Sample records for soil moisture analysis

  1. Soil Moisture

    NSDL National Science Digital Library

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

  2. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    PubMed

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

    2015-07-21

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Rank Stability Analysis of Surface and Profile Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Microwave soil moisture measurements and analysis

    NASA Technical Reports Server (NTRS)

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

    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.

  6. Soil Moisture Project Evaluation Workshop

    NASA Technical Reports Server (NTRS)

    Gilbert, R. H. (editor)

    1980-01-01

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

  7. Analysis of Soil Moisture Changes in Europe during a Single Growing Season in a New ECMWF Soil Moisture Assimilation System

    E-print Network

    Haak, Hein

    infrastructure. In the first topic the effect of the (spinup related) bias in 40-yr ECMWF Re-Analysis (ERA-40 in the climate system. Initial conditions in numerical weather prediction models of soil moisture for the upper and support the physical insight in the performance of the land surface component. It addresses four topics

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed Central

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

    2010-01-01

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

  11. Root-zone soil moisture analysis using microwave radiometry

    Microsoft Academic Search

    Jean-Christophe Calvet; Joël Noilhan; J.-P. Wigneron; Y. Kerr

    2001-01-01

    The SMOS project (CNES\\/ESA) aims at developing a L-band interferometric radiometer able to provide global estimates of surface soil moisture (ws) with a sampling time of 2-3 d. Several studies showed that the assimilation of ws time series enable one to retrieve the root-zone water content, provided the atmospheric forcing is available from ancillary information. Two real cases of variational

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    Microsoft Academic Search

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

    2010-01-01

    In this study, a variogram is used to analyze the spatial structure of the Air Force Weather Agency's (AFWA) Agricultural Meteorology (AGRMET) soil moisture model output and in-situ Oklahoma Mesonet soil moisture data. The spatial variability information is then used by a Kriging method to estimate soil moisture at unsampled locations. The spatial decorrelation length scale of soil moisture is

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work in Crow et al. (2009) developed an algorithm for enhancing satellite-based land rainfall products via the assimilation of remotely-sensed surface soil moisture retrievals into a water balance model. As a follow-up, this paper describes the benefits of modifying their approach to incorpor...

  15. Soil Moisture Workshop

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  16. A method to improve satellite soil moisture retrievals based on Fourier analysis

    NASA Astrophysics Data System (ADS)

    Du, Jinyang

    2012-08-01

    Knowledge of the spatial distribution and temporal changes of the global soil moisture for a long period of time is crucial to the understanding of climate changes and hydrological processes. By applying Fourier analysis to the time-series observations from the space-borne passive microwave sensors, this paper proposes a method to extract the high-frequency part of the satellite observed signals that reflect the soil moisture changes and help to generate the historical soil moisture datasets with an improved accuracy. The method is applied to the observations from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Validations using field sampled soil moisture from two watersheds in the U.S. indicate that the method can effectively improve the sensitivity of current National Aeronautics and Space Administration (NASA) soil moisture products to the temporal changes of the surface soil moisture, with the correlation coefficients of the retrievals and measurements increased from 0.462 to 0.595 and 0.403 to 0.613 for the two watersheds, respectively.

  17. Analysis and modeling of space-time organization of remotely sensed soil moisture

    Microsoft Academic Search

    Dyi-Huey Chang

    2002-01-01

    The characterization and modeling of the spatial variability of soil moisture is an important problem for various hydrological, ecological, and atmospheric processes. A compact representation of interdependencies among soil moisture distribution, mean soil moisture, soil properties and topography is necessary. This study attempts to provide such a compact representation using two complimentary approaches. In the first approach, we develop a

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

    NSDL National Science Digital Library

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  1. Soil Moisture Memory in Climate Models

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  2. Passive Microwave Soil Moisture Research

    Microsoft Academic Search

    Thomas Schmugge; Peggy O'Neill; James Wang

    1986-01-01

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

  3. Catchment scale validation of SMOS and ASCAT soil moisture products using hydrological modeling and temporal stability analysis

    NASA Astrophysics Data System (ADS)

    Rötzer, K.; Montzka, C.; Bogena, H.; Wagner, W.; Kerr, Y. H.; Kidd, R.; Vereecken, H.

    2014-11-01

    Since soil moisture is an important influencing factor of the hydrological cycle, knowledge of its spatio-temporal dynamics is crucial for climate and hydrological modeling. In recent years several soil moisture data products from satellite information have become available with global coverage and sub-monthly resolution. Since the remote sensing of soil moisture is an indirect measurement method and influenced by a large number of factors (e.g. atmospheric correction, vegetation, soil roughness, etc.), a comprehensive validation of the resulting soil moisture products is required. However, the coarse spatial resolution of these products hampers the comparison with point-scale in situ measurements. Therefore, upscaling of in situ to the scale of the satellite data is needed. We present the validation results of the soil moisture products of the years 2010-2012 retrieved from the Soil Moisture and Ocean Salinity (SMOS) and the Advanced Scatterometer (ASCAT) for the Rur and Erft catchments in western Germany. For the upscaling of in situ data obtained from three test sites of the Terrestrial Environmental Observatories (TERENO) initiative we used the hydrological model WaSiM ETH. Correlation of the SMOS product to modeled and upscaled soil moisture resulted in a mean correlation coefficient of 0.28 whereas for ASCAT a correlation coefficient of 0.50 was obtained. However, for specific regions the SMOS product showed similar correlation coefficients as the ASCAT product. While for ASCAT correlation was mainly dependent on topography and vegetation, SMOS was also influenced by radiofrequency interferences in our study area. Both products show dry biases as compared to the soil moisture reference. However, while SMOS showed relatively constant bias values, ASCAT bias is variable throughout the year. As an additional validation method we performed a temporal stability analysis of the retrieved spatio-temporal soil moisture data. Through investigation of mean relative differences of soil moisture for every pixel, their standard deviations and their rankings, we analyzed the temporal persistence of spatial patterns. Our results show high standard deviations for both SMOS and ASCAT soil moisture products as compared to modeled soil moisture, indicating a lower temporal persistence. The consistence of ranks of mean relative differences was low for SMOS and relative ASCAT soil moisture compared to modeled soil moisture, while ASCAT soil moisture, converted to absolute values, showed higher rank consistence.

