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Sample records for soil moisture ground

  1. CLPX-Ground: ISA Soil Moisture Measurements

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North...

  2. SMEX03 Regional Ground Soil Moisture Data: Georgia, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Georgia study...

  3. SMEX02 Iowa Regional Ground Soil Moisture Data

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric and volumetric soil moisture, bulk density, and soil temperature. This data set is part of the Soil Moisture...

  4. SMEX03 Regional Ground Soil Moisture Data: Alabama, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set comprises gravimetric soil moisture and soil bulk density data collected during the Soil Moisture Experiment 2003 (SMEX03), which was conducted during...

  5. SMEX03 Regional Ground Soil Moisture Data: Alabama

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set comprises gravimetric soil moisture and soil bulk density data collected during the Soil Moisture Experiment 2003 (SMEX03), which was conducted during...

  6. SMEX03 Regional Ground Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Oklahoma study...

  7. SMEX03 Regional Ground Soil Moisture Data: Georgia

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Georgia study...

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

    Science.gov (United States)

    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.

  9. CLPX-Ground: ISA Soil Moisture Measurements, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North...

  10. SMEX03 Watershed Ground Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set combines data for several parameters measured for the Soil Moisture Experiment 2003 (SMEX03). The parameters include bulk density, gravimetric and...

  11. SMEX03 Regional Ground Soil Moisture Data: Oklahoma, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes soil moisture measurements for the Oklahoma study region. Summary files containing field averages are also provided. This data set is part of...

  12. SMEX03 Watershed Ground Soil Moisture Data: Oklahoma, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set combines data for several parameters measured for the Soil Moisture Experiment 2003 (SMEX03). This study was conducted between 2 July 2003 and 17 July...

  13. GPM Ground Validation USDA ARS Soil Moisture IFloodS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation United States Department of Agriculture (USDA) Agricultural Research Service (ARS) Soil Moisture IFloodS dataset was collected during the...

  14. MAPPING SPATIAL MOISTURE CONTENT OF UNSATURATED AGRICULTURAL SOILS WITH GROUND-PENETRATING RADAR

    Directory of Open Access Journals (Sweden)

    O. Shamir

    2016-06-01

    Full Text Available Soil subsurface moisture content, especially in the root zone, is important for evaluation the influence of soil moisture to agricultural crops. Conservative monitoring by point-measurement methods is time-consuming and expensive. In this paper we represent an active remote-sensing tool for subsurface spatial imaging and analysis of electromagnetic physical properties, mostly water content, by ground-penetrating radar (GPR reflection. Combined with laboratory methods, this technique enables real-time and highly accurate evaluations of soils' physical qualities in the field. To calculate subsurface moisture content, a model based on the soil texture, porosity, saturation, organic matter and effective electrical conductivity is required. We developed an innovative method that make it possible measures spatial subsurface moisture content up to a depth of 1.5 m in agricultural soils and applied it to two different unsaturated soil types from agricultural fields in Israel: loess soil type (Calcic haploxeralf, common in rural areas of southern Israel with about 30% clay, 30% silt and 40% sand, and hamra soil type (Typic rhodoxeralf, common in rural areas of central Israel with about 10% clay, 5% silt and 85% sand. Combined field and laboratory measurements and model development gave efficient determinations of spatial moisture content in these fields. The environmentally friendly GPR system enabled non-destructive testing. The developed method for measuring moisture content in the laboratory enabled highly accurate interpretation and physical computing. Spatial soil moisture content to 1.5 m depth was determined with 1–5% accuracy, making our method useful for the design of irrigation plans for different interfaces.

  15. Ground-Penetrating Radar Evaluation of Moisture and Frost across Typical Saskatchewan Road Soils

    Directory of Open Access Journals (Sweden)

    Curtis Berthelot

    2010-01-01

    Full Text Available This study was undertaken to evaluate the effect of soil type, moisture content, and the presence of frost on road substructure permittivity. Permittivity sensitivity of typical road soils was characterized in the laboratory to provide baseline dielectric constant values which were compared to field ground penetrating radar (GPR survey results. Both laboratory devices, the complex dielectric network analyzer and the Adek Percometer, as well as the field GPR system were used in this study to measure the dielectric constant of soils. All three systems differentiated between coarse-grained and fine grained soils. In addition, at temperatures below freezing, all three systems identified an increase in water content in soils; however, when frozen, the sensitivity of dielectric constant across soil type and moisture content was significantly reduced. Based on the findings of this study, GPR technology has the ability to characterize in situ substructure soil type and moisture content of typical Saskatchewan road substructure soils. Given the influence of road soil type and moisture content on in-service road performance, this ability could provide road engineers with accurate estimates of in situ structural condition of road structures for preservation and rehabilitation planning and optimization purposes.

  16. Assimilation of Ground-Penetrating Radar Data to Update Vertical Soil Moisture Profile

    Science.gov (United States)

    Tran, Phuong; Vanclooster, Marnik; Lambot, Sébastien

    2013-04-01

    The root zone soil moisture has been long recognized as important information for hydrological, meteorological and agricultural research. In this study, we propose a closed-loop data assimilation procedure to update the vertical soil moisture profile from time-lapse ground-penetrating radar (GPR) data. The hydrodynamic model, Hydrus-1D (Simunek et al., 2009), is used to propagate the system state in time and a radar electromagnetic model (Lambot et al., 2004) to link the state variable (soil moisture profile) with the observation data (GPR data), which enables us to update the soil moisture profile by directly assimilating the GPR data. The assimilation was performed within the maximum likelihood ensemble filter (MLEF) framework developed by Zupanski et al., (2005), for which the problem of nonlinear observation operator is solved much more effectively than the Ensemble Kalman filter (EnKF) techniques. The method estimates the optimal state as the maximum of the probability density function (PDF) instead of the minimum variance like in most of the other ensemble data assimilation methods. Direct assimilation of GPR data is a prominent advantage of our approach. It avoids solving the time-consuming inverse problem as well as the estimation errors of the soil moisture caused by inversion. In addition, instead of using only surface soil moisture, the approach allows to use the information of the whole soil moisture profile, which is reflected via the ultra wideband (UWB) GPR data, for the assimilation. The use of the UWB antenna in this study is also an advantage as it provides more information about soil moisture profile with a better depth resolution compared to other classical remote sensing techniques. Our approach was validated by a synthetic study. We constructed a synthetic soil column with a depth of 80 cm and analyzed the effects of the soil type on the data assimilation by considering 3 soil types, namely, loamy sand, silt and clay. The assimilation of GPR

  17. Soil moisture characterization of the Valencia anchor station. Ground, aircraft measurements and simulations

    DEFF Research Database (Denmark)

    Lopez-Baeza, E; Antolin, M C; Balling, Jan E.

    2009-01-01

    . For the rehearsal activity which successfully took place in April - May 2008, a control area of 10 × 10 km2 was chosen at the VAS study area where a network of ground soil moisture (SM) measuring stations is being set up based on an original definition of homogeneous physio-hydrological units attending to climatic......, soil type, lithology, geology, elevation, slope and vegetation cover conditions. Complementary to the ground measurements, flight operations were performed over this control area using the Helsinki University of Technology TKK Short Skyvan research aircraft which contained onboard a payload constituted...

  18. Ground Albedo Neutron Sensing (GANS) method for measurements of soil moisture in cropped fields

    Science.gov (United States)

    Andres Rivera Villarreyes, Carlos; Baroni, Gabriele; Oswald, Sascha E.

    2013-04-01

    Measurement of soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. This study evaluates the applicability of the Ground Albedo Neutron Sensing (GANS) for integral quantification of seasonal soil moisture in the root zone at the scale of a field or small watershed, making use of the crucial role of hydrogen as neutron moderator relative to other landscape materials. GANS measurements were performed at two locations in Germany under different vegetative situations and seasonal conditions. Ground albedo neutrons were measured at (i) a lowland Bornim farmland (Brandenburg) cropped with sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. At both sites depth profiles of soil moisture were measured at several locations in parallel by frequency domain reflectometry (FDR) for comparison and calibration. Initially, calibration parameters derived from a previous study with corn cover were tested under sunflower and winter rye periods at the same farmland. GANS soil moisture based on these parameters showed a large discrepancy compared to classical soil moisture measurements. Therefore, two new calibration approaches and four different ways of integration the soil moisture profile to an integral value for GANS were evaluated in this study. This included different sets of calibration parameters based on different growing periods of sunflower. New calibration parameters showed a good agreement with FDR network during sunflower period (RMSE = 0.023 m3 m-3), but they underestimated soil moisture in the winter rye period. The GANS approach resulted to be highly affected by temporal changes of biomass and crop types which suggest the need of neutron corrections for long-term observations with crop rotation. Finally

  19. Statistical Modeling of Soil Moisture, Integrating Satellite Remote-Sensing (SAR and Ground-Based Data

    Directory of Open Access Journals (Sweden)

    Reza Hosseini

    2015-03-01

    Full Text Available We present a flexible, integrated statistical-based modeling approach to improve the robustness of soil moisture data predictions. We apply this approach in exploring the consequence of different choices of leading predictors and covariates. Competing models, predictors, covariates and changing spatial correlation are often ignored in empirical analyses and validation studies. An optimal choice of model and predictors may, however, provide a more consistent and reliable explanation of the high environmental variability and stochasticity of soil moisture observational data. We integrate active polarimetric satellite remote-sensing data (RADARSAT-2, C-band with ground-based in-situ data across an agricultural monitoring site in Canada. We apply a grouped step-wise algorithm to iteratively select best-performing predictors of soil moisture. Integrated modeling approaches may better account for observed uncertainty and be tuned to different applications that vary in scale and scope, while also providing greater insights into spatial scaling (upscaling and downscaling of soil moisture variability from the field- to regional scale. We discuss several methodological extensions and data requirements to enable further statistical modeling and validation for improved agricultural decision-support.

  20. GPM GROUND VALIDATION ENVIRONMENT CANADA (EC) PASSIVE MICROWAVE RADIOMETER AND SOIL MOISTURE-TEMPERATURE DATA GCPEX V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Environment Canada (EC) Passive Microwave Radiometer and Soil Moisture-Temperature Data GCPEx dataset gathered data during the GPM...

  1. Spatiotemporal analysis of soil moisture in using active and passive remotely sensed data and ground observations

    Science.gov (United States)

    Li, H.; Fang, B.; Lakshmi, V.

    2015-12-01

    Abstract: Soil moisture plays a vital role in ecosystem, biological processes, climate, weather and agriculture. The Soil Moisture Active Passive (SMAP) improves data by combining the advantages and avoiding the limitation of passive microwave remote sensing (low resolution), and active microwave (challenge of soil moisture retrieval). This study will advance the knowledge of the application of soil moisture by using the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) data as well as data collected at Walnut Gulch Arizona in August 2015 during SMAPVEX15. Specifically, we will analyze the 5m radar data from Unmanned Airborne Vehicle Synthetic Aperture Radar (UAVSAR) to study spatial variability within the PALS radiometer pixel. SMAPVEX12/15 and SMAP data will also be analyzed to evaluate disaggregation algorithms. The analytical findings will provide valuable information for policy-makers to initiate and adjust protocols and regulations for protecting land resources and improving environmental conditions. Keywords: soil moisture, Remote Sensing (RS), spatial statistic

  2. Modelling and observing soil moisture patterns in alpine meadows using multi-source ground and remote-sensing observations

    Science.gov (United States)

    Bertoldi, Giacomo; Notarnicola, Claudia; Pasolli, Luca; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike

    2013-04-01

    Soil moisture is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of soil moisture in mountain catchments is an essential step towards improving quantitative predictions of catchment processes and ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on soil moisture have been extensively investigated. However, due to the extreme variability in topography, soil and vegetation properties of mountain areas, obtaining reliable predictions of soil moisture of spatial and temporal patterns is still challenging. Physically-based hydrological models often face the problem of over-parameterization and equifinality. At the same time, field campaigns are intensive and limited to too small areas, whereas soil moisture retrieval from remote sensing in alpine context is promising. However, surface heterogeneity and overpassing frequency issues still limit its effectiveness. For this reason, an integration of hydrological models, ground surveys, and new remote-sensing products is essential to improve soil moisture estimation. In this contribution, we analyze the spatial dynamics of surface soil moisture (0 - 5 cm depth) of alpine meadows and pastures in the Mazia Valley (South Tyrol - Italy), at different spatial scales and with different techniques: (I) a network of fixed stations; (II) field campaigns with mobile ground sensors; (III) soil moisture retrieval from 20-m resolution polarimetric RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model. The strength and the weaknesses and the consistency of the different estimation techniques are evaluated and, in particular, the GEOtop model is used to understand the physical controls of the observed patterns in RADARSAT2 products. Results show that the model, once calibrated for

  3. Evaluation of Satellite and Reanalysis Soil Moisture Products over Southwest China Using Ground-Based Measurements

    Directory of Open Access Journals (Sweden)

    Jian Peng

    2015-11-01

    Full Text Available Long-term global satellite and reanalysis soil moisture products have been available for several years. In this study, in situ soil moisture measurements from 2008 to 2012 over Southwest China are used to evaluate the accuracy of four satellite-based products and one reanalysis soil moisture product. These products are the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E, the Advanced Scatterometer (ASCAT, the Soil Moisture and Ocean Salinity (SMOS, the European Space Agency’s Climate Change Initiative soil moisture (CCI SM, and the European Centre for Medium-Range Weather Forecasts (ECMWF Interim Reanalysis (ERA-Interim. The evaluation of soil moisture absolute values and anomalies shows that all the products can capture the temporal dynamics of in situ soil moisture well. For AMSR-E and SMOS, larger errors occur, which are likely due to the severe effects of radio frequency interference (RFI over the test region. In general, the ERA-Interim (R = 0.782, ubRMSD = 0.035 m3/m3 and CCI SM (R = 0.723, ubRMSD = 0.046 m3/m3 perform the best compared to the other products. The accuracy levels obtained are comparable to validation results from other regions. Therefore, local hydrological applications and water resource management will benefit from the long-term ERA-Interim and CCI SM soil moisture products.

  4. Distributed soil moisture from crosshole ground-penetrating radar travel times using stochastic inversion

    NARCIS (Netherlands)

    Linde, N.; Vrugt, J.A.

    2013-01-01

    In this paper two different subsurface parameterizations are compared for posterior soil moisture estimation from traveltime observations of crosshole GPR. The discrete cosine transform provides the most adequate and efficient results and enables linking MCMC derived parameter uncertainty to model

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

    Science.gov (United States)

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

    2014-05-01

    Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis

  6. Soil Moisture Characterization of the Valencia Anchor Station. Ground, Aircraft Measurements and Simulations

    Science.gov (United States)

    Lopez-Baeza, E.; Antolin, M. C.; Balling, J.; Belda, F.; Bouzinac, C.; Camacho, F.; Cano, A.; Carbo, E.; Delwart, S.; Domenech, C.; Ferreira, A. G.; Fidalgo, A.; Juglea, S.; Kerr, Y.; Marco, J.; Millan-Scheiding, C.; Narbon, C.; Rodriguez, D.; Saleh, K.; Sanchis, J.; Skou, N.; Sobjaerg, S.; Soriano, P.; Tamayo, J.; Tauriainen, S.; Torre, E.; Velazquez-Blazquez, A.; Wigneron, J.-P.; Wursteisen, P.

    In the framework of ESA SMOS Mission, the Valencia Anchor Station (VAS) has been selected as a core validation site. Its reasonable homogeneous characteristics make it appropriate to undertake the validation of SMOS Level 2 land products before attempting other more complex areas. Close to SMOS launch (2nd Nov. 2009), ESA defined the SMOS Validation Rehearsal Campaign Plan with the aim of testing the readiness, ensemble coordination and speed of operations, to be able to avoid as far as possible any unexpected deficiencies of the plan and procedure during the real Commissioning Phase campaigns.For the rehearsal activity which successfully took place in April - May 2008, a control area of 10 x 10 km2 was chosen at the VAS study area where a network of ground soil moisture (SM) measuring stations is being set up based on an original definition of homogeneous physio-hydrological units attending to climatic, soil type, lithology, geology, elevation, slope and vegetation cover conditions. Complementary to the ground measurements, flight operations were performed over this control area using the Helsinki University of Technology TKK Short Skyvan research aircraft which contained onboard a payload constituted of the following instruments: (i) L-band EMIRAD radiometer (Technical University of Denmark, TUD), (ii) L-band HUT-2D imaging interferometric radiometer (TKK), (iii) PARIS GPS reflectrometry system (Institute for Space Studies of Catalonia, IEEC), (iv) IR sensor (Finnish Institute of Maritime Research, FIMR).Together with the ground SM measurements, other ground and meteorological measurements from the VAS area, kindly provided by other institutions, are currently been used to simulate passive microwave brightness temperature to obtain satellite "match ups" for validation purposes and to test the retrieval algorithms. The spatialization of the ground measurements up to a SMOS pixel is carried out by using the SURFace EXternalisée (SURFEX) model from Météo France

  7. Evaluation of Soil Moisture Derived from Passive Microwave Remote Sensing Over Agricultural Sites in Canada using ground-based Soil Moisture Monitoring Networks

    NARCIS (Netherlands)

    Champagne, C.; Berg, A; Belanger, J.; McNairn, H.; de Jeu, R.A.M.

    2010-01-01

    Passive microwave soil moisture datasets can be used as an input to provide an integrated assessment of climate variability as it relates to agricultural production. The objective of this research was to examine three passive microwave derived soil moisture datasets over multiple growing seasons in

  8. Monitoring soil moisture patterns in alpine meadows using ground sensor networks and remote sensing techniques

    Science.gov (United States)

    Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike

    2015-04-01

    Soil moisture content (SMC) is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of SMC in mountain catchments is an essential step towards improving quantitative predictions of catchment hydrological processes and related ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on SMC and the influence of SMC patterns on runoff generation processes have been extensively investigated (Vereecken et al., 2014). However, in mountain areas, obtaining reliable SMC estimations is still challenging, because of the high variability in topography, soil and vegetation properties. In the last few years, there has been an increasing interest in the estimation of surface SMC at local scales. On the one hand, low cost wireless sensor networks provide high-resolution SMC time series. On the other hand, active remote sensing microwave techniques, such as Synthetic Aperture Radars (SARs), show promising results (Bertoldi et al. 2014). As these data provide continuous coverage of large spatial extents with high spatial resolution (10-20 m), they are particularly in demand for mountain areas. However, there are still limitations related to the fact that the SAR signal can penetrate only a few centimeters in the soil. Moreover, the signal is strongly influenced by vegetation, surface roughness and topography. In this contribution, we analyse the spatial and temporal dynamics of surface and root-zone SMC (2.5 - 5 - 25 cm depth) of alpine meadows and pastures in the Long Term Ecological Research (LTER) Area Mazia Valley (South Tyrol - Italy) with different techniques: (I) a network of 18 stations; (II) field campaigns with mobile ground sensors; (III) 20-m resolution RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model (Rigon et al

  9. Shallow soil moistureground thaw interactions and controls – Part 2: Influences of water and energy fluxes

    Directory of Open Access Journals (Sweden)

    X. J. Guan

    2010-07-01

    Full Text Available The companion paper (Guan et al., 2010 demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the presence of surface water was the key control in variable soil moisture and frost table interactions among sites. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological and energy processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.

  10. Effect of scrub oak and associated ground cover on soil moisture

    Science.gov (United States)

    Arthur R. Eschner

    1960-01-01

    Planting experiments have been conducted for the past 10 years in the scrub oak type at the Delaware-Lehigh Experimental Forest in eastern Pennsylvania. The object of these experiments is to find a practical method of establishing a high forest of greater value than the area's present cover. In the course of these studies it was suggested that soil moisture might...

  11. CPC Soil Moisture

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The monthly data set consists of a file containing 1/2 degree monthly averaged soil moisture water height equivalents for the globe from 1948 onwards. Values are...

  12. Soil Moisture Estimation Across Scales with Mobile Sensors for Cosmic-Ray Neutrons from the Ground and Air

    Science.gov (United States)

    Schrön, Martin; Köhler, Mandy; Bannehr, Lutz; Köhli, Markus; Fersch, Benjamin; Rebmann, Corinna; Mai, Juliane; Cuntz, Matthias; Kögler, Simon; Schröter, Ingmar; Wollschläger, Ute; Oswald, Sascha; Dietrich, Peter; Zacharias, Steffen

    2016-04-01

    Soil moisture is a key variable for environmental sciences, but its determination at various scales and depths is still an open challenge. Cosmic-ray neutron sensing has become a well accepted and unique method to monitor an effective soil water content, covering tens of hectares in area and tens of centimeters in depth. The technology is famous for its low maintanance, non-invasiveness, continous measurement, and most importantly its large footprint and penetration depth. Beeing more representative than point data, and finer resolved plus deeper penetrating than remote-sensing products, cosmic-ray neutron derived soil moisture products provide unrivaled advantage for agriculture, regional hydrologic and land surface models. The method takes advantage of omnipresent neutrons which are extraordinarily sensitive to hydrogen in soil, plants, snow and air. Unwanted hydrogen sources in the footprint can be excluded by local calibration to extract the pure soil water information. However, this procedure is not feasible for mobile measurements, where neutron detectors are mounted on a car to do catchment-scale surveys. As a solution to that problem, we suggest strategies to correct spatial neutron data with the help of available spatial data of soil type, landuse and vegetation. We further present results of mobile rover campaigns at various scales and conditions, covering small sites from 0.2 km2 to catchments of 100 km2 area, and complex terrain from agricultural fields, urban areas, forests, to snowy alpine sites. As the rover is limited to accessible roads, we further investigated the applicability of airborne measurements. First tests with a gyrocopter at 150 to 200m heights proofed the concept of airborne neutron detection for environmental sciences. Moreover, neutron transport simulations confirm an improved areal coverage during these campaigns. Mobile neutron measurements at the ground or air are a promising tool for the detection of water sources across many

  13. A bare ground evaporation revision in the ECMWF land-surface scheme: evaluation of its impact using ground soil moisture and satellite microwave data

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2012-10-01

    Full Text Available In situ soil moisture data from 122 stations across the United States are used to evaluate the impact of a new bare ground evaporation formulation at ECMWF. In November 2010, the bare ground evaporation used in ECMWF's operational Integrated Forecasting System (IFS was enhanced by adopting a lower stress threshold than for the vegetation, allowing a higher evaporation. It results in more realistic soil moisture values when compared to in situ data, particularly over dry areas. Use was made of the operational IFS and offline experiments for the evaluation. The latter are based on a fixed version of the IFS and make it possible to assess the impact of a single modification, while the operational analysis is based on a continuous effort to improve the analysis and modelling systems, resulting in frequent updates (a few times a year. Considering the field sites with a fraction of bare ground greater than 0.2, the root mean square difference (RMSD of soil moisture is shown to decrease from 0.118 m3 m−3 to 0.087 m3 m−3 when using the new formulation in offline experiments, and from 0.110 m3 m−3 to 0.088 m3 m−3 in operations. It also improves correlations. Additionally, the impact of the new formulation on the terrestrial microwave emission at a global scale is investigated. Realistic and dynamically consistent fields of brightness temperature as a function of the land surface conditions are required for the assimilation of the SMOS data. Brightness temperature simulated from surface fields from two offline experiments with the Community Microwave Emission Modelling (CMEM platform present monthly mean differences up to 7 K. Offline experiments with the new formulation present drier soil moisture, hence simulated brightness temperature with its surface fields are larger. They are also closer to SMOS remotely sensed brightness temperature.

  14. Microwave-derived soil moisture over Mediterranean land uses: from ground-based radiometry to SMOS first observations

    Science.gov (United States)

    Saleh, Kauzar; Antolín, Carmen; Juglea, Silvia; Kerr, Yann; Millán-Scheiding, Cristina; Novello, Nathalie; Pardé, Mickael; Wigneron, Jean-Pierre; Zribi, Mehrez; López-Baeza, Ernesto

    2010-05-01

    plant growing cycle. 2) Airborne-based experiments. 2.1) ESA's SMOS Rehearsal 2008. For this campaign an area of 100 km2 of vineyards in winter-like conditions was flown on four days using the EMIRAD radiometer. Soil moisture could be retrieved with good accuracy but only after surface roughness was determined. In fact, the campaign highlighted that close to specular modelling of the surface reflectivity using 0-6 cm measurements of soil moisture underestimated the surface emission. This was observed also in other airborne data sets (Saleh et al. 2009). 2.2) CNES CAROLS campaigns. In 2009, the L-band CAROLS radiometer was flown on three occasions over an area of 1500 km2 covering vineyards, shrub land and Mediterranean pine forest. Main results of CAROLS 2009 will be presented in this communication, and the emphasis will be on comparing local to regional scale results given that CAROLS flights were performed at ~4000 m above the surface. For soil moisture, SVAT-derived, field soil moisture, and surface-type derived soil moisture will be used as ground truth. 3) SMOS data Finally, the results of the above mentioned experiments concerning L-MEB parameterisations will be the basis for comparisons between simulated brightness temperatures (TB) and measured TBs from SMOS at the VAS site. These exercises will be conducted in order to have an assessment of the L-MEB performance in a highly studied and monitored area, and to help pinpointing future areas of investigation in microwave radiometry. References Cano A., Saleh K., Wigneron J.P., Antolín C., Balling J., Kerr Y.H., Kruszewski A., Millán-Scheiding C., Søbjaerg S.S., Skou N., López-Baeza E. (2009), The SMOS Medierranean Ecosystem L-band experiment (MELBEX-I) over natural shrubs, Remote Sensing of Environment, in press. Saleh K., Kerr Y.H., Richaume P., Escorihuela, M.J., Panciera R., Delwart S., Walker J., Boulet G., Maisongrande P., Wursteisen P., Wigneron, J.P. (2009), Soil moisture retrievals at L-band using a two

  15. Sampling Strategy for Soil Moisture Ground Measurements in the Campaigns of 2008 and 2009 at the Valencia Anchor Station (VAS)

    Science.gov (United States)

    Antolin, M. Carmen; Millan-Scheiding, Cristina; Carbo, Ester; Lopez-Baeza, Ernesto

    2010-12-01

    Knowledge of the distribution of soil moisture (SM) in semi-arid Mediterranean ecosystems, and of the environmental factors influencing it will enable the acquisition of in situ data simultaneous to the observations from SMOS in the area of the Valencia Anchor Station (VAS). In the Airborne Campaigns of 2008, 2009 and 2010 performed at the VAS site, different sample strategies have been followed with the objective of optimizing the work of acquisition of the necessary ground measurements for the validation of the airborne sensors and the relations with the environmental factors. The combined sampling designs used have enabled the estimation of SM values in larger areas, and the resulting SM maps are correlated with those produced by the airborne sensors. This confirms the use of these strategies for the calibration/validation of SMOS at the VAS.

  16. Soil Moisture Monitorization Using GNSS Reflected Signals

    CERN Document Server

    Egido, Alejandro; Caparrini, Marco; Martin, Cristina; Farres, Esteve; Banque, Xavier

    2008-01-01

    The use of GNSS signals as a source of opportunity for remote sensing applications, GNSS-R, has been a research area of interest for more than a decade. One of the possible applications of this technique is soil moisture monitoring. The retrieval of soil moisture with GNSS-R systems is based on the variability of the ground dielectric properties associated to soil moisture. Higher concentrations of water in the soil yield a higher dielectric constant and reflectivity, which incurs in signals that reflect from the Earth surface with higher peak power. Previous investigations have demonstrated the capability of GPS bistatic scatterometers to obtain high enough signal to noise ratios in order to sense small changes in surface reflectivity. Furthermore, these systems present some advantages with respect to others currently used to retrieve soil moisture. Upcoming satellite navigation systems, such as the European Galileo, will represent an excellent source of opportunity for soil moisture remote sensing for vario...

  17. Effect of soil moisture on landmine detection using ground penetrating radar

    NARCIS (Netherlands)

    Miller, T.W.; Borchers, B.; Hendrickx, J.M.H.; Hong, S.-H.; Lensen, H.A.; Schwering, P.B.W.; Rhebergen, J.

    2002-01-01

    Soil surface temperatures not only exhibit daily and annual cycles but also are very variable in space and time. Without knowledge of the spatial and temporal variability of soil surface temperatures, it will be difficult to determine what times of day are most suitable for mine detection using

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

    KAUST Repository

    Singh, Gurjeet

    2016-05-05

    Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA’s Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  19. Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

    Science.gov (United States)

    Choi, Joshua S.; Sanders, Antonio L.

    2012-01-01

    Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014.[double dagger] The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass ground operations can still reduce mission cost through smaller staffing of operators and limited work hours. The challenge, then, for the SMAP GDS engineering team is to formulate an automated operations strategy--and corresponding system architecture--to minimize operator intervention during operations, while balancing the development cost associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS--NASA's AMMOS Mission Data Processing and Control System (AMPCS)--provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

  20. A 868MHz-based wireless sensor network for ground truthing of soil moisture for a hyperspectral remote sensing campaign - design and preliminary results

    Science.gov (United States)

    Näthe, Paul; Becker, Rolf

    2014-05-01

    Soil moisture and plant available water are important environmental parameters that affect plant growth and crop yield. Hence, they are significant parameters for vegetation monitoring and precision agriculture. However, validation through ground-based soil moisture measurements is necessary for accessing soil moisture, plant canopy temperature, soil temperature and soil roughness with airborne hyperspectral imaging systems in a corresponding hyperspectral imaging campaign as a part of the INTERREG IV A-Project SMART INSPECTORS. At this point, commercially available sensors for matric potential, plant available water and volumetric water content are utilized for automated measurements with smart sensor nodes which are developed on the basis of open-source 868MHz radio modules, featuring a full-scale microcontroller unit that allows an autarkic operation of the sensor nodes on batteries in the field. The generated data from each of these sensor nodes is transferred wirelessly with an open-source protocol to a central node, the so-called "gateway". This gateway collects, interprets and buffers the sensor readings and, eventually, pushes the data-time series onto a server-based database. The entire data processing chain from the sensor reading to the final storage of data-time series on a server is realized with open-source hardware and software in such a way that the recorded data can be accessed from anywhere through the internet. It will be presented how this open-source based wireless sensor network is developed and specified for the application of ground truthing. In addition, the system's perspectives and potentials with respect to usability and applicability for vegetation monitoring and precision agriculture shall be pointed out. Regarding the corresponding hyperspectral imaging campaign, results from ground measurements will be discussed in terms of their contributing aspects to the remote sensing system. Finally, the significance of the wireless sensor

  1. Passive Microwave Soil Moisture Retrieval Using a Ground-Based L-Band (1.26 GHz) Radiometer Acquired During the Corn Growing Season in 2002

    Science.gov (United States)

    Joseph, A. T.; van der Velde, R.; O'Neill, P. E.; Su, Z.; Liang, S.; Jackson, T. J.; Lang, R. H.; Kim, E. J.; Gish, T.

    2006-05-01

    In the corn growing season of 2002, a tower-based L-band (1.26 GHz) microwave radiometer (Lrad) and a truck-mounted C- and L-band (5.3 and 1.4 GHz) radar were installed and operated along the side of the corn grown OPE3* experimental site managed by the USDA-ARS** Hydrology and Remote Sensing Laboratory (HRSL) in Beltsville, Maryland. The radiometer was programmed to acquire data automatically every hour, while the radar observations were collected once a week at four different times during the day. The radiometer as well as the radar collected several individual observations within an azimuth of 120 degrees at various incidence angles (25, 35, 45, 55 and 60 for the radiometer and 15, 35 and 55 degrees for the radar). Simultaneous to the microwave observations, an extensive ground truth data set was collected, which includes soil moisture, soil surface roughness, vegetation moisture and vegetation geometry. In this investigation, soil moisture retrieval results are presented primarily based on the passive microwave OPE3 data set. The soil moisture retrieval algorithm is employed targeting the direct retrieval of the H (horizontal) - and V (vertical) - polarized optical depth from H- and V-polarized L-band brightness temperatures (TB). The methodology can be directly applied to observations that will be acquired by the Soil Moisture and Ocean Salinity (SMOS) sensor and requires only input of the temperature of the emitting layer, surface roughness and single scattering albedo. *Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) **United States Department of Agriculture (USDA) Agricultural Research Service (ARS)

  2. Estimation of soil moisture using multispectral and FTIR techniques

    Directory of Open Access Journals (Sweden)

    Syed Muhammad Zubair Younis

    2015-12-01

    Full Text Available Soil moisture is a key capricious in hydrological process, the accessibility of moisture content in soil reins the mechanism amid the land surface and atmospheric progression. Precise soil moisture determination is influential in the weather forecast, drought monitoring, hydrological modeling, agriculture management and policy making. The aims of the study were to estimate soil moisture through remotely sensed data (FTIR & optical and establishment of the results with field measured soil moisture data. The ground measurements were carried out in 0–15 cm depth. Permutation of normalized difference vegetation index (NDVI and land surface temperature (LST were taken to derive temperature vegetation dryness index (TVDI for assessment of surface soil moisture. Correlation and regression analysis was conceded to narrate the TVDI with in situ calculated soil moisture. The spatial pattern of TVDI shows that generally low moisture distribution over study area. A significant (p < 0.05 negative correlation of r = 0.79 was found between TVDI and in situ soil moisture. The TVDI was also found adequate in temporal variation of surface soil moisture. The triangle method (TVDI confers consistent appraisal of moisture situation and consequently can be used to evaluate the wet conditions. Furthermore, the appraisal of soil moisture using the triangular method (TVDI was possible at medium spatial resolutions because the relationship of soil moisture with LST and NDVI lends an eloquent number of representative pixels for developing a triangular scatter plot.

  3. Soil Surface Sealing Effect on Soil Moisture at a Semiarid Hillslope: Implications for Remote Sensing Estimation

    OpenAIRE

    Shai Sela; Tal Svoray; Shmuel Assouline

    2014-01-01

    Robust estimation of soil moisture using microwave remote sensing depends on extensive ground sampling for calibration and validation of the data. Soil surface sealing is a frequent phenomenon in dry environments. It modulates soil moisture close to the soil surface and, thus, has the potential to affect the retrieval of soil moisture from microwave remote sensing and the validation of these data based on ground observations. We addressed this issue using a physically-based modeling approach...

  4. Evaluation of a Global Soil Moisture Product from Finer Spatial Resolution SAR Data and Ground Measurements at Irish Sites

    Directory of Open Access Journals (Sweden)

    Chiara Pratola

    2014-08-01

    Full Text Available In the framework of the European Space Agency Climate Change Initiative, a global, almost daily, soil moisture (SM product is being developed from passive and active satellite microwave sensors, at a coarse spatial resolution. This study contributes to its validation by using finer spatial resolution ASAR Wide Swath and in situ soil moisture data taken over three sites in Ireland, from 2007 to 2009. This is the first time a comparison has been carried out between three sets of independent observations from different sensors at very different spatial resolutions for such a long time series. Furthermore, the SM spatial distribution has been investigated at the ASAR scale within each Essential Climate Variable (ECV pixel, without adopting any particular model or using a densely distributed network of in situ stations. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values in temperate grasslands. Temporal and spatial variability analysis provided high levels of correlation (p < 0.025 and low errors between the three datasets, leading to confidence in the new ECV SM global product, despite limitations in its ability to track the driest and wettest conditions.

  5. Early Soil Moisture Field Experiments

    Science.gov (United States)

    Schmugge, T.

    2008-12-01

    Before the large scale field experiments described in the call for papers, there were a number of experiments devoted to a single parameter, e.g. soil moisture. In the early 1970's, before the launch of the first microwave radiometer by NASA, there were a number of aircraft experiments to determine utility of these sensors for land observations. For soil moisture, these experiments were conducted in southwestern United States over irrigated agricultural areas which could provide a wide range of moisture conditions on a given day. The radiometers covered the wavelength range from 0.8 to 21 cm. These experiments demonstrated that it is possible to observe soil moisture variations remotely using a microwave radiometer with a sensitivity of about 3 K / unit of soil moisture. The results also showed that the longer wavelengths were better, with a radiometer at the 21 cm wavelength giving the best results. These positive results led to the development of Push Broom Microwave Radiometer (PBMR) and the Electrically Scanned Thinned Array Radiometer (ESTAR) instruments at the 21-cm wavelength. They have been used extensively in the large-scale experiments such as HAPEX-MOBILHY, FIFE, Monsoon90, SMEX, etc. The multi-beam nature of these instruments makes it possible to obtain more extensive coverage and thus to map spatial variations of surface soil moisture. Examples of the early results along with the more recent soil moisture maps will be presented.

  6. Evaluation of dielectric mixing models for microwave soil moisture retrieval using data from the Combined Radar/Radiometer (ComRAD) ground-based SMAP simulator

    Science.gov (United States)

    Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...

  7. Effects of near surface soil moisture profiles during evaporation on far-field ground-penetrating radar data: A numerical study

    KAUST Repository

    Moghadas, Davood

    2013-01-01

    We theoretically investigated the effect of vapor flow on the drying front that develops in soils when water evaporates from the soil surface and on GPR data. The results suggest the integration of the full-wave GPR model with a coupled water, vapor, and heat flow model to accurately estimate the soil hydraulic properties. We investigated the Effects of a drying front that emerges below an evaporating soil surface on the far-field ground-penetrating radar (GPR) data. First, we performed an analysis of the width of the drying front in soils with 12 different textures by using an analytical model. Then, we numerically simulated vertical soil moisture profiles that develop during evaporation for the soil textures. We performed the simulations using a Richards flow model that considers only liquid water flow and a model that considers coupled water, vapor, and heat flows. The GPR signals were then generated from the simulated soil water content profiles taking into account the frequency dependency of apparent electrical conductivity and dielectric permittivity. The analytical approach indicated that the width of the drying front at the end of Stage I of the evaporation was larger in silty soils than in other soil textures and smaller in sandy soils. We also demonstrated that the analytical estimate of the width of the drying front can be considered as a proxy for the impact that a drying front could have on far-field GPR data. The numerical simulations led to the conclusion that vapor transport in soil resulted in S-shaped soil moisture profiles, which clearly influenced the GPR data. As a result, vapor flow needs to be considered when GPR data are interpreted in a coupled inversion approach. Moreover, the impact of vapor flow on the GPR data was larger for silty than for sandy soils. These Effects on the GPR data provide promising perspectives regarding the use of radars for evaporation monitoring. © Soil Science Society of America 5585 Guilford Rd., Madison, WI

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

    Science.gov (United States)

    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.

  9. Gravity changes, soil moisture and data assimilation

    Science.gov (United States)

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

    2003-04-01

    Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground

  10. Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

    Science.gov (United States)

    2011-01-01

    the relationship between reflec- tance and soil moisture where there is ground cover and ascertain the Normalized Difference Vegetation Index ( NDVI ...in those areas. This could establish a minimum NDVI for ground cover that would allow for estimation of soil moisture. Alternatively, they could...REPORT DATE (DD-MM-YYYY) 14-02-2012 2. REPORT TYPE Journal Article 3. DATES COVERED /From - To) 4. TITLE AND SUBTITLE Remote Sensing of Soil

  11. Soil Moisture Monitoring at Watershed Scale in Eastern India

    Science.gov (United States)

    Panda, R. K.

