010-09-01

    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.

  2. Comparative analysis of drought based on precipitation and soil moisture indices in Haihe basin of North China during the period of 1960-2010

    NASA Astrophysics Data System (ADS)

    Qin, Yue; Yang, Dawen; Lei, Huimin; Xu, Kai; Xu, Xiangyu

    2015-07-01

    Drought severity not only depends on weather anomaly, but is also related to terrestrial hydrological condition to a large extent. In this study, we analyzed droughts using indices based on precipitation and soil moisture during the period of 1960-2010 in Haihe basin, which is a typical drought-prone region in North China. The Soil Moisture Drought Severity (SMDS) and Standardized Precipitation Index (SPI) are used to evaluate drought severity. SMDS is calculated based on the monthly soil moisture of upper 50 cm from the simulation by Community Land Model (CLM 4.0) and SPI is calculated based on gridded precipitation at 0.05° resolution (5 km × 5 km approximately), which is spatially interpolated from observations. During the last 51 years, 36 severe drought events (affecting areas greater than 20,000 km2 and durations longer than 3 months) have been identified based on SMDS, and 41 drought events identified based on SPI. Results derived from SMDS indicate that there is a significant increasing trend in the drought affected area, and that the drought event occurred in 1999 has the largest affected area. Compared with the drought events derived from SMDS, the events derived from SPI have shorter durations but larger affected areas on average. Although the mean NDVI of the whole basin has been increasing since the 1980s, the two declining periods of 1992-1994 and 1999-2003 show fairly good agreement with the drought events identified in the same periods. The Anomaly of Normalized Difference Vegetation Index (A-NDVI) is introduced as NDVI anomaly from its trend line, thus the negative value of A-NDVI can reflect the drought impact on vegetation reasonably. Result indicates that both the SMDS and SPI are significantly correlated with A-NDVI, and correlation between annual SMDS and A-NDVI is higher than that of SPI.

  3. Plants and their relationship to soil moisture and tracer movement

    SciTech Connect

    Perkins, B.; DePoorter, G.L.

    1985-11-01

    To obtain a better understanding of the mechanisms for possible movement of radionuclides or other toxic materials from waste burial sites in arid to semiarid regions, changes in soil moisture and tracer (Co, Cs, Sr, and tritium) movement were compared for bare vs vegetated soils. During the course of two growing seasons, comparing vegetated with bare soils, plant transpiration processes significantly reduced the soil moisture. In the vegetated soils, most of the Co, Cs, and Sr remained in the region of original emplacement. In bare soils, Co and Cs underwent minimum movement, but the peak concentration of Sr moved downward. For all tracers in the vegetated soils, there was some evidence that slight amounts of tracer had been absorbed in the plant roots and brought to the surface through plant translocation processes. In all cases, there was no significant upward movement of Co, Cs, and Sr. For tritium, the vegetated soils, compared with the bare soils, retained the maximum inventories near the original emplacement location. Although all soils showed some tritium loss, it was greatest in the vegetated soils. A literature review associated with the experiment indicated that plant species alone does not determine rooting depth, rate of transpiration, nutrient uptake, and other plant-associated processes. Environmental conditions are just as important as plant species and must be included in modeling plant-related effects. More data are needed on the effects of tracer concentration, soil water composition, variations in precipitation with time and intensity, evaporation rates, variations in soil composition, soil microorganisms, other invertebrates and vertebrates that inhabit soils, litter decay, and colloid movement on contaminant movement under conditions of unsaturated flow.

  4. Potential application of satellite radar to monitor soil moisture

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.; Bradley, G. A.; Dobson, M. C.

    1981-01-01

    The microwave backscattering characteristics of soils as a function of moisture content are reviewed as a basis for the evaluation of the applicability of satellite radar to soil moisture determinations. Results of experiments showing the dependence of the complex dielectric constant, power reflection coefficient and backscattering coefficient of soil on its volumetric moisture content are presented. Results of a research program using the truck-mounted University of Kansas microwave active spectrometer to determine if, by the proper choice of sensor frequency, polarization and incidence, the sensor dynamic range in response to moisture variations may be greater than its response to other variations are considered in detail, and the optimum conditions of frequency (between 4 and 5 GHz), angular incidence (between 7 and 20 deg from nadir) and polarization (HH) obtained are indicated. An empirical model for the backscattering coefficient as a function of gravimetric moisture content derived on the basis of the experimental data is presented, and it is noted that available airborne and spaceborne data confirm the results of the ground-based sensors.

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

    PubMed

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

    2010-11-01

    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

  6. Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

    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 and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should pr