  4. A soil moisture budget analysis of Texas using basic climatic data 

    E-print Network

    Lowther, Ronald Paul

    1989-01-01

    properties. The soil moisture regime is established accounting for different soil types, infiltration rates, and vegetative cover. The daily soil moisture budget is computed over the entire period of record and the results are graphed using pentad periods... during the crop year. While the lowest mean state of the soil moisture occurs in the Panhandle region in spring, it occurs in the fall season in the eastern part of the state where the precipitation is higher. Other applications of thc computed model...

  5. 11, 79918022, 2014 Soil moisture

    E-print Network

    Gracia, Carlos

    BGD 11, 7991­8022, 2014 Soil moisture overrules temperature dependency of soil respiration C moisture overrule temperature dependency of soil respiration in Mediterranean riparian forests? C.-T. Chang of soil respiration C.-T. Chang et al. Title Page Abstract Introduction Conclusions References Tables

  6. Analysis of Soil Moisture Using a Long-term Record of Synthetic Aperture Radar Backscatter

    NASA Astrophysics Data System (ADS)

    Overduin, P. P.; Nolan, M.

    2001-12-01

    The promise of monitoring temporal variation in soil moisture levels has spurred much research into the capabilities of synthetic aperture radar techniques (SAR). SAR backscatter intensity is determined by characteristics of the reflecting surface, including the surface dielectric and roughness. In the boreal forest of interior Alaska, SAR imagery has been tested for its use as a measure of soil dielectric and therefore moisture content, but a clear correlation between C-band backscatter and soil dielectric has not been found. We examine a 5 year record of over 400 SAR images from the Caribou-Poker Creek Research Watershed in interior Alaska, including ERS-1, ERS-2, JERS and radarsat, and compare it to field ground-truthing data and detailed topographic and vegetation distribution information. Our objective is to place constraints on the usefulness of SAR data as an indicator of soil moisture levels in a variety of forest canopies. Pixel to field data comparisons do not show a clear link between the two, not a surprising result considering the different scales of measurement involved. Further, field measurements themselves do not show a clear correlation to weather, as the measurement of point data in tussock fields has considerable error. Trend analysis of changes between successive SAR scenes has yielded the most useful results. SAR images show strong seasonal signal corresponding to seasonal temperature fluctuations, the result of changes in backscatter due to changes in vegetation. The onset of snow melt also shows clearly through the canopy. Soil moisture variations through the canopy are much more subtle, though more evident in recent fire scars.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

    Milstead, B. W.

    1975-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Wiß, Felix; Stacke, Tobias; Hagemann, Stefan

    2014-05-01

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

  13. Global Soil Moisture Data Bank

    NSDL National Science Digital Library

    Robock, Alan

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

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  15. meeting summary: GEWEX\\/BAHC International Workshop on Soil Moisture Monitoring, Analysis, and Prediction for Hydrometeorological and Hydroclimatological Applications

    Microsoft Academic Search

    J. Leese; T. Jackson; A. Pitman; P. Dirmeyer

    2001-01-01

    The International Workshop on Soil Moisture Monitoring, Analysis, and Prediction for Hydrometeorological and Hydroclimatological Applications considered the potential for implementing a global system during this decade and for identifying the priorities for the research needed to achieve such a global system. The workshop attendees advised that a global system should provide measurements and\\/or estimates of volumetric soil water content on

  16. Analysis of soil moisture retrieval from airborne passive/active L-band sensor measurements in SMAPVEX 2012

    NASA Astrophysics Data System (ADS)

    Chen, Liang; Song, Hongting; Tan, Lei; Li, Yinan; Li, Hao

    2014-11-01

    Soil moisture is a key component in the hydrologic cycle and climate system. It is an important input parameter for many hydrologic and meteorological models. NASA'S upcoming Soil Moisture Active Passive (SMAP) mission, to be launched in October 2014, will address this need by utilizing passive and active microwave measurements at L-band, which will penetrate moderately dense canopies. In preparation for the SMAP mission, the Soil Moisture Validation Experiment 2012 (SMAPVEX12) was conducted from 6 June to 17 July 2012 in the Carment-Elm Creek area in Manitoba, Canada. Over a period of six weeks diverse land cover types ranging from agriculture over pasture and grassland to forested sites were re-visited several times a week. The Passive/Active L-band Sensor (PALS) provides radiometer products, vertically and horizontally polarized brightness temperatures, and radar products. Over the past two decades, successful estimation of soil moisture has been accomplished using passive and active L-band data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. This work focuses on analyzing the Passive/Active L-band Sensor observations of sites covered during SMAPVEX12, investigating the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks. The data and analysis results from this study are aimed at increasing the accuracy and range of validity of SMAP soil moisture retrievals via enhancing the accuracy for soil moisture retrieval.