    2015-12-01

    Understanding the spatio-temporal variation of soil moisture on time scales that range from minute to decades on the watershed scale is important for the hydrological, meteorological and agricultural communities. Lack of reliable, longterm soil moisture datasets in developing countries like India, is a bottleneck for soil moisture analysis and prediction. Recognizing the need of continuous, automated in-situ soil moisture observations, three in-situ soil moisture test-beds have been established in an agricultural watershed of the Eastern India. Test-beds have been specifically designed to capture the root zone soil moisture dynamic at different crop fields under both surplus and water deficit conditions in low, medium and up-lands of the study region. Both volumetric and tensiometric method based sensors, Campbell Scientific soil water content reflectometer (CS650) and matric potential sensor (CS229) are installed at depths of 5, 15, 30, 60 and 100 cm below the surface. GPRS communication modems were installed at each station for remote communication from the data loggers (Campbell Scientific, CR1000) for automatic data collection. To achieve a better understanding of the spatial variation of the soil moisture on watershed scale, the strategic ground-based surface measurements were made in diverse landscape using portable impedance probe. The primary aim of spatial and temporal scale soil moisture measurement is to validate current remote sensing products of Soil Moisture Active Passive (SMAP). In order to improve validation procedure, the soil texture and soil hydraulic parameters are also estimated across the spatial scales to develop dynamic relationship between these parameters. Herein, the strategies for the site selection, calibration of the soil moisture sensors, ground-based soil moisture monitoring, hydraulic properties estimation at spatial scale and the quality assurance techniques applied to the observations are provided.

  12. Nematode survival in relation to soil moisture

    NARCIS (Netherlands)

    Simons, W.R.

    1973-01-01

    Established nematode populations are very persistent in the soil. It is known that they need sufficient soil moisture for movement, feeding and reproduction (fig. 5), and that there are adverse soil moisture conditions which they cannot survive. The influence of soil moisture on survival

  13. Estimation of soil moisture and its effect on soil thermal ...

    Indian Academy of Sciences (India)

    Soil moisture is an important parameter of the earth's climate system. Regression model for estimation of soil moisture at various depths has been developed using the amount of moisture near the surface layer. The estimated values of soil moisture are tested with the measured moisture values and it is found that the ...

  14. SMEX03 Little Washita Micronet Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains volumetric soil moisture, soil temperature, soil conductivity, soil salinity, and surface temperature data collected during the Soil Moisture...

  15. Soil Moisture and Agromet Models

    Science.gov (United States)

    1981-03-01

    decade of each month also produces monthly summaries. The Soil Moisture program covers two geographical areas. Area 1, the " Europea |," or "Soviet...American Geophysical Union , 25, 683-693. Thornthwaite, C. W. and J. R. Mather, 1955: The Water Balance. Publicatiuns in Climatology, Drexel Inst. of

  16. Soil Moisture Retrieval from Aquarius

    Science.gov (United States)

    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...

  17. The soil moisture velocity equation

    Science.gov (United States)

    Ogden, Fred L.; Allen, Myron B.; Lai, Wencong; Zhu, Jianting; Seo, Mookwon; Douglas, Craig C.; Talbot, Cary A.

    2017-06-01

    Numerical solution of the one-dimensional Richards' equation is the recommended method for coupling groundwater to the atmosphere through the vadose zone in hyperresolution Earth system models, but requires fine spatial discretization, is computationally expensive, and may not converge due to mathematical degeneracy or when sharp wetting fronts occur. We transformed the one-dimensional Richards' equation into a new equation that describes the velocity of moisture content values in an unsaturated soil under the actions of capillarity and gravity. We call this new equation the Soil Moisture Velocity Equation (SMVE). The SMVE consists of two terms: an advection-like term that accounts for gravity and the integrated capillary drive of the wetting front, and a diffusion-like term that describes the flux due to the shape of the wetting front capillarity profile divided by the vertical gradient of the capillary pressure head. The SMVE advection-like term can be converted to a relatively easy to solve ordinary differential equation (ODE) using the method of lines and solved using a finite moisture-content discretization. Comparing against analytical solutions of Richards' equation shows that the SMVE advection-like term is >99% accurate for calculating infiltration fluxes neglecting the diffusion-like term. The ODE solution of the SMVE advection-like term is accurate, computationally efficient and reliable for calculating one-dimensional vadose zone fluxes in Earth system and large-scale coupled models of land-atmosphere interaction. It is also well suited for use in inverse problems such as when repeat remote sensing observations are used to infer soil hydraulic properties or soil moisture.Plain Language SummarySince its original publication in 1922, the so-called Richards' equation has been the only rigorous way to couple groundwater to the land surface through the unsaturated zone that lies between the water table and land surface. The soil moisture distribution and

  18. Measurement of soil moisture using gypsum blocks

    DEFF Research Database (Denmark)

    Friis Dela, B.

    For the past 50 years, gypsum blocks have been used to determine soil moisture content. This report describes a method for calibrating gypsum blocks for soil moisture measurements. Moisture conditions inside a building are strongly influenced by the moisture conditions in the soil surrounding...... the building. Consequently, measuring the moisture of the surrounding soil is of great importance for detecting the source of moisture in a building. Up till now, information has been needed to carry out individual calibrations for the different types of gypsum blocks available on the market and to account...

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

    Science.gov (United States)

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

    2016-01-01

    Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

  20. Ground-based investigation of soil moisture variability within remote sensing footprints during the Southern Great Plains 1997 (SGP97) Hydrology Experiment

    NARCIS (Netherlands)

    Famiglietti, J.S.; Devereaux, J.A.; Laymon, C.A.; Tsegaye, T.; Houser, P.R.; Jackson, T.J.; Graham, S.T.; Rodell, M.; Oevelen, van P.J.

    1999-01-01

    Surface soil moisture content is highly variable in both space and time. While remote sensing provides an effective methodology for mapping surface moisture content over large areas, it averages within-pixel variability thereby masking the underlying heterogeneity observed at the land surface. This

  1. Soil Moisture Mapping from ASAR Imagery of the Mulargia basin

    Science.gov (United States)

    Fois, L.; Montaldo, N.

    2016-12-01

    The state of the soil moisture is a key variable controlling surface water and energy balances. High resolution data of the ASAR (advanced synthetic aperture radar) sensor aboard European Space Agency's Envisat satellite offers the opportunity for monitoring surface soil moisture at high resolution (up to 30 m), which is suitable for distributed mapping within the small scales of typical Mediterranean basins. These basins are characterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution satellite images allow to estimate adequately soil moisture spatial variability. ASAR-based soil moisture mapping of the Mulargia basin (area of about 65 sq.km) are collected for 2003-2006 years. In Mediterranean basins, such as the Mulargia basin, characterized by water-limited conditions, even though there is no universal relationship between vegetation and soil patterns in water-limited conditions some relationship between soil water storage capacity and vegetation type and density can be found: for instance, typically an increase of woody vegetation dimension and canopy density when moving from uplands of a hillslope (with thin coarse textured soils) to alluvial fans (with deep soils of finer texture). We investigated the relationships between soil moisture spatial variability, soil depth and vegetation distribution, which impact strongly soil, vegetation and atmosphere interactions. For the case study ASAR products at single and double polarization are tested and validated. For validating radar soil moisture estimates, spatially distributed soil moisture ground-truth data have also been collected over the whole basin through the TDR technique and the gravimetric method, in days with available radar images. Results shows: 1) the high resolution ASAR imagery accuracy for producing maps of surface soil moisture patterns at the catchment scale and their reliability for different seasons (wet vs dry), and 2) a

  2. Evaluating ESA CCI soil moisture in East Africa

    Science.gov (United States)

    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.

  3. Soil moisture retrival from Sentinel-1 and Modis synergy

    Science.gov (United States)

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

    2017-04-01

    This study presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). In the two methodologies using change detection techniques, preprocessed radar data are combined with normalized difference vegetation index (NDVI) auxiliary data to estimate the mean soil moisture with a resolution of 1km. By modeling the relationship between the backscatter difference and NDVI, the soil moisture at a specific NDVI value is retrieved. The first algorithm is already developed on West Africa(Zribi et al., 2014) from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The proposed methodologies have been validated with the ground measurement in two demonstrative fields with RMS error about 0.05 (in volumetric moisture), and the coherence between soil moisture variations and rainfall events is observed. Soil moisture maps at 1km resolution are generated for the study area. The results demonstrate the potential of Sentinel-1 data for the retrieval of soil moisture at 1km or even better resolution.

  4. Evaluating ESA CCI Soil Moisture in East Africa

    Science.gov (United States)

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

    2016-01-01

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

  5. Total below-ground carbon and nitrogen partitioning of mature black spruce displaying genetic x soil moisture interaction in growth

    Science.gov (United States)

    John E. Major; Kurt H. Johnsen; Debby C. Barsi; Moira Campbell

    2012-01-01

    Total belowground biomass, soil C, and N mass were measured in plots of 32-year-old black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) from four full-sib families studied previously for drought tolerance and differential productivity on a dry and a wet site. Stump root biomass was greater on the wet than on the dry site;...

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

    Science.gov (United States)

    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. Model for Ground-Coupled Heat and Moisture Transfer from Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Deru, M.

    2003-06-01

    An important factor in soil heat transfer that is often over looked is the effect of moisture, which can vary the effective thermal conductivity by a factor of ten. The objective of this research was to investigate the ground-coupled heat and moisture transfer from buildings, and to develop results and tools to improve energy simulation of ground-coupled heat transfer.

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

    Science.gov (United States)

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

    2017-12-01

    Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

  9. Soil moisture from operational meteorological satellites

    NARCIS (Netherlands)

    Wagner, W; Naeimi, V.; Scipal, K.; De Jeu, R.A.M.; Fernandez, M.

    2007-01-01

    In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS

  10. Soil moisture from Operational Meteorological Satellites

    NARCIS (Netherlands)

    Wagner, W.; Naeimi, V.; Scipal, K.; de Jeu, R.A.M.; Martinez-Fernandez, J.

    2007-01-01

    In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS

  11. Retrieving and Validation Soil Moisture from SMOS Products in the Southwest of Iran

    Science.gov (United States)

    Jamei, Mozhdeh; Mousavi Baygi, Mohammad; Alizadeh, Amin; Irannejad, Parviz

    2016-08-01

    Soil moisture is one of the most important variables in the hydrological cycle. Since, direct soil moisture measurement are costly and time-consuming so these information are not practicable for wide-area. In recent years, indirect soil moisture measurements have become available from satellite-based microwave sensors. The southwest of Iran is the most important agricultural area in country, therefore simulation of soil moisture in this region is necessary to water resources management, weather forecasting and monitoring extreme events. The objective of this research was to retrieve and validate of soil moisture from ESA's SMOS (Soil Moisture and Ocean Salinity) mission. Validation of SMOS Level 1C (SCLF1C) products have done using ground based measurements and L-MEB (L-band Microwave Emission of the Biosphere) model, Level 2 (SMUDP2) products with ground based soil moisture measurement. The result of this research gives valuable information on the errors and uncertainties in SMOS Products in this region.

  12. Hysteresis of soil temperature under different soil moisture and ...

    African Journals Online (AJOL)

    ... in a solar greenhouse. The objective of this study was to find a simple method to estimate the hysteresis of soil temperature under three soil moisture and two fertilizer levels in solar greenhouse conditions with tomato crop (Lycopersicon esculentum Mill). The results show that the soil moisture had no significant effects on ...

  13. Upscaling In Situ Soil Moisture Observations to Pixel Averages with Spatio-Temporal Geostatistics

    Directory of Open Access Journals (Sweden)

    Jianghao Wang

    2015-09-01

    Full Text Available Validation of satellite-based soil moisture products is necessary to provide users with an assessment of their accuracy and reliability and to ensure quality of information. A key step in the validation process is to upscale point-scale, ground-based soil moisture observations to satellite-scale pixel averages. When soil moisture shows high spatial heterogeneity within pixels, a strategy which captures the spatial characteristics is essential for the upscaling process. In addition, temporal variation in soil moisture must be taken into account when measurement times of ground-based and satellite-based observations are not the same. We applied spatio-temporal regression block kriging (STRBK to upscale in situ soil moisture observations collected as time series at multiple locations to pixel averages. STRBK incorporates auxiliary information such as maps of vegetation and land surface temperature to improve predictions and exploits the spatio-temporal correlation structure of the point-scale soil moisture observations. In addition, STRBK also quantifies the uncertainty associated with the upscaled soil moisture which allows bias detection and significance testing of satellite-based soil moisture products. The approach is illustrated with a real-world application for upscaling in situ soil moisture observations for validating the Polarimetric L-band Multi-beam Radiometer (PLMR retrieved soil moisture product in the Heihe Water Allied Telemetry Experimental Research experiment (HiWATER. The results show that STRBK yields upscaled soil moisture predictions that are sufficiently accurate for validation purposes. Comparison of the upscaled predictions with PLMR soil moisture observations shows that the root-mean-squared error of the PLMR soil moisture product is about 0.03 m3·m−3 and can be used as a high-resolution soil moisture product for watershed-scale soil moisture monitoring.

  14. Global characterization of surface soil moisture drydowns

    Science.gov (United States)

    McColl, Kaighin A.; Wang, Wei; Peng, Bin; Akbar, Ruzbeh; Short Gianotti, Daniel J.; Lu, Hui; Pan, Ming; Entekhabi, Dara

    2017-04-01

    Loss terms in the land water budget (including drainage, runoff, and evapotranspiration) are encoded in the shape of soil moisture "drydowns": the soil moisture time series directly following a precipitation event, during which the infiltration input is zero. The rate at which drydowns occur—here characterized by the exponential decay time scale τ—is directly related to the shape of the loss function and is a key characteristic of global weather and climate models. In this study, we use 1 year of surface soil moisture observations from NASA's Soil Moisture Active Passive mission to characterize τ globally. Consistent with physical reasoning, the observations show that τ is lower in regions with sandier soils, and in regions that are more arid. To our knowledge, these are the first global estimates of τ—based on observations alone—at scales relevant to weather and climate models.

  15. Soil Surface Sealing Effect on Soil Moisture at a Semiarid Hillslope: Implications for Remote Sensing Estimation

    Directory of Open Access Journals (Sweden)

    Shai Sela

    2014-08-01

    Full Text Available Robust estimation of soil moisture using microwave remote sensing depends on extensive ground sampling for calibration and validation of the data. Soil surface sealing is a frequent phenomenon in dry environments. It modulates soil moisture close to the soil surface and, thus, has the potential to affect the retrieval of soil moisture from microwave remote sensing and the validation of these data based on ground observations. We addressed this issue using a physically-based modeling approach that accounts explicitly for surface sealing at the hillslope scale. Simulated mean soil moisture at the respective layers corresponding to both the ground validation probe and the radar beam’s typical effective penetration depth were considered. A cyclic pattern was found in which, as compared to an unsealed profile, the seal layer intensifies the bias in validation during rainfall events and substantially reduces it during subsequent drying periods. The analysis of this cyclic pattern showed that, accounting for soil moisture dynamics at the soil surface, the optimal time for soil sampling following a rainfall event is a few hours in the case of an unsealed system and a few days in the case of a sealed one. Surface sealing was found to increase the temporal stability of soil moisture. In both sealed and unsealed systems, the greatest temporal stability was observed at positions with moderate slope inclination. Soil porosity was the best predictor of soil moisture temporal stability, indicating that prior knowledge regarding the soil texture distribution is crucial for the application of remote sensing validation schemes.

  16. SMEX03 Little River Micronet Soil Moisture Data: Georgia

    Data.gov (United States)

    National Aeronautics and Space Administration — Parameters for this data set include precipitation, soil temperature, volumetric soil moisture, soil conductivity, and soil salinity measured in the Little River...

  17. Mapping soil moisture and surface heat fluxes by assimilating GOES land surface temperature and SMAP soil moisture data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; van de Giesen, Nick

    2017-04-01

    This study is focused on estimating soil moisture and sensible/latent heat fluxes by assimilating remotely-sensed land surface temperature (LST) and soil moisture data. Surface heat fluxes interact with the overlying atmosphere, and play a crucial role in the water and energy cycles. However, they cannot be directly measured using remote sensing. It has been demonstrated that LST time series contain information about the surface energy balance, and that assimilating soil moisture further improves the estimation by putting more constraints on the energy partitioning. In previous studies, two controlling factors were estimated: (1) a monthly constant bulk heat transfer coefficient (CHN) that scales the sum of surface heat fluxes, and (2) an evaporative fraction (EF) which governs the energy partitioning and stays quasi-constant during the near-peak hours. Considering the fact that CHN is not constant especially in the growing season, here CHN is assumed a function of leaf area index (LAI). LST data from GOES (Geostationary Operational Environmental Satellites) and soil moisture data from SMAP (Soil Moisture Active Passive) are both assimilated into a simply heat and water transfer model to update LST, soil moisture, CHN and EF , and to map surface heat fluxes over a study area in central US. A hybrid data assimilation strategy is necessary because SMAP data are available every 2-3 days, while GOES LST data are provided every hour. In this study, LST data are assimilated using an adaptive particle batch smoother (APBS) and soil moisture is periodically updated using a particle filter (PF). Results show that soil moisture is greatly improved, and that EF estimates are restored very well after assimilation. As forcing data are provided by remote sensing or reanalysis products to minimize the dependence on ground measurements, this methodology can be easily applied in other regions with limited data.

  18. SMEX02 Soil Moisture and Temperature Profiles, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains rainfall, soil moisture, and soil temperature data collected for the Soil Moisture Experiment 2002 (SMEX02). The parameters measured are soil...

  19. Space-time modeling of soil moisture

    Science.gov (United States)

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

    2017-11-01

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

  20. Effects of natural and synthetic soil conditioners on soil moisture ...

    African Journals Online (AJOL)

    The efficacy of a natural soil conditioner, Coco-Peat (C-P), and synthetic soil conditioners, Terawet (T-200) and Teraflow (T-F), in improving soil moisture content were examined on five Ghanaian soil series (Akroso, Akuse, Amo, Hake and Oyarifa). In general, the water retention of T-200 and C-P treated soils were similar ...

  1. Effects of soil moisture retention on ice distribution and active layer thickness subject to seasonal ground temperature variations in a dry loess terrace in Adventdalen, Svalbard.

    Science.gov (United States)

    Schuh, Carina; Frampton, Andrew; Christiansen, Hanne

    2017-04-01

    The active layer constitutes an important part of permafrost environments. Thermal and hydrological processes in the active layer determine local phenomena such as erosion and hydrological and ecosystem changes, and can have important implications for the global carbon-climate feedback. Permafrost degradation usually starts with a deepening of the active layer, followed by the formation of a talik and the subsequent thawing of permafrost. An increasing active layer thickness is therefore regarded as an indicator of permafrost degradation. The importance of hydrology for active layer processes is generally well acknowledged on a conceptual level, however the in general non-linear physical interdependencies between soil moisture, subsurface water and heat fluxes and active layer thaw progression are not fully understood. In this study, high resolution field data for the period 2000-2014 consisting of active layer and permafrost temperature, active layer soil moisture, and thaw depth progression from the UNISCALM research site in Adventdalen, Svalbard, is combined with a physically-based coupled cryotic and hydrogeological model to investigate active layer dynamics. The site is a loess-covered river terrace characterized by dry conditions with little to no summer infiltration and an unsaturated active layer. A range of soil moisture characteristic curves consistent with loess sediments is considered and their effects on ice and moisture redistribution, heat flux, energy storage through latent heat transfer, and active layer thickness is investigated and quantified based on hydro-climatic site conditions. Results show that soil moisture retention characteristics exhibit notable control on ice distribution and circulation within the active layer through cryosuction and are subject to seasonal variability and site-specific surface temperature variations. The retention characteristics also impact unfrozen water and ice content in the permafrost. Although these effects

  2. Site Averaged Neutron Soil Moisture: 1988 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

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

    Science.gov (United States)

    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.

  4. Site Averaged Gravimetric Soil Moisture: 1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  5. Site Averaged Gravimetric Soil Moisture: 1988 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  6. Site Averaged Gravimetric Soil Moisture: 1987 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  7. Site Averaged Gravimetric Soil Moisture: 1987 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  8. Soil moisture determinations using capacitance probe methodology

    National Research Council Canada - National Science Library

    Atkins, Ronald T

    1998-01-01

    ...) systems is a relatively new approach to soil moisture measurements. A unique probe assembly and a readout device that measures voltage drop and phase shift were developed and used for direct capacitance measurements...

  9. Microwave radiometric measurements of soil moisture in Italy

    Directory of Open Access Journals (Sweden)

    G. Macelloni

    2003-01-01

    Full Text Available Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz. The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz, is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields in different growth stages and on meadows. Ground data of soil moisture (SMC were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture data measured on the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths. Keywords: microwave radiometry, soil moisture

  10. Collective Impacts of Orography and Soil Moisture on the Soil Moisture-Precipitation Feedback

    Science.gov (United States)

    Imamovic, Adel; Schlemmer, Linda; Schär, Christoph

    2017-11-01

    Ensembles of convection-resolving simulations with a simplified land surface are conducted to dissect the isolated and combined impacts of soil moisture and orography on deep-convective precipitation under weak synoptic forcing. In particular, the deep-convective precipitation response to a uniform and a nonuniform soil moisture perturbation is investigated both in settings with and without orography. In the case of horizontally uniform perturbations, we find a consistently positive soil moisture-precipitation feedback, irrespective of the presence of low orography. On the other hand, a negative feedback emerges with localized perturbations: a dry soil heterogeneity substantially enhances rain amounts that scale linearly with the dryness of the soil, while a moist heterogeneity suppresses rain amounts. If the heterogeneity is located in a mountainous region, the relative importance of soil moisture heterogeneity decreases with increasing mountain height: A mountain 500 m in height is sufficient to neutralize the local soil moisture-precipitation feedback.

  11. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

    2017-10-01

    The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

  12. NASA Soil Moisture Active Passive (SMAP) Mission Formulation

    Science.gov (United States)

    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

  13. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    The digital soil moisture meter developed was compared with gravimetric method for soil moisture determination on fifteen soil samples added different level of water during calibration process. The results revealed a relatively linear relationship between the moisture content process and the digital soil moisture meter.

  14. Assessment of the SMAP Passive Soil Moisture Product

    Science.gov (United States)

    Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey; hide

    2016-01-01

    The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

  15. Disaggregation of SMOS soil moisture in southeastern Australia

    OpenAIRE

    Merlin, Olivier; Rüdiger, Christoph; Al Bitar, Ahmad; Richaume, Philippe; Walker, Jeffrey,; Kerr, Yann

    2012-01-01

    DisPATCh (Disaggregation based on Physical And Theoretical scale Change) is an algorithm dedicated to the disaggregation of soil moisture observations using high-resolution soil temperature data. DisPATCh converts soil temperature fields into soil moisture fields given a semi-empirical soil evaporative efficiency model, and a first order Taylor series expansion around the field-mean soil moisture. In this study, the disaggregation approach is applied to SMOS (Soil Moisture and Ocean Salinity)...

  16. Moisture Retention Characteristics of Soils of Different ...

    African Journals Online (AJOL)

    Least total available water was found in soils over alluvium (4.03). Total available water had a significant relationship with total sand (R2 = 0.56, P=0.01). Soil moisture retention characteristic dependent variable was highly predicted by independent variables of total sand, clay content and organic carbon at various tension ...

  17. Soil Temperature and Moisture Profile (STAMP) System Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Cook, David R. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-11-01

    The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.

  18. Surface-Atmosphere Moisture Coupling in Eurasian Frozen Ground Regions

    Science.gov (United States)

    Frauenfeld, O. W.; Ford, T.

    2014-12-01

    Permafrost represents an impermeable barrier to moisture, resulting in a saturated or near-saturated surface layer during the warm season in many continuous and discontinuous permafrost zones. These surface conditions could lead to enhanced convection and precipitation during the warm season, and significant local recycling of moisture. In areas underlain by sporadic or isolated permafrost, or in seasonally frozen areas, the moisture can drain away more readily, resulting in much drier soil conditions. As climate change causes frozen ground degradation, this will thus also alter the patterns of atmospheric convection, moisture recycling, and the hydrologic cycle in high-latitude land areas. In this study, we analyze evaporative fraction (EF) as a proxy for evapotranspiration, and precipitation from the Modern-Era Retrospective analysis for Research and Applications (MERRA-land) reanalysis dataset. We focus on 1979-2012 and document patterns and changes in EF over the Eurasian high latitudes. We find strong, positive April EF trends over the study period, particularly in the Lena River Basin, 80% of which is underlain by continuous permafrost. In fact, these significant positive trends in spring EF are strongest over continuous permafrost across the Eurasian high latitudes, but negative for sporadic and isolated permafrost. In addition, we find a strong, statistically significant relationship between EF anomalies and the probability of subsequent precipitation over the Lena Basin during April. This association therefore suggests a potential land-atmosphere coupling between frozen ground and precipitation. As the permafrost and seasonally frozen ground distribution changes in the future, this will likely have repercussions for the Arctic hydrologic cycle.

  19. Temporal transferability of soil moisture calibration equations

    Science.gov (United States)

    Rowlandson, Tracy L.; Berg, Aaron A.; Bullock, Paul R.; Hanis-Gervais, Krista; Ojo, E. RoTimi; Cosh, Michael H.; Powers, Jarrett; McNairn, Heather

    2018-01-01

    Several large-scale field campaigns have been conducted over the last 20 years that require accurate measurements of soil moisture conditions. These measurements are manually conducted using soil moisture probes which require calibration. The calibration process involves the collection of hundreds of soil moisture cores, which is extremely labor intensive. In 2012, a field campaign was conducted in southern Manitoba in which 55 fields were sampled and calibration equations were derived for each field. The Soil Moisture Active Passive Experiment 2016 (SMAPVEX16) was conducted in this same region, and 21 of the same fields were resampled. This study examines the temporal transferability of calibration equations between these two field campaigns. It was found that the larger range in soil moisture over which samples were collected in 2012 (average range 0.11-0.41 m3 m-3) generally resulted in lower errors when used in 2016 (average range 0.24-0.44 m3 m-3) than the equations derived in 2016 when used with data collected in 2012. Combining the data collected in 2012 and 2016 did not improve the errors, overall. These results suggest that the transfer of calibration equations from one year to the next is not recommended.

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

    Science.gov (United States)

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

    2016-01-01

    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

  1. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    user

    moisture meter developed was compared with gravimetric method for soil moisture determination on fifteen soil samples added different level of water during calibration process. The results revealed a relatively linear relationship between the moisture content process and the digital soil moisture meter. The regression ...

  2. Upscaling In Situ Soil Moisture Observations To Pixel Averages With Spatio-Temporal Geostatistics

    NARCIS (Netherlands)

    Wang, Jianghao; Ge, Yong; Heuvelink, Gerard B.M.; Zhou, Chenghu

    2015-01-01

    Validation of satellite-based soil moisture products is necessary to provide users with an assessment of their accuracy and reliability and to ensure quality of information. A key step in the validation process is to upscale point-scale, ground-based soil moisture observations to satellite-scale

  3. Soil moisture in sessile oak forest gaps

    Science.gov (United States)

    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.

  4. Soil moisture needs in earth sciences

    Science.gov (United States)

    Engman, Edwin T.

    1992-01-01

    The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas.

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

    Science.gov (United States)

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

    2011-05-01

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

  6. Soil Moisture Experiments 2004 and 2005 Results and Plans

    Science.gov (United States)

    Jackson, T. J.

    2005-05-01

    The Soil Moisture Experiments (SMEX) series of field campaigns was designed to address research priorities of several programs involving satellite remote sensing of surface soil moisture. These include the Advanced Scanning Microwave Radiometer (AMSR) on Aqua, the Windsat on Coriolis, and future missions that include NASAs Hydros, the European Space Agency Soil Moisture Ocean Salinity (SMOS) mission and NPOESS. Algorithms, scaling, technology and land-atmosphere studies have all been addressed in each experiment. Scaling is a key aspect of experiment design because of the spatial differences between ground point observations and satellite footprints. In all of the campaigns aircraft sensors have provided the critical link between these. Different geographic domains have been used to provide diverse conditions for algorithm development and validation and a variety of aircraft instruments have been used to support specific objectives. SMEX04 was conducted in August 2004 in the southwestern U.S. and northern Mexico. It was designed to address satellite footprint heterogeneity. The region has the diverse topography, vegetation and rainfall patterns necessary to address this issue. In addition, SMEX04 was timed to coincide with North American Monsoon Experiment (NAME). 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. Surface soil moisture can change dramatically after rain events. A review of SMEX04 and preliminary results will be presented. SMEX05 is being planned to understand what contributions to soil moisture retrieval and mapping may be achieved by using fully polarimetric passive microwave observations. This has not been a focus of land parameter investigations in the past. The Windsat instrument provides these measurements at several frequencies. For SMEX05 an aircraft simulator of Windsat will also be employed. The field campaign will be

  7. Hysteresis of soil temperature under different soil moisture and ...

    African Journals Online (AJOL)

    Jane

    2011-10-17

    Oct 17, 2011 ... heat output at an instant, given only heat input at that instant. For this reason, it is difficult to realistically predict soil temperature if not take into consideration, the hysteresis of soil temperature under the different soil moisture and fertilizer, especially in the solar greenhouse. The objective of this study was to ...

  8. Preliminary analysis of distributed in situ soil moisture measurements

    Directory of Open Access Journals (Sweden)

    L. Brocca

    2005-01-01

    Full Text Available Surface soil moisture content is highly variable in both space and time. Remote sensing can provide an effective methodology for mapping surface moisture content over large areas but ground based measurements are required to test its reliability and to calibrate retrieval algorithms. Recently, we had the opportunity to design and perform an experiment aimed at jointly acquiring measurements of surface soil water content at various locations and remotely sensed hyperspectral data. The area selected for the experiment is located in central Umbria and it extends for 90km2. For the area, detailed lithological and multi-temporal landslide inventory maps were available. We identified eight plots where measurements of soil water content were made using a Time Domain Reflectometer (TDR. The plots range in size from 100m2 to 600m2, and cover a variety of topographic and morphological settings. The TDR measurements were conducted during four days, on 5 April, 15 April, 2 May and 3 May 2004. On 3 May the NERC airborne CASI 2 acquired the hyperspectral data. Preliminary analysis concerning the matching between the landslides and the soil moisture were reported. Statistical and geostatistical analysis investigating the spatial-temporal soil moisture distribution were performed. These results will be compared with the data of surface temperature obtained from the remotely sensed hyperspectral sensor.

  9. DETERMINING SOIL MOISTURE REGIMES FOR VITICULTURAL ZONING PURPOSES

    Directory of Open Access Journals (Sweden)

    Rosa Maria Poch

    2013-07-01

    Full Text Available This paper aims to analyse the suitability of Soil Taxonomy to characterize the soil moisture regime for viticultural zoning studies, comparing the soil moisture parameters used in the Soil Taxonomy classification with soil moisture parameters relevant to the grapevine phenological stages. The results show that Soil Taxonomy does not adequately reflect the variability of soil moisture dynamics during vineyard growing. Then, a proposal for soil moisture regime classification is realised by means of a cluster analysis. This classification is based on determining dry days, as indicated by Soil Taxonomy, in different vine phenological periods, and grouping the cases according to their variability. The soil moisture regime classes, resulting from cluster analysis, show significant differences in soil moisture status in all phenological periods, and therefore present different implications for viticulture, related to potential for vegetative growth, grape production and the grape ripening process.

  10. A capacitive soil moisture sensor

    Science.gov (United States)

    Eller, H.; Denoth, A.

    1996-11-01

    A new sensor for field measurements of the water content of natural soils has been developed. The measurement quantity is the complex permittivity at a frequency of 32 MHz; it is derived by an impedance measurement with a capacitive sensor of a fork-like geometry, which was found to the best geometry for field use. The impedance is measured with a twin T-bridge which has been optimized to cover the extremely large range of permittivities of natural soils. An analysis of measured soil permittivities showed a dominant influence of liquid water content on dielectric permittivity, whereas soil-specific parameters such as grain-size distribution, chemical composition and bulk density have only a negligible influence at this comparable high measurement frequency. The loss factor, however, depends strongly on both the type of soil and the water content. In addition, comparative studies with commonly used measurement methods such as the thermogravimetric method and time domain reflectometry showed satisfactory agreement. As an application of practical interest, a field measurement of a vertical water content distribution at a snow-soil interface is presented.

  11. Mode Decomposition Methods for Soil Moisture Prediction

    Science.gov (United States)

    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.

  12. Soil moisture sensors based on metamaterials

    Directory of Open Access Journals (Sweden)

    Goran Kitić

    2012-12-01

    Full Text Available In this paper novel miniature metamaterial-based soil moisture sensors are presented. The sensors are based on resonant-type metamaterials and employ split-ring resonators (SRR, spiral resonators and fractal SRRs to achieve small dimensions, high sensitivity, and compatibility with standard planar fabrication technologies. All these features make the proposedsensors suitable for deployment in agriculture for precise mapping of soil humidity.

  13. Soil Moisture Remote Sensing: Status and Outlook

    Science.gov (United States)

    Satellite-based passive microwave sensors have been available for thirty years and provide the basis for soil moisture monitoring and mapping. The approach has reached a level of maturity that is now limited primarily by technology and funding. This is a result of extensive research and development ...

  14. AMSR2 Soil Moisture Product Validation

    Science.gov (United States)

    Bindlish, R.; Jackson, T.; Cosh, M.; Koike, T.; Fuiji, X.; de Jeu, R.; Chan, S.; Asanuma, J.; Berg, A.; Bosch, D.; hide

    2017-01-01

    The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W) mission. AMSR2 fills the void left by the loss of the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) after almost 10 years. Both missions provide brightness temperature observations that are used to retrieve soil moisture. Merging AMSR-E and AMSR2 will help build a consistent long-term dataset. Before tackling the integration of AMSR-E and AMSR2 it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites. Three products that rely on different algorithms were evaluated; the JAXA Soil Moisture Algorithm (JAXA), the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). Results indicate that overall the SCA has the best performance based upon the metrics considered.

  15. Estimation of soil moisture and its effect on soil thermal ...

    Indian Academy of Sciences (India)

    The soil temperatures at 0.05, 0.10, 0.20, 0.30, and 0.50 m depths and soil moisture at 0.05 and 0.10 m are measured using the hydrometeorological data acquisition system installed at the observational site. For soil water contents ranging between 11 and 42% in the soil layer of depth 0.05–0.10 m, the mean values of the ...

  16. Benton Lake National Wildlife Refuge : Soil and Moisture Plan

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This Soil and Moisture Plan for Benton Lake NWR explains how the Soil and Moisture Program relates to Refuge objectives, outlines Program policies, and presents...

  17. SMEX03 ThetaProbe Soil Moisture Data: Alabama

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes soil moisture data measured with Delta-T Devices’ ThetaProbe ML2 sensors for the Soil Moisture Experiment 2003 (SMEX03), conducted during June...

  18. SoilNet - A Zigbee based soil moisture sensor network

    Science.gov (United States)

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

    2007-12-01

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

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

    Science.gov (United States)

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

    2017-04-01

    Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE 0.8).

  20. Soil moisture mapping for aquarius

    Science.gov (United States)

    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...

  1. Data Assimilation to Extract Soil Moisture Information from SMAP Observations

    OpenAIRE

    Jana Kolassa; Rolf H. Reichle; Qing Liu; Michael Cosh; David D. Bosch; Todd G. Caldwell; Andreas Colliander; Chandra Holifield Collins; Thomas J. Jackson; Stan J. Livingston; Mahta Moghaddam; Patrick J. Starks

    2017-01-01

    This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural network (NN) and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA) Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture...

  2. Dry-end surface soil moisture variability during NAFE'06

    NARCIS (Netherlands)

    Teuling, A.J.; Uijlenhoet, R.; Hurkmans, R.T.W.L.; Merlin, O.; Panciera, R.; Walker, J.P.; Troch, P.A.

    2007-01-01

    Characterization of the space-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical model to investigate how, at the dry-end of the soil moisture range, the main characteristics of the soil moisture field (spatial mean and variability,

  3. Inference of soil hydrologic parameters from electronic soil moisture records

    Science.gov (United States)

    Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge, and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity, and permanent wilting point have been deter...

  4. Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and...

  5. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  6. Microwave Soil Moisture Retrieval Under Trees

    Science.gov (United States)

    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

  7. Impacts of soil moisture content on visual soil evaluation

    Science.gov (United States)

    Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick

    2017-04-01

    Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References

  8. Soil Moisture Profile Effect on Radar Signal Measurement

    Directory of Open Access Journals (Sweden)

    André Chanzy

    2008-01-01

    Full Text Available The objective of this paper is to analyze the behaviour of a backscattered signalaccording to soil moisture depth over bare soils. Analysis based on experimental verticalmoisture profiles and ASAR/ENVISAT measurements has been carried out. A modifiedIEM model with three permittivity layers (0-1cm, 1-2cm, 2-5cm has been developed andused in this study. Results show a small effect of moisture profile on the backscatteredsignal (less than 0.5dB. However, measurements and simulations have provided a moredetailed insight into the behaviour of the radar signal and have shown that it was importantto consistently use the same protocol when performing ground truth measurements of soilmoisture.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2017-01-01

    NASA's SMAP (Soil Moisture Active Passive) calibration and validation program revealed that the soil moisture products are experiencing difficulties in meeting the mission requirements in certain agricultural areas. Therefore, the mission organized airborne field experiments at two core validation sites to investigate these anomalies. The SMAP Validation Experiment 2016 included airborne observations with the PALS (Passive Active L-band Sensor) instrument and intensive ground sampling. The goal of the PALS measurements are to investigate the soil moisture retrieval algorithm formulation and parameterization under the varying (spatially and temporally) conditions of the agricultural domains and to obtain high resolution soil moisture maps within the SMAP pixels. In this paper the soil moisture retrieval using the PALS brightness temperature observations in SMAPVEX16 is presented.

  11. NASA Soil Moisture Active Passive (SMAP) Applications

    Science.gov (United States)

    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.

  12. Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation

    Directory of Open Access Journals (Sweden)

    M. Zribi

    2011-01-01

    Full Text Available The present paper proposes a method for the evaluation of soil evaporation, using soil moisture estimations based on radar satellite measurements. We present firstly an approach for the estimation and monitoring of soil moisture in a semi-arid region in North Africa, using ENVISAT ASAR images, over two types of vegetation covers. The first mapping process is dedicated solely to the monitoring of moisture variability related to rainfall events, over areas in the "non-irrigated olive tree" class of land use. The developed approach is based on a simple linear relationship between soil moisture and the backscattered radar signal normalised at a reference incidence angle. The second process is proposed over wheat fields, using an analysis of moisture variability due to both rainfall and irrigation. A semi-empirical model, based on the water-cloud model for vegetation correction, is used to retrieve soil moisture from the radar signal. Moisture mapping is carried out over wheat fields, showing high variability between irrigated and non-irrigated wheat covers. This analysis is based on a large database, including both ENVISAT ASAR and simultaneously acquired ground-truth measurements (moisture, vegetation, roughness, during the 2008–2009 vegetation cycle. Finally, a semi-empirical approach is proposed in order to relate surface moisture to the difference between soil evaporation and the climate demand, as defined by the potential evaporation. Mapping of the soil evaporation is proposed.