  17. An analysis of the soil moisture-rainfall feedback, based on direct observations from Illinois

    Microsoft Academic Search

    Kirsten L. Findell; Elfatih A. B. Eltahir

    1997-01-01

    Many global and regional climate modeling studies have demonstrated the importance of the initial soil water condition in their simulations of regional rainfall distribution. However, none of these modeling studies has been tested against directly observed data. This study tests the hypothesis that soil saturation is positively correlated with subsequent precipitation by analyzing a 14-year soil moisture data set from

  18. Radar scattering and soil moisture

    NASA Technical Reports Server (NTRS)

    Levine, D. M.; Neill, P. O.

    1988-01-01

    Research is being conducted on microwave scattering from vegetation. The objective is to develop techniques for measuring parameters of the vegetation canopy (such as biomass) needed for understanding global biogeochemical cycles and to develop techniques for correcting microwave measurements of soil moisture for the effects of the vegetation canopy. Measurements of vegetation and soil moisture are important for understanding the environment on a global scale. For example, moisture in the soil is an important, highly variable, element in the global hydrologic cycle. The hydrologic cycle, in turn, is strongly coupled to weather and climate through moisture (and energy) fluxes at the surface. The amount and distribution of vegetation is an important element in biogeochemical cycles; and knowledge of both the vegetation canopy and soil moisture is of practical importance in agricultural management. These theories are examined.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    PubMed Central

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

    2009-01-01

    Some outcomes of a feasibility analysis of a spaceborne bistatic radar mission for soil moisture retrieval are presented in this paper. The study starts from the orbital design of the configuration suitable for soil moisture estimation identified in a previous study. This configuration is refined according to the results of an analysis of the spatial resolution. The paper focuses on the assessment of the spatial coverage i.e., on the verification that an adequate overlap between the footprints of the antennas is ensured and on the duty cycle, that is the fraction of orbital period during which the bistatic data are acquired. A non-cooperating system is considered, in which the transmitter is the C-band Advanced Synthetic Aperture Radar aboard Envisat. The best performances in terms of duty cycle are achieved if the transmitter operates in Wide Swath Mode. The higher resolution Image Swath Modes that comply with the selected configuration have a duty cycle that is never less than 12% and can exceed 21%. When Envisat operates in Wide Swath Mode, the bistatic system covers a wide latitude range across the equator, while in some of the Image Swath Modes, the bistatic measurements, collected from the same orbit, cover mid-latitude areas. In the latter case, it might be possible to achieve full coverage in an Envisat orbit repeat cycle, while, for a very large latitude range such as that covered in Wide Swath Mode, bistatic acquisitions could be obtained over about 65% of the area. PMID:22399996

  2. Bistatic radar configuration for soil moisture retrieval: analysis of the spatial coverage.

    PubMed

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

    2009-01-01

    Some outcomes of a feasibility analysis of a spaceborne bistatic radar mission for soil moisture retrieval are presented in this paper. The study starts from the orbital design of the configuration suitable for soil moisture estimation identified in a previous study. This configuration is refined according to the results of an analysis of the spatial resolution. The paper focuses on the assessment of the spatial coverage i.e., on the verification that an adequate overlap between the footprints of the antennas is ensured and on the duty cycle, that is the fraction of orbital period during which the bistatic data are acquired. A non-cooperating system is considered, in which the transmitter is the C-band Advanced Synthetic Aperture Radar aboard Envisat. The best performances in terms of duty cycle are achieved if the transmitter operates in Wide Swath Mode. The higher resolution Image Swath Modes that comply with the selected configuration have a duty cycle that is never less than 12% and can exceed 21%. When Envisat operates in Wide Swath Mode, the bistatic system covers a wide latitude range across the equator, while in some of the Image Swath Modes, the bistatic measurements, collected from the same orbit, cover mid-latitude areas. In the latter case, it might be possible to achieve full coverage in an Envisat orbit repeat cycle, while, for a very large latitude range such as that covered in Wide Swath Mode, bistatic acquisitions could be obtained over about 65% of the area. PMID:22399996

  3. Soil moisture controls beyond the Darcy scale

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2013-12-01

    Processes controlling soil moisture distribution beyond the Darcy scale have not yet been adequately explored. Akin to the presence of certain soil moisture thresholds at the Darcy scale beyond which processes like vapor flow, film flow and capillary flow become more dominating than the others, it is hypothesized that similar thresholds may exist for the coarser scale. Coarse scale soil moisture distribution is known to depend on different processes like infiltration, interception, stem flow, sub-surface flow etc. These processes occur due to heterogeneity in physical factors, namely, soil, vegetation, topography and meteorological factors. This study evaluates the quantitative relative contribution of different physical factors (% sand, % clay, elevation, slope, flow accumulation and leaf area index) on the structure of soil moisture at different scales (1.6, 3.2, 6.4, 12.8 and 25.6 km) and determines the presence of certain scale based ';thresholds' at which the relationship between physical controls and soil moisture distribution changes. Coarse change maps representing soil moisture change at different time scales were generated using airborne soil moisture data collected during various soil moisture campaigns (SGP97, SMEX02 and SMEX04) to assess the nature of drying/wetting dynamics that exist in a particular region. Wavelet analysis was conducted on these change maps and physical factors and scale based correlations between soil moisture dynamics and physical factors were determined. The study has been conducted over 3 hydro-climates (humid, sub-humid and semi-arid) to assess the transferability of these results across hydro-climates. It has been found that within a particular hydro-climate, it may be possible to define fuzzy threshold boundaries at which different physical factors (and related physical processes) become dominant. However, across hydro-climates the results are not transferable. It indicates that the composition of heterogeneity of a particular hydro-climate (i.e. combination of topography, soil and vegetation) influences the effect that each physical factor has on the soil moisture distribution. Thus, the influence of physical factors on soil moisture distribution is non-linear. However, the effect of different physical factors within a hydro-climate itself is dependent upon the spatial support scale of analysis.