  13. MONITORING SOIL MOISTURE IN A COAL MINING AREA WITH MULTI-PHASE LANDSAT IMAGES

    Directory of Open Access Journals (Sweden)

    J. L. Kong

    2016-06-01

    Full Text Available The coal development zone of Northern Shaanxi, China is one of the eight largest coal mines in the world, also the national energy and chemical bases. However, the coal mining leads to ground surface deformation and previous studies show that in collapse fissure zone soil water losses almost 50% compared with non-fissure zone. The main objective of this study is to develop a retrieval model that is reliable and sensitive to soil moisture in the whole coal mining zone of Northern Shaanxi based upon the soil sample parameters collected from in situ site investigation, spectral data gathered simultaneously and the images of Landsat7 ETM. The model uses different phases of Landsat data to retrieve soil moisture and analyze the patterns of spatial and temporal variations of soil moisture caused by ground deformation in the coal mining areas. The study indicated that band4 of Landsat7 ETM is the most sensitive band for soil moisture retrieval using the spectrum method. The quadratic model developed by remote sensing reflectance (Rrs4 (corresponding to the band4 is the best pattern with the correlation coefficient of 0.858 between the observed and the estimated soil moisture. Two-phase Landsat7 ETM data of 2002 and 2009 and one phase Landsat8 OLI data of 2015 for the study area were selected to retrieve soil moisture information. The result showed that the mean relative error was 35.16% and the root-mean-squared error (RMSE was 0.58%. The changes of the spatial distribution of inversed soil moisture revealed that the trend of soil moisture contents of the study area was in general being gradually reduced from 2002 to 2015. The study results can serve as the baseline for monitoring environmental impacts on soil moisture in the regions due to coal mining.

  14. Spatiotemporal Distribution of Soil Moisture and Salinity in the Taklimakan Desert Highway Shelterbelt

    Directory of Open Access Journals (Sweden)

    Yuan Huang

    2015-08-01

    Full Text Available Salinization and secondary salinization often appear after irrigation with saline water. The Taklimakan Desert Highway Shelterbelt has been irrigated with saline ground water for more than ten years; however, soil salinity in the shelterbelt has not been evaluated. The objective of this study was to analyze the spatial and temporal distribution of soil moisture and salinity in the shelterbelt system. Using a non-uniform grid method, soil samples were collected every two days during one ten-day irrigation cycle in July 2014 and one day in spring, summer, and autumn. The results indicated that soil moisture declined linearly with time during the irrigation cycle. Soil moisture was greatest in the southern and eastern sections of the study area. In contrast to soil moisture, soil electrical conductivity increased from 2 to 6 days after irrigation, and then gradually decreased from 6 to 8 days after irrigation. Soil moisture was the greatest in spring and the least in summer. In contrast, soil salinity increased from spring to autumn. Long time drip-irrigation with saline groundwater increased soil salinity slightly. The soil salt content was closely associated with soil texture. The current soil salt content did not affect plant growth, however, the soil in the shelterbelt should be continuously monitored to prevent salinization in the future.

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

    Science.gov (United States)

    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.

  16. Design and Fabrication of a Soil Moisture Meter Using Thermal Conductivity Properties of Soil

    National Research Council Canada - National Science Library

    Subir Das; Biplab Bag; T S Sarkar; Nisher Ahmed; B Chakrabrty

    2011-01-01

    ... of soil moisture modeling. In this present work design of a soil moisture measurement meter using thermal conductivity properties of soil has been proposed and experimental results are reported...

  17. Integrating Real-time and Manual Monitored Soil Moisture Data to Predict Hillslope Soil Moisture Variations with High Temporal Resolutions

    Science.gov (United States)

    Zhu, Qing; Lv, Ligang; Zhou, Zhiwen; Liao, Kaihua

    2016-04-01

    Spatial-temporal variability of soil moisture 15 has been remaining an challenge to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time soil moisture monitoring methods. This restricted the comprehensive and intensive examination of soil moisture dynamics. In this study, we aimed to integrate the manual and real-time monitored soil moisture to depict the hillslope dynamics of soil moisture with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear models (support vector machines-SVM) were used to predict soil moisture at 38 manual sites (collected 1-2 times per month) with soil moisture automatically collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each manual site, optimal soil moisture prediction model of this site was then determined. Results show that soil moisture at these 38 manual sites can be reliably predicted (root mean square errorsindex, profile curvature, and relative difference of soil moisture and its standard deviation influenced the selection of prediction model since they related to the dynamics of soil water distribution and movement. By using this approach, hillslope soil moisture spatial distributions at un-sampled times and dates were predicted after a typical rainfall event. Missing information of hillslope soil moisture dynamics was then acquired successfully. This can be benefit for determining the hot spots and moments of soil water movement, as well as designing the proper soil moisture monitoring plan at the field scale.

  18. A soil moisture network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, N.; Jensen, Karsten Høgh

    2012-01-01

    pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes representing......The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data of global coverage every three days. Product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and soil temperature sensor...... the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature and precipitation...

  19. A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS Soil Moisture: Retrieval Ensembles

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

    Full Text Available Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV bias correction method for Soil Moisture and Ocean Salinity (SMOS soil moisture. To the best of our knowledge, this is the first paper to present the probabilistic presentation of SMOS soil moisture using retrieval ensembles. We illustrate that retrieval ensembles effectively mitigated the overestimation problem of SMOS soil moisture arising from brightness temperature errors over West Africa in a computationally efficient way (ensemble size: 12, no time-integration. In contrast, the existing method of Cumulative Distribution Function (CDF matching considerably increased the SMOS biases, due to the limitations of relying on the imperfect reference data. From the validation at two semi-arid sites, Benin (moderately wet and vegetated area and Niger (dry and sandy bare soils, it was shown that the SMOS errors arising from rain and vegetation attenuation were appropriately corrected by ensemble approaches. In Benin, the Root Mean Square Errors (RMSEs decreased from 0.1248 m3/m3 for CDF matching to 0.0678 m3/m3 for the proposed ensemble approach. In Niger, the RMSEs decreased from 0.14 m3/m3 for CDF matching to 0.045 m3/m3 for the ensemble approach.

  20. Soil moisture data for the validation of permafrost models using direct and indirect measurement approaches at three alpine sites

    Directory of Open Access Journals (Sweden)

    Cécile ePellet

    2016-01-01

    Full Text Available In regions affected by seasonal and permanently frozen conditions soil moisture influences the thermal regime of the ground as well as its ice content, which is one of the main factors controlling the sensitivity of mountain permafrost to climate changes. In this study, several well established soil moisture monitoring techniques were combined with data from geophysical measurements to assess the spatial distribution and temporal evolution of soil moisture at three high elevation sites with different ground properties and thermal regimes. The observed temporal evolution of measured soil moisture is characteristic for sites with seasonal freeze/thaw cycles and consistent with the respective site-specific properties, demonstrating the general applicability of continuous monitoring of soil moisture at high elevation areas. The obtained soil moisture data were then used for the calibration and validation of two different model approaches in permafrost research in order to characterize the lateral and vertical distribution of ice content in the ground. Calibration of the geophysically based four-phase model (4PM with spatially distributed soil moisture data yielded satisfactory two dimensional distributions of water-, ice- and air content. Similarly, soil moisture time series significantly improved the calibration of the one-dimensional heat and mass transfer model COUP, yielding physically consistent soil moisture and temperature data matching observations at different depths.

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

    Science.gov (United States)

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

    2017-04-01

    optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.

  2. Monitoring soil moisture through assimilation of active microwave remote sensing observation into a hydrologic model

    Science.gov (United States)

    Liu, Qian; Zhao, Yingshi

    2015-08-01

    Soil moisture can be estimated from point measurements, hydrologic models, and remote sensing. Many researches indicated that the most promising approach for soil moisture is the integration of remote sensing surface soil moisture data and computational modeling. Although many researches were conducted using passive microwave remote sensing data in soil moisture assimilation with coarse spatial resolution, few researches were carried out using active microwave remote sensing observation. This research developed and tested an operational approach of assimilation for soil moisture prediction using active microwave remote sensing data ASAR (Advanced Synthetic Aperture Radar) in Heihe Watershed. The assimilation was based on ensemble Kalman filter (EnKF), a forward radiative transfer model and the Distributed Hydrology Soil Vegetation Model (DHSVM). The forward radiative transfer model, as a semi-empirical backscattering model, was used to eliminate the effect of surface roughness and vegetation cover on the backscatter coefficient. The impact of topography on soil water movement and the vertical and lateral exchange of soil water were considered. We conducted experiments to assimilate active microwave remote sensing data (ASAR) observation into a hydrologic model at two field sites, which had different underlying conditions. The soil moisture ground-truth data were collected through the field Time Domain Reflectometry (TDR) tools, and were used to assess the assimilation method. The temporal evolution of soil moisture measured at point-based monitoring locations were compared with EnKF based model predictions. The results indicated that the estimate of soil moisture was improved through assimilation with ASAR observation and the soil moisture based on data assimilation can be monitored in moderate spatial resolution.

  3. Estimating runoff and soil moisture deficit in guinea savannah region ...

    African Journals Online (AJOL)

    Estimating runoff and soil moisture deficit in guinea savannah region of Nigeria using water balance method. ... The estimation ofrunoff and soil moisture deficit in Guinea Savannah region using semi arid model based on soil water balance technique (SAMBA) was carried out. The input to the SAMBA model are daily rainfall ...

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

    Science.gov (United States)

    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

  5. A simulation test of the impact on soil moisture by agricultural ...

    African Journals Online (AJOL)

    To study the impact by agricultural machinery on changes in soil moisture, we used a simulated test method employing round iron plate based on the ground pressure ratio between the front and rear wheels of wheeled tractors and crawler tractors. We conducted soil compactions with five pressure loads (35, 98, 118, 196 ...

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

    Science.gov (United States)

    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

  7. Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images

    Directory of Open Access Journals (Sweden)

    Azza Gorrab

    2015-08-01

    Full Text Available The aim of this paper is to propose a methodology combing multi-temporal X-band SAR images (TerraSAR-X with continuous ground thetaprobe measurements, for the retrieval of surface soil moisture and texture at a high spatial resolution. Our analysis is based on seven radar images acquired at a 36° incidence angle in the HH polarization, over a semi-arid site in Tunisia (North Africa. The soil moisture estimations are based on an empirical change detection approach using TerraSAR-X data and ground auxiliary thetaprobe network measurements. Two assumptions were tested: (1 roughness variations during the three-month radar acquisition campaigns were not accounted for; (2 a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. By considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. Maps of soil moisture, clay and sand percentages at the studied site are derived.

  8. Drought monitoring with soil moisture active passive (SMAP) measurements

    Science.gov (United States)

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

    2017-09-01

    Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an

  9. Calibration of Soil Moisture Measurement Using Pr2 Moisture Meter and Gravimetric-Based Approaches

    Directory of Open Access Journals (Sweden)

    Olotu Yahaya

    2016-10-01

    Full Text Available The research study strongly focused on creating strong mechanism for measuring and evaluating soil moisture content comparing PR2 capacitance moisture meter and gravimetric approach. PR2 moisture meter shows a better performance accuracy of ± 6%; 0.06 m 3 /m 3 and intercept a0 =1.8; indicating the field is heavy clay. It measures to 1000 mm depth with high precision; while realistic result could not be obtained from gravimetric method at this measuring depth. Therefore, effective soil moisture measuring, monitoring and evaluation can be achieved with PR2 moisture meter.

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

    Science.gov (United States)

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

    2017-05-01

    This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

  11. Soil moisture calibration of TDR multilevel probes

    Directory of Open Access Journals (Sweden)

    Serrarens Daniel

    2000-01-01

    Full Text Available Time domain reflectometry (TDR probes are increasingly used for field estimation of soil water content. The objective of this study was to evaluate the accuracy of the multilevel TDR probe under field conditions. For this purpose, eight such TDR probes were installed in small plots that were seeded with beans and sorghum. Data collection from the probes was such that soil moisture readings were automated and logged using a standalone field unit. Neutron probe measurements were used to calibrate the TDR probes. Soil-probe contact and soil compaction were critical to the accuracy of the TDR, especially when a number of TDR probes are combined for a single calibration curve. If each probe is calibrated individually, approximate measurement errors were between 0.005 and 0.015 m³ m-3. However, measurement errors doubled to approximately 0.025 to 0.03 m³ m-3, when TDR probes were combined to yield a single calibration curve.

  12. Assessment of Errors in AMSR-E Derived Soil Moisture

    Science.gov (United States)

    Champagne, C.; McNairn, H.; Berg, A.; de Jeu, R. A.

    2009-05-01

    Soil moisture derived from passive microwave satellites provides information at a coarse spatial scale, but with temporally frequent, global coverage that can be used for monitoring applications over agricultural regions. Passive microwave satellites measure surface brightness temperature, which is largely a function of vegetation water content (which is directly related to the vegetation optical depth), surface temperature and surface soil moisture at low frequencies. Retrieval algorithms for global soil moisture data sets by necessity require limited site-specific information to derive these parameters, and as such may show variations in local accuracy. The objective of this study is to examine the errors in passive microwave soil moisture data over agricultural sites in Canada to provide guidelines on data quality assessment for using these data sets in monitoring applications. Global gridded soil moisture was acquired from the AMSR-E satellite using the Land Parameter Retrieval Model, LPRM (Owe et al., 2008). The LPRM model derives surface soil moisture through an iterative optimization procedure using a polarization difference index to estimate vegetation optical depth and surface dielectric constant using frequencies at 6.9 and 10.7 GHz. The LPRM model requires no a-priori information on surface conditions, but retrieval errors are expected to increase as the amount of open water and dense vegetation within each pixel increases (Owe et al., 2008) Satellite-derived LPRM soil moisture values were used to assess changes in soil moisture retrieval accuracy over the 2007 growing season for a largely agricultural site near Guelph (Ontario), Canada. Accuracy was determined by validating LPRM soil moisture against a network of 16 in-situ monitoring sites distributed at the pixel scale for AMSR-E. Changes in squared error, and pairwise correlation coefficient between satellite and in-situ surface soil moisture were assessed against changes in satellite orbit and

  13. NASA's Soil Moisture Active and Passive (SMAP) Mission

    Science.gov (United States)

    Kellogg, Kent; Njoku, Eni; Thurman, Sam; Edelstein, Wendy; Jai, Ben; Spencer, Mike; Chen, Gun-Shing; Entekhabi, Dara; O'Neill, Peggy; Piepmeier, Jeffrey; hide

    2010-01-01

    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 Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the

  14. Validation of SMOS Satellite Soil Moisture Products over Tropical Region

    Science.gov (United States)

    Kanniah, Kasturi; Siang, Kang Chuen

    2016-07-01

    Calibration and validation (cal/val) activities on Soil Moisture and Ocean Salinity (SMOS) satellite derived soil moisture products has been conducted worldwide since the data has become available but not over the tropical region . This study focuses on the installation of a soil moisture data collection network over an agricultural site in a tropical region in Peninsular Malaysia, and the validation of SMOS soil moisture products. The in-situ data over one year period was analysed and validation of SMOS Soil Moisture products with these in-situ data was conducted.Bias and root mean square errors (RMSE) were computed between SMOS soil moisture products and the in-situ surface soil moisture collected at the satellite passing time (6 am and 6 pm local time). Due to the known limitations of SMOS soil moisture retrieval over vegetated areas with vegetation water content higher than 5 kgm-2, overestimation of SMOS soil moisture products to in-situ data was noticed in this study. The bias is ranging from 0.064 to 0.119 m3m-3 and the RMSE is from 0.090 to 0.158 m3m-3, when both ascending and descending data were validated. This RMSE was found to be similar to a number of studies conducted previously at different regions. However a wet bias was found during the validation, while previous validation activities at other regions showed dry biases. The result of this study is useful to support the continuous development and improvement of SMOS soil moisture retrieval model, aims to produce soil moisture products with higher accuracy, especially in the tropical region.

  15. Divergent surface and total soil moisture projections under global warming

    Science.gov (United States)

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

    2017-01-01

    Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

  16. Effect of soil moisture on trace elements concentrations using

    African Journals Online (AJOL)

    H. Sahraoui and M. Hachicha

    2017-01-01

    Jan 1, 2017 ... produced by the water influence moisture content and corrected ... Previous studies indicated that PXRF analysis was capable of detecting soil trace elements ..... determination of some heavy metals in soil using an x-ray ...

  17. Evaluation of Simplified Polarimetric Decomposition for Soil Moisture Retrieval over Vegetated Agricultural Fields

    Directory of Open Access Journals (Sweden)

    Hongquan Wang

    2016-02-01

    Full Text Available This paper investigates a simplified polarimetric decomposition for soil moisture retrieval over agricultural fields. In order to overcome the coherent superposition of the backscattering contributions from vegetation and underlying soils, a simplification of an existing polarimetric decomposition is proposed in this study. It aims to retrieve the soil moisture by using only the surface scattering component, once the volume scattering contribution is removed. Evaluation of the proposed simplified algorithm is performed using extensive ground measurements of soil and vegetation characteristics and the time series of UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar data collected in the framework of SMAP (Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12. The retrieval process is tested and analyzed in detail for a variety of crops during the phenological stages considered in this study. The results show that the performance of soil moisture retrieval depends on both the crop types and the crop phenological stage. Soybean and pasture fields present the higher inversion rate during the considered phenological stage, while over canola and wheat fields, the soil moisture can be retrieved only partially during the crop developing stage. RMSE of 0.06–0.12 m3/m3 and an inversion rate of 26%–38% are obtained for the soil moisture retrieval based on the simplified polarimetric decomposition.

  18. ELBARA II, an L-band radiometer system for soil moisture research.

    Science.gov (United States)

    Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

    2010-01-01

    L-band (1-2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user.

  19. The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

    Science.gov (United States)

    Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

    2014-01-01

    Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

  20. The Effect of Row Structure on Soil Moisture Retrieval Accuracy from Passive Microwave Data

    Directory of Open Access Journals (Sweden)

    Zheng Xingming

    2014-01-01

    Full Text Available Row structure causes the anisotropy of microwave brightness temperature (TB of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Qp model and discrete model, including the effect of row structure, and flat rough surface assumption (Qp model, ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm3/cm3 better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm3/cm3 better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

  1. Assimilating soil moisture into an Earth System Model

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan

    2017-04-01

    Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern

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

    Science.gov (United States)

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

    2014-05-01

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

  3. Soil moisture and groundwater recharge under a mixed conifer forest

    Science.gov (United States)

    Robert R. Ziemer

    1978-01-01

    The depletion of soil moisture within the surface 7 m by a mixed conifer forest in the Sierra Nevada was measured by the neutron method every 2 weeks during 5 consecutive summers. Soil moisture recharge was measured periodically during the intervening winters. Groundwater fluctuations within the surface 17 m were continuously recorded during the same period.

  4. Variability of soil moisture and its relationship with surface albedo ...

    Indian Academy of Sciences (India)

    Continuous observation data collected over the year 2008 at Astronomical Observatory, Thiruvananthapuram in south Kerala (76° 59′E longitude and 8° 30′N latitude) are used to study the diurnal, monthly and seasonal soil moisture variations. The effect of rainfall on diurnal and seasonal soil moisture is discussed.

  5. ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns

    Science.gov (United States)

    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...

  6. The global distribution and dynamics of surface soil moisture

    Science.gov (United States)

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

    2017-01-01

    Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

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

    Science.gov (United States)

    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 ...

  8. Feasibility of soil moisture estimation using passive distributed temperature sensing

    NARCIS (Netherlands)

    Steele-Dunne, S.C.; Rutten, M.M.; Krzeminska, D.M.; Hausner, M.; Tyler, S.W.; Selker, J.; Bogaard, T.A.; Van de Giesen, N.C.

    2010-01-01

    Through its role in the energy and water balances at the land surface, soil moisture is a key state variable in surface hydrology and land?atmosphere interactions. Point observations of soil moisture are easy to make using established methods such as time domain reflectometry and gravimetric

  9. Soil moisture remote sensing: State of the science

    Science.gov (United States)

    Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac...

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

    Science.gov (United States)

    James Reardon; Gary Curcio; Roberta Bartlette

    2009-01-01

    Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...

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

    Science.gov (United States)

    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

  12. COSMOS: the COsmic-ray Soil Moisture Observing System

    Directory of Open Access Journals (Sweden)

    M. Zreda

    2012-11-01

    Full Text Available The newly-developed cosmic-ray method for measuring area-average soil moisture at the hectometer horizontal scale is being implemented in the COsmic-ray Soil Moisture Observing System (or the COSMOS. The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the eventual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COSMOS project, and give example time series of soil moisture obtained from COSMOS probes.

  13. On the Synergy of Airborne GNSS-R and Landsat 8 for Soil Moisture Estimation

    Directory of Open Access Journals (Sweden)

    Nilda Sánchez

    2015-08-01

    Full Text Available While the synergy between thermal, optical, and passive microwave observations is well known for the estimation of soil moisture and vegetation parameters, the use of remote sensing sources based on the Global Navigation Satellite Systems (GNSS remains unexplored. During an airborne campaign performed in August 2014, over an agricultural area in the Duero basin (Spain, an innovative sensor developed by the Universitat Politècnica de Catalunya-Barcelona Tech based on GNSS Reflectometry (GNSS-R was tested for soil moisture estimation. The objective was to evaluate the combined use of GNSS-R observations with a time-collocated Landsat 8 image for soil moisture retrieval under semi-arid climate conditions. As a ground reference dataset, an intensive field campaign was carried out. The Light Airborne Reflectometer for GNSS-R Observations (LARGO observations, together with optical, infrared, and thermal bands from Landsat 8, were linked through a semi-empirical model to field soil moisture. Different combinations of vegetation and water indices with LARGO subsets were tested and compared to the in situ measurements. Results showed that the joint use of GNSS-R reflectivity, water/vegetation indices and thermal maps from Landsat 8 not only allows capturing soil moisture spatial gradients under very dry soil conditions, but also holds great promise for accurate soil moisture estimation (correlation coefficients greater than 0.5 were obtained from comparison with in situ data.

  14. Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula

    Science.gov (United States)

    Cho, Eunsang; Choi, Minha

    2014-08-01

    An understanding soil moisture spatio-temporal variability is essential for hydrological and meteorological research. This work aims at evaluating the spatio-temporal variability of near surface soil moisture and assessing dominant meteorological factors that influence spatial variability over the Korean peninsula from May 1 to September 29, 2011. The results of Kolmogorov-Smirnov tests for goodness of fit showed that all applied distributions (normal, log-normal and generalized extreme value: GEV) were appropriate for the datasets and the GEV distribution described best spatial soil moisture patterns. The relationship between the standard deviation and coefficient of variation (CV) of soil moisture with mean soil moisture contents showed an upper convex shape and an exponentially negative pattern, respectively. Skewness exhibited a decreasing pattern with increasing mean soil moisture contents and kurtosis exhibited the U-shaped relationship. In this regional scale (99,720 km2), we found that precipitation indicated temporally stable features through an ANOVA test considering the meteorological (i.e. precipitation, insolation, air temperature, ground temperature and wind speed) and physical (i.e. soil texture, elevation, topography, and land use) factors. Spatial variability of soil moisture affected by the meteorological forcing is shown as result of the relationship between the meteorological factors (precipitation, insolation, air temperature and ground temperature) and the standard deviation of relative difference of soil moisture contents (SDRDt) which implied the spatial variability of soil moisture. The SDRDt showed a positive relationship with the daily mean precipitation, while a negative relationship with insolation, air temperature and ground temperature. The variation of spatial soil moisture pattern is more sensitive to change in ground temperature rather than air temperature changes. Therefore, spatial variability of soil moisture is greatly affected

  15. Soil Moisture Memory in Karst and Non-Karst Landscapes

    Science.gov (United States)

    Sobocinski-Norton, H. E.; Dirmeyer, P.

    2016-12-01

    Underlying geology plays an important role in soil column hydrology that is largely overlooked within the land surface model (LSM) parameterizations used in weather and climate models. LSMs typically treat the soil column as a set of horizontally homogeneous layers through which liquid water diffuses. These models parameterize the flow of water out of the bottom of the active soil column as "baseflow" that is typically a function of mean surface slope and the soil moisture in the lowest model layer. However, roughly 25% of the United States is underlain by karst systems that are characterized by heavily fractured bedrock or unconsolidated materials. These heavily fractured systems allow for more rapid drainage, increasing "baseflow" and reducing the amount of soil moisture available for surface fluxes. This increased drainage can also affect soil moisture memory, which is key to determining the strength of land-atmosphere coupling. We examine lagged autocorrelations of in-situ soil moisture data from climatologically similar stations over different substrates, to determine the extent to which karst affects soil moisture memory. These results are compared to simulations with the NCEP Noah LSM with both default parameters and setting all soil types to sand to enhance drainage in a crude approximation of karst macropores. Given the importance of soil moisture in surface fluxes and in turn land-atmospheric coupling, we will demonstrate the importance of representing shallow geology as realistically as possible, and develop better parameterizations of these processes for LSMs.

  16. GNSSProbe, penetrating GNSS signals for measuring soil moisture

    Science.gov (United States)

    Martin, Francisco; Navarro, Victor; Reppucci, Antonio; Mollfulleda, Antonio; Balzter, Heiko; Nicolas-Perea, Virginia; Kissick, Lucy

    2016-04-01

    Soil moisture content (SMC) is an essential parameter from both a scientific and economical point of view. On one hand, it is key for the understanding of hydrological. Secondly, it is a most relevant parameter for agricultural activities and water management. Wide research has been done in this field using different sensors, spanning different parts of the measured electromagnetic spectrum, leading thus several methodologies to estimate soil moisture content. However complying with requirements in terms of accuracy and spatial resolution is still a major challenge. A novel approach based on the measurement of GNSS signals penetrating a soil volume is proposed here. This model relates soil moisture content to the measured soil transmissivity, and attenuation coefficient, which are a function of the soil characteristics (i.e soil moisture content, soit type, soil temperature, etc). A preliminary experiment has been performed to demonstrate the validity of this technique, where the signal received by a GNSS-R L1/E1 RHCP antenna buried at 5, 10, and 15 cm below the surface, was compared to the one received by a GNSS-R L1/E1 RHCP antenna with clear sky visibility. Preliminary results show agreement with theoretical results based on transmissivity and with previous campaigns performed where the soil moisture were collected at two different depths (5 and 15 cm). Details related to the GNSS soil moisture modeling, instrument preparation, measurement campaign, data processing and main results will be presented at the conference.

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

    Science.gov (United States)

    Fang, Bin

    -band hh-polarization radar spatial resolutions of 1500 m and 5 m/800 m, respectively. All three algorithms were validated using ground measurements from network in situ stations or handheld hydra probes. The validation results demonstrate the practicability on coarse resolution passive microwave soil moisture products.

  18. Validation of SMAP soil moisture over a complex agricultural catchment in Austria

    Science.gov (United States)

    Pfeil, Isabella Maria; Vreugdenhil, Mariette; Strauss, Peter; Oismueller, Markus; Wagner, Wolfgang; Bloeschl, Guenter

    2017-04-01

    NASA's Soil Moisture Active Passive (SMAP) mission was launched in January 2015. After an irrecoverable failure of the radar, the remaining passive L-band radiometer is now providing soil moisture in the upper layer of the soil as well as freeze-thaw state every 2-3 days on a 36 km Earth-fixed grid. The first aim of this work is to validate SMAP soil moisture data against in situ ground measurements from the soil moisture network at the Hydrological Open Air Laboratory in Petzenkirchen (Lower Austria), which was installed in 2013. A heterogeneous agricultural catchment, the HOAL is characteristic for a range of catchments around the world. The network consists of 20 permanent and 11 temporary soil moisture stations distributed over an area of 66 ha. The challenge is to find a suitable combination of the in situ stations to represent the SMAP footprint. Therefore, additional sensors were installed outside of the catchment to facilitate upscaling of the in situ data to the scale of SMAP. A validation at a similar spatial scale is performed using soil moisture data from the Advanced Scatterometer (ASCAT) on-board the Metop satellites and AMSR2 on-board GCOM-W1, respectively. Results show strong correspondence (Pearson R > 0.5) between SMAP and in situ and satellite soil moisture datasets. This investigation follows the work by Chan et al. (2016), using longer time series and validation data from a not yet investigated ground truthing site, and will help assess the performance of the SMAP mission.

  19. A technique to determine the electromagnetic properties of soil using moisture content

    Directory of Open Access Journals (Sweden)

    Petrus J. Coetzee

    2014-05-01

    Full Text Available Accurate electromagnetic ground constants are required for applications such as modelling of ground wave propagation of radio signals and antennas above a real, imperfect earth and for use in geological surveys and agricultural applications. A simple method to determine the ground parameters (conductivity and relative dielectric constant for any radio frequency is outlined here. The method has been verified over the 2-30-MHz frequency range but should be applicable up to several GHz. First, a low cost, commercial soil moisture meter using time domain reflectometry techniques is used to determine the soil moisture percentage. Then previously published universal soil models implemented on a programmable calculator or a PC are used to calculate the required constants at the frequency of interest according to the measured moisture percentage. The results obtained by this method compare favourably with those obtained by the input impedance of a low horizontal dipole technique. The received signal strength of a ground wave, HF transmission also compares favourably with that predicted by GRWave using ground constants calculated by the soil moisture technique. This method offers significant advantages in terms of simplicity, speed and cost when compared with current techniques.

  20. SMEX02 Watershed Vitel Network Soil Moisture Data, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains several parameters measured for the Soil Moisture Experiment 2002 (SMEX02). The parameters include soil moisture, temperature, conductivity,...

  1. Radar-guided radiometer downscaling for combined soil moisture retrieval

    Science.gov (United States)

    Stampoulis, D.; Haddad, Z. S.; Anagnostou, E. N.

    2013-12-01

    of its variety of land classes and the availability of ground-based validation soil moisture data. Is there a correlation between radar backscatter and emissivity values?

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

    Science.gov (United States)

    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

  3. SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

    Science.gov (United States)

    Fang, B.; Lakshmi, V.

    2016-12-01

    Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

  4. Response of grassland ecosystems to prolonged soil moisture deficit

    Science.gov (United States)

    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

  5. Variability in Soil Moisture in a Temperate Deciduous Forest Using Electrical Resistivity and Throughfall Data

    Science.gov (United States)

    Ma, Y.; Van Dam, R. L.; Jayawickreme, D.

    2013-12-01

    In deciduous forests, soil moisture is an important driver of energy and carbon cycling, as well as ecosystem dynamics. The amount and distribution of soil moisture also influences soil microbial activity, nutrient fluxes, and groundwater recharge. Consequently, accurate characterization of interactions and interdependencies between vegetation and soil moisture is critical to forecast water resources and ecosystem health in a changing climate. Such relationships and processes are nevertheless difficult to measure, both in time and space because of our limited ability to monitor the subsurface at necessary scales and frequencies. Several recent studies have shown that electrical resistivity tomography (ERT), using an array of minimally invasive surface electrodes, is a promising method for in-situ soil moisture monitoring. To this point, however, only few studies have used ERT to investigate spatial variability of soil moisture in temperate deciduous forests and to explore any links between soil water and above ground ecosystem variables. In our study in a central Michigan (USA) maple forest during the 2012 growing season, we combined ERT with detailed vegetation surveys and throughfall measurements to obtain better insight into spatial variations in rainwater input and soil water patterns. Resistivity data were collected on a weekly basis along an array of 84 electrodes with a spacing of 1.5 m. The inversion results were temperature corrected, converted to soil moisture, and differenced to obtain 2D images of soil moisture changes. The throughfall data were obtained using a novel method based on dissolution of plaster-of-paris tablets that were positioned below funnels, at 19 locations in the forest. Our results show that: 1) resistivity changes spatially with vegetation distribution, 2) in-season temporal changes in resistivity are related to plant characteristics, in particular to tree count and basal area, and 3) our low-budget throughfall method was capable of

  6. The Murrumbidgee soil moisture monitoring network data set

    Science.gov (United States)

    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.

    2012-07-01

    This paper describes a soil moisture data set from the 82,000 km2 Murrumbidgee River Catchment in southern New South Wales, Australia. Data have been archived from the Murrumbidgee Soil Moisture Monitoring Network (MSMMN) since its inception in September 2001. The Murrumbidgee Catchment represents a range of conditions typical of much of temperate Australia, with climate ranging from semiarid to humid and land use including dry land and irrigated agriculture, remnant native vegetation, and urban areas. There are a total of 38 soil moisture-monitoring sites across the Murrumbidgee Catchment, with a concentration of sites in three subareas. The data set is composed of 0-5 (or 0-8), 0-30, 30-60, and 60-90 cm average soil moisture, soil temperature, precipitation, and other land surface model forcing at all sites, together with other ancillary data. These data are available on the World Wide Web at http://www.oznet.org.au.

  7. Soil moisture sensor calibration for organic soil surface layers

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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; hide

    2009-01-01

    The Soil Moisture Active and Passive (SMAP) Mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy and carbon transfers between land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP soil moisture and freeze/thaw timing observations will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept would utilize an L-band radar and radiometer. These instruments will share a rotating 6-meter mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. The SMAP instruments provide direct measurements of surface conditions. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and estimates of land surface-atmosphere exchanges of water, energy and carbon. SMAP is scheduled for a 2014 launch date

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

    Science.gov (United States)

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

    2015-12-01

    Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

  10. Core vs. Bulk Samples in Soil-Moisture Tension Analyses

    Science.gov (United States)

    Walter M. Broadfoot

    1954-01-01

    The usual laboratory procedure in determining soil-moisture tension values is to use "undisturbed" soil cores for tensions up to 60 cm. of water and bulk soil samples for higher tensions. Low tensions are usually obtained with a tension table and the higher tensions by use of pressure plate apparatus. In tension analysis at the Vicksburg Infiltration Project...

  11. Variability of soil moisture and its relationship with surface albedo ...

    Indian Academy of Sciences (India)

    α. Surface albedo. Su. Reflected solar radiation (W/m. 2. ) Sd. Total downward solar radiation. (W/m. 2. ) T. Soil temperature (. ◦. C) k. Soil thermal diffusivity (m. 2 s. −1. ) ... Soil moisture; rainfall; surface albedo; solar elevation angle; thermal diffusivity; atmospheric sciences; ... the diurnal, monthly and seasonal variations of.

  12. Estimation of Soil Moisture for Vegetated Surfaces Using Multi-Temporal L-Band SAR Measurements

    Science.gov (United States)

    Shi, Jian-Cheng; Sun, G.; Hsu, A.; Wang, J.; ONeill, P.; Ranson, J.; Engman, E. T.

    1997-01-01

    This paper demonstrates the technique to estimate ground surface and vegetation scattering components, based on the backscattering model and the radar decomposition theory, under configuration of multi-temporal L-band polarimetric SAR measurement. This technique can be used to estimate soil moisture of vegetated surface.

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

    Science.gov (United States)

    Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.

    2017-01-01

    The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The

  14. Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

    Science.gov (United States)

    Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

    2017-04-01

    The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE soil and terrain information is necessary when using this method. The stratified sampling strategy can only be used if no pre-knowledge about soil moisture variation is available. This information will help in selecting the optimal methods for estimation the area mean soil moisture.

  15. A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

    Science.gov (United States)

    Capecchi, V.; Gozzini, B.

    2012-04-01

    The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently

  16. Surface sealing effect on validation of remotely sensed soil moisture predictions

    Science.gov (United States)

    Sela, Shai; Svoray, Tal; Assouline, Shmuel

    2013-04-01

    Recent advances in remote sensing technologies have led spaceborn platforms to emerge as successful tools in studying and monitoring soil moisture dynamics. A common need for all remote sensing missions is intensive ground soil moisture samplings for validating predictions and the calibration of retrieval algorithms usually conducted using a network of soil moisture probes. These probes generally have a minimal size of approximately 5 cm, due to technical limits. When these probes are used for validation at the top soil layer, the validation depth is deeper than the sensor effective penetration depth generally of 0-3 cm, a bias which can affect validation results. In dryland areas, where physical sealing of the soil is a wide spread phenomenon, validation can be even more complex. The seal layer has different hydraulic parameters than the underlying soil, with a much lower hydraulic conductivity that affect both infiltration and evaporation fluxes. The seal layer effective depth was found to be 2 cm or more, depending on soil type and initial conditions at formation. Therefore, the sensor effective penetration depth lies within the seal layer, while the soil moisture probe used for validation is averaging soil moisture reading of both the seal and the underneath soil layers. Whether this can lead to a bias in validation is still an open research gap. To address this gap, a physically-based model was used to simulate synthetic soil moisture dynamics at a single soil profile. The seal layer was assumed to have a 2 cm thickness and was integrated into the model using the Mualem and Assouline (1989) model. The results indicate a significant difference between soil moisture values of the 0-2 and 0-5 cm soil depth intervals under unsealed conditions, with a strong signal of diurnal effect. This effect was found to be highly supressed when the presence of the seal layer is accounted for. Stepwise regression between hourly soil moisture values in the profile and

  17. response of three forage legumes to soil moisture stress

    African Journals Online (AJOL)

    MR PRINCE

    The mean P content of the plants decreased with decreasing soil moisture content while, that of K increased as moisture stress increased. The overall plant performance pointed to Centrosema as a more favoured for- age plant for dry environments . Keywords: Crop productivity, legumes, food security, water use efficiency.

  18. Response Of Three Forage Legumes To Soil Moisture Stress ...

    African Journals Online (AJOL)

    The mean P content of the plants decreased with decreasing soil moisture content while, that of K increased as moisture stress increased. The overall plant performance pointed to Centrosema as a more favoured for-age plant for dry environments . Keywords: Crop productivity, legumes, food security, water use efficiency ...

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

    Science.gov (United States)

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

    2011-01-01

    ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

  20. Soil and Moisture Conservation Program Report Fiscal Year 1969

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This report summarizes the progress of the soil and moisture conservation program for Pungo National Wildlife Refuge for fiscal year 1969. Surveys and maps are...

  1. Soil Moisture for Western Russia and The Ukraine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset, DSI-6411 is comprised of soil moisture data and the accompanying information for the agricultural regions of Western Russia (west of ~ 60E) and The...

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

    Science.gov (United States)

    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.

  3. Site Averaged Gravimetric Soil Moisture: 1987-1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  4. Site Averaged Gravimetric Soil Moisture: 1987-1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  5. SMEX02 Watershed Soil Moisture Data, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set combines data for several parameters measured for the Soil Moisture Experiment 2002 (SMEX02). The parameters include bulk density, gravimetric and...