  4. Radar sensing of soil moisture

    Microsoft Academic Search

    Fawwaz T. Ulaby; Richard K. Moore

    1973-01-01

    Remote sensing of soil moisture is of primary concern to hydrologists involved in flood forecasting and in the large-scale water resource management of farming regions and to meteorologists interested in the energy and mass exchange at the airsoil interface. For terrain surfaces such as soil, the dielectric properties are strongly de endent upon the free water content in the soil;

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

  6. Aircraft radar response to soil moisture

    NASA Technical Reports Server (NTRS)

    Bradley, G. A.; Ulaby, F. T.

    1981-01-01

    An analysis is presented of aircraft response to soil moisture in the upper surface layer of agricultural fields. Measurements (taken at 1.6 GHz and 4.75 GHz using HH and HV polarizations, and at 13.3 GHz using VV polarization from an experiment conducted in 1978 at Colby, Kansas) are used to derive the radar soil moisture sensitivities and correlations. It is shown that the aircraft response to soil moisture is optimum at C-band frequencies and incidence angles of 10-20 deg. confirming previous truck-radar results. Like-polarization radar response is unaffected by vegetation but is dependent on row-tillage patterns; cross-polarization response also is unaffected by vegetation but is approximately independent of tillage patterns. These results show that remote sensing radars can be used effectively for the detection and estimation of near-surface soil moisture in agricultural fields.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Microsoft Academic Search

    Todd Lookingbill; Dean Urban

    2004-01-01

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

  9. Overview of hydros radar soil moisture algorithm

    Microsoft Academic Search

    Yunjin Kim; Jakob van Zyl

    2005-01-01

    In this paper, we will describe the Hydros algorithms to derive soil moisture from L-band polarimetric radar measurements. The baseline Hydros radar algorithm to estimate soil moisture is composed of three steps: land classification, preliminary soil moisture estimation, and final time-series improvement. Before soil moisture is estimated using Hydros radar data, each pixel will be classified in order to apply

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

    NASA Technical Reports Server (NTRS)

    Peterson, John B. (Inventor)

    1982-01-01

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

  11. Vadose Zone Journal Soil Moisture Retrieval Using

    E-print Network

    Krakauer, Nir Y.

    Vadose Zone Journal Soil Moisture Retrieval Using Ground-Based L-Band Passive Microwave includes a mobile L-band dual-polarized radiometer with an in situ soil tem- perature and soil moisture measure- ments of L-band brightness temperatures, surface temperature, soil moisture, and soil temperature

  12. Active Microwave Soil Moisture Research

    Microsoft Academic Search

    M. CRAIG DOBSON; FAWWAZ T. ULABY

    1986-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. A soil moisture budget analysis of Texas using basic climatic data while assuming a possible warming trend across the state 

    E-print Network

    Bjornson, Brian Matthew

    1990-01-01

    Evapotranspiration and Temperature 3. A Control Soil Moisture Budget . B, A Soil Moisture Budget Based on a Warming Trend 26 28 29 35 37 CHAFIER IV. PRESENTATION OF THE RESULTS A. Soil Moisture Regime 1. Relationship Between MMP and MMT . 2. Relationship... Between Evapotranspiration and Temperature B. A Control Soil Moisture Budget and a Soil Moisture Budget Based on a Warming Trend I. High Plains (Table 7) 2. North Central (Table 8) 3. East Texas (Table 9) 4. Edwards Plateau (Table 10) 5. South...

  16. Global Soil Moisture Data Bank

    NSDL National Science Digital Library

    From the Department of Environmental Sciences at Rutgers, The State University of New Jersey, highlights of this site include data sets from soil moisture observation stations in Eurasia (including China, India, Mongolia, and the former Soviet Union) as well as the slightly less exotic locales of Iowa and Illinois. These data sets are available by clicking on a map of Eurasia and the two US states. Links to other data sets include those for Australia, Brazil, Europe, Russia and Ukraine, and the US. The site also offers abstracts and full-text papers on soil moisture research. Finally, additional sections lead to carefully selected links for model calculations, related projects, and soil moisture measurements.

  17. Gravimetric Soil Moisture Protocols

    NSDL National Science Digital Library

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

    2003-08-01

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

  18. Remote sensing of soil moisture - Recent advances

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.

    1983-01-01

    Recent advancements in microwave remote sensing of soil moisture include a method for estimating the dependence of the soil dielectric constant on its texture, the use of a percent of field capacity to express soil moisture magnitudes independently of soil texture, methods of estimating soil moisture sampling depth, and models for describing the effect of surface roughness on microwave response in terms of surface height variance and horizontal correlation length, as well as the verification of radiative transfer model predictions of microwave emission from soils and methods for the estimation of vegetation effects on the microwave response to soil moisture. Such researches have demonstrated that it is possible to remotely sense soil moisture in the 0-5 cm soil surface layer, and simulation studies have indicated how remotely sensed surface soil moisture may be used to estimate evapotranspiration rates and root-zone soil moisture.

  19. Large Scale Evaluation of AMSR-E Soil Moisture Products Based on Ground Soil Moisture Network Measurements

    NASA Astrophysics Data System (ADS)

    Gruhier, C.; de Rosnay, P.; Richaume, P.; Kerr, Y.; Rudiger, C.; Boulet, G.; Walker, J. P.; Mougin, E.; Ceschia, E.; Calvet, J.