  6. SMAPVEX12 PALS Soil Moisture Data V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains soil moisture data obtained by the Passive Active L-band System (PALS) aircraft instrument. The data were collected as part of SMAPVEX12, the...

  7. SMAP Level 4 Surface and Root Zone Soil Moisture

    Science.gov (United States)

    Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R.

    2017-01-01

    The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

  8. Aquarius L2 Swath Single Orbit Soil Moisture V004

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains Level-2 global soil moisture estimates derived from the NASA Aquarius passive microwave radiometer on the Satélite de Aplicaciones Científicas...

  9. A comparison of soil moisture relations between standing and ...

    African Journals Online (AJOL)

    A comparison of soil moisture relations between standing and clearfelled plots with burnt and unburnt harvest residue treatments of a clonal eucalypt plantation on the Zululand Coastal Plain, South Africa.

  10. Special soil & moisture report : Quivira National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This report is a summary of 18 months of soil and moisture work accomplished on the 7,000 acres of land purchased for Quivira National Wildlife Refuge to date...

  11. Uncertainty of Deardorff’s soil moisture model based on continuous TDR measurements for sandy loam soil

    Directory of Open Access Journals (Sweden)

    Brandyk Andrzej

    2016-03-01

    Full Text Available Knowledge on soil moisture is indispensable for a range of hydrological models, since it exerts a considerable influence on runoff conditions. Proper tools are nowadays applied in order to gain in-sight into soil moisture status, especially of uppermost soil layers, which are prone to weather changes and land use practices. In order to establish relationships between meteorological conditions and topsoil moisture, a simple model would be required, characterized by low computational effort, simple structure and low number of identified and calibrated parameters. We demonstrated, that existing model for shallow soils, considering mass exchange between two layers (the upper and the lower, as well as with the atmosphere and subsoil, worked well for sandy loam with deep ground water table in Warsaw conurbation. GLUE (Generalized Likelihood Uncertainty Estimation linked with GSA (Global Sensitivity Analysis provided for final determination of parameter values and model confidence ranges. Including the uncertainty in a model structure, caused that the median soil moisture solution of the GLUE was shifted from the one optimal in deterministic sense. From the point of view of practical model application, the main shortcoming were the underestimated water exchange rates between the lower soil layer (ranging from the depth of 0.1 to 0.2 m below ground level and subsoil. General model quality was found to be satisfactory and promising for its utilization for establishing measures to regain retention in urbanized conditions.

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

    Science.gov (United States)

    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

  13. Soil moisture content estimation from passive temperature measurements

    Science.gov (United States)

    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.

  14. Analysis of a Least-Squares Soil Moisture Retrieval Algorithm from L-band Passive Observations

    Directory of Open Access Journals (Sweden)

    Alessandra Monerris

    2010-01-01

    Full Text Available The Soil Moisture and Ocean Salinity (SMOS mission of the European Space Agency (ESA, launched on November 2009, is an unprecedented initiative to globally monitor surface soil moisture using a novel 2-D L-band interferometric radiometer concept. Airborne campaigns and ground-based field experiments have proven that radiometers operating at L-band are highly sensitive to soil moisture, due to the large contrast between the dielectric constant of soil minerals and water. Still, soil moisture inversion from passive microwave observations is complex, since the microwave emission from soils depends strongly on its moisture content but also on other surface characteristics such as soil type, soil roughness, surface temperature and vegetation cover, and their contributions must be carefully de-coupled in the retrieval process. In the present study, different soil moisture retrieval configurations are examined, depending on whether prior information is used in the inversion process or not. Retrievals are formulated in terms of vertical (Tvv and horizontal (Thh polarizations separately and using the first Stokes parameter (TI , over six main surface conditions combining dry, moist and wet soils with bare and vegetation-covered surfaces. A sensitivity analysis illustrates the influence that the geophysical variables dominating the Earth’s emission at L-band have on the precision of the retrievals, for each configuration. It shows that, if adequate constraints on the ancillary data are added, the algorithm should converge to more accurate estimations. SMOS-like brightness temperatures are also generated by the SMOS End-to-end Performance Simulator (SEPS to assess the retrieval errors produced by the different cost function configurations. Better soil moisture retrievals are obtained when the inversion is constrained with prior information, in line with the sensitivity study, and more robust estimates are obtained using TI than using Tvv and Thh. This

  15. An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2009-02-01

    Full Text Available A long term data acquisition effort of profile soil moisture is currently underway at 13 automatic weather stations located in Southwestern France. In this study, the soil moisture measured in-situ at 5 cm is used to evaluate the normalised surface soil moisture (SSM estimates derived from coarse-resolution (25 km active microwave data of the ASCAT scatterometer instrument (onboard METOP, issued by EUMETSAT for a period of 6 months (April–September in 2007. The seasonal trend is removed from the satellite and in-situ time series by considering scaled anomalies. One station (Mouthoumet of the ground network, located in a mountainous area, is removed from the analysis as very few ASCAT SSM estimates are available. No correlation is found for the station of Narbonne, which is close to the Mediterranean sea. On the other hand, nine stations present significant correlation levels. For two stations, a significant correlation is obtained when considering only part of the ASCAT data. The soil moisture measured in-situ at those stations, at 30 cm, is used to estimate the characteristic time length (T of an exponential filter applied to the ASCAT product. The best correlation between a soil water index derived from ASCAT and the in-situ soil moisture observations at 30 cm is obtained with a T-value of 14 days.

  16. An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France

    Science.gov (United States)

    Albergel, C.; Rüdiger, C.; Carrer, D.; Calvet, J.-C.; Fritz, N.; Naeimi, V.; Bartalis, Z.; Hasenauer, S.

    2009-02-01

    A long term data acquisition effort of profile soil moisture is currently underway at 13 automatic weather stations located in Southwestern France. In this study, the soil moisture measured in-situ at 5 cm is used to evaluate the normalised surface soil moisture (SSM) estimates derived from coarse-resolution (25 km) active microwave data of the ASCAT scatterometer instrument (onboard METOP), issued by EUMETSAT for a period of 6 months (April-September) in 2007. The seasonal trend is removed from the satellite and in-situ time series by considering scaled anomalies. One station (Mouthoumet) of the ground network, located in a mountainous area, is removed from the analysis as very few ASCAT SSM estimates are available. No correlation is found for the station of Narbonne, which is close to the Mediterranean sea. On the other hand, nine stations present significant correlation levels. For two stations, a significant correlation is obtained when considering only part of the ASCAT data. The soil moisture measured in-situ at those stations, at 30 cm, is used to estimate the characteristic time length (T) of an exponential filter applied to the ASCAT product. The best correlation between a soil water index derived from ASCAT and the in-situ soil moisture observations at 30 cm is obtained with a T-value of 14 days.

  17. Surface temperature and soil moisture retrieval in the Sahel from airborne multifrequency microwave radiometry

    Energy Technology Data Exchange (ETDEWEB)

    Calvet, J.C. [Meteo-France/CNRM, Toulouse (France); Chanzy, A.; Wigneron, J.P. [Inst. National de la Recherche Agronomique, Avignon (France)

    1996-03-01

    Bipolarized microwave brightness temperatures of Sahel semiarid landscapes are analyzed at two frequencies: 5.05 and 36.5 GHz. These measurements were performed in Niger, West Africa, by the radiometer PORTOS in the framework of the Hydrologic Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), during the end of the rainy season (August--September 1992). The airborne microwave data were collected simultaneously with radiosoundings of the atmosphere, and ground measurements of surface temperature, soil moisture, and biomass of several vegetation types. After estimating the soil roughness parameters, it is shown that two kinds of vegetation canopies must be considered: sparse canopies and patchy canopies including bare soil strips. The mixed soil vegetation microwave emission is analyzed using a random continuous approach. The sparse canopy emission is efficiently described by considering the vegetation layer as homogeneous. Conversely, a simple soil-vegetation mixing equation must be used for the patchy canopies. The problem with retrieving the canopy temperature and the near-surface soil moisture is addressed. For every canopy, soil moisture retrieval is possible. Soil moisture maps are proposed. The canopy temperature can also be retrieved with good accuracy provided both vertical (v) and horizontal (h) polarizations are available. It is shown that the retrieved variables can be used to separate landscape units through a classification procedure.

  18. Potential of ASCAT Soil Moisture Product to Improve Runoff Prediction

    Science.gov (United States)

    Brocca, L.; Melone, F.; Moramarco, T.; Wagner, W.; Naeimi, V.; Bartalis, Z.; Hasenauer, S.

    2009-11-01

    The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale) with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates have to be carefully checked. Therefore, the assessment of the effects of assimilating satellite- derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue. In this context, the soil wetness index (SWI) product derived from the Advanced Scatterometer (ASCAT) sensor was tested in this study. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc). Then, by using a simple data assimilation technique, the SWI was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place.The most significant flood events, which occurred in the period 2000-2009 for five subcatchments of the Upper Tiber River in central Italy, ranging in extension between 100 and 650 km2, were used as case studies. Results reveal that the SWI derived from the ASCAT sensor can be conveniently used to improve runoff prediction in the study area, mainly if the initial soil wetness conditions are unknown.

  19. Predicting root zone soil moisture using surface data

    Science.gov (United States)

    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

  20. Soil Moisture Estimate Under Forest Using a Semi-Empirical Model at P-Band

    Science.gov (United States)

    Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

    2013-01-01

    Here we present the result of a semi-empirical inversion model for soil moisture retrieval using the three backscattering coefficients: sigma(sub HH), sigma(sub VV) and sigma(sub HV). In this paper we focus on the soil moisture estimate and use the biomass as an ancillary parameter estimated automatically from the algorithm and used as a validation parameter, We will first remind the model analytical formulation. Then we will sow some results obtained with real SAR data and compare them to ground estimates.

  1. Soil nutrient content, soil moisture and yield of Katumani maize in a ...

    African Journals Online (AJOL)

    This study investigated soil parameters and their influence on yield. It was carried out at the University of Nairobi's Dryland, Research and Utilisation Station located at Kibwezi. Soil parameters measured included soil organic carbon, total soil nitrogen, available phosphorus, soil moisture and soil texture and nitrogen ...

  2. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    Science.gov (United States)

    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.

  3. Evaluation of random cascade hierarchical and statistical arrangement model in disaggregation of SMOS soil moisture

    Science.gov (United States)

    Hosseini, M.; Magagi, R.; Goita, K.

    2013-12-01

    Soil moisture is an important parameter in hydrology that can be derived from remote sensing. In different studies, it was shown that optical-thermal, active and passive microwave remote sensing data can be used for soil moisture estimation. However, the most promising approach to estimate soil moisture in large areas is passive microwave radiometry. Global estimation of soil moisture is now operational by using remote sensing techniques. The Advanced Microwave Scanning Radiometer-Earth Observing System Sensor (AMSR-E) and Soil Moisture and Ocean Salinity (SMOS) passive microwave radiometers that were lunched on 2002 and 2009 respectively along with the upcoming Soil Moisture Active-Passive (SMAP) satellite that was planned to be lunched in the time frame of 2014-2015 make remote sensing to be more useful in soil moisture estimation. However, the spatial resolutions of AMSR-E, SMOS and SMAP are 60 km, 40 km and 10 km respectively. These very low spatial resolutions can not show the temporal and spatial variability of soil moisture in field or small scales. So, using disaggregation methods is required to efficiently using the passive microwave derived soil moisture information in different scales. The low spatial resolutions of passive microwave satellites can be improved by using disaggregation methods. Random Cascade (RC) model (Over and Gupta, 1996) is used in this research to downscale the 40 km resolution of SMOS satellite. By using this statistical method, the SMOS soil moisture resolutions are improved to 20 km, 10 km, 5 km and 2.5 km, respectively. The data that were measured during Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) field campaign are used to do the experiments. Totally the ground data and SMOS images that were obtained during 13 different days from 7-June-2012 to 13-July-2012 are used. By comparison with ground soil moisture, it is observed that the SMOS soil moisture is underestimated for all the images and so bias amounts

  4. Soil Moisture Profile Effect on Radar Signal Measurement

    OpenAIRE

    André Chanzy; Nicolas Baghdadi; Mehrez Zribi; Aurélie Le Morvan

    2008-01-01

    The objective of this paper is to analyze the behaviour of a backscattered signal according to soil moisture depth over bare soils. Analysis based on experimental vertical moisture profiles and ASAR/ENVISAT measurements has been carried out. A modified IEM model with three permittivity layers (0-1cm, 1-2cm, 2-5cm) has been developed and used in this study. Results show a small effect of moisture profile on the backscattered signal (less than 0.5dB). However, measurements and simulations have ...

  5. Soil moisture dynamics modeling considering multi-layer root zone.

    Science.gov (United States)

    Kumar, R; Shankar, V; Jat, M K

    2013-01-01

    The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.

  6. Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

    Science.gov (United States)

    Juglea, S.; Kerr, Y.; Mialon, A.; Wigneron, J.-P.; Lopez-Baeza, E.; Cano, A.; Albitar, A.; Millan-Scheiding, C.; Antolin, M. Carmen; Delwart, S.

    2010-05-01

    The main goal of the SMOS (Soil Moisture and Ocean Salinity) mission is to deliver global fields of surface soil moisture and sea surface salinity using L-band (1.4 GHz) radiometry. Within the context of the Science preparation for SMOS, the Valencia Anchor Station (VAS) experimental site, in Spain, was chosen to be one of the main test sites in Europe for Calibration/Validation (Cal/Val) activities. In this framework, the paper presents an approach consisting in accurately simulating a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over the wide VAS surface (50×50 km2). Ground and meteorological measurements over the area are used as the input of a Soil-Vegetation-Atmosphere-Transfer (SVAT) model, SURFEX (Externalized Surface) - module ISBA (Interactions between Soil-Biosphere-Atmosphere) to simulate the spatial and temporal distribution of surface soil moisture. The calibration as well as the validation of the ISBA model are performed using in situ soil moisture measurements. It is shown that a good consistency is reached when point comparisons between simulated and in situ soil moisture measurements are made. Actually, an important challenge in remote sensing approaches concerns product validation. In order to obtain an representative soil moisture mapping over the Valencia Anchor Station (50×50 km2 area), a spatialization method is applied. For verification, a comparison between the simulated spatialized soil moisture and remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E) and from the European Remote Sensing Satellites (ERS-SCAT) is performed. Despite the fact that AMSR-E surface soil moisture product is not reproducing accurately the absolute values, it provides trustworthy information on surface soil moisture temporal variability. However, during the vegetation growing season the signal is perturbed. By using the polarization ratio a better agreement is

  7. Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

    Directory of Open Access Journals (Sweden)

    S. Juglea

    2010-05-01

    Full Text Available The main goal of the SMOS (Soil Moisture and Ocean Salinity mission is to deliver global fields of surface soil moisture and sea surface salinity using L-band (1.4 GHz radiometry. Within the context of the Science preparation for SMOS, the Valencia Anchor Station (VAS experimental site, in Spain, was chosen to be one of the main test sites in Europe for Calibration/Validation (Cal/Val activities. In this framework, the paper presents an approach consisting in accurately simulating a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over the wide VAS surface (50×50 km2. Ground and meteorological measurements over the area are used as the input of a Soil-Vegetation-Atmosphere-Transfer (SVAT model, SURFEX (Externalized Surface - module ISBA (Interactions between Soil-Biosphere-Atmosphere to simulate the spatial and temporal distribution of surface soil moisture. The calibration as well as the validation of the ISBA model are performed using in situ soil moisture measurements. It is shown that a good consistency is reached when point comparisons between simulated and in situ soil moisture measurements are made.

    Actually, an important challenge in remote sensing approaches concerns product validation. In order to obtain an representative soil moisture mapping over the Valencia Anchor Station (50×50 km2 area, a spatialization method is applied. For verification, a comparison between the simulated spatialized soil moisture and remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E and from the European Remote Sensing Satellites (ERS-SCAT is performed. Despite the fact that AMSR-E surface soil moisture product is not reproducing accurately the absolute values, it provides trustworthy information on surface soil moisture temporal variability. However, during the vegetation growing season the signal is perturbed. By using the

  8. RESEARCH OF MOISTURE MIGRATION DURING PARTIAL FREEZING OF GROUND BEEF

    Directory of Open Access Journals (Sweden)

    V. M. Stefanovskiy

    2016-01-01

    Full Text Available The concept of «ideal product» is proposed for the study of mass transfer during partial freezing of food products by freezing plate. The ideal product is a product, in which number of factors affecting the «real product» (meat are excluded. These factors include chemical composition of meat, quality grade of raw material (NOR, DFD, PSE, cryoscopic temperature that determines the degree of water transformation into ice, the phenomenon of osmosis, rate of freezing, etc. By using the concept of «ideal product» and its implementation in a physical experiment, it is proved that the “piston effect” causing the migration of moisture is due to frozen crust formation during partial freezing of the body. During partial freezing of the product by freezing plate, «ideal» and «real» food environment is transformed from closed system into open one with inflow of moisture to unfrozen part of the body. In the «ideal product», there is an expulsion of unfrozen moisture from freezing front, so the water appears on the body surface. Thus, the displacement of moisture increases by the same law, according to which the thickness (weight of frozen layer increases. During partial freezing of ground meat, moisture does not appear on the surface of the product, but hydrates the unfrozen part of meat. The reason of this phenomenon is the expulsion of water during formation of frozen crust and water-binding capacity of meat.

  9. Error Characterization of Multiple Sensor Soil Moisture Data for Improved Long-Term Global Soil Moisture Records

    Science.gov (United States)

    Dorigo, Wouter; Scipal, Klaus; de Jeu, Richard; Parinussa, Robert; Wagner, Wolfgang; Naeimi, Vahid

    2009-11-01

    In the framework of the Water Cycle Multi-mission Observation Strategy (WACMOS) project of ESA, a first multi-decadal (30+ years) global soil moisture record is generated by merging data sets from various active and passive microwave sensors. Combining multiple data sets brings many advantages in terms of enhanced temporal and spatial coverage and temporal resolution. Nevertheless, to benefit from this strategy, error budgets of the individual data sets have to be well characterized, and apt strategies for reducing the errors in the final product need to be developed.This study exploits the triple collocation error estimation technique to assess the error and systematic biases between three different independent soil moisture data sets: soil moisture data derived from the AMSR-E radiometer, scatterometer based estimates from MetOp- ASCAT, and modelled soil moisture from the ECMWF ERA Interim reanalysis program. The results suggest that the method provides realistic error estimates and allow us to identify systematic differences between the active and passive microwave derived soil moisture products, e.g. with respect to varying land cover or climatological zones. This in turn will help us in developing adequate strategies for merging active and passive observations for the generation of an accurate long-term soil moisture data set.

  10. Estimating Soil Moisture Using Polsar Data: a Machine Learning Approach

    Science.gov (United States)

    Khedri, E.; Hasanlou, M.; Tabatabaeenejad, A.

    2017-09-01

    Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. This is due to the difficulty in calculating soil moisture in vast territories and high-cost nature as well as spatial and local variability of soil moisture. Polarimetric synthetic aperture radar (PolSAR) imaging is a powerful tool for estimating soil moisture. These images provide a wide field of view and high spatial resolution. For estimating soil moisture, in this study, a model of support vector regression (SVR) is proposed based on obtained data from AIRSAR in 2003 in C, L, and P channels. In this endeavor, sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated to select suitable features of polarized image dataset for high efficient modeling. We compare the obtained data with in-situ data. Output results show that the SBS-SVR method results in higher modeling accuracy compared to SFS-SVR model. Statistical parameters obtained from this method show an R2 of 97% and an RMSE of lower than 0.00041 (m3/m3) for P, L, and C channels, which has provided better accuracy compared to other feature selection algorithms.

  11. Sensitivity of Active and Passive Microwave Observations to Soil Moisture during Growing Corn

    Science.gov (United States)

    Judge, J.; Monsivais-Huertero, A.; Liu, P.; De Roo, R. D.; England, A. W.; Nagarajan, K.

    2011-12-01

    at the site were Lakeland fine sand, with 89% sand content by volume. The crop was heavily irrigated via a linear move irrigation system. Every 15-minute ground-based passive and active microwave observations at L-band were conducted at an incidence angle of 40°. In addition, concurrent observations were conducted of soil moisture, temperature, heat flux at various depths in the root zone, along with concurrent micrometeorological conditions. Weekly vegetation sampling included measurements of LAI, green and dry biomass of stems, leaves, and ears, crop height and width, vertical distribution of moisture in the canopy, leaf size and orientation, other phonological observations. Such observations at high temporal density allow detailed sensitivity analyses as the vegetation grows.

  12. Validation of remotely-sensed soil moisture in the absence of in situ soil moisture: the case of the Yankin Basin, a tributary of the Niger River basin

    CSIR Research Space (South Africa)

    Badou, DF

    2017-10-01

    Full Text Available Soil moisture is known to be important in hydrology, agronomy, floods and drought forecasting. Acquisition of in situ soil moisture data is time consuming, costly, and does not cover the scale required for basin analysis. The consideration...

  13. [New index for soil moisture monitoring based on deltaT(s)-albedo spectral information].

    Science.gov (United States)

    Yao, Yun-Jun; Qin, Qi-Ming; Zhao, Shao-Hua; Shen, Xin-Yi; Sui, Xin-Xin

    2011-06-01

    Monitoring soil moisture by remote sensing has been an important problem for both agricultural drought monitoring and water resources management. In the present paper, we acquire the land surface temperature difference (deltaT(s)) and broadband albedo using MODIS Terra reflectance and land surface temperature products to construct the deltaT(s)-albedo spectral feature space. According to the soil moisture variation in spectral feature space, we put forward a simple and practical temperature difference albedo drought index (TDADI) and validate it using ground-measured 0-10 cm averaged soil moisture of Ningxia plain The results show that the coefficient of determination (R2) of both them varies from 0.36 to 0.52, and TDADI has higher accuracy than temperature albedo drought index (TADI) for soil moisture retrieval. The good agreement of TDADI, Albedo/LST, LST/ NDVI and TVDI for analyzing the trends of soil moisture change supports the reliability of TDADI. However, TDADI has been designed only at Ningxia plain and still needs further validation in other regions.

  14. Better to Be Active (Rather Than Passive) When Considering How Soil Moisture Can Help Decision Makers

    Science.gov (United States)

    Mace, R.

    2016-12-01

    As recent events have shown, Texas is a land of drought and flood. Texas experienced the worst one-year drought of record in 2011; the second worst statewide drought of record between 2010 and 2015; and record-breaking floods in the spring of 2015, fall of 2015, and spring of 2016 (with flash droughts occurring during the summers of 2015 and 2016). Soil moisture is one factor that links drought and flood in addressing key policy and management questions: When will soil moisture be high enough to allow groundwater recharge and runoff into reservoirs? When will soil moisture be high enough to cause flash floods with excessive rainfall? After tragic floods in Wimberley in the spring of 2015, Texas is expanding its stream-flow monitoring capabilities and is starting a statewide mesonet called TexMesonet to provide more detailed weather information to flood forecasters but also to provide baseline information on soil moisture for flood, drought, and water conservation purposes. Our hope is that the TexMesonet will help ground-truth SMAP and other remote sensing systems, help improve the National Water Model (a next generation tool for flood forecasting), and spark research into sub-basin soil moisture predictors of runoff which break water-supply droughts or lead to major floods.

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

    Science.gov (United States)

    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

  16. The moisture response of soil heterotrophic respiration: interaction with soil properties

    DEFF Research Database (Denmark)

    Moyano, F E; Vasilyeva, N; Bouckaert, L

    2012-01-01

    the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data......-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects...... predictions of the response of soil carbon to future climate scenarios will require the integration of soil-dependent moisture-respiration functions coupled with realistic representations of soil water dynamics....

  17. Development and evaluation of the MTVDI for soil moisture monitoring

    Science.gov (United States)

    Zhu, Wenbin; Lv, Aifeng; Jia, Shaofeng; Sun, Liang

    2017-06-01

    Several parameterization schemes have been developed to retrieve the soil moisture information involved in the remotely sensed surface temperature-vegetation index (Ts - VI) space. However, most of them are performed with the constraint of the dry edge of the Ts - VI space to define the maximum water stressed conditions. In view of the subjectivity and uncertainty involved in the determination of the dry edge, a new index termed as the Modified Temperature-Vegetation Dryness Index (MTVDI) was developed in this paper to reduce the reliance of the parameterization scheme on the dry edge. In the parameterization scheme of MTVDI, isopleth lines of soil moisture involved in the feature space were retrieved by the temperature-vegetation index method, and only the maximum surface temperature of bare soil (Tsmax) was indispensable in the definition of maximum water stressed conditions. For evaluation purpose, the MTVDI was demonstrated in the Southern Great Plains region of the U.S. and was compared with two other traditional soil moisture indexes developed under the constraint of dry edge. The comparison confirmed the effectivity of the MTVDI in monitoring the spatial pattern and seasonal variation of soil moisture. Our analyses also suggest that Tsmax, the only parameter needed in the definition of maximum water stressed conditions, can be retrieved directly from the parameterization scheme itself. Therefore, the retrieval of MTVDI can be performed independent of the dry edge, which is a significant improvement to the traditional parameterization schemes of soil moisture from the Ts - VI feature space.

  18. Soil moisture sampling and decision frameworks for agriculture

    Science.gov (United States)

    Sampling of soil moisture involves temporal and spatial components. The spatial component can be further expanded into a vertical and horizontal array of observations that are required to understand the dynamics of processes occurring with the soil profile. The decision frameworks for agriculture re...

  19. Additional Soil Evaluations at Yuma Proving Ground

    National Research Council Canada - National Science Library

    Kurtz, James

    1997-01-01

    .... These tests were performed for the Army Research Laboratory. The objectives of this effort were primarily to characterize the soil conditions, particularly moisture and dielectric permittivity, in support of anticipated unexploded ordnance (UXO...

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

    Science.gov (United States)

    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.

  1. Regional soil moisture monitoring network in the Raam catchment in the Netherlands. Dataset.

    NARCIS (Netherlands)

    Benninga, H.F.; Carranza, C.D.U.; Pezij, Michiel; van der Ploeg, M.J.; Augustijn, Dionysius C.M.; van der Velde, R.

    2017-01-01

    The Raam soil moisture measurement network dataset contains soil moisture and soil temperature measurements for 15 locations in the Raam, which is a 223-km2 river catchment in the southeast of the Netherlands. The network monitors soil moisture in the unsaturated zone for different soil textures and

  2. Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

    NARCIS (Netherlands)

    Wanders, N.|info:eu-repo/dai/nl/364253940; Karssenberg, D.|info:eu-repo/dai/nl/241557119; Bierkens, M. F. P.|info:eu-repo/dai/nl/125022794; Van Dam, J. C.; De Jong, S. M.|info:eu-repo/dai/nl/120221306

    Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture

  3. JSC Mars-1 Soil Moisture Characteristic and Soil Freezing Characteristic Curves for Modeling Bulk Vapor Flow and Soil Freezing

    Science.gov (United States)

    Dinwiddie, C. L.; Sizemore, H. G.

    2008-03-01

    A new JSC Mars-1 particle size distribution is used to establish soil moisture characteristic and soil freezing characteristic curves that are needed for modeling bulk (Darcy) vapor flow and soil freezing in the variably saturated subsurface of Mars.

  4. Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data

    Directory of Open Access Journals (Sweden)

    Chi Xu

    2016-01-01

    Full Text Available This research examines the simultaneous retrieval of surface soil moisture and salt concentrations using hyperspectral reflectance data in an arid environment. We conducted laboratory and outdoor field experiments in which we examined three key soil variables: soil moisture, salt and texture (silty loam, clay and silty clay. The soil moisture content models for multiple textures (M_SMC models were based on selected hyperspectral reflectance data located around 1460, 1900 and 2010 nm and resulted in R2 values higher than 0.933. Meanwhile, the soil salt concentrations were also accurately (R2 > 0.748 modeled (M_SSC models based on wavebands located at 540, 1740, 2010 and 2350 nm. When the different texture samples were mixed (SL + C + SC models, soil moisture was still accurately retrieved (R2 = 0.937 but the soil salt not as well (R2 = 0.47. After stratifying the samples by retrieved soil moisture levels, the R2 of calibrated M_SSCSMC models for soil salt concentrations improved to 0.951. This two-step method also showed applicability for analyzing soil-salt samples in the field. The M_SSCSMC models resulted in R2 values equal to 0.912 when moisture is lower than 0.15, and R2 values equal to 0.481 when soil moisture is between 0.15 and 0.2.

  5. Uncertain soil moisture feedbacks in model projections of Sahel precipitation

    Science.gov (United States)

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

    2017-06-01

    Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes (positive feedback), in others they dampen them

  6. Thresholds and interactive effects of soil moisture on the temperature response of soil respiration

    DEFF Research Database (Denmark)

    Lellei-Kovács, Eszter; Kovács-Láng, Edit; Botta-Dukát, Zoltán

    2011-01-01

    Ecosystem carbon exchange is poorly understood in low-productivity, semiarid habitats. Here we studied the controls of soil temperature and moisture on soil respiration in climate change field experiment in a sandy forest-steppe. Soil CO2 efflux was measured monthly from April to November in 2003......–2008 on plots receiving either rain exclusion or nocturnal warming, or serving as ambient control. Based on this dataset, we developed and compared empirical models of temperature and moisture effects on soil respiration. Results suggest that in this semiarid ecosystem the main controlling factor for soil CO2...... efflux is soil temperature, while soil moisture has less, although significant effect on soil respiration. Clear thresholds for moisture effects on temperature sensitivity were identified at 0.6, 4.0 and 7.0vol% by almost each model, which relate well to other known limits for biological activity...

  7. Monthly Summaries of Soil Temperature and Soil Moisture in Mongolia, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains soil temperature and soil moisture data from the Delger (White Bloom) site in Mongolia. Other variables include wind speed, wind direction,...

  8. Multivariate assimilation of coarse scale soil moisture, cosmic-ray soil moisture, land surface temperature and leaf area index in CLM4.5

    Science.gov (United States)

    Han, Xujun; Hendricks Franssen, Harrie-Jan; Schalge, Bernd; Baroni, Gabriele; Rihani, Jehan; Kollet, Stefan; Vereecken, Harry; Simmer, Clemens

    2017-04-01

    The land surface plays a central role in the atmosphere - land surface - subsurface continuum. Surface soil moisture for instance impacts the partitioning of absorbed radiation in heating ground and atmosphere and thus impacts resulting evapotranspiration. The land surface also drives partitioning of rainfall between infiltration which ends up as groundwater recharge and surface runoff contributing to stream discharge. It is therefore expected that the use of observations for characterizing and predicting the land surface state also leads to improved state estimations and predictions in all the other sub-compartments of the system we consider: groundwater, stream discharge and atmosphere. To test this hypothesis requires efficient data assimilation schemes that are capable to take up specific requirements of different compartments, such as different time windows of observations. In this study we will derive such data assimilation methods and quantify the improvement of predictions in the different compartments due to assimilation of multiple observations, and evaluate to what extent assimilation of land surface observations will also improve predictions of land surface states and fluxes for atmosphere and groundwater. We argue that improvements can be achieved by implementing a data assimilation methodology that is capable of simultaneous assimilation of many data sources (remote sensing soil moisture, cosmic-ray measurement for soil moisture, land surface temperature and leaf area index) at different spatial scales ranging from 102 m to 104 m. The multivariate data assimilation system for the land-surface component will be developed and extended to assimilate the coarse scale remote sensing soil moisture, cosmic-ray soil moisture, land surface temperature and leaf area index, and their different combinations using the local ensemble transform Kalman filter. The multivariate data assimilation will be evaluated using a synthetic study which mimics the Neckar

  9. Use of digital images to estimate soil moisture

    Directory of Open Access Journals (Sweden)

    João F. C. dos Santos

    Full Text Available ABSTRACT The objective of this study was to analyze the relation between the moisture and the spectral response of the soil to generate prediction models. Samples with different moisture contents were prepared and photographed. The photographs were taken under homogeneous light condition and with previous correction for the white balance of the digital photograph camera. The images were processed for extraction of the median values in the Red, Green and Blue bands of the RGB color space; Hue, Saturation and Value of the HSV color space; and values of the digital numbers of a panchromatic image obtained from the RGB bands. The moisture of the samples was determined with the thermogravimetric method. Regression models were evaluated for each image type: RGB, HSV and panchromatic. It was observed the darkening of the soil with the increase of moisture. For each type of soil, a model with best fit was observed and to use these models for prediction purposes, it is necessary to choose the model with best fit in advance, according to the soil characteristics. Soil moisture estimation as a function of its spectral response by digital image processing proves promising.

  10. Towards Generating Long-term AMSR-based Soil Moisture Data Record

    Science.gov (United States)

    Mladenova, I. E.; Jackson, T. J.; Bindlish, R.; Cosh, M. H.

    2014-12-01

    Research done over the past couple of years, such as Jung et al. (Nature, 2010) among others, demonstrates the potential for using soil moisture as an indicator and parameter for identifying long-term changes in climate trends. The study mentioned links the reduction in global evapotranspiration observed after the 1998 El Nino to decline in moisture supplies in the soil profile. Due to its crucial role in the terrestrial cycles and the demonstrated strong feedback with other climate variables, soil moisture has been recognized by the Global Climate Observing System as one of the 50 Essential Climate Variables (ECVs). The most cost and time effective way of monitoring soil moisture at global scale on routine basis, which is one of the requirements for ECVs, is using satellite technologies. AMSR-E was the first satellite mission to include soil moisture as an operational product. AMSR-E provided us with almost a decade of soil moisture data that are now extended by AMSR2, allowing the generation of a consistent and continuous global soil moisture data record. AMSR-E and AMSR2 are technically alike, thus, they are expected to have similar performance and accuracy, which needs to be confirmed and this the main focus of our research. AMSR-E stopped operating at its optimal rotational speed about 6 months before the launch of AMSR2, which complicates the direct inter-comparison and assessment of AMSR2 performance relative to AMSR-E. The AMSR-E and AMSR2 brightness temperature data and the corresponding soil moisture retrievals derived using the Single Channel Approach were evaluated separately at several ground validation sides located in the US. Brightness temperature inter-comparisons were done using monthly climatology and the low spin AMSR-E data acquired at 2 rpm. Both analyses showed very high agreement between the two instruments and revealed a constant positive bias at all locations in the AMSR2 observations relative to AMSR-E. Removal of this bias is essential

  11. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    Directory of Open Access Journals (Sweden)

    A. Castillo

    2015-04-01

    Full Text Available 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. Automated general temperature correction method for dielectric soil moisture sensors

    Science.gov (United States)

    Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

    2017-08-01

    An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a

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

    Science.gov (United States)

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

    2018-02-01

    Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently

  14. Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

    Science.gov (United States)

    Tana Wood; M. Detto; W.L. Silver

    2013-01-01

    Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal...

  15. Design and Fabrication of a Soil Moisture Meter Using Thermal Conductivity Properties of Soil

    Directory of Open Access Journals (Sweden)

    Subir DAS

    2011-09-01

    Full Text Available Study of soil for agricultural purposes is one of the main focuses of research since the beginning of civilization as food related requirements is closely linked with the soil. The study of soil has generated an interest among the researchers for very similar other reasons including understanding of soil water dynamics, evolution of agricultural water stress and validation of soil moisture modeling. In this present work design of a soil moisture measurement meter using thermal conductivity properties of soil has been proposed and experimental results are reported.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  18. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

    Jiankang, Ji; Thomsen, A.; Skriver, Henning

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...... of surface parameters with the bilinear model, the correlation coefficient between the estimated and measured soil moisture, as well as rms height, is about 0.77. To improve the result, the local incidence angles need to be taken into account...

  19. Irrigation Signals Detected From SMAP Soil Moisture Retrievals

    Science.gov (United States)

    Lawston, Patricia M.; Santanello, Joseph A.; Kumar, Sujay V.

    2017-12-01

    Irrigation can influence weather and climate, but the magnitude, timing, and spatial extent of irrigation are poorly represented in models, as are the resulting impacts of irrigation on the coupled land-atmosphere system. One way to improve irrigation representation in models is to assimilate soil moisture observations that reflect an irrigation signal to improve model states. Satellite remote sensing is a promising avenue for obtaining these needed observations on a routine basis, but to date, irrigation detection in passive microwave satellites has proven difficult. In this study, results show that the new enhanced soil moisture product from the Soil Moisture Active Passive satellite is able to capture irrigation signals over three semiarid regions in the western United States. This marks an advancement in Earth-observing satellite skill and the ability to monitor human impacts on the water cycle.

  20. [The relationship between the variation rate of MODIS land surface temperature and AMSR-E soil moisture and its application to downscaling].

    Science.gov (United States)

    Wang, An-Qi; Xie, Chao; Shi, Jian-Cheng; Gong, Hui-Li

    2013-03-01

    Using AMSR-E soil moisture, MODIS land surface temperature (Ts) and vegetation index product, the authors discuss the relationship between the variation rate of land surface temperature and surface soil moisture. Selecting the plains region of central United States as the study area, the authors propose the distribution triangle of the variation rate of land surface temperature and soil moisture. In the present paper, temperature variation and vegetation index (TVVI), a new index containing the information of temperature variation and vegetation, is introduced. The authors prove that TVVI and soil moisture show a steady relationship of exponential function; and build a quantitative model of soil moisture(SM) and instantaneous surface temperature variation (VTs). The authors later achieve downscaling of AMSR-E soil moisture data, through the above stated functional relationships and high-resolution MODIS data. Comparison with measured data on ground surface indicates that this method of downscaling is of high precision

  1. Version 3 of the SMAP Level 4 Soil Moisture Product

    Science.gov (United States)

    Reichle, Rolf; Liu, Qing; Ardizzone, Joe; Crow, Wade; De Lannoy, Gabrielle; Kolassa, Jana; Kimball, John; Koster, Randy

    2017-01-01

    The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

  2. Relationships between some soil physical and chemical properties with magnetic properties in different soil moisture regimes in Golestan province

    Directory of Open Access Journals (Sweden)

    M. Valaee

    2016-09-01

    Full Text Available Introduction: 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. It is the most important factor in soil formation, soil evolution and fertility affecting on crop production and management. Also, it widely is practical in soil classification and soil mapping. The soil moisture regime depends on the soil properties, climatic and weather conditions, characteristics of natural plant formations and, in cultivated soils, is affected by the characteristics of crops grown, as well as the cultivation practices. Determination of soil moisture regime within a landscape scale requires high information and data about moisture balance of soil profile during some years according to Soil Survey Manual (2010. This approach is very expensive, labor, time and cost consuming. Therefore, achievement to an alternative approach is seems essential to overcome these problems. The main hypothesis of this study was to use capability of magnetic susceptibility as a cheap and rapid technique could determine the soil moisture regimes. Magnetic properties of soils reflect the impacts of soil mineral composition, particularly the quantity of ferrimagnetic minerals such as maghemite and magnetite. Magnetic susceptibility measurements can serve a variety of applications including the changes in soil forming processes and ecological services, understanding of lithological effects, insight of sedimentation processes and soil drainage. Materials and Methods: This study was conducted in an area located between 36°46َ 10˝ and 37° 2’ 28˝ N latitudes, and 54° 29’ 31˝ and 55° 12’ 47˝ E longitudes in Golestan province, northern Iran. In the study region mean annual temperature varies from 12.4 to 19.4 °C. The average annual rainfall and evapotranspiration varies from 230 mm and 2335 mm in Inchebrun district (Aridic regime, to 732

  3. Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

    Science.gov (United States)

    Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

    2017-04-01

    West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

  4. Robust Initial Wetness Condition Framework of an Event-Based Rainfall–Runoff Model Using Remotely Sensed Soil Moisture

    Directory of Open Access Journals (Sweden)

    Wooyeon Sunwoo

    2017-01-01

    Full Text Available Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC prior to a rainfall event. Soil moisture is one of the most important variables in rainfall–runoff modeling, and remotely sensed soil moisture is recognized as an effective way to improve the accuracy of runoff prediction. In this study, the IWC was evaluated based on remotely sensed soil moisture by using the Soil Conservation Service-Curve Number (SCS-CN method, which is one of the representative event-based models used for reducing the uncertainty of runoff prediction. Four proxy variables for the IWC were determined from the measurements of total rainfall depth (API5, ground-based soil moisture (SSMinsitu, remotely sensed surface soil moisture (SSM, and soil water index (SWI provided by the advanced scatterometer (ASCAT. To obtain a robust IWC framework, this study consists of two main parts: the validation of remotely sensed soil moisture, and the evaluation of runoff prediction using four proxy variables with a set of rainfall–runoff events in the East Asian monsoon region. The results showed an acceptable agreement between remotely sensed soil moisture (SSM and SWI and ground based soil moisture data (SSMinsitu. In the proxy variable analysis, the SWI indicated the optimal value among the proposed proxy variables. In the runoff prediction analysis considering various infiltration conditions, the SSM and SWI proxy variables significantly reduced the runoff prediction error as compared with API5 by 60% and 66%, respectively. Moreover, the proposed IWC framework with

  5. Estimation of Soil Moisture Index Using Multi-Temporal Sentinel-1 Images over Poyang Lake Ungauged Zone

    Directory of Open Access Journals (Sweden)

    Yufang Zhang

    2017-12-01

    Full Text Available The C-band radar instruments onboard the two-satellite GMES Sentinel-1 constellation provide global measurements with short revisit time (about six days and medium spatial resolution (5 × 20 m, which are appropriate for watershed scale hydrological applications. This paper aims to explore the potential of Sentinel-1 for estimating surface soil moisture using a multi-temporal approach. To this end, a linear mixed effects (LME model was developed over Poyang Lake ungauged zone, using time series Sentinel 1A and 1B images and soil moisture ground measurements from 15 automatic observation sites. The model assumed a linear relationship that varied with both time and space between soil moisture and backscattering coefficient (SM- σ 0 . Results showed that three LME models developed with different polarized σ 0 images all meet the European Space Agency (ESA accuracy requirement for GMES soil moisture product (≤5% in volume, with the vertical transmit and vertical receive (VV polarized model achieving the best performance. However, the SM- σ 0 relationship was found to depend strongly on space, making it difficult to predict absolute soil moisture for each grid. Therefore, a relative soil moisture index was then proposed to correct for site effect. When compared with those of the linear fixed effects model, the soil moisture indices predicted by the LME model captured the temporal dynamics of measured soil moisture better, with the overall R2 and cross-validated R2 being 0.68 and 0.64, respectively. These results indicate that the LME model can be effectively applied to estimate soil moisture from multi-temporal Sentinel-1 images, which is useful for monitoring flood and drought disasters, and for improving stream flow prediction over ungauged zones.

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

    Science.gov (United States)

    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.

  7. Unsaturated soil moisture drying and wetting diffusion coefficient measurements in the laboratory.

    Science.gov (United States)

    2009-09-01

    ABSTRACTTransient moisture flow in an unsaturated soil in response to suction changes is controlled by the unsaturated moisture diffusion coefficient. The moisture diffusion coefficient can be determined by measuring suction profiles over time. The l...

  8. Soil Physical and Environmental Conditions Controlling Patterned-Ground Variability at a Continuous Permafrost Site, Svalbard

    DEFF Research Database (Denmark)

    Watanabe, Tatsuya; Matsuoka, Norikazu; Christiansen, Hanne Hvidtfeldt

    2017-01-01

    This study examines soil physical and environmental conditions controlling patterned-ground variability on an alluvial fan in a continuous permafrost landscape, at Adventdalen, Svalbard. On-site monitoring of ground temperature, soil moisture and snow depth, laboratory analyses of soil physical...... properties and principal component analysis indicate that the distribution of patterned ground depends primarily on soil texture, soil moisture and the winter ground thermal regime associated with snow cover. Mudboils and composite patterns (mudboils surrounded by small polygons) occupy well-drained areas...... composed of clay-rich aeolian sediments. Compared to mudboils, composite patterns show a sharper contrast in soil texture between barren centres and vegetated rims. Hummocks filled with organic materials develop on poorly drained lowlands associated with a shallow water table. Ice-wedge polygons...

  9. A wireless soil moisture sensor powered by solar energy.

    Science.gov (United States)

    Jiang, Mingliang; Lv, Mouchao; Deng, Zhong; Zhai, Guoliang

    2017-01-01

    In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.

  10. Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach

    OpenAIRE

    Alexakis, Dimitrios D.; Mexis, Filippos-Dimitrios K.; Vozinaki, Anthi-Eirini K.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2017-01-01

    A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach usi...

  11. Integral quantification of seasonal soil moisture changes in farmland by cosmic-ray neutrons

    Directory of Open Access Journals (Sweden)

    C. A. Rivera Villarreyes

    2011-12-01

    Full Text Available Soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only a few methods are on the way to close this gap between point measurements and remote sensing. One new measurement methodology that could determine integral soil moisture at this scale is the aboveground sensing of cosmic-ray neutrons, more precisely of ground albedo neutrons. The present study performed ground albedo neutron sensing (GANS at an agricultural field in northern Germany. To test the method it was accompanied by other soil moisture measurements for a summer period with corn crops growing on the field and a later autumn-winter period without crops and a longer period of snow cover. Additionally, meteorological data and aboveground crop biomass were included in the evaluation. Hourly values of ground albedo neutron sensing showed a high statistical variability. Six-hourly values corresponded well with classical soil moisture measurements, after calibration based on one reference dry period and three wet periods of a few days each. Crop biomass seemed to influence the measurements only to minor degree, opposed to snow cover which has a more substantial impact on the measurements. The latter could be quantitatively related to a newly introduced field neutron ratio estimated from neutron counting rates of two energy ranges. Overall, our study outlines a procedure to apply the ground albedo neutron sensing method based on devices now commercially available, without the need for accompanying numerical simulations and suited for longer monitoring periods after initial calibration.

  12. PRELIMINARY RESULTS OF ESTIMATING SOIL MOISTURE OVER BARE SOIL USING FULL-POLARIMETRIC ALOS-2 DATA

    Directory of Open Access Journals (Sweden)

    A. Sekertekin

    2016-10-01

    Full Text Available Synthetic Aperture Radar (SAR imaging system is one of the most effective way for Earth observation. The aim of this study is to present the preliminary results about estimating soil moisture using L-band Synthetic Aperture Radar (SAR data. Full-polarimetric (HH, HV, VV, VH ALOS-2 data, acquired on 22.04.2016 with the incidence angle of 30.4o, were used in the study. Simultaneously with the SAR acquisition, in-situ soil moisture samples over bare agricultural lands were collected and evaluated using gravimetric method. Backscattering coefficients for all polarizations were obtained and linear regression analysis was carried out with in situ moisture measurements. The best correlation coefficient was observed with VV polarization. Cross-polarized backscattering coefficients were not so sensitive to soil moisture content. In the study, it was observed that soil moisture maps can be retrieved with the accuracy about 14% (RMSE.

  13. Preliminary Results of Estimating Soil Moisture Over Bare Soil Using Full-Polarimetric ALOS-2 Data

    Science.gov (United States)

    Sekertekin, A.; Marangoz, A. M.; Abdikan, S.; Esetlili, M. T.

    2016-10-01

    Synthetic Aperture Radar (SAR) imaging system is one of the most effective way for Earth observation. The aim of this study is to present the preliminary results about estimating soil moisture using L-band Synthetic Aperture Radar (SAR) data. Full-polarimetric (HH, HV, VV, VH) ALOS-2 data, acquired on 22.04.2016 with the incidence angle of 30.4o, were used in the study. Simultaneously with the SAR acquisition, in-situ soil moisture samples over bare agricultural lands were collected and evaluated using gravimetric method. Backscattering coefficients for all polarizations were obtained and linear regression analysis was carried out with in situ moisture measurements. The best correlation coefficient was observed with VV polarization. Cross-polarized backscattering coefficients were not so sensitive to soil moisture content. In the study, it was observed that soil moisture maps can be retrieved with the accuracy about 14% (RMSE).

  14. Estimation of Soil Moisture Under Vegetation Cover at Multiple Frequencies

    Science.gov (United States)

    Jadghuber, Thomas; Hajnsek, Irena; Weiß, Thomas; Papathanassiou, Konstantinos P.

    2015-04-01

    Soil moisture under vegetation cover was estimated by a polarimetric, iterative, generalized, hybrid decomposition and inversion approach at multiple frequencies (X-, C- and L-band). Therefore the algorithm, originally designed for longer wavelength (L-band), was adapted to deal with the short wavelength scattering scenarios of X- and C-band. The Integral Equation Method (IEM) was incorporated together with a pedo-transfer function of Dobson et al. to account for the peculiarities of short wavelength scattering at X- and C-band. DLR's F-SAR system acquired fully polarimetric SAR data in X-, C- and L-band over the Wallerfing test site in Lower Bavaria, Germany in 2014. Simultaneously, soil and vegetation measurements were conducted on different agricultural test fields. The results indicate a spatially continuous inversion of soil moisture in all three frequencies (inversion rates >92%), mainly due to the careful adaption of the vegetation volume removal including a physical constraining of the decomposition algorithm. However, for X- and C-band the inversion results reveal moisture pattern inconsistencies and in some cases an incorrectly high inversion of soil moisture at X-band. The validation with in situ measurements states a stable performance of 2.1- 7.6vol.% at L-band for the entire growing period. At C- and X-band a reliable performance of 3.7-13.4vol.% in RMSE can only be achieved after distinct filtering (X- band) leading to a loss of almost 60% in spatial inversion rate. Hence, a robust inversion for soil moisture estimation under vegetation cover can only be conducted at L-band due to a constant availability of the soil signal in contrast to higher frequencies (X- and C-band).

  15. High resolution soil moisture radiometer. [large space structures

    Science.gov (United States)

    Wilheit, T. T.

    1978-01-01

    An electrically scanned pushbroom phased antenna array is described for a microwave radiometer which can provide agriculturally meaningful measurements of soil moisture. The antenna size of 100 meters at 1400 MHz or 230 meters at 611 MHz requires several shuttle launches and orbital assembly. Problems inherent to the size of the structure and specific instrument problems are discussed as well as the preliminary design.

  16. Effect of ambient gases and soil moisture regimes on carbohydrate ...

    African Journals Online (AJOL)

    ... Batha site samples have lower values of these fractions. Batha site reduced the flux of carbohydrates from source to the sinks of both soil moisture regimes. This study concluded that there was a good relation between the effect of highly polluted localities and kidneybean leaves carbohydrate content and its translocation.

  17. Response of maize and cucumber intercrop to soil moisture control ...

    African Journals Online (AJOL)

    GREGO

    2007-03-05

    Mar 5, 2007 ... Response of maize and cucumber intercrop to soil moisture control through irrigation and mulching during the dry season in Nigeria. Josiah M. Ayotamuno1*, K. Zuofa2, Sunday A. Ofori2 and Reginald B. Kogbara1. 1Department of Agricultural and Environmental Engineering, Rivers State University of ...

  18. NASA Soil Moisture Active Passive Mission Status and Science Performance

    Science.gov (United States)

    Yueh, Simon H.; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni; Entin, Jared K.

    2016-01-01

    The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational since mid-April 2015. The SMAP radiometer has been operating flawlessly, but the radar transmitter ceased operation on July 7. This paper provides a status summary of the calibration and validation of the SMAP instruments and the quality assessment of its soil moisture and freeze/thaw products. Since the loss of the radar in July, the SMAP project has been conducting two parallel activities to enhance the resolution of soil moisture products. One of them explores the Backus Gilbert optimum interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer. The other investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic radar data to obtain soil moisture products at about 1 to 3 kilometers resolution. In addition, SMAP's L-band data have found many new applications, including vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.

  19. Development of a aquarius/sac-d soil moisture product

    Science.gov (United States)

    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 will increase the value and impact of the Aquarius mission by including a broader sci...

  20. A comparison of soil moisture relations between standing and ...

    African Journals Online (AJOL)

    Soil moisture was recharged within a few months after clearfelling, but became rapidly depleted as the canopy of new crop developed and approached canopy closure. A decreased wetting-front velocity and a marginally higher field capacity were proposed as evidence of pore clogging that appeared to occur during the ...

  1. Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

    Science.gov (United States)

    Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

    2017-01-01

    The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

  2. Response of maize and cucumber intercrop to soil moisture control ...

    African Journals Online (AJOL)

    Replicate field plots were used in experiments aimed at evaluating the yield potentials of maize and cucumber intercrop resulting from the control of soil moisture through irrigation and mulching, for a period of eleven weeks. Three irrigation depths, 2.5, 3.5 and 4.5 mm; and two mulch levels, zero mulch and 10 ton/ha of oil ...

  3. Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

    Science.gov (United States)

    Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

    2017-04-01

    Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

  4. Effects of land preparation and plantings of vegetation on soil moisture in a hilly loess catchment in China

    NARCIS (Netherlands)

    Tianjiao, Feng; Wei, Wei; Liding, Chen; Keesstra, Saskia D.; Yang, Yu

    2018-01-01

    In the dryland and degraded regions, soil moisture is the primary factor determining ecological restoration. Proper land preparations and vegetation restoration can improve soil moisture and benefit land restoration. Identifying their effects on soil moisture is thus essential for developing

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

    Science.gov (United States)

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

    2011-01-01

    The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

  6. SMEX02 Sliced Core Soil Moisture Data, Walnut Creek Watershed, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes sliced soil core moisture data collected during the Soil Moisture Experiment 2002 (SMEX02), conducted during June and July 2002 in the Walnut...

  7. Polarimetric Decompositions for Soil Moisture Retrieval from Vegetated Soils in TERENO Observatories

    Science.gov (United States)

    Jagdhuber, Thomas; Hajnsek, Irena; Papathanassiou, Konstantinos P.

    2013-08-01

    A refined hybrid polarimetric decomposition and inversion method for soil moisture estimation under vegetation is investigated for its potential to retrieve soil moisture from vegetated soils in TERENO observatories. The refined algorithm is applied on L- band fully polarimetric data acquired by DLR's novel F-SAR sensor. Two flight and field measurement campaigns were conducted in 2011 and 2012 for the TERENO Harz, Eifel and DEMMIN observatories, located all across Germany. The applied algorithm reveals distinct potential to invert soil moisture with inversion rates higher than >98% for a variety of crop types, phenological conditions and for pronounced topography. A quality assessment is conducted by validation with FDR, TDR and a wireless soil moisture network. The RMSE stays below 6.1vol.% for the different test sites and data takes including a variety of vegetation types in different phenological stages.

  8. Linking Spatial and Temporal Patterns of Soil Moisture with Upland Soil Iron Reduction

    Science.gov (United States)

    Hodges, C. A.; Markewitz, D.; Thompson, A.

    2015-12-01

    Iron minerals play important roles in governing soil nutrient availability and carbon dynamics. Periods of intermittent anoxia (low-oxygen) in upland soils can drive microbial reduction and dissolution of iron minerals. However, quantifying ecosystem-scale iron reduction in upland soils is challenging. The key condition necessary for soil iron reduction is water saturation of soil micropores, even if the entire soil profile is not flooded. We assessed soil moisture and texture across three first-order watersheds at the Calhoun Critical Zone Observatory in South Carolina, USA over one year using electromagnetic induction (EMI). From these point measurements, we have created monthly maps of interpolated soil moisture. From the EMI data, we found that locations that remain relatively wet or dry throughout the year are not related to hill-slope position but to differences in soil texture along a catena. Across a gradient of soil moisture and texture (based on soil conductivity from the EMI probe) we installed passive redox sensors and conducted in situ iron reduction experiments. This data will be presented and the relationships between iron reduction, the spatial distribution of soil moisture/clay content, and the significance of these data with respect to soil carbon cycling will be discussed.

  9. Soil moisture from active microwave data for monitoring and modeling

    Science.gov (United States)

    Doubkova, M.; Bartsch, A.; Wagner, W.

    2008-12-01

    Soil moisture content impacts land surface energy dynamics, regional runoff dynamics and vegetation productivity. Coarse to medium resolution data from active microwave instruments onboard satellites which are currently in space are able to provide such valuable information for operational use. Scatterometer (ERS, Metop ASCAT) can be applied on regional to global scale. ScanSAR systems are suitable for regional to continental monitoring and for the investigation of scaling issues. The original soil moisture derivation approach which was developed for scatterometer data (Wagner et al. 1999) has been transferred to ScanSAR data as the most important product of the ESA Tiger innovator project SHARE (Soil moisture for hydrometeorological application in the Southern African Development Community, www.ipf.tuwien.ac.at/radar/share). The aim of this project was to provide soil moisture maps on a dynamic basis, freely accessible to user communities. Due to the successful implementation this service has been extended to other regions. Data from the ENVISAT ASAR instrument operating in Global Mode (1km resolution) have been used not only over the southern African subcontinent, but also over entire Australia and within other regional studies (e.g. Oklahoma, US; Lena Delta, Russia; central and eastern Europe). These time series in conjunction with the operational meteorological satellite Metop ASCAT provide a valuable tool for identification of soil moisture anomalies which relate to drought and flooding. Currently more than 250 registered users make use the free datasets provided by the Institute of Photogrammetry and Remote Sensing at Vienna University of Technology. Most recent results from validation activities, scaling analyses and modeling will be presented.

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

    Science.gov (United States)

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

    2017-04-01

    Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial

  11. Microwave soil moisture measurements and analysis

    Science.gov (United States)

    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.

  12. Effects of soil moisture on the temperature sensitivity of soil heterotrophic respiration: a laboratory incubation study.

    Directory of Open Access Journals (Sweden)

    Weiping Zhou

    Full Text Available The temperature sensitivity (Q10 of soil heterotrophic respiration (Rh is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity--WHC and five temperature levels (10, 17, 24, 31, and 38°C. Under each moisture treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC, microbial community structure and soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC than at higher moisture level (80% WHC during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three moisture levels during the late stage of incubation. In contrast, soil Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the moisture-induced Q10 changes. This study implies that global warming's impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration.

  13. The Raam regional soil moisture monitoring network in the Netherlands

    Science.gov (United States)

    Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier

    2018-01-01

    We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56" target="_blank">https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.

  14. The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

    Science.gov (United States)

    Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

    2017-05-01

    Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr(-1) , but also highlight regions of uncertainty

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

    Fois, Laura; Montaldo, Nicola

    2017-04-01

    Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity

  17. Sensitivity of soil moisture analyses to contrasting background and observation error scenarios

    Science.gov (United States)

    Munoz-Sabater, Joaquín; de Rosnay, Patricia; Albergel, Clément; Isaksen, Lars

    2017-04-01

    Soil moisture is a crucial variable for numerical weather prediction. Accurate, global initialization of soil moisture is obtained through data assimilation systems. However analyses depend largely on the way observations and background errors are defined. In this paper a wide range of short experiments with contrasted specification of the observation error and soil moisture background were conducted. As observations, screen-level variables and brightness temperatures from the Soil Moisture and Ocean Salinity (SMOS) mission were used. The region of interest was North America given the good availability of in-situ observations. The impact of these experiments on soil moisture and the atmospheric layer near the surface were evaluated. The results highlighted the importance of assimilating sensitive observations to soil moisture for air temperature and humidity forecasts. The benefits on the soil water content were more noticeable with increasing the SMOS observation error and with the introduction of soil texture dependency in the soil moisture background error.

  18. Sensitivity of LISEM predicted catchment discharge to initial soil moisture content of soil profile

    NARCIS (Netherlands)

    Sheikh, V.; van Loon, E.; Hessel, R.; Jetten, V.

    2010-01-01

    This study conducts a broad sensitivity analysis, taking into account the influence of initial soil moisture content in two soil layers, layer depths, event properties, and two infiltration models. A distributed hydrology and soil erosion model (LISEM) is used. Using the terrain data from the Catsop

  19. Spatial and temporal monitoring of soil moisture using surface electrical resistivity tomography in Mediterranean soils

    NARCIS (Netherlands)

    Alamry, Abdulmohsen S.; van der Meijder, Mark; Noomen, Marleen; Addink, Elisabeth A.; van Benthem, Rik; de Jong, Steven M.

    2017-01-01

    ERT techniques are especially promising in (semi-arid) areas with shallow and rocky soils where other methods fail to produce soil moisture maps and to obtain soil profile information. Electrical Resistivity Tomography (ERT) was performed in the Peyne catchment in southern France at four sites

  20. Spatially and Temporally Complete Satellite Soil Moisture Data Based on a Data Assimilation Method

    Directory of Open Access Journals (Sweden)

    Zhiqiang Xiao

    2016-01-01

    Full Text Available Multiple soil moisture products have been generated from data acquired by satellite. However, these satellite soil moisture products are not spatially or temporally complete, primarily due to track changes, radio-frequency interference, dense vegetation, and frozen soil. These deficiencies limit the application of soil moisture in land surface process simulation, climatic modeling, and global change research. To fill the gaps and generate spatially and temporally complete soil moisture data, a data assimilation algorithm is proposed in this study. A soil moisture model is used to simulate soil moisture over time, and the shuffled complex evolution optimization method, developed at the University of Arizona, is used to estimate the control variables of the soil moisture model from good-quality satellite soil moisture data covering one year, so that the temporal behavior of the modeled soil moisture reaches the best agreement with the good-quality satellite soil moisture data. Soil moisture time series were then reconstructed by the soil moisture model according to the optimal values of the control variables. To analyze its performance, the data assimilation algorithm was applied to a daily soil moisture product derived from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E, the Microwave Radiometer Imager (MWRI, and the Advanced Microwave Scanning Radiometer 2 (AMSR2. Preliminary analysis using soil moisture data simulated by the Global Land Data Assimilation System (GLDAS Noah model and soil moisture measurements at a multi-scale Soil Moisture and Temperature Monitoring Network on the central Tibetan Plateau (CTP-SMTMN was performed to validate this method. The results show that the data assimilation algorithm can efficiently reconstruct spatially and temporally complete soil moisture time series. The reconstructed soil moisture data are consistent with the spatial precipitation distribution and have strong

  1. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    Science.gov (United States)

    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 pValencia 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

  2. Evaluation of AMSR-E derived soil moisture over Australia, /Remote Sensing of Environment

    NARCIS (Netherlands)

    Draper, C.S.; Walker, J.P.; Steinle, P.J.; De Jeu, R.A.M.; Holmes, T.R.H.

    2009-01-01

    This paper assesses remotely sensed near-surface soil moisture over Australia, derived from the passive microwave Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument. Soil moisture fields generated by the AMSR-E soil moisture retrieval algorithm developed at the Vrije

  3. A simple interpretation of the surface tenperature/vegetation index space for assessment of soil moisture status

    DEFF Research Database (Denmark)

    Sandholt, Inge; Andersen, J.; Rasmussen, Kjeld

    2002-01-01

    Remote Sensing, soil moisture, surface temperature, vegetation index, hydrology, Africa, Senegal, semiarid......Remote Sensing, soil moisture, surface temperature, vegetation index, hydrology, Africa, Senegal, semiarid...

  4. A simulation test of the impact on soil moisture by agricultural ...

    African Journals Online (AJOL)

    use

    2011-11-21

    Nov 21, 2011 ... 1Institute of Efficient Water Use for Arid Agriculture of China, Northwest A&F University, Yangling, China. 2Institute of Soil and Water ... (2009) studied agricultural machinery compaction models under different soil water .... moisture soil content, which affects soil bulk density well. The soil moisture at 0 to 5 ...

  5. Spatial Variability of Soil Moisture and the Validation of Remote Sensing Products in a Unique Beach Environment

    Science.gov (United States)

    Rogers, J.; Berg, A. A.

    2010-12-01

    Soil water conditions are crucial for understanding the exchange of energy and mass at the earth's surface. The need for a better description of the heterogeneity of surface soil moisture in both space and time has garnered interest from areas including agricultural management and drought monitoring, water resources and flood prediction, and more recently climate modeling. Soil moisture has also been identified as a critical parameter in the initiation of particle entrainment by wind due to the alteration of physical properties such as aggregate structure and inter-particle cohesion. Therefore the dynamics of soil moisture are of great interest for regional wind erosion modeling as well as for the development of agricultural productivity and soil loss models. In this study, a unique environment for the study of soil moisture was investigated at Williston Reservoir in Northern British Columbia, Canada. For a period of a month or more before the reservoir is filled by the spring melt, several thousand hectares of fine-grained sediments are exposed to wind causing significant erosion and therefore potential air quality concerns. Here we present a study of the spatial and temporal patterning of surface soil moisture in exposed sediments. Measurements at small scales are used in the validation of remote sensing products at large scales and these estimates have been implemented into blowing dust models. Active microwave (RADARSAT-2) and optical (LandSAT-5) scenes were obtained between May 24th - June 2nd, 2009. On the ground, point measurements using capacitance based probes were performed over 4 test plots coincident with satellite overpass. Areal averages of soil moisture collected on the ground are used in the validation of soil moisture estimates from four backscatter inversion models (microwave) and a thermal band mono-window brightness temperature algorithm (optical). The studied environment represents an important validity test because backscatter inversion models

  6. Combining modelled and remote sensing soil moisture anomalies for an operational global drought monitoring

    Science.gov (United States)

    Cammalleri, Carmelo; Vogt, Jürgen

    2017-04-01

    Soil moisture anomalies (i.e., deviations from the climatology) are often seen as a reliable tool to monitor and quantify the occurrence of drought events and their potential impacts, especially in agricultural and naturally vegetated lands. Soil moisture datasets (or their proxy) can be derived from a variety of sources, including land-surface models and thermal and microwave satellite remote sensing images. However, each data source has different advantages and drawbacks that prevent to unequivocally prefer one dataset over the others, especially in global applications that encompass a wide range of soil moisture regimes. The analysis of the spatial reliability of the different datasets at global scale is further complicated by the lack of reliable long-term soil moisture records for a ground validation over most regions. To overcome this limitation, in recent years the Triple Collocation (TC) technique has been deployed in order to quantify the likely errors associated to three mutually-independent datasets without assuming that one of them represents the "truth". In this study, three global datasets of soil moisture anomalies are investigated: the first one derived from the runs of the Lisflood hydrological model, the second one obtained from the combined active/passive microwave dataset produced in the framework of the European Space Agency (ESA) Climate Change Initiative (CCI), and the last one derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) observations. A preliminary analysis of the three datasets aimed at detecting the areas where the TC technique can be successfully applied, hence the spatial distribution of the random error variance for each model is evaluated. This study allows providing useful advises for a robust combination of the three datasets into a single product for a more reliable global drought monitoring.

  7. Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

    Science.gov (United States)

    Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

    2016-10-01

    Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

  8. Characterization of Rape Field Microwave Emission and Implications to Surface Soil Moisture Retrievals

    Directory of Open Access Journals (Sweden)

    Alexander Loew

    2012-01-01

    Full Text Available In the course of Soil Moisture and Ocean Salinity (SMOS mission calibration and validation activities, a ground based L-band radiometer ELBARA II was situated at the test site Puch in Southern Germany in the Upper Danube Catchment. The experiment is described and the different data sets acquired are presented. The L-band microwave emission of the biosphere (L-MEB model that is also used in the SMOS L2 soil moisture algorithm is used to simulate the microwave emission of a winter oilseed rape field in Puch that was also observed by the radiometer. As there is a lack of a rape parameterization for L-MEB the SMOS default parameters for crops are used in a first step which does not lead to satisfying modeling results. Therefore, a new parameterization for L-MEB is developed that allows us to model the microwave emission of a winter oilseed rape field at the test site with better results. The soil moisture retrieval performance of the new parameterization is assessed in different retrieval configurations and the results are discussed. To allow satisfying results, the periods before and after winter have to be modeled with different parameter sets as the vegetation behavior is very different during these two development stages. With the new parameterization it is possible to retrieve soil moisture from multiangular brightness temperature data with a root mean squared error around 0.045–0.051 m³/m³ in a two parameter retrieval with soil moisture and roughness parameter Hr as free parameters.

  9. Quantifying the effects of soil temperature, moisture and sterilization on elemental mercury formation in boreal soils.

    Science.gov (United States)

    Pannu, Ravinder; Siciliano, Steven D; O'Driscoll, Nelson J

    2014-10-01

    Soils are a source of elemental mercury (Hg(0)) to the atmosphere, however the effects of soil temperature and moisture on Hg(0) formation is not well defined. This research quantifies the effect of varying soil temperature (278-303 K), moisture (15-80% water filled pore space (WFPS)) and sterilization on the kinetics of Hg(0) formation in forested soils of Nova Scotia, Canada. Both, the logarithm of cumulative mass of Hg(0) formed in soils and the reduction rate constants (k values) increased with temperature and moisture respectively. Sterilizing soils significantly (p rate limiting biotic process that generates a large pool of reducible Hg(II). Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. A Tilt, Soil Moisture, and Pore Water Pressure Sensor System for Slope Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Rosanno de Dios

    2009-06-01

    Full Text Available This paper describes the design, implementation and characterization of a sensor network intended for monitoring of slope deformation and potential failures. The sensor network system consists of a tilt and moisture sensor column, a pore water pressure sensor column and a personal computer for data storage and processing. The tilt sensor column consists of several pipe segments containing tri-axial accelerometers and signal processing electronics. Each segment is joined together by flexible joints to allow for the column to deform and subsequently track underground movement. Capacitive-type sensors for soil moisture measurement are also included in the sensor column, which are used to measure the soil moisture at different depths. The measurements at each segment are transferred via a Controller Area Network (CAN bus, where the CAN master node is located at the top of the column above ground. The CAN master node transmits the collected data from the slave nodes via a wireless connection to a personal computer that performs data storage, processing and display via a Python-based graphical user interface (GUI. The entire system was deployed and characterized on a small-scale slope model. Slope failure was induced via water seepage and the system was demonstrated to ably measure the inclination and soil moisture content throughout the landslide event.

  11. Data Assimilation to Extract Soil Moisture Information from SMAP Observations

    Directory of Open Access Journals (Sweden)

    Jana Kolassa

    2017-11-01

    Full Text Available This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP observations. Neural network (NN and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

  12. The NASA Soil Moisture Active Passive (SMAP) Mission Formulation

    Science.gov (United States)

    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-tier projects recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is in formulation phase and it is scheduled for launch in 2014. The SMAP mission is designed to produce high-resolution and accurate global mapping of soil moisture and its freeze/thaw state using an instrument architecture that incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer. The simultaneous radar and radiometer measurements will be combined to derive global soil moisture mapping at 9 [km] resolution with a 2 to 3 days revisit and 0.04 [cm3 cm-3] (1 sigma) soil water content accuracy. The radar measurements also allow the binary detection of surface freeze/thaw state. The project science goals address in water, energy and carbon cycle science as well as provide improved capabilities in natural hazards applications.

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

    Science.gov (United States)

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

    2011-01-01

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

  14. Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation

    Science.gov (United States)

    Tarpanelli, A.; Massari, C.; Ciabatta, L.; Filippucci, P.; Amarnath, G.; Brocca, L.

    2017-10-01

    A merging procedure is applied to five daily rainfall estimates achieved via SM2RAIN applied to the soil moisture products obtained by the Advanced SCATterometer, the Advanced Microwave Scanning Radiometer 2, the Soil Moisture Active and Passive mission, the Soil Moisture and Ocean Salinity mission and backscattering observations of RapidScat. The precipitation estimates are evaluated against dense ground networks in the period ranging from April to December, 2015, in India and in Italy, at 0.25°/daily spatial/temporal resolution. The merged product derived by combining the different SM2RAIN rainfall products shows better results in term of statistical and categorical metrics with respect to the use of the single products. A good agreement with reference to ground observations is obtained, with median correlations equal to 0.65 and 0.77 in India and in Italy, respectively. The merged dataset is found to slightly outperform those of the IMERG product of the Global Precipitation Measurement mission underlying the large potential of the proposed approach.

  15. MISTRALE: Soil moisture mapping service based on a UAV-embedded GNSS-Reflectometry sensor

    Science.gov (United States)

    Van de Vyvere, Laura; Desenfans, Olivier

    2016-04-01

    Around 70 percent of worldwide freshwater is used by agriculture. To be able to feed an additional 2 billion people by 2030, water demand is expected to increase tremendously in the next decades. Farmers are challenged to produce "more crop per drop". In order to optimize water resource management, it is crucial to improve soil moisture situation awareness, which implies both a better temporal and spatial resolution. To this end, the objective of the MISTRALE project (Monitoring soIl moiSture and waTeR-flooded Areas for agricuLture and Environment) is to provide UAV-based soil moisture maps that could complement satellite-based and field measurements. In addition to helping farmers make more efficient decisions about where and when to irrigate, MISTRALE moisture maps are an invaluable tool for risk management and damage evaluation, as they provide highly relevant information for wetland and flood-prone area monitoring. In order to measure soil water content, a prototype of a new sensor, called GNSS-Reflectometry (GNSS-R), is being developed in MISTRALE. This approach consists in comparing the direct signal, i.e. the signal travelling directly from satellite to receiver (in this case, embedded in the UAV), with its ground-reflected equivalent. Since soil dielectric properties vary with moisture content, the reflected signal's peak power is affected by soil moisture, unlike the direct one. In order to mitigate the effect of soil surface roughness on measurements, both left-hand and right-hand circular polarization reflected signals have to be recorded and processed. When it comes to soil moisture, using GNSS signals instead of traditional visible/NIR imagery has many advantages: it is operational under cloud cover, during the night, and also under vegetation (bushes, grass, trees). In addition, compared to microwaves, GNSS signal (which lies in L-band, between 1.4 and 1.8 GHz) is less influenced by variation on thermal background. GNSS frequencies are then ideal

  16. An Improved Technique for dry Soil Moisture Release Curves to Determine Soil Mineralogical and Physical Properties

    Science.gov (United States)

    Campbell, G. S.; Campbell, C. S.; Cobos, D. R.

    2008-12-01

    Soil moisture release curves (MRC) or moisture sorption isotherms, which relate the amount of water in soil to its water potential or water activity, have many applications in soil physics and geotechnical engineering including determining soil water flow, specific surface area, swelling potential, and clay mineralogy and activity. Although research showing MRC for various soils dates back more than 50 years, limitations with the measurement technique have made developing MRC time consuming and inaccurate, especially in dry soils. Recently, an instrument was developed to create moisture sorption isotherms for various food and pharmaceutical products. The objective of this research was to investigate its use in soils for obtaining MRC in dry soils simply and accurately. Several different soil types were tested in the instrument from pure sand to bentonite and smectite clays. From the MRC of these soils, we were able to develop good correlations between actual and derived clay activity, surface area, and swelling potential. In addition, we were able to see hysteresis in dry soil water uptake for all soils, including sand. According to our tests, this new instrument will provide a powerful tool to investigate several soil physical properties simply and accurately.

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

    Science.gov (United States)

    Shafian, S.; Maas, S. J.

    2015-12-01

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

  18. Kinematic Models for Soil Moisture and Solute Transport

    Science.gov (United States)

    Charbeneau, Randall J.

    1984-06-01

    The kinematic theory of soil moisture and solute transport in the vertical direction for unsaturated groundwater recharge is considered. The general theory of kinematic models is reviewed and applied for an isolated wetting event wherein the soil starts at and eventually drains to field capacity. Analytical expressions are developed for the water content and moisture flux as a function of depth and time. The approach is extended for an arbitrary sequence of surface flux or water content boundary conditions. The transport of a solute with a general nonlinear sorption isotherm is also considered. It is shown that for the general isotherm the vertical displacement of a solute isochore during an arbitrary wetting sequence depends only on the total depth of water infiltrated and not on how the infiltration rate varies with time.

  19. Testing of a conceptualisation of catchment scale surface soil moisture in a hydrologic model

    Science.gov (United States)

    Komma, J.; Parajka, J.; Naeimi, V.; Blöschl, G.; Wagner, W.

    2009-04-01

    In this study the simulated surface soil moisture of a dual layer conceptual hydrologic model is tested against ERS scatterometer top soil moisture observations. The study catchment at the Kamp river with a size of 1550 km² is located in north-eastern Austria. The hydrologic simulations in this study are based on a well calibrated hydrologic model. The model consists of a spatially distributed soil moisture accounting scheme and a flood routing component. The spatial and temporal resolutions of the model are 1 x 1 km² and 15 minutes. The soil moisture accounting scheme simulates the mean moisture state over the entire vertical soil column. To get additional information about moisture states in a thin surface soil layer from the continuous rainfall-runoff model, the soil moisture accounting scheme is extended by a thin skin soil storage sitting at the top of the main soil reservoir. The skin soil storage is filled by rain and snow melt. The skin soil reservoir and the main soil reservoir are connected by a bidirectional moisture flux which is assumed to be a linear function of the vertical soil moisture gradient. The calibration of the additional dual layer component is based on hydrologic reasoning and the incorporation of measured soil water contents close to the study catchment. The comparison of the simulated surface soil moisture with the ERS scatterometer top soil moisture observations is performed in the period 1993-2005. On average, about 3 scatterometer images per month with a mean spatial coverage of about 82% are available at the Kamp catchment. The correlation between the catchment mean values of the two top soil moisture estimates changes with the season. The differences tend to be smaller due the summer month from July to October. The results indicate a good agreement between the modelled and remote sensed spatial moisture patterns in the study area.

  20. Soil Moisture Sensing via Swept Frequency Based Microwave Sensors

    Directory of Open Access Journals (Sweden)

    Greg A. Holt

    2012-01-01

    Full Text Available There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR. The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT. The measurement is comparable to time domain transmissometry (TDT with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument’s ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/−105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r2 = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the

  1. Soil moisture data as a constraint for groundwater recharge estimation.

    OpenAIRE

    Mathias, Simon A.; Sorensen, James P.R.; Butler, Adrian P.

    2017-01-01

    Estimating groundwater recharge rates is important for water resource management studies. Modeling approaches to forecast groundwater recharge typically require observed historic data to assist calibration. It is generally not possible to observe groundwater recharge rates directly. Therefore, in the past, much effort has been invested to record soil moisture content (SMC) data, which can be used in a water balance calculation to estimate groundwater recharge. In this context, SMC data is mea...