    2007-05-01

    This paper presents an evaluation of AMSR-E (Advanced Microwave Scanning Radiometer for EOS) soil moisture products, based on a comparison with three ground soil moisture networks. The selected ground sites are representative of various climatic, hydrologic and environmental conditions in temperate and semi-arid areas. They are located in the south-west of France, south-east of Australia and the Gourma region of the Sahel. These sites were respectively implemented in the framework of the projects SMOSREX (Surface Monitoring Of Soil Reservoir Experiment), SASMAS/GoREx (Scaling and Assimilation of Soil Moisture and Streamflow in the Goulburn River Experimental catchment) and AMMA (African Monsoon Multidisciplinary Analysis). In all cases, the arrangement of the soil moisture measuring sites was specifically designed to address the validation of remotely sensed soil moisture in the context of the preparation of the SMOS (Soil Moisture and Ocean Salinity) project. For the purpose of this study, 25km AMSR-E products were used, including brightness temperatures at 6.9 and 10.7 GHz, and derived soil moisture. The study is focused on the year 2005. It is based on ground soil moisture network measurements from 4 stations for SMOSREX extended to the SUDOUEST project of CESBIO, 12 stations for GoRex, and 4 stations for AMMA. Temporal and spatial features of soil moisture variability and stability is a critical issue to be addressed for remotely sensed soil moisture validation. While ground measurements provide information on soil moisture dynamics at local scale and high temporal resolution (hourly), satellite measurements are sparser in time (up to several days), but cover a larger region (25km x 25km for AMSR-E). First, a statistical analysis, including mean relative difference and Spearman rank, is conducted for the three soil moisture networks. This method is mainly based on the approach proposed by Cosh et al. (2004) for the purpose of the use of ground networks for satellite remote sensing validation. It allows to capture soil moisture variability features and to identify for each site the most representative station. Second, a comparison of AMSR-E derived and in-situ soil moisture measurements was conducted. Volumetric soil moisture obtained from ground and satellite measurements are compared for both absolute and normalized values. For the three sites, results suggest that although AMSR-E soil moisture products are not able to capture the same range of soil moisture values as in-situ measurements, they provide reliable information on surface soil moisture temporal variability over the three sites. It is shown, however, that the use of radiometric products such as polarization ratio provide better agreement with ground stations, than the derived soil moisture products.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  1. Numerical studies on soil moisture distributions in heterogeneous catchments

    Microsoft Academic Search

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

    2007-01-01

    The paper deals with numerical studies of basin-scale dynamics of soil moisture in arbitrarily heterogeneous conditions (i.e., in presence of heterogeneity of climate, soil, vegetation and land use). Its relevance stems from comparative analysis of the probabilistic structure of spatially averaged soil moisture fields with the corresponding exact solutions of the underlying simplified stochastic point processes. The probabilistic structure of

  2. Operational Downscaling of Soil Moisture Fields Using Ancillary Data

    Microsoft Academic Search

    G. Kim; A. P. Barros

    2001-01-01

    The scaling analysis of large-scale soil moisture data from the Southern Great Plains Hydrology experiment (SGP'97) showed that the scaling behavior of soil moisture is multifractal varying with the scale of observations and hydroclimatological conditions which can be explained with scaling behavior of soil hydraulic properties. These results suggested that it should be possible to use the spatial patterns of

  3. Interaction between soil moisture memory and different climate variables

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2015-04-01

    A large number of modelling studies show a potential impact of the soil moisture state on regional climate on different time scales. Especially for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. The physical reasoning for such effects are usually attributed to the soil moisture - temperature as well as the soil moisture - precipitation feedbacks. We designed a model experiment to investigate the time scale until the effect of arbitrary soil moisture initialization is forgotten by the model. This time period is called soil moisture memory and computed for different seasons based on an ensemble of nine, 3 year long, simulations per season. These simulations are done using the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). Soil moisture memory was found to range between few days up to several months. While the longest memory often coincides with either snow-covered conditions or follows on monsoon periods, short memory is computed prior to snow-melt and rainy seasons. Additionally, the correlations between soil moisture memory and a number of surface variables was investigated. We found that the magnitude of the initial soil moisture perturbations explains at most 50% of the spatial variation in soil moisture memory while the remaining variance is associated with soil properties and - even stronger - with dynamical variables like surface temperature, evapotranspiration and runoff. This effect differs for different seasons and soil moisture regimes which demonstrates the complexity of soil moisture - climate interactions. Further analysis will be focused on the re-occurrence of soil moisture memory after periods of insignificant memory and the possibility of memory transfer between different land surface state variables.

  4. Passive microwave remote sensing of soil moisture

    Microsoft Academic Search

    Eni G. Njokul; Dara Entekhabi

    1996-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are

  5. Measurement Scheduling for Soil Moisture Sensing

    E-print Network

    Mahajan, Aditya

    INVITED P A P E R Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal energy consumption is presented; the paper is grounded in the physics of soil moisture. By David I Shuman of the observed phenomenon, we obtain statistics of soil moisture evolution from a physical model. We formulate

  6. The Soil Moisture Active Passive (SMAP) Mission

    Microsoft Academic Search

    Dara Entekhabi; Eni G. Njoku; Peggy E. O'Neill; Kent H. Kellogg; Wade T. Crow; Wendy N. Edelstein; Jared K. Entin; Shawn D. Goodman; Thomas J. Jackson; Joel Johnson; John Kimball; Jeffrey R. Piepmeier; Randal D. Koster; Neil Martin; Kyle C. McDonald; Mahta Moghaddam; Susan Moran; Rolf Reichle; J. C. Shi; Michael W. Spencer; Samuel W. Thurman; Leung Tsang; Jakob Van Zyl

    2010-01-01

    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. SMAP will make global measurements of the soil moisture present at the Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze\\/thaw state from

  7. Optimum Radar Parameters for Mapping Soil Moisture

    Microsoft Academic Search

    Fawwaz Ulaby; Percy Batlivala

    1976-01-01

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

  8. Continental-Scale Evaluation of Remotely Sensed Soil Moisture Products

    Microsoft Academic Search

    Wade T. Crow; Xiwu Zhan

    2007-01-01

    A new data assimilation-based approach for the continental-scale evaluation of remotely sensed surface soil moisture retrievals is applied to four separate soil moisture products over the contiguous U.S. The approach is based on quantifying the ability of a given soil moisture product to correct for known rainfall errors when sequentially assimilated into a simple water balance model. Analysis results provide

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  10. A soil moisture budget analysis of Texas using basic climatic data while assuming a possible warming trend across the state

    E-print Network

    Bjornson, Brian Matthew

    1990-01-01

    percent soil moisture profiles are plotted for each division (only for divisions where soil moisture is above 0% during any month) for all months of the year. A soil moisture profile was predicted using regression equations for the calculation... of precipitation and PET as temperatures increased in . the model. Only equations which were statistically significant (p-value x 0. 05) were used to estimate precipitation as temperature increased I'F between I'F and 4'F. The mean monthly precipitation...

  11. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  12. The North American Soil Moisture Database

    NASA Astrophysics Data System (ADS)

    Ford, T.; Quiring, S.

    2012-12-01

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

  13. Simulation of soil moisture and its variability in East Asia

    NASA Astrophysics Data System (ADS)

    Du, Chuanli; Wu, Wanli; Liu, Xiaodong; Gao, Wei

    2006-08-01

    Soil moisture and related hydrological process play an important role in regional and global climates. However, large-scale and long-term observation of soil moisture is sparse. In this study, the latest NCAR Community Land Model is used to simulate regional soil moisture in East Asia for recent 25 years with the atmospheric forcing provided by NCEP/DOE reanalysis. A 50-year simulation has been conducted with the first 25 years as the model spins up for soil moisture to reach steady state. The last 25 years simulation provides a soil moisture dataset with physical consistency and spatio-temporal continuity. Our analysis focuses on spatial and temporal variability of the regional soil moisture based on the last 25-year modeling. Additionally, The trend in the regional soil moisture and its possible link to climate warming is examined. The main conclusions can be summarized as follows: 1. Simulated soil moisture exhibits clear sensitivity to its initial condition. Such sensitivity is a function of soil depth. This study indicates that the equilibrium time of soil moisture increases with the depth of soil layers. It takes about 20 years to reach equilibrium below 1.5m. Therefore either a longer spin-up (20 years or more) or accurate initial soil moisture is necessary for a quality land surface modeling. 2. In comparison with the reanalysis and in-situ measurements, the model reproduces the observed large-scale structure reasonably well. The simulation shows mesoscale spatial variation as well. 3. Linear trend analysis shows that soil has become drier in most areas of East Asia in recent years except southern China and the Tibetan Plateau where soil gets wetter. Further analysis indicates that such dry trend may have a close link to warming surface climate through enhanced evaporation.

  14. Surface Soil Moisture Assimilation with SWAT

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Remote Sensing of Soil Moisture: Recent Advances

    Microsoft Academic Search

    Thomas J. Schmugge

    1983-01-01

    In the past few years there have been many advances in our understanding of microwave approaches for the remote sensing of soil moisture. These advances include a method for estimating the dependence of the soil's dielectric constant on its texture; the use of percent of field capacity to express soil moisture magnitudes independently of soil texture; experimental and theoretical estimates

  16. Influence of soil moisture on soil respiration

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Zawadzki, Jaros?aw; K?dzior, Mateusz

    2014-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  19. IMPROVING HYDROLOGICAL FORECASTING USING SPACEBORNE SOIL MOISTURE RETRIEVALS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using existing data sets of passive microwave spaceborne soil moisture retrievals, streamflow, and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Mission (TRMM...

  20. ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Seasonal to interannual variations of soil moisture measured in Oklahoma

    NASA Astrophysics Data System (ADS)

    Illston, Bradley G.; Basara, Jeffrey B.; Crawford, Kenneth C.

    2004-12-01

    Agriculture is a $2 billion component of the state economy in Oklahoma. As a result, meteorological, climatological, and agricultural communities should benefit from an improved understanding of soil moisture conditions and how those conditions vary spatially and temporally. The Oklahoma Mesonet is an automated observing network that provides real-time hydrometeorological observations at 115 stations across Oklahoma. In 1996, sensors were installed at 60 Mesonet sites to provide near-real-time observations of soil moisture.This study focuses on 6 years of soil moisture data collected between 1997 and 2002 to analyse the annual cycle and temporal characteristics of soil moisture across Oklahoma. The statewide analysis of the annual cycle of soil moisture revealed four distinct soil moisture phases. In addition, the four statewide phases were also observed in each of the nine climate divisions across Oklahoma, although the temporal characteristics of each phase were unique for each division. Further analysis demonstrated that, at shallow soil depths (5 and 25 cm), the spatial variability of soil moisture across Oklahoma was most homogeneous during the winter and spring periods and most heterogeneous during the summer and autumn periods. Conversely, at greater depths (60 and 75 cm), soil moisture was most heterogeneous during the winter period and the most homogeneous during the late spring.