  2. Spatio-temporal variability of global soil moisture products

    Science.gov (United States)

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

    2015-03-01

    Being an important variable for various applications, for example hydrological and weather prediction models or data assimilation, a large range of global soil moisture products from different sources, such as modeling or active and passive microwave remote sensing, are available. The diverse measurement and estimation methods can lead to differences in the characteristics of the products. This study investigates the spatial and temporal behavior of three different products: (i) the Soil Moisture and Ocean Salinity (SMOS) Level 2 product, retrieved with a physically based approach from passive microwave remote sensing brightness temperatures, (ii) the MetOp-A Advanced Scatterometer (ASCAT) product retrieved with a change detection method from radar remote sensing backscattering coefficients, and (iii) the ERA Interim product from a weather forecast model reanalysis. Results show overall similar patterns of spatial soil moisture, but high deviations in absolute values. A ranking of mean relative differences demonstrates that ASCAT and ERA Interim products show most similar spatial soil moisture patterns, while ERA and SMOS products show least similarities. For selected regions in different climate classes, time series of the ASCAT product generally show higher variability of soil moisture than SMOS, and especially than ERA products. The relationship of spatial mean and variance is, especially during wet periods, influenced by sensor and retrieval characteristics in the SMOS product, while it is determined to a larger degree by the precipitation patterns of the respective regions in the ASCAT and ERA products. The decomposition of spatial variance into temporal variant and invariant components exhibits high dependence on the retrieval methods of the respective products. The change detection retrieval method causes higher influence of temporal variant factors (e.g. precipitation, evaporation) on the ASCAT product, while SMOS and ERA products are stronger determined by

  3. NASA Soil Moisture Active Passive Mission Status and Science Highlights

    Science.gov (United States)

    Yueh, Simon; Entekhabi, Dara; O'Neill, Peggy; Entin, Jared

    2017-01-01

    The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational during April 2015. This paper provides a summary of the quality assessment of its baseline soil moisture and freeze/thaw products as well as an overview of new products. The first new product explores the Backus Gilbert optimum interpolation based on the oversampling characteristics of the SMAP radiometer. The second one investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic aperture radar (SAR) data to obtain soil moisture products at about 1 to 3 km resolution. In addition, SMAPs L-band data have been found useful for many scientific applications, including depictions of water cycles, vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.The SMAP soil moisture, freeze/taw state and SSSprovide a synergistic view of water cycle. For example, Fig.7 illustrates the transition of freeze/thaw state, change of soilmoisture near the pole and SSS in the Arctic Ocean fromApril to October in 2015 and 2016. In April, most parts ofAlaska, Canada, and Siberia remained frozen. Melt onsetstarted in May. Alaska, Canada, and a big part of Siberia havebecome thawed at the end of May; some freshwater dischargecould be found near the mouth of Mackenzie in 2016, but notin 2015. The soil moisture appeared to be higher in the Oband Yenisei river basins in Siberia in 2015. As a result,freshwater discharge was more widespread in the Kara Seanear the mouths of both rivers in June 2015 than in 2016. TheNorth America and Siberia have become completely thawedin July. After June, the freshwater discharge from other riversinto the Arctic, indicated by blue, also became visible. Thefreeze-up started in September and the high latitude regionsin North America and Eurasia became frozen. Comparing

  4. Data Assimilation to Extract Soil Moisture Information From SMAP Observations

    Science.gov (United States)

    Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

    2017-01-01

    Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

  5. Effects of soil moisture variations on deposition velocities above vegetation.

    Energy Technology Data Exchange (ETDEWEB)

    Wesely, M. L.; Song, J.; McMillen, R. T.; Meyers, T. P.; Environmental Research; Northern Illinois Univ.; National Oceanic and Atmospheric Administration

    2001-01-01

    The parameterized subgrid-scale surface flux (PASS) model provides a simplified means of using remote sensing data from satellites and limited surface meteorological information to estimate the influence of soil moisture on bulk canopy stomatal resistances to the uptake of gases over extended areas. PASS-generated estimates of bulk canopy stomatal resistance were used in a dry deposition module to compute gas deposition velocities with a horizontal resolution of 200 m for approximately 5000 km{sup 2} of agricultural crops and rangeland. Results were compared with measurements of O{sub 3} flux and concentrations made during April and May 1997 at two surface stations and from an aircraft. The trend in simulated O{sub 3} deposition velocity during soil moisture drydown over a period of a few days matched the trend observed at the two surface stations. For areas under the aircraft flight paths, the variability in simulated O{sub 3} deposition velocity was substantially smaller than the observed variability, while the averages over tens of kilometers were usually in agreement within 0.1 cm s{sup -1}. Model results indicated that soil moisture can have a major role in deposition of O{sub 3} and other substances strongly affected by canopy stomatal resistance.

  6. Uncertainty in SMAP Soil Moisture Measurements Caused by Dew

    Science.gov (United States)

    Hornbuckle, B. K.; Kruger, A.; Rowlandson, T. L.; Logsdon, S. D.; Kaleita, A.; Yueh, S. H.

    2009-12-01

    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 Soil Moisture and Ocean Salinity (SMOS) mission; and NASA's Soil Moisture Active-Passive (SMAP) mission. SMAP is unique in that it will measure both L-band brightness temperature and backscatter. Changes in the water content of vegetation tissue, as well as transient liquid water within the vegetation canopy such as dew or intercepted precipitation, all affect the L-band terrestrial brightness temperature and backscatter. Although dew will often be present during the planned SMAP overpass at 6 AM, the effect of dew on the L-band brightness temperature and backscatter is not completely understood. Some progress has been made in terms of the effect of dew on the L-band brightness temperature. For example, it is known that dew can either increase or decrease the L-band terrestrial brightness temperature (by up to 10 K) depending on the type of vegetation. This effect is significant but relatively small when compared to the sensitivity of L-band brightness temperature to soil moisture. On the other hand, NO measurements of the effect of dew on L-band backscatter have been reported. Considering the effect of dew on the backscatter at slightly shorter microwave wavelengths (X- and C-band) we hypothesize that there is the potential for an error of more the 5% in the estimate of soil moisture from the L-band backscatter when dew is present, which is unacceptable. We will present the first case study of the effect of dew on the L-band backscatter. We will use data collected by NASA's Passive and Active L-band System (PALS) over corn and soybean fields at the Iowa Validation Site on September 23 and 25, 2008. The conditions during this three-day experiment were ideal for deducing

  7. Multi-channel ground-penetrating radar to explore spatial variations in thaw depth and moisture content in the active layer of a permafrost site

    Directory of Open Access Journals (Sweden)

    U. Wollschläger

    2010-08-01

    Full Text Available Multi-channel ground-penetrating radar (GPR was applied at a permafrost site on the Tibetan Plateau to investigate the influence of surface properties and soil texture on the late-summer thaw depth and average soil moisture content of the active layer. Measurements were conducted on an approximately 85 × 60 m2 sized area with surface and soil textural properties that ranged from medium to coarse textured bare soil to finer textured, sparsely vegetated areas covered with fine, wind blown sand, and it included the bed of a gravel road. The survey allowed a clear differentiation of the various units. It showed (i a shallow thaw depth and low average soil moisture content below the sand-covered, vegetated area, (ii an intermediate thaw depth and high average soil moisture content along the gravel road, and (iii an intermediate to deep thaw depth and low to intermediate average soil moisture content in the bare soil terrain. From our measurements, we found hypotheses for the permafrost processes at this site leading to the observed late-summer thaw depth and soil moisture conditions. The study clearly indicates the complicated interactions between surface and subsurface state variables and processes in this environment. Multi-channel GPR is an operational technology to efficiently study such a system at scales varying from a few meters to a few kilometers.

  8. In-situ characterization of soil moisture content using a monopole probe

    Science.gov (United States)

    Sagnard, F. M.; Guilbert, V.; Fauchard, C.

    2009-06-01

    In this paper, a microwave non-destructive experimental tool based on a monopole antenna is used for the determination of the complex permittivity of soils. The monopole mounted on a ground plane is buried in the soil, and its reflection coefficient measured at the feed point by a vector network analyzer (VNA) depends on the dielectric properties of the surrounding medium at a given frequency. In particular, this study is focused on the evaluation of the change of dielectric properties of different soils with the moisture content. In general, the dependence of the dielectric properties of a soil with the antenna reflection coefficient is nonlinear in nature, and the solution of the inverse problem requires a sophisticated algorithm. Thus, we have used two types of modeling, analytical (Wu's approach) and numerical (FDTD), to further understand the influence of fundamental parameters (antenna geometry and soil properties) on the frequency response of the antenna reflection coefficient. These models have allowed us to develop a novel inverse algorithm for the determination of the mean real permittivity based on the position of the antenna resonant frequencies in a wide frequency range. Moreover, a high resolution algorithm based on the Prony's approach has been developed in order to fit the complex reflection coefficient and determine afterwards the complex permittivity and the volumetric moisture content of a soil. Experimental results from different types of sands have been analyzed.

  9. A review of the methods available for estimating soil moisture and its implications for water resource management

    Science.gov (United States)

    Dobriyal, Pariva; Qureshi, Ashi; Badola, Ruchi; Hussain, Syed Ainul

    2012-08-01

    SummaryThe maintenance of elevated soil moisture is an important ecosystem service of the natural ecosystems. Understanding the patterns of soil moisture distribution is useful to a wide range of agencies concerned with the weather and climate, soil conservation, agricultural production and landscape management. However, the great heterogeneity in the spatial and temporal distribution of soil moisture and the lack of standard methods to estimate this property limit its quantification and use in research. This literature based review aims to (i) compile the available knowledge on the methods used to estimate soil moisture at the landscape level, (ii) compare and evaluate the available methods on the basis of common parameters such as resource efficiency, accuracy of results and spatial coverage and (iii) identify the method that will be most useful for forested landscapes in developing countries. On the basis of the strengths and weaknesses of each of the methods reviewed we conclude that the direct method (gravimetric method) is accurate and inexpensive but is destructive, slow and time consuming and does not allow replications thereby having limited spatial coverage. The suitability of indirect methods depends on the cost, accuracy, response time, effort involved in installation, management and durability of the equipment. Our review concludes that measurements of soil moisture using the Time Domain Reflectometry (TDR) and Ground Penetrating Radar (GPR) methods are instantaneously obtained and accurate. GPR may be used over larger areas (up to 500 × 500 m a day) but is not cost-effective and difficult to use in forested landscapes in comparison to TDR. This review will be helpful to researchers, foresters, natural resource managers and agricultural scientists in selecting the appropriate method for estimation of soil moisture keeping in view the time and resources available to them and to generate information for efficient allocation of water resources and

  10. Assimilation of neural network soil moisture in land surface models

    Science.gov (United States)

    Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

    2017-04-01

    In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

  11. Automated system for generation of soil moisture products for agricultural drought assessment

    Science.gov (United States)

    Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

    2014-11-01

    Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically

  12. Application of Cosmic-ray Soil Moisture Sensing to Understand Land-atmosphere Interactions in Three North American Monsoon Ecosystems

    Science.gov (United States)

    Schreiner-McGraw, A.; Vivoni, E. R.; Franz, T. E.; Anderson, C.

    2013-12-01

    Human impacts on desert ecosystems have wide ranging effects on the hydrologic cycle which, in turn, influence interactions between the critical zone and the atmosphere. In this contribution, we utilize cosmic-ray soil moisture sensors at three human-modified semiarid ecosystems in the North American monsoon region: a buffelgrass pasture in Sonora, Mexico, a woody-plant encroached savanna ecosystem in Arizona, and a woody-plant encroached shrubland ecosystem in New Mexico. In each case, landscape heterogeneity in the form of bare soil and vegetation patches of different types leads to a complex mosaic of soil moisture and land-atmosphere interactions. Historically, the measurement of spatially-averaged soil moisture at the ecosystem scale (on the order of several hundred square meters) has been problematic. Thus, new advances in measuring cosmogenically-produced neutrons present an opportunity for observational and modeling studies in these ecosystems. We discuss the calibration of the cosmic-ray soil moisture sensors at each site, present comparisons to a distributed network of in-situ measurements, and verify the spatially-aggregated observations using the watershed water balance method at two sites. We focus our efforts on the summer season 2013 and its rainfall period during the North American monsoon. To compare neutron counts to the ground sensors, we utilized an aspect-elevation weighting algorithm to compute an appropriate spatial average for the in-situ measurements. Similarly, the water balance approach utilizes precipitation, runoff, and evapotranspiration measurements in the footprint of the cosmic-ray sensors to estimate a spatially-averaged soil moisture field. Based on these complementary approaches, we empirically determined a relationship between cosmogenically-produced neutrons and the spatially-aggregated soil moisture. This approach may improve upon existing methods used to calculate soil moisture from neutron counts that typically suffer from

  13. Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop

    Directory of Open Access Journals (Sweden)

    S. Zhang

    2017-09-01

    Full Text Available This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS Signal to Noise Ratio (SNR data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR. Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March. The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2  =  0.74, RMSE  =  0.009 m3 m−3 when the wheat is smaller than one wavelength (∼ 19 cm. The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2  =  0.98, RMSE  =  6

  14. Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop

    Science.gov (United States)

    Zhang, Sibo; Roussel, Nicolas; Boniface, Karen; Ha, Minh Cuong; Frappart, Frédéric; Darrozes, José; Baup, Frédéric; Calvet, Jean-Christophe

    2017-09-01

    This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2 = 0.74, RMSE = 0.009 m3 m-3) when the wheat is smaller than one wavelength (˜ 19 cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2 = 0.98, RMSE = 6.2 cm). The latter correlates with modeled above-ground dry

  15. Soil Moisture Active Passive (SMAP) Mission Level 4 Surface and Root Zone Soil Moisture (L4_SM) Product Specification Document

    Science.gov (United States)

    Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.

    2015-01-01

    This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.

  16. Lodgepole pine site index in relation to synoptic measures of climate, soil moisture and soil nutrients.

    Science.gov (United States)

    G. Geoff Wang; Shongming Huang; Robert A. Monserud; Ryan J. Klos

    2004-01-01

    Lodgepole pine site index was examined in relation to synoptic measures of topography, soil moisture, and soil nutrients in Alberta. Data came from 214 lodgepole pine-dominated stands sampled as a part of the provincial permanent sample plot program. Spatial location (elevation, latitude, and longitude) and natural subregions (NSRs) were topographic variables that...

  17. Soil moisture effects on the carbon isotope composition of soil respiration

    Science.gov (United States)

    Claire L. Phillips; Nick Nickerson; David Risk; Zachary E. Kayler; Chris Andersen; Alan Mix; Barbara J. Bond

    2010-01-01

    The carbon isotopic composition (δ13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low soil moisture or by low atmospheric humidity. Air humidity has also been shown to correlate with the δ13C of soil respiration, which suggests indirectly that recently fixed photosynthates...

  18. Effects of soil moisture content and temperature on methane uptake by grasslands on sandy soils.

    NARCIS (Netherlands)

    Pol-Van Dasselaar, van den A.; Beusichem, van M.L.; Oenema, O.

    1998-01-01

    Aerobic grasslands may consume significant amounts of atmospheric methane (CH4). We aimed (i) to assess the spatial and temporal variability of net CH4 fluxes from grasslands on aerobic sandy soils, and (ii) to explain the variability in net CH4 fluxes by differences in soil moisture content and

  19. Influence of soil moisture content on surface albedo and soil thermal ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 123; Issue 5. Influence of soil moisture content on surface albedo and soil thermal ... Department of Physics, Government College for Women, Thiruvananthapuram 695 014, Kerala, India. Kerala State Council for Science, Technology and Environment, Sasthra ...

  20. Influence of soil moisture content on surface albedo and soil thermal ...

    Indian Academy of Sciences (India)

    ture on the moraine of the Zongo glacier (Bolivia): Impli- cations for land surface modeling; Geophys. Res. Lett. 36. L02405, doi: 10.1029/2008GL036377. Guan X D, Huang J P, Guo N, Bi J R and Wang G Y. 2009 Variability of soil moisture and its relationship with surface albedo and soil thermal parameters over the Loess.

  1. Making Soil Moisture Sensors Better for Hydroclimatic Applications

    Science.gov (United States)

    Xu, C.; Zhang, K.; Hasan, E.; Hong, Y.

    2016-12-01

    Soil Moisture (SM) is key to understanding the flows of water and heat energy between the surface and atmosphere that impact weather and climate. The recent advances in remote sensing sensors, remarkably passive microwave, have provided significant information on soil water content and, if augmented with existing soil and other geographic information, such as terrain elevation and slope, may provide accurate data on soil water content. NASA's Soil Moisture Active Passive (SMAP) mission is an orbiting observatory that measures the top 5 cm of SM everywhere on Earth's surface over a three-year period, every 2-3 days. ESA's Soil Moisture and Ocean Salinity (SMOS) mission is partly dedicated to making global observations of SM. JAXA's Advanced Microwave Scanning Radiometer (AMSR)-2 measures weak microwave emissions from the surface and the atmosphere of the Earth and offers a set of daytime and nighttime data with more than 99% coverage of the Earth every 2 days. Factors such as vegetation cover, soil properties (density and texture), and surface roughness may affect the accuracy of remotely-sensed SM. Therefore, it is critical to compare the remotely-sensed SM data with in situ observations for calibration. The Oklahoma Mesonet monitors a wealth of atmospheric and hydrologic variables including solar radiation, humidity, temperature, wind speed and direction, and SM to aid in operational weather forecasting and environmental research across the state. The objective of this study is to evaluate the potential utility of the SM data retrieved from remote sensing techniques (SMAP, SMOS, and AMSR-2) by comparing them to Oklahoma Mesonet data. The correlation between the remotely-sensed SM data and daily Mesonet SM observations from the top 5, 25, and 60 cm of soil are determined for each site. This work is aimed at assessing the effectiveness of remotely-sensed data at observing hydro-climatological phenomena, calibrating the error in remote sensing observations, and

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

    Science.gov (United States)

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

    2011-08-01

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

  3. Winter soil respiration in a humid temperate forest: The roles of moisture, temperature, and snowpack

    Science.gov (United States)

    Contosta, Alexandra R.; Burakowski, Elizabeth A.; Varner, Ruth K.; Frey, Serita D.

    2016-12-01

    Winter soil respiration at midlatitudes can comprise a substantial portion of annual ecosystem carbon loss. However, winter soil carbon dynamics in these areas, which are often characterized by shallow snow cover, are poorly understood due to infrequent sampling at the soil surface. Our objectives were to continuously measure winter CO2 flux from soils and the overlying snowpack while also monitoring drivers of winter soil respiration in a humid temperate forest. We show that the relative roles of soil temperature and moisture in driving winter CO2 flux differed within a single soil-to-snow profile. Surface soil temperatures had a strong, positive influence on CO2 flux from the snowpack, while soil moisture exerted a negative control on soil CO2 flux within the soil profile. Rapid fluctuations in snow depth throughout the winter likely created the dynamic soil temperature and moisture conditions that drove divergent patterns in soil respiration at different depths. Such dynamic conditions differ from many previous studies of winter soil microclimate and respiration, where soil temperature and moisture are relatively stable until snowmelt. The differential response of soil respiration to temperature and moisture across depths was also a unique finding as previous work has not simultaneously quantified CO2 flux from soils and the snowpack. The complex interplay we observed among snow depth, soil temperature, soil moisture, and CO2 flux suggests that winter soil respiration in areas with shallow seasonal snow cover is more variable than previously understood and may fluctuate considerably in the future given winter climate change.

  4. Active layer and permafrost properties, including snow depth, soil temperature, and soil moisture, Barrow, Alaska, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains soil temperature, soil moisture, thaw depth, and snow depth data collected at test sites near Barrow, Alaska, during the following years. Soil...

  5. Spatial distribution of moisture and its relation with soil texture

    Directory of Open Access Journals (Sweden)

    Kenneth Largaespada

    2015-11-01

    Full Text Available At Esmeralda Farm (Guácimo, Limón Province, C.R., planted to banana cv. Valery, the spatial distribution of soil humidity, and its relationship to some physical properties, were analyzed to determine the variability between the traditional method and use of TDR (Time Domain Reflectrometer in the determination of soil humidity. Sampling was done in a quadricuar pattern, with 36 measurement points georeferenced by GPS at 2 soil depths. At each point the volumetric soil water was measured with 3 different TDR equipments (300, MP and MT, and compared with the traditional method of volumetric humidity (VHM determination. Soil samples were also collected, for texture analysis; with these data, a geostatistical analysis was performed and the corresponding maps were drafted. The soils, of Loam to clayey Loam texture, showed variability between TDR and these determinations regarding the MHV, regardless of depth. On the surface, the highest correlation was found between the values of MHV and TDR-300 (r=0.69, followed by TDRMT (r=0.63 and finally the TDR-MP (r=0.59. At 30 to 60 cm depth, a positive but lower ratio values was found compared MHV with TRD- 300 and TDR-MP (0.47 and 0.38, respectively; no relationship was found with TDR-MT at this depth. In terms of field moisture map, a good representation between methods was found and it can be said that this method was effective in representing the spatial variation of soil moisture.

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

    Science.gov (United States)

    Camargo, Edinalvo R; Senseman, Scott A; Haney, Richard L; Guice, John B; McCauley, Garry N

    2013-12-01

    Saflufenacil dissipation in soils under different moisture conditions is not available in the scientific literature. 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. The accelerated solvent extraction (ASE) residue analytical method developed to conduct the study resulted in recovery greater than 80% for the combinations of soils and moisture conditions. Saflufenacil degradation was faster at field capacity for all soils, except for Morey soil. Herbicide half-life was 28.6, 15.0 and 23.1 days under field capacity treatments and 58.8, 36.9 and 79.7 under saturated conditions for Nada, Crowley and Gilbert soils respectively. A half-life no longer than 80 days was observed for the combination of soils and moisture treatments. An ASE method was developed and used to extract saflufenacil from soil samples. Half-life averaged among soils was 59 and 33 days for saturated and field capacity respectively. Saflufenacil persistence in the environment was 2-3 times longer under flooded conditions for most of the soils studied. © 2013 Society of Chemical Industry.

  7. Influence of physical and chemical properties of different soil types on optimal soil moisture for tillage

    Directory of Open Access Journals (Sweden)

    Vladimir Zebec

    2017-01-01

    Full Text Available Soil plasticity is the area of soil consistency, i.e. it represents a change in soil condition due to different soil moisture influenced by external forces activity. Consistency determines soil resistance in tillage, therefore, the aim of the research was to determine the optimum soil moisture condition for tillage and the influence of the chemical and physical properties of the arable land horizons on the soil plasticity on three different types of soil (fluvisol, luvisol and humic glaysol. Statistically significant differences were found between all examined soil types, such as the content of clay particles, the density of packaging and the actual and substitution acidity, the cation exchange capacity and the content of calcium. There were also statistically significant differences between the examined types of soil for the plasticity limit, liquid limit and the plasticity index. The average established value of plasticity limit as an important element for determining the optimal moment of soil tillage was 18.9% mass on fluvisol, 24.0% mass on luvisol and 28.6% mass on humic glaysol. Very significant positive direction correlation with plasticity limits was shown by organic matter, clay, fine silt, magnesium, sodium and calcium, while very significant negative direction correlation was shown by hydrolytic acidity, coarse sand, fine sand and coarse silt. Created regression models can estimate the optimal soil moisture condition for soil cultivation based on the basic soil properties. The model precision is significantly increased by introducing a greater number of agrochemical and agrophysical soil properties, and the additional precision of the model can be increased by soil type data.

  8. Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

    Science.gov (United States)

    Shi, Jian-Cheng; Wang, James; Hsu, Ann Y.; ONeill, Peggy E.; Engman, Edwin T.

    1997-01-01

    An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

  9. The Soil Moisture Active Passive Experiments (SMAPEx) for SMAP Algorithm Development (Invited)

    Science.gov (United States)

    Panciera, R.; Walker, J. P.; Ryu, D.; Gray, D.; Jackson, T. J.; Yardley, H.

    2010-12-01

    The availability of global L-band observations from passive (the recently launched SMOS), and active (such as the PALSAR) microwave sensors has boosted the interest in making joint use of the two techniques to improve the retrieval of global near-surface soil moisture at unprecedented resolutions. The Soil Moisture Active Passive (SMAP) mission (scheduled launch, 2014) will fully exploit this synergy by providing concurrent active (radar) and passive (radiometer) microwave observations, resulting in passive-only, active-only and a merged active-passive soil moisture products at spatial resolutions of respectively 40km, 3km and 9km. The Soil Moisture Active Passive Experiments (SMAPEx) are a series of airborne field experiments specifically designed for algorithm development for SMAP and currently ongoing in the context of the SMAP pre-launch cal/val activities for Australia. Four SMAPEx campaigns are scheduled across the 2010-2011 seasonal cycle, with the first campaign (SMAPEx-1) successfully conducted on moderately wet winter conditions (July 5-10, 2010) and the second campaign (SMAPEx-2), scheduled for the summer (December 4-8,2010). SMAPEx is making use of a novel SMAP airborne simulator, including an L-band radar and radiometer to collect SMAP-like data over a well monitored semi-arid agricultural area in the Murrumbidgee catchment in south-eastern Australia. High resolution radar and radiometer observations collected during SMAPEx are supported by extensive ground sampling of soil moisture and ancillary data, allowing for testing of a variety of algorithms over semi-arid agricultural areas, typical of the Australian environment but similar to large areas of the central continental USA, including radiometer-only, radar-only, merged active-passive, downscaling and radar change-detection algorithms. In this paper a preliminary assessment of the performance of the radar-only and radiometer-only retrieval algorithms proposed as baseline for SMAP is presented. The

  10. A sensor array system for monitoring moisture dynamics inunsaturated soil

    Energy Technology Data Exchange (ETDEWEB)

    Salve, R.; Cook, P.J.

    2007-05-15

    To facilitate investigations of moisture dynamics inunsaturated soil, we have developed a technique to qualitatively monitorpatterns of saturation changes. Field results suggest that this device,the sensor array system (SAS), is suitable for determining changes inrelative wetness along vertical soil profiles. The performance of theseprobes was compared with that of the time domain reflectometry (TDR)technique under controlled and field conditions. Measurements from bothtechniques suggest that by obtaining data at high spatial and temporalresolution, the SAS technique was effective in determining patterns ofsaturation changes along a soil profile. In addition, hardware used inthe SAS technique was significantly cheaper than the TDR system, and thesensor arrays were much easier to install along a soilprofile.

  11. Observation of soil moisture variability in agricultural and grassland field soils using a wireless sensor network

    Science.gov (United States)

    Priesack, Eckart; Schuh, Max

    2014-05-01

    Soil moisture dynamics is a key factor of energy and matter exchange between land surface and atmosphere. Therefore long-term observation of temporal and spatial soil moisture variability is important in studying impacts of climate change on terrestrial ecosystems and their possible feedbacks to the atmosphere. Within the framework of the network of terrestrial environmental observatories TERENO we installed at the research farm Scheyern in soils of two fields (of ca. 5 ha size each) the SoilNet wireless sensor network (Biogena et al. 2010). The SoilNet in Scheyern consists of 94 sensor units, 45 for the agricultural field site and 49 for the grassland site. Each sensor unit comprises 6 SPADE sensors, two sensors placed at the depths 10, 30 and 50 cm. The SPADE sensor (sceme.de GmbH, Horn-Bad Meinberg Germany) consists of a TDT sensor to estimate volumetric soil water content from soil electrical permittivity by sending an electromagnetic signal and measuring its propagation time, which depends on the soil dielectric properties and hence on soil water content. Additionally the SPADE sensor contains a temperature sensor (DS18B20). First results obtained from the SoilNet measurements at both fields sites will be presented and discussed. The observed high temporal and spatial variability will be analysed and related to agricultural management and basic soil properties (bulk density, soil texture, organic matter content and soil hydraulic characteristics).

  12. State of the Art in Large-Scale Soil Moisture Monitoring

    Science.gov (United States)

    Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.; hide

    2013-01-01

    Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

  13. Spatial Variability of Soil Properties and its Impact on Simulated Surface Soil Moisture Patterns

    Science.gov (United States)

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

    2015-12-01

    The spatial variability of soil properties (particle size distribution, PSD, and bulk density, BD) has large effects on the spatial variability of soil moisture and therefore on plant growth and surface exchange processes. In model studies, soil properties from soil maps are considered homogeneous over mapping units, which neglects the small scale variability of soil properties and leads to underestimated small scale variability of simulated soil moisture. This study focuses on the validation of spatial variability of simulated surface soil moisture (SSM) in a winter wheat field in Western Germany using the eco-hydrological simulation system DANUBIA. SSM measurements were conducted at 20 different sampling points and nine different dates in 2008. Frequency distributions of BD and PSD were derived from an independent dataset (n = 486) of soil physical properties from Germany and the USA. In the simulations, BD and PSD were parameterized according to these frequency distributions. Mean values, coefficients of variation and frequency distributions of simulated SSM were compared to the field measurements. Using the heterogeneous model parameterization, up to 76 % of the frequency distribution of the measured SSM can be explained. Furthermore, the results show that BD has a larger impact on the variability of SSM than PSD. The introduced approach can be used for simulating mean SSM and SSM variability more accurately and can form the basis for a spatially heterogeneous parameterization of soil properties in mesoscale models.

  14. [Response of mineralization of dissolved organic carbon to soil moisture in paddy and upland soils in hilly red soil region].

    Science.gov (United States)

    Chen, Xiang-Bi; Wang, Ai-Hua; Hu, Le-Ning; Huang, Yuan; Li, Yang; He, Xun-Yang; Su, Yi-Rong

    2014-03-01

    Typical paddy and upland soils were collected from a hilly subtropical red-soil region. 14C-labeled dissolved organic carbon (14C-DOC) was extracted from the paddy and upland soils incorporated with 14C-labeled straw after a 30-day (d) incubation period under simulated field conditions. A 100-d incubation experiment (25 degrees C) with the addition of 14C-DOC to paddy and upland soils was conducted to monitor the dynamics of 14C-DOC mineralization under different soil moisture conditions [45%, 60%, 75%, 90%, and 105% of the field water holding capacity (WHC)]. The results showed that after 100 days, 28.7%-61.4% of the labeled DOC in the two types of soils was mineralized to CO2. The mineralization rates of DOC in the paddy soils were significantly higher than in the upland soils under all soil moisture conditions, owing to the less complex composition of DOC in the paddy soils. The aerobic condition was beneficial for DOC mineralization in both soils, and the anaerobic condition was beneficial for DOC accumulation. The biodegradability and the proportion of the labile fraction of the added DOC increased with the increase of soil moisture (45% -90% WHC). Within 100 days, the labile DOC fraction accounted for 80.5%-91.1% (paddy soil) and 66.3%-72.4% (upland soil) of the cumulative mineralization of DOC, implying that the biodegradation rate of DOC was controlled by the percentage of labile DOC fraction.

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

    Directory of Open Access Journals (Sweden)

    J. A. Yeakley

    1998-01-01

    Full Text Available Soil moisture gradients along hillslopes in humid watersheds, although indicated by vegetation gradients and by studies using models, have been difficult to confirm empirically. While soil properties and topographic features are the two general physio-graphic factors controlling soil moisture on hillslopes, studies have shown conflicting results regarding which factor is more important. The relative importance of topographic and soil property controls was examined in an upland forested watershed at the Coweeta Hydrologic Laboratory in the southern Appalachian mountains. Soil moisture was measured along a hillslope transect with a mesic-to-xeric forest vegetation gradient over a period spanning precipitation extremes. The hillslope was transect instrumented with a time domain reflectometry (TDR network at two depths. Soil moisture was measured during a severe autumn drought and subsequent winter precipitation recharge. In the upper soil depth (0-30 cm, moisture gradients persisted throughout the measurement period, and topography exerted dominant control. For the entire root zone (0-90 cm, soil moisture gradients were found only during drought. Control on soil moisture was due to both topography and storage before drought. During and after recharge, variations in soil texture and horizon distribution exerted dominant control on soil moisture content in the root zone (0-90 cm. These results indicate that topographic factors assert more control over hillslope soil moisture during drier periods as drainage progresses, while variations in soil water storage properties are more important during wetter periods. Hillslope soil moisture gradients in southern Appalachian watersheds appear to be restricted to upper soil layers, with deeper hillslope soil moisture gradients occurring only with sufficient drought.

  16. Soil moisture data as a constraint for groundwater recharge estimation

    Science.gov (United States)

    Mathias, Simon A.; Sorensen, James P. R.; Butler, Adrian P.

    2017-09-01

    Estimating groundwater recharge rates is important for water resource management studies. Modeling approaches to forecast groundwater recharge typically require observed historic data to assist calibration. It is generally not possible to observe groundwater recharge rates directly. Therefore, in the past, much effort has been invested to record soil moisture content (SMC) data, which can be used in a water balance calculation to estimate groundwater recharge. In this context, SMC data is measured at different depths and then typically integrated with respect to depth to obtain a single set of aggregated SMC values, which are used as an estimate of the total water stored within a given soil profile. This article seeks to investigate the value of such aggregated SMC data for conditioning groundwater recharge models in this respect. A simple modeling approach is adopted, which utilizes an emulation of Richards' equation in conjunction with a soil texture pedotransfer function. The only unknown parameters are soil texture. Monte Carlo simulation is performed for four different SMC monitoring sites. The model is used to estimate both aggregated SMC and groundwater recharge. The impact of conditioning the model to the aggregated SMC data is then explored in terms of its ability to reduce the uncertainty associated with recharge estimation. Whilst uncertainty in soil texture can lead to significant uncertainty in groundwater recharge estimation, it is found that aggregated SMC is virtually insensitive to soil texture.

  17. Soil Moisture Retrieval Based on GPS Signal Strength Attenuation

    Directory of Open Access Journals (Sweden)

    Franziska Koch

    2016-07-01

    Full Text Available Soil moisture (SM is a highly relevant variable for agriculture, the emergence of floods and a key variable in the global energy and water cycle. In the last years, several satellite missions have been launched especially to derive large-scale products of the SM dynamics on the Earth. However, in situ validation data are often scarce. We developed a new method to retrieve SM of bare soil from measurements of low-cost GPS (Global Positioning System sensors that receive the freely available GPS L1-band signals. The experimental setup of three GPS sensors was installed at a bare soil field at the German Weather Service (DWD in Munich for almost 1.5 years. Two GPS antennas were installed within the soil column at a depth of 10 cm and one above the soil. SM was successfully retrieved based on GPS signal strength losses through the integral soil volume. The results show high agreement with measured and modelled SM validation data. Due to its non-destructive, cheap and low power setup, GPS sensor networks could also be used for potential applications in remote areas, aiming to serve as satellite validation data and to support the fields of agriculture, water supply, flood forecasting and climate change.

  18. Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

    Directory of Open Access Journals (Sweden)

    C. Cammalleri

    2017-12-01

    Full Text Available Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/, the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1 the soil moisture from the Lisflood distributed hydrological model (namely LIS, (2 the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST, and (3 the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI. Due to the independency of these three datasets, the triple collocation (TC technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.

  19. Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

    Science.gov (United States)

    Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad

    2017-12-01

    Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, edo.jrc.ec.europa.eu/gdo/" target="_blank">http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the

  20. [Effect of Biochar Application on Soil Aggregates Distribution and Moisture Retention in Orchard Soil].

    Science.gov (United States)

    An, Yan; Ji, Qiang; Zhao, Shi-xiang; Wang, Xu-dong

    2016-01-15

    Applying biochar to soil has been considered to be one of the important practices in improving soil properties and increasing carbon sequestration. In order to investigate the effects of biochar application on soil aggregates distribution and its organic matter content and soil moisture constant in different size aggregates, various particle-size fractions of soil aggregates were obtained with the dry-screening method. The results showed that, compared to the treatment without biochar (CK), the application of biochar reduced the mass content of 5-8 mm and biochar application. The mean diameter of soil aggregates was reduced by biochar application at 0-10 cm soil horizon. However, the effect of biochar application on the mean diameter of soil aggregates at 10-20 cm soil horizon was not significant. Compared to CK, biochar application significantly increased soil organic carbon content in aggregates, especially in 1-2 mm aggregates which was increased by > 70% compared to CK. Both the water holding capacity and soil porosity were significantly increased by biochar application. Furthermore, the neutral biochar was more effective than alkaline biochar in increasing soil moisture.

  1. Microwave brightness temperature and thermal inertia - towards synergistic method of high-resolution soil moisture retrieval

    Science.gov (United States)

    Lukowski, Mateusz; Usowicz, Boguslaw; Sagan, Joanna; Szlazak, Radoslaw; Gluba, Lukasz; Rojek, Edyta

    2017-04-01

    Soil moisture is an important parameter in many environmental studies, as it influences the exchange of water and energy at the interface between the land surface and the atmosphere. Accurate assessment of the soil moisture spatial and temporal variations is crucial for numerous studies; starting from a small scale of single field, then catchment, mesoscale basin, ocean conglomeration, finally ending at the global water cycle. Despite numerous advantages, such as fine accuracy (undisturbed by clouds or daytime conditions) and good temporal resolution, passive microwave remote sensing of soil moisture, e.g. SMOS and SMAP, are not applicable to a small scale - simply because of too coarse spatial resolution. On the contrary, thermal infrared-based methods of soil moisture retrieval have a good spatial resolution, but are often disturbed by clouds and vegetation interferences or night effects. The methods that base on point measurements, collected in situ by monitoring stations or during field campaigns, are sometimes called "ground truth" and may serve as a reference for remote sensing, of course after some up-scaling and approximation procedures that are, unfortunately, potential source of error. Presented research concern attempt to synergistic approach that join two remote sensing methods: passive microwave and thermal infrared, supported by in situ measurements. Microwave brightness temperature of soil was measured by ELBARA, the radiometer at 1.4 GHz frequency, installed at 6 meters high tower at Bubnow test site in Poland. Thermal inertia around the tower was modelled using the statistical-physical model whose inputs were: soil physical properties, its water content, albedo and surface temperatures measured by an infrared pyrometer, directed at the same footprint as ELBARA. The results coming from this method were compared to in situ data obtained during several field campaigns and by the stationary agrometeorological stations. The approach seems to be

  2. Feasibility of soil moisture monitoring with heated fiber optics

    Science.gov (United States)

    Sayde, Chadi; Gregory, Christopher; Gil-Rodriguez, Maria; Tufillaro, Nick; Tyler, Scott; van de Giesen, Nick; English, Marshall; Cuenca, Richard; Selker, John S.

    2010-06-01

    Accurate methods are needed to measure changing soil water content from meter to kilometer scales. Laboratory results demonstrate the feasibility of the heat pulse method implemented with fiber optic temperature sensing to obtain accurate distributed measurements of soil water content. A fiber optic cable with an electrically conductive armoring was buried in variably saturated sand and heated via electrical resistance to create thermal pulses monitored by observing the distributed Raman backscatter. A new and simple interpretation of heat data that takes advantage of the characteristics of fiber optic temperature measurements is presented. The accuracy of the soil water content measurements varied approximately linearly with water content. At volumetric moisture content of 0.05 m3/m3 the standard deviation of the readings was 0.001 m3/m3, and at 0.41 m3/m3 volumetric moisture content the standard deviation was 0.046 m3/m3. This uncertainty could be further reduced by averaging several heat pulse interrogations and through use of a higher-performance fiber optic sensing system.

  3. Soil moisture determination by means of the data driven models

    Science.gov (United States)

    Cisty, Milan; Suchar, Martin; Bajtek, Zbynek

    2010-05-01

    Information's about soil water content are in the planning of water resources and management very valuable. Modeling and predicting soil water transfer is very important in agriculture or hydrology - e.g. for purposes of the effective irrigation management. Many tried and proven methods of estimating or measuring soil moisture are available. The choice of the method which in particular case is eligible, depends on a variety of factors such as accuracy, cost, and ease of use. One of the most important hydro physical characteristics of soil is water retention curve (WRC), which is input to various hydraulic and hydrological models and reflects the energy dependence of soil water and the water content, e.g. the relationship between soil moisture and moisture potential. The method of determining the water retention curve points in laboratory conditions is very expensive, time consuming and labor intensive. In soil physics, therefore, were developed methods for determining soil hydro physical characteristics from easier obtained characteristics - soil granularity composition, organic matter content and bulk density. For these models (or relations) have been established title pedotransfer functions (PTF). These functions specify different soil characteristics and properties from relationship with another. The submitted work compares the creation of such functional dependencies using neural networks, hybrid self-organizing map (SOM) and support vector machines (SVM) model and standard multi-linear regression method. The SVMs formulate a quadratic optimization problem that avoids local minima problems, which makes them often superior to traditional (iterative) learning algorithms such as multi-layer perceptron (MLP) type of neural network. Input data are taken from Zahorská lowland in Slovakia. It was taken 140 soil samples from various localities of Zahorská lowland on finding soil characteristics and on the expression of water retention curve points. Sandy soils are

  4. Soil Moisture Monitoring using Surface Electrical Resistivity measurements

    Science.gov (United States)

    Calamita, Giuseppe; Perrone, Angela; Brocca, Luca; Straface, Salvatore

    2017-04-01

    The relevant role played by the soil moisture (SM) for global and local natural processes results in an explicit interest for its spatial and temporal estimation in the vadose zone coming from different scientific areas - i.e. eco-hydrology, hydrogeology, atmospheric research, soil and plant sciences, etc... A deeper understanding of natural processes requires the collection of data on a higher number of points at increasingly higher spatial scales in order to validate hydrological numerical simulations. In order to take the best advantage of the Electrical Resistivity (ER) data with their non-invasive and cost-effective properties, sequential Gaussian geostatistical simulations (sGs) can be applied to monitor the SM distribution into the soil by means of a few SM measurements and a densely regular ER grid of monitoring. With this aim, co-located SM measurements using mobile TDR probes (MiniTrase), and ER measurements, obtained by using a four-electrode device coupled with a geo-resistivimeter (Syscal Junior), were collected during two surveys carried out on a 200 × 60 m2 area. Two time surveys were carried out during which Data were collected at a depth of around 20 cm for more than 800 points adopting a regular grid sampling scheme with steps (5 m) varying according to logistic and soil compaction constrains. The results of this study are robust due to the high number of measurements available for either variables which strengthen the confidence in the covariance function estimated. Moreover, the findings obtained using sGs show that it is possible to estimate soil moisture variations in the pedological zone by means of time-lapse electrical resistivity and a few SM measurements.

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

    Science.gov (United States)

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

    2015-01-01

    Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

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

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available 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.

  7. FTIR and ESEM Analysis of soil moisture Microscopic conservation feature with liquid membrane

    Directory of Open Access Journals (Sweden)

    Gu Jian

    2016-01-01

    Full Text Available Liquid membrane applied in soil has a good soil moisture conservation and evaporation suppression performance. Application of spectrum analysis technology to understand its structure and micro morphological characteristics will be help to reveal the soil moisture conservation mechanism of liquid membrane. In this paper, we used the three types of liquid membrane as the research object based on the laboratory preparation, with infrared spectrometer (FTIR and environmental scanning electron microscope (ESEM as the means, analysis the soil moisture mechanism of liquid membrane. The results showed that the -OH between the CMC and PVA generated intermolecular hydrogen bonds, the formation of hydrogen bonds between molecules of the two components strengthened the two-phase’s compatibility, increasing the liquid membrane’s effective groups and forming a dense mesh structure.ESEM observation showed that liquid membrane can effectively cementing soil particles, generating the soil-membrane structure, reducing soil moisture to evaporate, improve soil moisture conservation performance.

  8. Quantifying the heterogeneity of soil compaction, physical soil properties and soil moisture across multiple spatial scales

    Science.gov (United States)

    Coates, Victoria; Pattison, Ian; Sander, Graham

    2016-04-01

    England's rural landscape is dominated by pastoral agriculture, with 40% of land cover classified as either improved or semi-natural grassland according to the Land Cover Map 2007. Since the Second World War the intensification of agriculture has resulted in greater levels of soil compaction, associated with higher stocking densities in fields. Locally compaction has led to loss of soil storage and an increased in levels of ponding in fields. At the catchment scale soil compaction has been hypothesised to contribute to increased flood risk. Previous research (Pattison, 2011) on a 40km2 catchment (Dacre Beck, Lake District, UK) has shown that when soil characteristics are homogeneously parameterised in a hydrological model, downstream peak discharges can be 65% higher for a heavy compacted soil than for a lightly compacted soil. However, at the catchment scale there is likely to be a significant amount of variability in compaction levels within and between fields, due to multiple controlling factors. This research focusses in on one specific type of land use (permanent pasture with cattle grazing) and areas of activity within the field (feeding area, field gate, tree shelter, open field area). The aim was to determine if the soil characteristics and soil compaction levels are homogeneous in the four areas of the field. Also, to determine if these levels stayed the same over the course of the year, or if there were differences at the end of the dry (October) and wet (April) periods. Field experiments were conducted in the River Skell catchment, in Yorkshire, UK, which has an area of 120km2. The dynamic cone penetrometer was used to determine the structural properties of the soil, soil samples were collected to assess the bulk density, organic matter content and permeability in the laboratory and the Hydrosense II was used to determine the soil moisture content in the topsoil. Penetration results show that the tree shelter is the most compacted and the open field area

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

    Science.gov (United States)

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

    2016-12-01

    Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.

  10. Long-term soil moisture patterns in a northern Minnesota forest

    Science.gov (United States)

    Salli F. Dymond; Randall K. Kolka; Paul V. Bolstad; Stephen D. Sebestyen

    2014-01-01

    Forest hydrological and biogeochemical processes are highly dependent on soil water. At the Marcell Experimental Forest, seasonal patterns of soil moisture have been monitored at three forested locations since 1966. This unique, long-term data set was used to analyze seasonal trends in soil moisture as well as the influence of time-lagged precipitation and modified...

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

    Science.gov (United States)

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

  12. Persistence and memory timescales in root-zone soil moisture dynamics

    Science.gov (United States)

    Khaled Ghannam; Taro Nakai; Athanasios Paschalis; Andrew C. Oishi; Ayumi Kotani; Yasunori Igarashi; Tomo' omi Kumagai; Gabriel G. Katul

    2016-01-01

    The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however,...

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

    Science.gov (United States)

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

    1998-01-01

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

  14. The use of soil moisture - remote sensing products for large-scale groundwater modeling and assessment

    NARCIS (Netherlands)

    Sutanudjaja, E.H.

    2012-01-01

    In this thesis, the possibilities of using spaceborne remote sensing for large-scale groundwater modeling are explored. We focus on a soil moisture product called European Remote Sensing Soil Water Index (ERS SWI, Wagner et al., 1999) - representing the upper profile soil moisture. As a test-bed, we

  15. Regional soil moisture monitoring network in the Raam catchment in the Netherlands - 2016-04 / 2017-04

    NARCIS (Netherlands)

    Benninga, H.F.; Carranza, C.D.; Pezij, M.; Ploeg, van der M.J.; Augustijn, D.C.M.; Velde, van der R.

    2017-01-01

    The Raam soil moisture measurement network dataset contains soil moisture and soil temperature measurements for 15 locations in the Raam, which is a 223-km2 river catchment in the southeast of the Netherlands. The network monitors soil moisture in the unsaturated zone for different soil textures and

  16. Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

  17. A soil moisture and temperature network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, Niels; Jensen, K. H.

    2011-01-01

    SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes......The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data globally, and thus product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and temperature network of Decagon ECH2O 5TE...... representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature...

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

    Science.gov (United States)

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

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be

  19. The role of tree species and soil moisture in soil organic matter stabilization and destabilization

    Science.gov (United States)

    Hatten, J. A.; Dewey, J.; Roberts, S.; McNeal, K.; Shaman, A.

    2014-12-01

    Inputs of labile organic substrates to soils are commonly associated with elevated soil organic carbon mineralization rates; this process is known as the priming effect. Plant presence and soil conditions (i.e. water regime, nutrient status) are known to be interacting factors governing priming. In this study, we examine the role of differing species, loblolly pine (Pinus taeda L.) and nuttall oak (Quercus texana B.), and moisture regimes (low and high) upon the soil priming effect in a fine textured soil. We explore whether there is depletion of original soil carbon and concurrent replacement through addition of fresh organic matter from the planted tree species. By employing a series of planted and plant-free pots in a greenhouse mesocosm study, we were able to characterize the composition of soil organic matter and its carbon with the use of CuO oxidation products (e.g. lignin, cutin/suberin biomarkers). Carbon was elevated on the low moisture samples relative to all other treatments, and the C:N ratio suggests that newly produced plant carbon replaced original soil carbon. The soil lignin content of the planted treatments was lower than the plant-free treatments suggesting that lignin present in the original soil may have been preferentially degraded by priming and not replaced. We will discuss the utility of CuO oxidation products to explore soil organic carbon dynamics and the implications of understanding the role of species and soil moisture in predicting the response of soil carbon to land use and climate change.

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

    Science.gov (United States)

    Narayan, Ujjwal

    Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it

  1. Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data

    Directory of Open Access Journals (Sweden)

    Yayong Sun

    2017-03-01

    Full Text Available The Soil Moisture Active Passive (SMAP satellite makes coincident global measurements of soil moisture using an L-band radar instrument and an L-band radiometer. It is crucial to evaluate the errors in the newest L-band SMAP satellite-derived soil moisture products, before they are routinely used in scientific research and applications. This study represents the first evaluation of the SMAP radiometer soil moisture product over China. In this paper, a preliminary evaluation was performed using sparse in situ measurements from 655 China Meteorological Administration (CMA monitoring stations between 1 April 2015 and 31 August 2016. The SMAP radiometer-derived soil moisture product was evaluated against two schemes of original soil moisture and the soil moisture anomaly in different geographical zones and land cover types. Four performance metrics, i.e., bias, root mean square error (RMSE, unbiased root mean square error (ubRMSE, and the correlation coefficient (R, were used in the accuracy evaluation. The results indicated that the SMAP radiometer-derived soil moisture product agreed relatively well with the in situ measurements, with ubRMSE values of 0.058 cm3·cm−3 and 0.039 cm3·cm−3 based on original data and anomaly data, respectively. The values of the SMAP radiometer-based soil moisture product were overestimated in wet areas, especially in the Southwest China, South China, Southeast China, East China, and Central China zones. The accuracies over croplands and in Northeast China were the worst. Soil moisture, surface roughness, and vegetation are crucial factors contributing to the error in the soil moisture product. Moreover, radio frequency interference contributes to the overestimation over the northern portion of the East China zone. This study provides guidelines for the application of the SMAP-derived soil moisture product in China and acts as a reference for improving the retrieval algorithm.

  2. Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

    Directory of Open Access Journals (Sweden)

    S. Juglea

    2010-08-01

    Full Text Available In the framework of Soil Moisture and Ocean Salinity (SMOS Calibration/Validation (Cal/Val activities, this study addresses the use of the PERSIANN-CCS1database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km2. The study focuses on the Valencia Anchor Station (VAS experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe.

    A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km2 requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66% but the precipitation occurrences are in general retrieved (about 67%.

    To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT model – ISBA (Interactions between Soil Biosphere Atmosphere is used. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil is depicted by a comparison between different soil moisture data. Point-like and spatialized simulated data using rain gauge observations or PERSIANN – CCS database as well as ground measurements are used. It is shown that a good adequacy is reached in most part of the year, the precipitation differences having less impact upon the simulated soil moisture. The behaviour of simulated surface soil moisture at SMOS scale is verified by the use of remote sensing data from the Advanced

  3. Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

    Science.gov (United States)

    Juglea, S.; Kerr, Y.; Mialon, A.; Lopez-Baeza, E.; Braithwaite, D.; Hsu, K.

    2010-08-01

    In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS1database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km2). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km2) requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66%) but the precipitation occurrences are in general retrieved (about 67%). To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT) model - ISBA (Interactions between Soil Biosphere Atmosphere) is used. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil is depicted by a comparison between different soil moisture data. Point-like and spatialized simulated data using rain gauge observations or PERSIANN - CCS database as well as ground measurements are used. It is shown that a good adequacy is reached in most part of the year, the precipitation differences having less impact upon the simulated soil moisture. The behaviour of simulated surface soil moisture at SMOS scale is verified by the use of remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E). We show

  4. Solar-induced Chloropyll Fluorescence Reveals Depth-specific Relationships to Soil Moisture: An Assesment Based on a Novel Automated Field Spectroscopy System

    Science.gov (United States)

    Liu, L.; Wu, J.

    2016-12-01

    Soil moisture play an important role in regulating both the water and energy balance of land surface. Water stress is frequently happened when soil moisture cannot meet the needs of normal growth and developments of plants. It will thus influence the efficiency of photosynthesis and spatial and temporal distribution characteristics of chlorophyll fluorescence. As a consequence, chlorophyll fluorescence can not only be the proxy of photosynthesis but may also provide some information on soil moisture. To prove the viewpoint, a novel automatic system was designed to measure long time series of solar induced chlorophyll fluorescence (SIF) at 760 nm (F760) and 687 nm (F687) of wheat in two plots with different hydraulic gradients. F760 and F687 showed a negative correlation with averaged soil moisture at seasonal scales (R2=0.14, p<0.05 and R2=0.25, p<0.01). However, the significance of correlation varied with depths of soil. Surface soil moisture in 10 cm or 20 cm has a better correlation with SIF than that in 50 cm (for F760, R2 =0.30 (p<0.01), 0.40 (p<0.01) and 0.17 (p<0.05); for F687, R2 =0.20 (p<0.01), 0.31 (p<0.01) and 0.07 (not significance)). Moreover, SIF at different bands also showed different relationships with soil moisture in surface soil. For example, soil moisture in the same depth showed better correlation with F760 than F687. Based on above results, F760 and F687 were used to distinguish two plots with different soil moisture. Each of them showed significant difference of two plots when soil moisture difference is greater than 0.11m3/m3.Yet fluorescence ratio F687/F760 was a better index to distinguish difference of soil moisture than F760 and F687, it showed significant difference in all selected days at 0.05 significant level. Our results provide ground-based evidence that SIF is directly related to soil moisture, and confirm that F687/F760 is better to recognize the difference of soil moisture than F760 and F687, hence SIF has a potential as a new

  5. Simulation of Soil Moisture Development in Flood Protecting Earth Dams

    Science.gov (United States)

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

    2007-12-01

    Extreme floods represent an increased risk for urban areas and agriculture. Time to time the protective earth dams are destroyed by a suddenly increased amount of water with destroing or even cathastrophic consequences. A numerical study of the soil moisture development within the earth body during the flood is simulated under a selection of boundary conditions. Several soil materials are considered. Simulations are performed firstly for homogeneous materials using the 2D single domain approach, in the second step the dual permeability simulations are done assuming inhomogeneities in the construction which may lead to the preferential flow. Results for saturated as well as for unsaturated part of the dam are analyzed. Using the appropriate simulation model may help to design safer flood dams and evaluate the reason of possible failures to prevent future disasters. The research has been performed in the frame of research project VZ 04 CEZ MSM 6840770005.

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

    Directory of Open Access Journals (Sweden)

    Francesco Mattia

    2008-07-01

    Full Text Available Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale.

  7. Spatial patterns of soil moisture from two regional monitoring networks in the United States

    Science.gov (United States)

    Wang, Tiejun; Liu, Qin; Franz, Trenton E.; Li, Ruopu; Lang, Yunchao; Fiebrich, Christopher A.

    2017-09-01

    Understanding soil moisture spatial variability (SMSV) at regional scales is of great value for various purposes; however, relevant studies are still limited and have yielded inconsistent findings about the primary controls on regional SMSV. To further address this issue, long-term soil moisture data were retrieved from two large scale monitoring networks located in the continental United States, including the Michigan Automated Weather Network and the Oklahoma Mesonet. To evaluate different controls on SMSV, supporting datasets, which contained data on climate, soil, topography, and vegetation, were also compiled from various sources. Based on temporal stability analysis, the results showed that the mean relative difference (MRD) of soil moisture was more correlated with soil texture (e.g., negative correlations between MRD and sand fraction, and positive ones between MRD and silt and clay fractions) than with meteorological forcings in both regions, which differed from the traditional notion that meteorological forcings were the dominant controls on regional SMSV. Moreover, the results revealed that contrary to the previous conjecture, the use of soil moisture temporal anomaly did not reduce the impacts of static properties (e.g., soil properties) on soil moisture temporal dynamics. Instead, it was found that the magnitude of soil moisture temporal anomaly was mainly negatively correlated with sand fraction and positively with silt and clay fractions in both regions. Finally, the relationship between the spatial average and standard deviation of soil moisture as well as soil moisture temporal anomaly was investigated using the data from both networks. The field data showed that the relationship for both soil moisture and soil moisture temporal anomaly was more affected by soil texture than by climatic conditions (e.g., precipitation). The results of this study provided strong field evidence that local factors (e.g., soil properties) might outweigh regional

  8. Copula-based Probabilistic Estimation of Soil Moisture and its Potential Application in Air Pollution Meteorology

    Science.gov (United States)

    Das, S. K.; Maity, R.

    2016-12-01

    Soil moisture at monthly to weekly scale for point locations can be simulated using climate inputs for different soil texture or hydrologic soil groups, based on the association between soil moisture and Combined Hydro-Meteorological (CHM) index. The use of Supervised PCA (SPCA) is found suitable for reducing the dimension of input matrix by deriving the CHM index and Archimedean copula as a tool to derive conditional joint distribution of soil moisture and climate inputs. While static copula is sufficient to capture the association at monthly scale, dynamic copula is appropriate for finer temporal scale, e.g. weekly. The simulated soil moisture both at monthly and weekly scale found to perform reasonably well compared to the existing soil moisture data sets. The simulated soil moisture at point location can be utilized to produce simulated soil moisture maps for a region based on results of cross-validation techniques, e.g. Leave One-station Out Cross-Validation (LOOCV). The gridded climate input data sets can be used for such mapping after treating the missing data points with interpolation techniques, like spring metaphor. Using such meteorologiac inputs, typical high resolution soil moisture maps are generated based on the proposed hydrometeorological approach. Such gridded soil moisture data/map are potentially useful in various fields including the assessment of air pollution meteorology as the mixing height directly depends on the rigional soil moisture content through intial spin-up of convective movement in the Atmospheric Boundary Layer (ABL). Keywords: Soil Moisture; Climate; Probabilistic Modelling; Copula; Hydrometeorology

  9. The Soil Moisture Active Passive (SMAP) Applications Activity

    Science.gov (United States)

    Brown, Molly E.; Moran, Susan; Escobar, Vanessa; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni

    2011-01-01

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP measurements will allow global and high-resolution mapping of soil moisture and its freeze/thaw state at resolutions from 3-40 km. These measurements will have high value for a wide range of environmental applications that underpin many weather-related decisions including drought and flood guidance, agricultural productivity estimation, weather forecasting, climate predictions, and human health risk. In 2007, NASA was tasked by The National Academies to ensure that emerging scientific knowledge is actively applied to obtain societal benefits by broadening community participation and improving means for use of information. SMAP is one of the first missions to come out of this new charge, and its Applications Plan forms the basis for ensuring its commitment to its users. The purpose of this paper is to outline the methods and approaches of the SMAP applications activity, which is designed to increase and sustain the interaction between users and scientists involved in mission development.

  10. Impact of soil moisture on extreme maximum temperatures in Europe

    Directory of Open Access Journals (Sweden)

    Kirien Whan

    2015-09-01

    Full Text Available Land-atmosphere interactions play an important role for hot temperature extremes in Europe. Dry soils may amplify such extremes through feedbacks with evapotranspiration. While previous observational studies generally focused on the relationship between precipitation deficits and the number of hot days, we investigate here the influence of soil moisture (SM on summer monthly maximum temperatures (TXx using water balance model-based SM estimates (driven with observations and temperature observations. Generalized extreme value distributions are fitted to TXx using SM as a covariate. We identify a negative relationship between SM and TXx, whereby a 100 mm decrease in model-based SM is associated with a 1.6 °C increase in TXx in Southern-Central and Southeastern Europe. Dry SM conditions result in a 2–4 °C increase in the 20-year return value of TXx compared to wet conditions in these two regions. In contrast with SM impacts on the number of hot days (NHD, where low and high surface-moisture conditions lead to different variability, we find a mostly linear dependency of the 20-year return value on surface-moisture conditions. We attribute this difference to the non-linear relationship between TXx and NHD that stems from the threshold-based calculation of NHD. Furthermore the employed SM data and the Standardized Precipitation Index (SPI are only weakly correlated in the investigated regions, highlighting the importance of evapotranspiration and runoff for resulting SM. Finally, in a case study for the hot 2003 summer we illustrate that if 2003 spring conditions in Southern-Central Europe had been as dry as in the more recent 2011 event, temperature extremes in summer would have been higher by about 1 °C, further enhancing the already extreme conditions which prevailed in that year.

  11. [Soil moisture content and fine root biomass of rubber tree (Hevea brasiliensis) plantations at different ages].

    Science.gov (United States)

    Lin, Xi-Hao; Chen, Qiu-Bo; Hua, Yuan-Gang; Yang, Li-Fu; Wang, Zhen-Hui

    2011-02-01

    By using soil core sampling method, this paper studied the soil moisture regime of rubber plantations and the fine root biomass of Hevea brasiliensis in immature period (5 a), early yielding period (9 a), and peak yielding period (16 a). With the increasing age of rubber trees, the soil moisture content of rubber plantations increased but the fine root biomass decreased. The soil moisture content at the depth of 0-60 cm in test rubber plantations increased with soil depth, and presented a double-peak pattern over the period of one year. The fine root biomass of rubber trees at different ages had the maximum value in the top 10 cm soil layers and decreased with soil depth, its seasonal variation also showed a double-peak pattern, but the peak values appeared at different time. Soil moisture content and soil depth were the main factors affecting the fine root biomass of H. brasiliensis.

  12. Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

    Science.gov (United States)

    Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

    2011-01-01

    Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  13. Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint

    Directory of Open Access Journals (Sweden)

    B. Li

    2012-01-01

    Full Text Available Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of near surface soil moisture in a footprint area, and can be used to reduce bias of model estimates (at locations near the surface through data assimilation techniques. While assimilating the retrievals can reduce bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF with a mass conservation updating scheme was developed to assimilate Advanced Microwave Scanning Radiometer (AMSR-E soil moisture retrievals, as they are without any scaling or pre-processing, to improve the estimated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  14. A practical algorithm to estimate soil thawing onset with the soil moisture active passive (SMAP) data

    Science.gov (United States)

    Chen, X.; Liu, L.

    2016-12-01

    The Soil Moisture Active Passive (SMAP) satellite simultaneously collected active and passive microwave data at L-band from April to July, 2015. The L-band radiometer brightness temperature (TB) data are strongly sensitive to the change of soil moisture, therefore, can be used to estimate freeze/thaw state of soil. We applied an edge detection method to detect the onset of thawing based on the SMAP level-1C TB data. This method convolves the first derivative of the Gaussian function as a kernel with the TB time series. When thawing occurs, soil moisture increases abruptly and leads to a decrease in TB. Therefore, a primary thaw event can be identified when the convolved signal reaches a local minimum. Considering the noise of the radiometer data, not all local minimums correspond to a thaw event. Therefore, we further applied a filter based on a priori or in situ soil temperature observation to eliminate false events. We compared the TB-based estimates with in situ measurements of soil temperature, moisture, and snow depth from April to June from 5 SNOTEL sites in Alaska. Our results show that at 4 out of the 5 sites the estimated thawing onsets and in-situ data agree within 5 to 10 days. However, we found a distinct inconsistency of 41 days at the fifth site. One possible reason is the mismatch in spatial coverage: one pixel of SMAP radiometer data has a size of 36 km, within which different areas may have different freeze/thaw states. The SMAP radar backscatter coefficient (σ0) data are also very sensitive to soil moisture, and has finer spatial resolution of 1 km, making it more directly comparable with the in situ measurements. We applied a seasonal threshold method to estimate thawing onset based on this data. Firstly, we set a thaw onset based on the in situ soil temperature and moisture measurements at 5 cm depth. Then we averaged σ0 observations from April 14th to 7 days before the thaw onset to represent the frozen soil, and used the mean value from 7

  15. Investigating the Effect of Soil Moisture on Net Ecosystem Exchange in Shale Hills

    Science.gov (United States)

    Griffiths, Z. G.; Davis, K. J.; He, Y.

    2016-12-01

    Carbon sinks have the ability to absorb more carbon dioxide than what they emit. The terrestrial biome acts as a huge carbon sink, however, this ability is dependent on different environmental factors. This study focused on the effects of soil moisture on net ecosystem exchange(NEE) in the Shale Hills Critical Zone Observatory, PA. It was hypothesized that the strength of the carbon sink would grow with wetter soils. Data was collected from the eddy-covariance flux tower, a COSMOS soil moisture probe, automated soil respiration chambers and sap flow probes for May to August between the years 2011-2016. Since temperature and photosynthetically active radiation(PAR) also have an effect on carbon fluxes, these variables were isolated to properly study soil moisture and carbon fluxes. Generally, less carbon dioxide was absorbed with increasing soil moisture. Since NEE is a combination of photosynthesis and respiration, the effect of soil moisture was studied separately for each process. The sap flow data showed a decrease in activity with increasing soil moisture, hence photosynthesis was most likely reduced. Additionally, more carbon dioxide was emitted from respiration with increasing soil moisture. These findings could possibly explain why the forest at Shale Hills tends to release more carbon dioxide with increasing soil moisture.

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

    Science.gov (United States)

    Wu, Mousong; Sholze, Marko

    2017-04-01

    We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

  17. SOIL MOISTURE REGIME ON LUVISOL IN THE EAST CROATIA

    Directory of Open Access Journals (Sweden)

    Domagoj Rastija

    2008-12-01

    Full Text Available The aim of the research was to determine water deficit in the soil (to 60 cm depth on the basis of field measurements as well as calculation of soil water balance during the vegetation season of maize and winter wheat. In the first year of research (2003 water deficit was emphasized during the whole vegetation season of maize (Zelčin 336 mm; Donji Miholjac 326 mm; but the most marked water shortage was evident in the July and August; having negative effect on maize grain yield (5.52 t ha-1. The second year of research (2004 was more favourable; and water deficit which on the both sites occurred only in the May (Zelčin 40;5 mm; Donji Miholjac 32;6 mm; did not affect wheat grain yield (5.07 t ha-1. Particularly low values of available water content (AWC were observed during the summer of 2003; and the lowest values (8% for Zelčin; and 7% for Donji Miholjac were recorded in the third decade of September. In the 2004 much higher values of AWC were achieved (40.5% for Zelčin; and 32.6% for Donji Miholjac. In the deeper soil layers significantly higher (P<1% values of soil moisture were determined. The correlations between measured and calculated values of AWC were also very significant on both sites (r =0.93**; r =0.91**.

  18. Potential feedbacks between snow cover, soil moisture and surface energy fluxes in Southern Norway

    Science.gov (United States)

    Brox Nilsen, Irene; Tallaksen, Lena M.; Stordal, Frode

    2017-04-01

    At high latitudes, the snow season has become shorter during the past decades because snowmelt is highly sensitive to a warmer climate. Snowmelt influences the energy balance by changing the albedo and the partitioning between latent and sensible heat fluxes. It further influences the water balance by changing the runoff and soil moisture. In a previous study, we identified southern Norway as a region where significant temperature changes in summer could potentially be explained by land-atmosphere interactions. In this study we hypothesise that changes in snow cover would influence the summer surface fluxes in the succeeding weeks or months. The exceptionally warm summer of 2014 was chosen as a test bed. In Norway, evapotranspiration is not soil moisture limited, but energy limited, under normal conditions. During warm summers, however, such as in 2014, evapotranspiration can be restricted by the available soil moisture. Using the Weather Research and Forecasting (WRF) model we replace the initial ground conditions for 2014 with conditions representative of a snow-poor spring and a snow-rich spring. WRF was coupled to Noah-MP at 3 km horizontal resolution in the inner domain, and the simulations covered mid-May through September 2014. Boundary conditions used to force WRF were taken from the Era-Interim reanalysis. Snow, runoff, soil moisture and soil temperature observational data were provided by the Norwegian Water Resources and Energy Directorate for validation. The validation shows generally good agreement with observations. Preliminary results show that the reduced snowpack, hereafter "sim1" increased the air temperature by up to 5 K and the surface temperature by up to 10 K in areas affected by snow changes. The increased snowpack, hereafter "sim2", decreased the air and surface temperature by the same amount. These are weekly mean values for the first eight simulation weeks from mid May. Because of the higher net energy available ( 100 Wm-2) in sim 1, both

  19. High Energy Moisture Characteristics: Linking Between Soil Physical Processes and Structure Stability

    Science.gov (United States)

    Water storage and flow in soils is usually complicated by the intricate nature of and changes in soil pore size distribution (PSD) due to modifications in soil structure following changes in agricultural management. The paper presents the Soil High Energy Moisture Characteristic (Soil-HEMC) method f...

  20. A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals

    Directory of Open Access Journals (Sweden)

    W. T. Crow

    2009-01-01

    Full Text Available A number of recent studies have focused on enhancing runoff prediction via the assimilation of remotely-sensed surface soil moisture retrievals into a hydrologic model. The majority of these approaches have viewed the problem from purely a state or parameter estimation perspective in which remotely-sensed soil moisture estimates are assimilated to improve the characterization of pre-storm soil moisture conditions in a hydrologic model, and consequently, its simulation of runoff response to subsequent rainfall. However, recent work has demonstrated that soil moisture retrievals can also be used to filter errors present in satellite-based rainfall accumulation products. This result implies that soil moisture retrievals have potential benefit for characterizing both antecedent moisture conditions (required to estimate sub-surface flow intensities and subsequent surface runoff efficiencies and storm-scale rainfall totals (required to estimate the total surface runoff volume. In response, this work presents a new sequential data assimilation system that exploits remotely-sensed surface soil moisture retrievals to simultaneously improve estimates of both pre-storm soil moisture conditions and storm-scale rainfall accumulations. Preliminary testing of the system, via a synthetic twin data assimilation experiment based on the Sacramento hydrologic model and data collected from the Model Parameterization Experiment, suggests that the new approach is more efficient at improving stream flow predictions than data assimilation techniques focusing solely on the constraint of antecedent soil moisture conditions.

  1. Forest soil respiration rate and delta13C is regulated by recent above ground weather conditions.

    Science.gov (United States)

    Ekblad, Alf; Boström, Björn; Holm, Anders; Comstedt, Daniel

    2005-03-01

    Soil respiration, a key component of the global carbon cycle, is a major source of uncertainty when estimating terrestrial carbon budgets at ecosystem and higher levels. Rates of soil and root respiration are assumed to be dependent on soil temperature and soil moisture yet these factors often barely explain half the seasonal variation in soil respiration. We here found that soil moisture (range 16.5-27.6% of dry weight) and soil temperature (range 8-17.5 degrees C) together explained 55% of the variance (cross-validated explained variance; Q2) in soil respiration rate (range 1.0-3.4 micromol C m(-2) s(-1)) in a Norway spruce (Picea abies) forest. We hypothesised that this was due to that the two components of soil respiration, root respiration and decomposition, are governed by different factors. We therefore applied PLS (partial least squares regression) multivariate modelling in which we, together with below ground temperature and soil moisture, used the recent above ground air temperature and air humidity (vapour pressure deficit, VPD) conditions as x-variables. We found that air temperature and VPD data collected 1-4 days before respiration measurements explained 86% of the seasonal variation in the rate of soil respiration. The addition of soil moisture and soil temperature to the PLS-models increased the Q2 to 93%. delta13C analysis of soil respiration supported the hypotheses that there was a fast flux of photosynthates to root respiration and a dependence on recent above ground weather conditions. Taken together, our results suggest that shoot activities the preceding 1-6 days influence, to a large degree, the rate of root and soil respiration. We propose this above ground influence on soil respiration to be proportionally largest in the middle of the growing season and in situations when there is large day-to-day shifts in the above ground weather conditions. During such conditions soil temperature may not exert the major control on root respiration.

  2. EVALUATION OF RADON EMANATION FROM SOIL WITH VARYING MOISTURE CONTENT IN A SOIL CHAMBER

    Science.gov (United States)

    The paper describes measurements to quantitatively identify the extent to which moisture affects radon emanation and diffusive transport components of a sandy soil radon concentration gradient obtained in the EPA test chamber. The chamber (2X2X4 m long) was constructed to study t...

  3. Simulating carbon fluxes in Siberia using assimilation of remotely sensed soil moisture data

    Science.gov (United States)

    van der Molen, Michiel; de Jeu, Richard; Belelli Marchesini, Luca; Peters, Wouter

    2013-04-01

    Simulating biogenic carbon fluxes in Siberia is difficult, because the growing season is short and the transitions between the seasons are fast. At the start of the growing season, when the snow has melted, the soil is still frozen. The melt water therefore either runs off quickly in non-flat terrain, or waterlogs the soil in flat terrain. Consequently, the soil moisture content during soil thawing tends to the extremes, either very wet or towards dry. This 'bi-modal' behaviour of soil moisture at the start of the growing season is difficult to capture by vegetation models. Consequently, the carbon fluxes and transpiration rates are either too much limited by anticipated water stress, or too little limited during waterlogging. We present here a method to improve the simulated soil moisture in a vegetation model, SiBCASA (Schaefer et al., 2008) by assimilating remotely sensed soil moisture into the SiBCASA. We use the blended active and passive microwave soil moisture data set of Liu et al., (2011, 2012) for this purpose, which has a time resolution of 1 day and a horizontal resolution of 0.25°×0.25°. We explain the methodology for relating the top soil moisture observations to whole profile simulated soil moisture, and for translating the meaning of mean and extremes of soil moisture between remote sensing observations and SiBCASA. Ultimately, we present the effect of better representing soil moisture content on simulating the carbon fluxes in Siberia, and we compare the simulated data with observations of soil moisture and carbon fluxes at 14 locations across Boreal Eurasia.

  4. Radius of influence for a cosmic-ray soil moisture probe : theory and Monte Carlo simulations.

    Energy Technology Data Exchange (ETDEWEB)

    Desilets, Darin

    2011-02-01

    The lateral footprint of a cosmic-ray soil moisture probe was determined using diffusion theory and neutron transport simulations. The footprint is radial and can be described by a single parameter, an e-folding length that is closely related to the slowing down length in air. In our work the slowing down length is defined as the crow-flight distance traveled by a neutron from nuclear emission as a fast neutron to detection at a lower energy threshold defined by the detector. Here the footprint is defined as the area encompassed by two e-fold distances, i.e. the area from which 86% of the recorded neutrons originate. The slowing down length is approximately 150 m at sea level for neutrons detected over a wide range of energies - from 10{sup 0} to 10{sup 5} eV. Both theory and simulations indicate that the slowing down length is inversely proportional to air density and linearly proportional to the height of the sensor above the ground for heights up to 100 m. Simulations suggest that the radius of influence for neutrons >1 eV is only slightly influenced by soil moisture content, and depends weakly on the energy sensitivity of the neutron detector. Good agreement between the theoretical slowing down length in air and the simulated slowing down length near the air/ground interface support the conclusion that the footprint is determined mainly by the neutron scattering properties of air.

  5. Data assimilation using support vector machines and ensemble Kalman filter for multi-layer soil moisture prediction

    Directory of Open Access Journals (Sweden)

    Di Liu

    2010-12-01

    Full Text Available Hybrid data assimilation (DA is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines (SVMs and the ensemble Kalman filter (EnKF technology was used for the prediction of soil moisture in different soil layers: 0–5 cm, 30 cm, 50 cm, 100 cm, 200 cm, and 300 cm. The SVM methodology was first used to train the ground measurements of soil moisture and meteorological parameters from the Meilin study area, in East China, to construct soil moisture statistical prediction models. Subsequent observations and their statistics were used for predictions, with two approaches: the SVM predictor and the SVM-EnKF model made by coupling the SVM model with the EnKF technique using the DA method. Validation results showed that the proposed SVM-EnKF model can improve the prediction results of soil moisture in different layers, from the surface to the root zone.

  6. Soil Moisture-Ecosystem-Climate Interactions in a Changing Climate

    Science.gov (United States)

    Seneviratne, S. I.; Davin, E.; Hirschi, M.; Mueller, B.; Orlowsky, B.; Teuling, A.