  2. A simplified bi-dimensional variational analysis of soil moisture from screen-level observations in a mesoscale numerical weather-prediction model

    Microsoft Academic Search

    G. Balsamo; F. Bouyssel; J. Noilhan

    2004-01-01

    The analysis of soil moisture for the initialization of a mesoscale numerical weather-prediction (NWP) model is considered subject to operational constraints, both in terms of computational cost and data availability. A variational technique is used to analyse the soil moisture by assimilating screen-level observations of temperature and relative humidity. We consider a simplified bi-dimensional (z and t) variational approach (simplified

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

    Microsoft Academic Search

    Edson Eyji Sano

    1997-01-01

    In this study, the sensitivity of the C-band (5.3 GHz) with a 23sp° incidence angle and the Ku-band (14.85 GHz) with 35sp° ,\\\\ 55sp° , and 75sp° incidence angles to surface soil moisture content from a semiarid region were evaluated. To obtain an improved soil moisture estimation, a practical technique to reduce the influence of soil roughness and vegetation in

  4. An evaluation of remotely sensed soil moisture over Australia

    Microsoft Academic Search

    C. S. Draper; J. P. Walker; P. J. Steinle

    Novel remote sensing technologies offer the potential to replace these indirect soil moisture initialisation schemes with techniques that utilise observed surface soil moisture. It has already been demonstrated that assimilating remotely sensed soil moisture into land surface models can be benefit modelled soil moisture (e.g., Reichle and Koster, 2005). Currently, the most advanced techniques for remote sensing soil moisture over

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Soil Moisture Monitorization Using GNSS Reflected Signals

    E-print Network

    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...

  8. Electrical methods of determining soil moisture content

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  9. Operational Downscaling of Soil Moisture Fields Using Ancillary Data

    NASA Astrophysics Data System (ADS)

    Kim, G.; Barros, A. P.

    2001-05-01

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

  10. Gravity changes, soil moisture and data assimilation

    Microsoft Academic Search

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

    2003-01-01

    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

  11. Radar mapping of surface soil moisture

    Microsoft Academic Search

    Fawwaz T. Ulaby; Pascale C. Dubois; Jakob van Zyl

    1996-01-01

    Intended as an overview aimed at potential users of remotely sensed spatial distributions and temporal variations of soil moisture, this paper begins with an introductory section on the fundamentals of radar imaging and associated attributes. To place the soil moisture sensing task in proper perspective, the prerequisite step of classifying terrain into four basic types—bare surfaces, short vegetation, tall vegetation,

  12. Soil moisture retrievals: where are we?

    NASA Astrophysics Data System (ADS)

    Kerr, Y.; Leroux, D.; Richaume, P.; Wigneron, J. P.; Mialon, A.; Mahmoodi, A.; Bitar, A. Al; Novello, N.; Gruhier, C.; Pellarin, T.; Rudiger, C.; Lawrence, H.; De rosnay, P.; Albergel, C.

    2012-04-01

    Soil moisture is one of the most important variables regarding climate evolution ans plays a major role in the transfers between the soil and the atmosphere ([1]). Soil moisture needs to be considered as a global variable to improve our global comprehension of the climate. Several approaches have been developed to either model soil moisture or to retrieve it from satellite data. The European Center for Medium range Weather Forecasting (ECMWF) provides global maps of modeled soil moisture but there exists also regional climate models such as SIM, ???. Recently, satellite missions, specially designed for soil moisture monitoring such as the Soil Moisture and Ocean Salinity,(SMOS) have been proposed. SMOS was indeed successfully launched in November 2009 and SMAP (Soil Moisture Active Passive) is scheduled for launch in November 2014. Several algorithms have been created to retrieve soil moisture from higher frequencies measurements obtained from existing satellites such as : SMMR (1978-87), SSM/I (1987), AMSR-E (2004), ERS-ASCAT (1991-2006). Even if their lowest frequencies (5-20 GHz) are not the most suitable for soil moisture retrievals (very sensitive to vegetation growth and atmosphere), it remains a valuable time series from 1979 until now. All these products are obtained at a coarse resolution (typically around 50 km) and it is not always straight-forward to relate them to point measurements for the validation purposes especially at a global scale. It is thus necessary to validate coarse scale soil moisture estimates with model outputs or area representative points. SMOS validation has been performed on a number of sites but it is also necessary to inter-compare with other existing products (satellite products and model outputs) to identify the overall behavior at the global scale. The present paper deals with this topic.

  13. Investigation of remote sensing techniques of measuring soil moisture

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  14. Validation of SMOS and ASCAT Soil Moisture Products - Time Series Analysis in the Rur and Erft Catchments

    NASA Astrophysics Data System (ADS)

    Rötzer, K.; Montzka, C.; Bogena, H.; Wagner, W.; Kidd, R.; Vereecken, H.

    2012-04-01

    As soil moisture is an important driver for various climatic and hydrological processes, area-wide time series of soil moisture data are important for numerical weather predictions, for example at the European Centre for Medium-Range Weather Forecasts (ECMWF), as well as for climate and hydrological modeling. The Soil Moisture and Ocean Salinity (SMOS) satellite, launched in 2009, is an attempt to provide global soil moisture data in the required temporal resolution. SMOS records brightness temperatures in the L-Band at 1.4 GHz, which are converted into soil moisture through inverse modeling. This study uses reprocessed SMOS Level 2 soil moisture data from the year 2010 for a long-term validation in the Rur and Erft catchments in Northrhine-Westfalia, Germany. They are compared to time-series of soil moisture derived from Advanced Scatterometer (ASCAT) data. ASCAT is a real-aperture radar that measures surface backscattering coefficients in the C-band at 5.255 GHz with a resolution of 30 to 50 km. Through a time series-based change detection approach relative soil moisture is retrieved from the backscattering coefficients, which is then converted to absolute soil moisture with data on soil properties. The individual accuracy and suitability of both datasets for the further use in numerical weather prediction and hydrological modeling are analyzed with the help of a soil moisture reference calculated by WaSiM ETH, a grid-element-based hydrological model. The model was calibrated with soil moisture data from the wireless sensor network at two test sites in the study area. Regression between the in situ data and the model values shows good results, despite a small bias, with an overall RMSE coefficient of 0.05. Time-series of the observed and modeled data also indicate a good agreement. A first comparison of SMOS data with the soil moisture reference does not show a high correlation. Furthermore, the temporal development of the data is different for SMOS soil moisture and the reference. A strong bias can be observed for the whole period: SMOS shows constantly lower values of soil moisture than the reference data. Partition into ascending and descending nodes does not show better results. Calculation of RMSE for every SMOS footprint over the whole period displays smaller values in the northern part of the study area than in the southern part. That can be due to the mountainous terrain but also to the dense vegetation with much forest in this area. When comparing a L-band radiometer like SMOS and a C-band scatterometer like ASCAT, disparities in the time series can occur because of different vegetation penetration abilities and soil penetration depths, distinct sensitivities to surface roughness, and sensitivity to radio frequency interferences (RFI).