    2011-12-01

    Soil moisture is a key variable of the climate system. It constrains plant transpiration and photosynthesis in several regions of the world, with consequent impacts on the water, energy and biogeochemical cycles (e.g. Seneviratne et al. 2010). Moreover it is a storage component for precipitation and radiation anomalies, inducing persistence in the climate system. Finally, it is involved in a number of feedbacks at the local, regional and global scales, and plays a major role in climate-change projections. This presentation will provide an overview on these interactions, based on several recent publications (e.g. Seneviratne et al. 2006, Orlowsky and Seneviratne 2010, Teuling et al. 2010, Hirschi et al. 2011). In particular, it will highlight possible impacts of soil moisture-ecosystem coupling for climate extremes such as heat waves and droughts, and the resulting interconnections between biophysical and biogeochemical feedbacks in the context of climate change. Finally, it will also address recent regional- to global-scale trends in land hydrology and ecosystem functioning, as well as issues and potential avenues for investigating these trends (e.g. Jung et al. 2010, Mueller et al. 2011). References Hirschi, M., S.I. Seneviratne, V. Alexandrov, F. Boberg, C. Boroneant, O.B. Christensen, H. Formayer, B. Orlowsky, and P. Stepanek, 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nature Geoscience, 4, 17-21, doi:10.1038/ngeo1032. Jung, M., et al., 2010: Recent decline in the global land evapotranspiration trend due to limited moisture supply. Nature, 467, 951-954. doi:10.1038/nature09396 Mueller, B., S.I. Seneviratne, et al.: Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations, Geophys. Res. Lett., 38, L06402, doi:10.1029/2010GL046230 Orlowsky, B., and S.I. Seneviratne, 2010: Statistical analyses of land-atmosphere feedbacks and their possible pitfalls. J. Climate, 23(14), 3918

  7. On Transpiration and Soil Moisture Content Sensitivity to Soil Hydrophysical Data

    Science.gov (United States)

    Ács, Ferenc

    Sensitivity of evapotranspiration E and root zone soil moisture content θ to the parameterization of soil water retention Ψ(θ) and soil water conductivity K(Ψ), as well as to the definition of field capacity soil moisture content, is investigated by comparing Psi1-PMSURF and Theta-PMSURF models. The core of PMSURF (Penman-Monteith Surface Fluxes) consists of a 3-layer soil moisture prediction module based on Richard’s equation in combination with the Penman-Monteith concept for estimating turbulent heat fluxes. Psi1- PMSURF and Theta-PMSURF differ only in the parameterization of the moisture availability function Fma. In Psi1,Fma is parameterized by using Ψ(θ) and K(Ψ) hydrophysical functions; in Theta, Fma is parameterized by using hydrophysical parameters: the field capacity θf and wilting point θw soil moisture contents. Both Psi1 and Theta are based on using soil hydrophysical data, that is, there is no conceptual difference between them in the parameterization of E even if in Psi1Fma depends on 12 parameters, while in Theta only on two soil/vegetation parameters. Sensitivity tests are performed using the Cabauw dataset. Three soil datasets are used: the vG (van Genuchten), CH/vG (Clapp and Hornberger/van Genuchten) and CH/PILPS (Clapp and Hornberger/Project for Intercomparison of Land-surface Parameterization Schemes) datasets. The vG dataset is used in van Genuchten’s parameterization, while in Clapp and Hornberger’s the CH/vG and CH/PILPS datasets are used. It is found that the consistency of soil hydrophysical data in the simulation of transpiration is quite important. The annual sum of E obtained by Psi1EPsi1, differs from the annual sum of E obtained by Theta, ETheta, because of the inconsistency between the fitting parameters of Ψ(θ) and K(Ψ) and the θf, and not because of the differencies in the parameterization of Fma. Further, θf can be estimated not only on the basis of using soil hydrophysical functions (the θf so obtained is

  8. Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China

    Science.gov (United States)

    Wang, S.; Fu, B. J.; Gao, G. Y.; Yao, X. L.; Zhou, J.

    2012-08-01

    We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET) of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass (Andropogon), subshrub (Artemisia scoparia), shrub (Spiraea pubescens), plantation forest (Robinia pseudoacacia), and crop (Zea mays) vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

  9. Multi-source hydrological soil moisture state estimation using data fusion optimisation

    Science.gov (United States)

    Zhuo, Lu; Han, Dawei

    2017-07-01

    Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. Although there have been a number of soil moisture products, they cannot be directly used in hydrological modelling. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from SAC-SMA (soil moisture), MODIS (land surface temperature), and SMOS (multi-angle brightness temperatures in H-V polarisations). The simple yet effective local linear regression model is applied for the data fusion purpose in the Pontiac catchment. Four schemes according to temporal availabilities of the data sources are developed, which are pre-assessed and best selected by using the well-proven feature selection algorithm gamma test. The hydrological accuracy of the produced soil moisture data is evaluated against the Xinanjiang hydrological model's soil moisture deficit simulation. The result shows that a superior performance is obtained from the scheme with the data inputs from all sources (NSE = 0.912, r = 0.960, RMSE = 0.007 m). Additionally, the final daily-available hydrological soil moisture product significantly increases the Nash-Sutcliffe efficiency by almost 50 % in comparison with the two most popular soil moisture products. The proposed method could be easily applied to other catchments and fields with high confidence. The misconception between the hydrological soil moisture state variable and the real-world soil moisture content, and the potential to build a global routine hydrological soil moisture product are discussed.

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

    Science.gov (United States)

    Koster, Randal

    2010-01-01

    This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these

  11. Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China

    Directory of Open Access Journals (Sweden)

    S. Wang

    2012-08-01

    Full Text Available We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass (Andropogon, subshrub (Artemisia scoparia, shrub (Spiraea pubescens, plantation forest (Robinia pseudoacacia, and crop (Zea mays vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

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

    Science.gov (United States)

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

    2011-11-01

    By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.

  13. SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product

    National Research Council Canada - National Science Library

    Roberto Fernandez-Moran; Amen Al-Yaari; Arnaud Mialon; Ali Mahmoodi; Ahmad Al Bitar; Gabrielle De Lannoy; Nemesio Rodriguez-Fernandez; Ernesto Lopez-Baeza; Yann Kerr; Jean-Pierre Wigneron

    2017-01-01

    .... The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global...

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

    Science.gov (United States)

    Hut, R.; Campbell, C. S.

    2015-12-01

    A low power bluetooth Low Energy (BLE) device is burried 20cm into the soil and a smartphone is placed on top of the soil to test if bluetooth signal strength can be related to soil moisture. The smartphone continuesly records and stores bluetooth signal strength of the device. The soil is artifcially wetted and drained. Results show a relation between BLE signal strength and soil moisture that could be used to measure soil moisture using these off-the-shelf consumer electronics. This opens the possibily to develop sensors that can be buried into the soil, possibly below the plow-line. These sensors can measure local parameters such as electric conductivity, ph, pressure, etc. Readings would be uploaded to a device on the surface using BLE. The signal strength of this BLE would be an (additional) measurement of soil moisture.

  15. The estimation of soil moisture from ERS wind scatterometer data over the Tibetan Plateau

    NARCIS (Netherlands)

    Wen, J.; Su, Z.

    2003-01-01

    With the consideration of microwave radiation transfer process, physically based simple algorithms have been proposed to estimate land surface soil Fresnel reflectivity or soil moisture and vegetation fractional coverage from ERS wind scatterometer data. The proposed algorithms have been

  16. Soil CO2 Flux, Moisture, Temperature, and Litterfall, La Selva, Costa Rica, 2003-2010

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides measurements of soil carbon dioxide (CO2) emission rates, soil moisture, relative humidity (RH), temperature, and litterfall from six types of...

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

    Science.gov (United States)

    Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott

    2018-02-01

    Many forested mountain watersheds worldwide evolved with frequent fire, which Twentieth Century fire suppression activities eliminated, resulting in unnaturally dense forests with high water demand. Restoration of pre-suppression forest composition and structure through a variety of management activities could improve forest resilience and water yields. This study explores the potential for "managed wildfire", whereby naturally ignited fires are allowed to burn, to alter the water balance. Interest in this type of managed wildfire is increasing, yet its long-term effects on water balance are uncertain. We use soil moisture as a spatially-distributed hydrologic indicator to assess the influence of vegetation, fire history and landscape position on water availability in the Illilouette Creek Basin in Yosemite National Park. Over 6000 manual surface soil moisture measurements were made over a period of three years, and supplemented with continuous soil moisture measurements over the top 1m of soil in three sites. Random forest and linear mixed effects models showed a dominant effect of vegetation type and history of vegetation change on measured soil moisture. Contemporary and historical vegetation maps were used to upscale the soil moisture observations to the basin and infer soil moisture under fire-suppressed conditions. Little change in basin-averaged soil moisture was inferred due to managed wildfire, but the results indicated that large localized increases in soil moisture had occurred, which could have important impacts on local ecology or downstream flows.

  18. Selenium in Oklahoma ground water and soil

    Energy Technology Data Exchange (ETDEWEB)

    Atalay, A.; Vir Maggon, D.

    1991-03-30

    Selenium with a consumption of 2 liters per day (5). The objectives of this study are: (1) to determine the concentrations of Se in Oklahoma ground water and soil samples. (2) to map the geographical distribution of Se species in Oklahoma. (3) to relate groundwater depth, pH and geology with concentration of Se.

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

    Science.gov (United States)

    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.

  20. Soil moisture influences the development of Haemonchus contortus and Trichostrongylus colubriformis to third stage larvae.

    Science.gov (United States)

    Khadijah, S; Kahn, L P; Walkden-Brown, S W; Bailey, J N; Bowers, S F

    2013-09-01

    Two climate chamber experiments were conducted to determine the effect of varying initial soil moisture (0, 10 and 15%), simulated rainfall amount (0, 12 and 24 mm) and simulated rainfall timing (days -1, 0 and 3 relative to faecal deposition) on development (day 14) of Haemonchus contortus and Trichostrongylus colubriformis to the third stage larvae (L3) and faecal moisture (FM). Increasing initial soil moisture content from 0 to 10 or 15% led to higher recovery of total L3 (Pmoisture and simulated rainfall amount on the recovery of total L3, showing that the benefit of increased simulated rainfall lessened with increasing soil moisture. Simulated rainfall on the day of deposition resulted in higher recovery of L3 (Prelative to faecal deposition was best associated with recovery of total H. contortus and T. colubriformis L3 (R(2)=0.32-0.46), reinforcing the importance of sufficient moisture soon after faecal deposition. The effects of initial soil moisture, and the amount and timing of simulated rainfall on development to L3 were largely explained by changes to FM and soil moisture values within 4 days relative to faecal deposition. These results highlight the influence of soil moisture and its interaction with rainfall on development of H. contortus and T. colubriformis to L3. Consequently we recommend that soil moisture be given greater importance and definition in the conduct of ecological studies of parasitic nematodes, in order to improve predictions of development to L3. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Soil moisture and texture primarily control the soil nutrient stoichiometry across the Tibetan grassland.

    Science.gov (United States)

    Tian, Liming; Zhao, Lin; Wu, Xiaodong; Fang, Hongbing; Zhao, Yonghua; Hu, Guojie; Yue, Guangyang; Sheng, Yu; Wu, Jichun; Chen, Ji; Wang, Zhiwei; Li, Wangping; Zou, Defu; Ping, Chien-Lu; Shang, Wen; Zhao, Yuguo; Zhang, Ganlin

    2018-05-01

    Soil nutrient stoichiometry and its environmental controllers play vital roles in understanding soil-plant interaction and nutrient cycling under a changing environment, while they remain poorly understood in alpine grassland due to lack of systematic field investigations. We examined the patterns and controls of soil nutrients stoichiometry for the top 10cm soils across the Tibetan ecosystems. Soil nutrient stoichiometry varied substantially among vegetation types. Alpine swamp meadow had larger topsoil C:N, C:P, N:P, and C:K ratios compared to the alpine meadow, alpine steppe, and alpine desert. In addition, the presence or absence of permafrost did not significantly impact soil nutrient stoichiometry in Tibetan grassland. Moreover, clay and silt contents explained approximately 32.5% of the total variation in soil C:N ratio. Climate, topography, soil properties, and vegetation combined to explain 10.3-13.2% for the stoichiometry of soil C:P, N:P, and C:K. Furthermore, soil C and N were weakly related to P and K in alpine grassland. These results indicated that the nutrient limitation in alpine ecosystem might shifts from N-limited to P-limited or K-limited due to the increase of N deposition and decrease of soil P and K contents under the changing climate conditions and weathering stages. Finally, we suggested that soil moisture and mud content could be good predictors of topsoil nutrient stoichiometry in Tibetan grassland. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Soil moisture estimation using reflected solar and emitted thermal infrared radiation

    Science.gov (United States)

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

    1978-01-01

    Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.

  3. Data assimilation of soil water flow via ensemble Kalman filter: Infusing soil moisture data at different scales

    Science.gov (United States)

    Zhu, Penghui; Shi, Liangsheng; Zhu, Yan; Zhang, Qiuru; Huang, Kai; Williams, Mathew

    2017-12-01

    This paper assesses the value of multi-scale near-surface (0∼5 cm) soil moisture observations to improve state-only or state-parameter estimation based on the ensemble Kalman filter (EnKF). To the best of our knowledge, studies on assimilating multi-scale soil moisture data into a distributed hydrological model with a series of detailed vertical soil moisture profiles are rare. Our analysis factors include spatial measurement scales, soil spatial heterogeneity, multi-scale data with contrasting information and systematic measurement errors. Results show that coarse-scale soil moisture data are also very useful for identifying finer-scale parameters and states given biased initial parameter fields, but it becomes increasingly difficult to recover the finer-scale spatial heterogeneity of soil property as the observation grids become coarser. In state-only estimation, near-surface soil moisture data result in improvement for shallow soil moisture profiles and degradation for deeper soil moisture profiles, with stronger influences from finer-scale data. With the decrease of background spatial heterogeneity of soil property, the value of coarse-scale data increases notably. Soil moisture data at two scales with contrasting information are found to be both useful. By updating spatially correlated soil hydraulic parameters, deviated observations still contain considerably useful information for finer-scale state-parameter estimation. Eventually, by presenting a difference information assimilation method based on EnKF we successfully extract useful information from soil moisture data containing systematic measurement errors. The current study can be extended to consider more complex atmosphere input and topography, etc.

  4. 1km Soil Moisture from Downsampled Sentinel-1 SAR Data: Harnessing Assets and Overcoming Obstacles.

    Science.gov (United States)

    Bauer-Marschallinger, Bernhard; Cao, Senmao; Schaufler, Stefan; Paulik, Christoph; Naeimi, Vahid; Wagner, Wolfgang

    2017-04-01

    Radars onboard Earth observing satellites allow estimating Surface Soil Moisture (SSM) regularly and globally. The use of coarse-scale measurements from active or passive radars for SSM retrieval is well established and in operational use. Thanks to the Sentinel-1 mission, launched in 2014 and deploying Synthetic Aperture Radars (SAR), high-resolution radar imagery is routinely available at the scale of 20 meters, with a high revisit frequency of 3-6 days and with unprecedented radiometric accuracy. However, the direct exploitation of high-resolution SAR data for SSM retrieval is complicated by several problems: Small-scaled contributions to the radar backscatter from individual ground features often obscure the soil moisture signal, rendering common algorithms insensitive to SSM. Furthermore, the influence of vegetation dynamics on the radar signal is less understood than in the coarse-scale case, leading to biases during the vegetation period. Finally, the large data volumes of high-resolution remote sensing data present a great load on hardware systems. Consequently, a spatial resampling of the high-resolution SAR data to a 500 meters sampling is done, allowing the exploitation of information at 10 meter sampling, but reducing effectively the inherent uncertainties. The thereof retrieved 1km SSM product aims to describe the soil moisture dynamics at medium scale with high quality. We adopted the TU-Wien Change Detection algorithm to the Sentinel-1 data, which was already successfully used for retrieving SSM from ERS-1/2 and Envisat-ASAR observations. The adoption entails a new method for SAR image resampling, including a masking for pixels that do not carry soil moisture signals, preventing them to spread during downsampling. Furthermore, the observation angle between the radar sensors and the ground is treated in a different way, as Sentinel-1 sensors observe from fixed orbit paths (in contrast to other radar sensors). Here, a regression model is developed that

  5. Role of subsurface physics in the assimilation of surface soil moisture observations

    Science.gov (United States)

    Soil moisture controls the exchange of water and energy between the land surface and the atmosphere and exhibits memory that may be useful for climate prediction at monthly time scales. Though spatially distributed observations of soil moisture are increasingly becoming available from remotely sense...

  6. Validation of two gridded soil moisture products over India with in ...

    Indian Academy of Sciences (India)

    Surface level soil moisture from two gridded datasets over India are evaluated in this study. The firstone is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation systembased on Extended Kalman Filter method (EKF), which make use of satellite observation of AdvancedScatterometer ...

  7. The impact of assumed error variances on surface soil moisture and snow depth hydrologic data assimilation

    Science.gov (United States)

    Accurate knowledge of antecedent soil moisture and snow depth conditions is often important for obtaining reliable hydrological simulations of stream flow. Data assimilation (DA) methods can be used to integrate remotely-sensed (RS) soil moisture and snow depth retrievals into a hydrology model and...

  8. Soil moisture retrieval in forest biomes: field experiment focus for SMAP 2018-2020 and beyond

    Science.gov (United States)

    The Soil Moisture Active Passive (SMAP) project has made excellent progress in addressing the requirements and science goals of the primary mission. The primary mission baseline requirement is estimates of global surface soil moisture with an error of no greater than 4% volumetric (one sigma) exclud...

  9. Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

    Science.gov (United States)

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

    2017-01-01

    Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.

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

    Science.gov (United States)

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

    2017-01-01

    NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core calval sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.

  11. Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

    Directory of Open Access Journals (Sweden)

    A. Loew

    2013-09-01

    Full Text Available Soil moisture is an essential climate variable (ECV of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture. The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

  12. Evapotranspiration and soil moisture dynamics in a temperate grassland ecosystem in Inner Mongolia China

    Science.gov (United States)

    L. Hao; Ge Sun; Yongqiang Liu; G. S. Zhou; J. H.   Wan;  L. B. Zhang; J. L. Niu; Y. H. Sang;  J. J He

    2015-01-01

    Precipitation, evapotranspiration (ET), and soil moisture are the key controls for the productivity and functioning of temperate grassland ecosystems in Inner Mongolia, northern China. Quantifying the soil moisture dynamics and water balances in the grasslands is essential to sustainable grassland management under global climate change. We...

  13. Temperature Vegetation Dryness Index Estimation of Soil Moisture under Different Tree Species

    Directory of Open Access Journals (Sweden)

    Shulin Chen

    2015-08-01

    Full Text Available The Laoshan forest is the largest forest in Nanjing, and it plays an important role in water resource management in Nanjing. The objectives of this study are to determine if the temperature vegetation dryness index (TVDI is suitable to estimate the soil moisture and if soil moisture is significantly affected by tree species in the Laoshan forest. This paper calculated the spatial distribution of TVDI using LANDSAT-5 TM data. Sixty-two observation points of in situ soil moisture measurements were selected to validate the effectiveness of the TVDI as an index for assessing soil moisture in the Laoshan forest. With the aid of the three different temporal patterns, which are 10 January 2011, 18 May 2011 and 23 September 2011, this paper used the TVDI to investigate the differences of soil moisture under four kinds of mono-species forests and two kinds of mixed forests. The results showed that there is a strong and significant negative correlation between the TVDI and the in situ measured soil moisture (R2 = 0.15–0.8, SE = 0.015–0.041 cm3/cm3. This means that the TVDI can reflect the soil moisture status under different tree species in the Laoshan forest. The soil moisture under these six types of land cover from low to high is listed in the following order: Eucommia ulmoides, Quercus acutissima, broadleaf mixed forest, Cunninghamia lanceolata, coniferous and broadleaf mixed forest and Pinus massoniana.

  14. Fostering Application Opportunites for the NASA Soil Moisture Active Passive (SMAP) Mission

    Science.gov (United States)

    Moran, M. Susan; O'Neill, Peggy E.; Entekhabi, Dara; Njoku, Eni G.; Kellogg, Kent H.

    2010-01-01

    The NASA Soil Moisture Active Passive (SMAP) Mission will provide global observations of soil moisture and freeze/thaw state from space. We outline how priority applications contributed to the SMAP mission measurement requirements and how the SMAP mission plans to foster applications and applied science.

  15. Radio-Frequency Interference (RFI) Mitigation for the Soil, Moisture Active/Passive (SMAP) Radiometer

    Science.gov (United States)

    Bradley, Damon; Brambora, Cliff; Wong, Mark Englin; Miles, Lynn; Durachka, David; Farmer, Brian; Mohammed, Priscilla; Piepmier, Jeff; Medeiros, Jim; Martin Neil; hide

    2010-01-01

    The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASA s Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson and Ruf.

  16. Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin

    Science.gov (United States)

    Increasing air temperatures are expected to continue in the future. The relation between soil moisture and near surface air temperature is significant for climate change and climate extremes. Evaluation of the relations between soil moisture and temperature was performed by devel...

  17. Evaluation of Two Methods for Determining Surface Soil Moisture from Radar Imagery

    Science.gov (United States)

    Thoma, D.; Moran, M.; Bryant, R.; Holifield, C.; Skirvin, S.; Rahman, M.; Kershner, C.; Watts, J.; Slocum, K.

    2003-12-01

    Distributed soil moisture data are useful for determining cross-country mobility, irrigation scheduling, pest management strategy, biomass production and potential for soil erosion and infiltration. Large area monitoring of surface soil moisture (to depths of 5 cm) is possible with radar remote sensing techniques, but accuracy must be assessed before it can be implemented operationally. Two methods for predicting surface soil moisture from radar satellite imagery were tested in sparsely vegetated, semi-arid Arizona rangelands. In the first approach, the Integral Equation Method (IEM) model was run in the forward direction to generate a Look-Up-Table (LUT) of radar backscatter for the expected range of surface roughness and moisture content in the study area. The LUT was used to derive surface soil moisture estimates from radar images acquired at the study site. In the second approach, a difference index was made from time series differences in radar backscatter signals from wet and dry soils. The difference index minimized variations in surface roughness and resulted in a direct relation between difference and surface soil moisture. For both approaches, results were validated against in situ measurements of surface soil moisture at 46 sites with dielectric probes at the time of satellite overpass. The modeling approach requires surface roughness inputs which may be difficult to obtain, whereas the difference technique requires only a dry surface reference backscatter for comparison with wetter surface backscatter to determine moisture content.

  18. A global analysis of satellite derived and DGVM surface soil moisture products

    NARCIS (Netherlands)

    Rebel, K.T.; Jeu, R.A.M. de; Ciais, P.; Viovy, N.; Piao, S.L.; Kiely, G.; Dolman, A.J.

    2011-01-01

    Soil moisture availability is important in regulating photosynthesis and controlling land surface-climate feedbacks at both the local and global scale. Recently, global remote-sensing datasets for soil moisture have become available. In this paper we assess the possibility of using remotely sensed

  19. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval

    Science.gov (United States)

    Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture. A factor that can play a significant role in the modeling...

  20. Extending the soil moisture record of the climate reference network with machine learning

    Science.gov (United States)

    Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ...

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

    Science.gov (United States)

    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...

  2. Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

    Science.gov (United States)

    Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

    2016-01-01

    Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

  3. Aquarius/SAC-D soil moisture product using V3.0 observations

    Science.gov (United States)

    Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development ...

  4. Assimilation of Satellite-Based Soil Moisture into the USDA Global Crop Production Decision Support System

    Science.gov (United States)

    The timely and accurate monitoring of climate conditions is essential for assessing agriculture efficiency and managing natural resources. Of particular importance is the estimation of near-surface soil moisture, which influences many aspects of local weather and global climate. Soil moisture is als...

  5. Global Soil Moisture Patterns Observed by Space Borne Microwave Radiometers and Scatterometers

    NARCIS (Netherlands)

    de Jeu, R.A.M.; Wagner, W.W.; Holmes, T.R.H.; Dolman, A.J.; van de Giesen, N.C.; Friesen, J.

    2008-01-01

    Within the scope of the upcoming launch of a new water related satellite mission (SMOS) a global evaluation study was performed on two available global soil moisture products. ERS scatterometer surface wetness data was compared to AMSR-E soil moisture data. This study pointed out a strong similarity

  6. Variation in herbaceous vegetation and soil moisture under treated and untreated oneseed juniper trees

    Science.gov (United States)

    Hector Ramirez; Alexander Fernald; Andres Cibils; Michelle Morris; Shad Cox; Michael Rubio

    2008-01-01

    Clearing oneseed juniper (Juniperus monosperma) may make more water available for aquifer recharge or herbaceous vegetation growth, but the effects of tree treatment on soil moisture dynamics are not fully understood. This study investigated juniper treatment effects on understory herbaceous vegetation concurrently with soil moisture dynamics using vegetation sampling...

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

    Science.gov (United States)

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

    2013-01-01

    Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

  8. Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

    Science.gov (United States)

    Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

    2016-04-01

    Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas

  9. [Controlling effects of dual mulching on soil moisture in an apple orchard].

    Science.gov (United States)

    Tian, Fei; Xie, Yong-Sheng; Suo, Gai-Di; Ding, Ya-Dong

    2014-08-01

    To investigate the controlling effects of dual mulching on soil moisture in an apple orchard on the Weibei rainfed highland, soil moisture in the 0-600 cm soil profile of the apple orchard was measured under four mulching treatments (plastic film plus straw, plastic film and straw mulches, as well as a non-mulching control) , and meanwhile the apple yield and branch growth increment were analyzed statistically. Results showed that the dual mulching treatment had the best effect on soil moisture conservation, and the soil water storage in such a soil profile was 6.7% higher than the control treatment. Long-term dual mulching could effectively alleviate soil desiccation occurring in deep soil layer in the region, and the monthly averaged soil water storage in stable layer (240-600 cm) was 64.22 mm higher than that of the control treatment. Both plastic film plus straw and plastic film mulches were able to reduce the temporal fluctuation of soil moisture in shallow soil (0-60 cm) and enhance the temporal stability of soil moisture in the layer. Compared with the single mulching treatments, the dual mulching treatment could effectively decrease the vertical variation of soil moisture in the profile and improve the stability of the vertical soil moisture distribution. The apple yield under the dual mulching treatment was evidently increased by 48.2%, as compared with the control treatment. All the analyses showed that dual mulching had more advantages in controlling soil moisture and improving apple yield than single mulching.

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

    Science.gov (United States)

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

    2017-12-01

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

  11. Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates

    Science.gov (United States)

    Lievens, H.; Reichle, R. H.; Liu, Q.; De Lannoy, G. J. M.; Dunbar, R. S.; Kim, S. B.; Das, N. N.; Cosh, M.; Walker, J. P.; Wagner, W.

    2017-06-01

    SMAP (Soil Moisture Active and Passive) radiometer observations at ˜40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9 km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatiotemporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations.

  12. Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site

    Directory of Open Access Journals (Sweden)

    Alberto Pistocchi

    2013-10-01

    Full Text Available In this paper, the results of a comparison between the soil moisture content (SMC estimated from C-band SAR, the SMC simulated by a hydrological model, and the SMC measured on ground are presented. The study was carried out in an agricultural test site located in North-west Italy, in the Scrivia river basin. The hydrological model used for the simulations consists of a one-layer soil water balance model, which was found to be able to partially reproduce the soil moisture variability, retaining at the same time simplicity and effectiveness in describing the topsoil. SMC estimates were derived from the application of a retrieval algorithm, based on an Artificial Neural Network approach, to a time series of ENVISAT/ASAR images acquired over the Scrivia test site. The core of the algorithm was represented by a set of ANNs able to deal with the different SAR configurations in terms of polarizations and available ancillary data. In case of crop covered soils, the effect of vegetation was accounted for using NDVI information, or, if available, for the cross-polarized channel. The algorithm results showed some ability in retrieving SMC with RMSE generally <0.04 m3/m3 and very low bias (i.e., <0.01 m3/m3, except for the case of VV polarized SAR images: in this case, the obtained RMSE was somewhat higher than 0.04 m3/m3 (≤0.058 m3/m3. The algorithm was implemented within the framework of an ESA project concerning the development of an operative algorithm for the SMC retrieval from Sentinel-1 data. The algorithm should take into account the GMES requirements of SMC accuracy (≤5% in volume, spatial resolution (≤1 km and timeliness (3 h from observation. The SMC estimated by the SAR algorithm, the SMC estimated by the hydrological model, and the SMC measured on ground were found to be in good agreement. The hydrological model simulations were performed at two soil depths: 30 and 5 cm and showed that the 30 cm simulations indicated, as expected, SMC

  13. Electromagnetic wave scattering from vegetation (Potato) and vegetation covered soil moisture for remote sensing

    Science.gov (United States)

    Singh, Keshev

    In the country with limited resources, where the nutrition level of the population has to be maintained under inhospitable situation, the potato has a special value as food. Therefore efforts should be made for improvement and spreading the cultivation of this important crop. It demands an effective program that may provide information about potato growing areas and the growth conditions. Remote sensing has been acknowledged to be a valuable source of spatially comprehensive and temporally repeatable information of crop covered soil moisture, crop growth climatic information etc, which is useful and necessary for agriculture purposes. For this purpose, microwave remote sensing has evolved as an important tool. Since microwave are able to penetrate more deeply into vegetation and underneath ground surface. It is also preferred to the optical frequency band because microwave can work in all type of weather and have a wide signal dynamic range compared optical wavelengths. However interpretation of microwave scattering from agricultural crops requires an understanding the interaction among microwave, vegetative material and the soil. In order to develop useful forward and inverse models for retrieving the vegetation characteristic, it is necessary to know in detail the dielectric properties and plant structure of the vegetation over the range of expected growing conditions. In this paper, a theoretical model based on microwave interaction with potato crop along with examination of biomass of potato crop with the varying underlying soil moisture is studied. For this purpose, X-band (9.5GHz) scatterometer is used for studying the interaction of microwave with potato crop biomass and underlying soil moisture at various sensor parameters (i.e. angular variation and polarization, HH- and VV-). Although there may be a lot of crop parameters (i.e. crop height, leaf area index, etc) which also gives their effect on microwave. All this parameters are interlinked in the crop

  14. Scatterometer-Derived Soil Moisture Calibrated for Soil Texture With a One-Dimensional Water-Flow Model

    NARCIS (Netherlands)

    Lange, de R.; Beck, R.; Giesen, van de N.; Friesen, J.; Wit, de A.J.W.; Wagner, W.

    2008-01-01

    Current global satellite scatterometer-based soil moisture retrieval algorithms do not take soil characteristics into account. In this paper, the characteristic time length of the soil water index has been calibrated for ten sampling frequencies and for different soil conductivity associated with 12

  15. Effects of hedgerow systems on soil moisture and unsaturated hydraulics conductivity measured by the Libardi method

    Directory of Open Access Journals (Sweden)

    S . Prijono

    2016-01-01

    Full Text Available The hedgerow systems are the agroforestry practices suggesting any positive impacts and negative impacts on soil characteristics. This study evaluated the effects of hedgerows on the unsaturated hydraulic conductivity of soil with the Libardi method approach. This study was conducted in North Lampung for 3 months on the hedgerow plots of Peltophorum dassyrachis (P, Gliricidia sepium (G, and without hedgerow plot (K, with four replications. Each plot was watered as much as 150 liters of water until saturated, then the soil surface were covered with the plastic film. Observation of soil moisture content was done to a depth of 70 cm by the 10 cm intervals. Soil moisture content was measured using the Neutron probe that was calibrated to get the value of volumetric water content. Unsaturated hydraulic conductivity of soil was calculated by using the Libardi Equation. Data were tested using the analysis of variance, the least significant different test (LSD, Duncan Multiple Range Test (DMRT, correlation and regression analysis. The results showed that the hedgerow significantly affected the soil moisture content and unsaturated hydraulic conductivity. Soil moisture content on the hedgerow plots was lower than the control plots. The value of unsaturated hydraulic conductivity in the hedgerow plots was higher than the control plots. Different types of hedgerows affected the soil moisture content and unsaturated hydraulic conductivity. The positive correlation was found between the volumetric soil moisture content and the unsaturated hydraulic conductivity of soil.

  16. Consequences of artic ground squirrels on soil carbon loss from Siberian tundra

    Science.gov (United States)

    Golden, N. A.; Natali, S.; Zimov, N.

    2014-12-01

    A large pool of organic carbon (C) has been accumulating in the Arctic for thousands of years. Much of this C has been frozen in permafrost and unavailable for microbial decomposition. As the climate warms and permafrost thaws, the fate of this large C pool will be driven not only by climatic conditions, but also by ecosystem changes brought about by arctic animal populations. In this project we studied arctic ground squirrels (Spermophilus parryii), which are widely-distributed throughout the Arctic. These social mammals create subterranean burrows that mix soil layers, increase aeration, alter soil moisture and temperature, and redistribute soil nutrients, all of which may impact microbial decomposition. We examined the effects of arctic ground squirrel activity on soil C mineralization in dry heath tundra underlain by continuous permafrost in the Kolyma River watershed in northeast Siberia, Russia. Vegetation cover was greatly reduced on the ground squirrel burrows (80% of ground un-vegetated), compared to undisturbed sites (35% of ground un-vegetated). Soils from ground squirrel burrows were also significantly dryer and warmer. To examine effects of ground squirrel activity on microbial respiration, we conducted an 8-day incubation of soil fromburrows and from adjacent undisturbed tundra. In addition, we assessed the impact of nutrient addition by including treatments with low and high levels of nitrogen addition. Microbial respiration (per gram soil) was three-fold higher in incubated soils from the undisturbed sites compared to soils collected from the burrows. The lower rates of respiration from the disturbed soils may have been a result of lower carbon quality or low soil moisture. High nitrogen addition significantly increased respiration in the undisturbed soils, but not in the disturbed burrow soils, which suggests that microbial respiration in the burrow soils was not primarily limited by nitrogen. These results demonstrate the importance of wildlife

  17. Upscaling of Surface Soil Moisture Using a Deep Learning Model with VIIRS RDR

    Directory of Open Access Journals (Sweden)

    Dongying Zhang

    2017-04-01

    Full Text Available In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, the performance of most models is largely determined by the size of the training data and the limited generalization ability to accomplish correlation extraction in regression models, which are unsuitable for larger scale practices. In this paper, a deep learning model was proposed to estimate soil moisture on a national scale. The deep learning model has the advantage of representing nonlinearities and modeling complex relationships from large-scale data. To illustrate the deep learning model for soil moisture estimation, the croplands of China were selected as the study area, and four years of Visible Infrared Imaging Radiometer Suite (VIIRS raw data records (RDR were used as input parameters, then the models were trained and soil moisture estimates were obtained. Results demonstrate that the estimated models captured the complex relationship between the remote sensing variables and in situ surface soil moisture with an adjusted coefficient of determination of R ¯ 2 = 0.9875 and a root mean square error (RMSE of 0.0084 in China. These results were more accurate than the Soil Moisture Active Passive (SMAP active radar soil moisture products and the Global Land data assimilation system (GLDAS 0–10 cm depth soil moisture data. Our study suggests that deep learning model have potential for operational applications of upscaling in situ surface soil moisture data at the national scale.

  18. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Directory of Open Access Journals (Sweden)

    R. Orth

    2013-10-01

    Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  19. Wind erosion and its impact on soil carbon and moisture scarcity

    NARCIS (Netherlands)

    Wang Xiaobin,; Cai, D.; Oenema, O.; Perdok, U.D.; Hoogmoed, W.B.

    2005-01-01

    This review discusses the duststorm-related soil erosion and its impact on soil carbon losses and moisture scarcity in northern China. Heavily affected areas show a loss of nutrients, organic carbon and field water capacity of soils. Compared with nondegraded soil, the carbon content in degraded

  20. Vertical and lateral soil moisture patterns on a Mediterranean karst hillslope

    Directory of Open Access Journals (Sweden)

    Canton Yolanda

    2016-09-01

    . Understanding how terrain attributes, ground cover and soil factors interact for controlling θ pattern on karst hillslope is crucial to understand water fluxes in the vadose zone and dominant percolation mechanisms which also contribute to estimate groundwater recharge rates. Therefore, understanding of soil moisture dynamics provides very valuable information for designing rational strategies for the use and management of water resources, which is especially urgent in regions where groundwater supports human consume or key economic activities.

  1. Moisture content effect in the relationship between apparent electrical conductivity and soil attributes

    Directory of Open Access Journals (Sweden)

    Marcelo Marques Costa

    2014-08-01

    Full Text Available To map the spatial variability of a field to define the variable rate application, an intensive sampling of the soil-plant system is necessary. The apparent soil electrical conductivity (ECa has been used for soil mapping because it correlates well with soil attributes, allows for dense sampling and can be obtained at low cost. However, ECa is influenced by soil moisture content, and the variability of this attribute can reduce the reliability of the ECa maps to explain the physical and chemical soil attributes. The objective of this study was to identify conditions that maximize the correlations between the ECa and the soil attributes. The results show that the mean soil moisture content of soil sampled on different dates was correlated with the mean of the ECa. The ideal time for measuring ECa occurred when the mean moisture content of the soil was higher. In this condition, the coefficient of variation for the soil moisture content was lower, there was no correlation between ECa and soil moisture content, and ECa was more correlated with other soil attributes evaluated in this work.

  2. Characteristics and performance of L-band radar-based soil moisture retrievals using Soil Moisture Active Passive (SMAP) synthetic aperture radar observations

    Science.gov (United States)

    Kim, S.; Johnson, J. T.; Moghaddam, M.; Tsang, L.; Colliander, A.

    2016-12-01

    Surface soil moisture of the top 5-cm was estimated at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Radar observations of soil moisture offer the advantage of high spatial resolution, but have been challenging in the past due to the complicating factors of surface roughness and vegetation scattering. In this work, physically-based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of roughness and dynamic vegetation. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-RMSE (root mean square error, ubRMSE) and -0.05 dB (bias). The forward models further allow the mechanisms of radar scattering to be examined to identify the sensitivity of radar scattering to soil moisture. Global patterns of the soil moistures retrieved by the algorithm generally match well with those from other satellite sensors. However biases exist in dry regions, and discrepancies are found in thick vegetation areas. The retrievals are compared with in situ measurements of soil moisture in locations characterized as cropland, grassland, and woody vegetation. Terrain slopes, subpixel heterogeneity, tillage practices, and vegetation growth influence the retrievals, but are largely corrected by the retrieval processes. Soil moisture retrievals agree with the in-situ measurements at 0.052 m3/m3 ubRMSE, -0.015 m3/m3 bias, and a correlation of 0.50. These encouraging retrieval results demonstrate the feasibility of a physically-based time-series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation types. The findings are important for future L-band radar missions with frequent revisits that permit time

  3. Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US

    Science.gov (United States)

    As soil moisture increases, slope stability decreases. Remotely sensed soil moisture data can provide routine updates of slope conditions necessary for landslide predictions. For regional scale landslide investigations, only remote sensing methods have the spatial and temporal resolution required to...

  4. TMI/TRMM surface soil moisture (LPRM) L2 V001 (LPRM_TMI_SOILM2) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — TMI/TRMM surface soil moisture (LPRM) L2 V001 is a Level 2 (swath) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and...

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

    Science.gov (United States)

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

    2013-01-01

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

  6. Synergistic method for boreal soil moisture and soil freeze retrievals using active and passive microwave instruments

    Science.gov (United States)

    Smolander, Tuomo; Lemmetyinen, Juha; Rautiainen, Kimmo; Schwank, Mike; Pulliainen, Jouni

    2017-04-01

    Soil moisture and soil freezing are important for diverse hydrological, biogeochemical, and climatological applications. They affect surface energy balance, surface and subsurface water flow, and exchange rates of carbon with the atmosphere. Soil freezing controls important biogeochemical processes, like photosynthetic activity of plants and microbial activity within soils. Permafrost covers approximately 24% of the land surface in the Northern Hemisphere and seasonal freezing occurs on approximately 51% of the area. The retrieval method presented is based on an inversion technique and applies a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil permittivity, the extinction coefficient of forest canopy, surface roughness, incidence angle, and radar frequency. It gives an estimate of soil permittivity using active microwave measurements. Applying a Bayesian assimilation scheme, it is also possible to use other soil permittivity retrievals to regulate this estimate to combine for example low resolution passive observations with high resolution active observations for a synergistic retrieval. This way the higher variance in the active retrieval can be constricted with the passive retrieval when at the same time the spatial resolution of the product is improved compared to the passive-only retrieval. The retrieved soil permittivity estimate can be