  15. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

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

  16. Airborne microwave remote sensing of soil moisture 

    E-print Network

    Black, Quentin Robert

    1980-01-01

    Subject: Electrical Engineering AIRBORNE MICROWAVE REMOTE SENSING OF SOIL MOISTURE A Thesis by QUENTIN ROBERT BLACK ' Approved as to style and content by: Chairman of Committee ember P~~~ Member Mm er ad of De par tmen t December 1980 ABSTRACT... Airborne Microwave Remote Sensing of Soil Moisture (August 1980) (}uentin Robert Black, B. S. , Texas AEM University Chairman of Advisory Committee: Dr. Richard W. Newton Studies of the theory of microwave emissions from moist soil and experimental...

  17. Soil Moisture Measurement System For An Improved Flood Warning

    NASA Astrophysics Data System (ADS)

    Schaedel, W.; Becker, R.

    Precipitation-runoff processes are correlated with the catchment's hydrological pre- conditions that are taken into account in some hydrological models, e.g. by pre- precipitation index. This statistically generated variable is unsuitable in case of ex- treme flood events. Thus a non-statistical estimation of the catchment's preconditions is of tremendous importance for an improvement in reliability of flood warning. This can be achieved by persistent operational observation of the catchment's soil mois- ture condition. The soil moisture acts as a state variable controlling the risk of surface runoff, which is assumed to provoke critical floods. Critical soil moisture conditions can be identified by measurements in certain areas representative for the catchment. Therefore a measurement arrangement that does not effect the structure of soils is realised with twin rod probes. Spatial resolution algorithms result in soil moisture profiles along the probe rods. In this set up a quasi three dimensional soil moisture distribution can be interpolated with point measurements of up to 47 twin rod probes per cluster, connected via multiplexer. The large number of probes per cluster is of use for detailed observation of small-scaled moisture variability. As regionalized grid cell moisture the cluster information calibrates the default, state depending soil moisture distribution of the catchment. This distribution is explained by diverse soil moisture influencing properties, which are found by Landsat satellite image. Therefore the im- age is processed with principal component analysis to extract the soil moisture distri- bution. The distribution is calibrated by the detailed measurements, acting as ground based truth. Linear multiple regression operated on the calibrated distribution identi- fies the mentioned properties. In this fashion the catchment status can be determined and combined with precipitation forecasts, thus allowing for the comprehensive risk calculation of critical floods.

  18. GPS Multipath as a Soil Moisture Sensor

    NASA Astrophysics Data System (ADS)

    Larson, K. M.; Small, E. E.; Gutmann, E.; Bilich, A. L.; Braun, J.; Zavorotny, V.

    2008-12-01

    Measurements of soil moisture are required to study the water and carbon cycles. A global network of in situ soil moisture stations would be helpful to supplement datasets from satellite sensors, but such a network does not currently exist. In contrast, the GPS community has installed thousands of GPS receivers in soil, and is likely to install many more in the next decade. Could some of these GPS sites be used to measure soil moisture? We show results from an Earthscope Plate Boundary Observatory site (P041) where GPS reflected signals are strongly correlated with in situ soil moisture sensors buried at a depth of 2.5 cm. Limitations of the technique will be discussed.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

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

    PubMed Central

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

    2009-01-01

    In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration. PMID:22399956

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

    PubMed

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

    2009-01-01

    In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration. PMID:22399956

  2. Introducing a Soil Moisture Scaling Triangle

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Lakshmi, Venkat; Fang, Bin

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Sano, Edson Eyji

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

  5. Soil moisture mapping for aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Soil Moisture Constants and Physical Properties

    E-print Network

    Standiford, Richard B.

    constants. This paper reports the results of these analyses. Methods and Procedures At each sampling site scientist of the U.S. Soil Con- servation Service. Bulk samples composited from three locations within a 21Soil Moisture Constants and Physical Properties of Selected Soils in Hawaii Teruo Yamamoto U S

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    The SMAP mission will produce high-resolution and accurate global maps of soil moisture and its freeze/thaw state using data from a non-imaging synthetic aperture radar and a radiometer, both operating at L-band.

  9. The Soil Moisture Active Passive (SMAP) Mission

    E-print Network

    Entekhabi, Dara

    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. SMAP will make global measurements of ...

  10. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1974-01-01

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

  11. Downscaling of Global Soil Moisture using Auxiliary Data

    Microsoft Academic Search

    Genong Yu; Liping Di; Wenli Yang

    2008-01-01

    Soil moisture is important to land surface modeling and climate modeling, which usually use soil moisture as a critical parameter. Derivation of soil moisture by radar remote sensing has theoretically and practically proven to be possible. However, radar-derived soil moisture is at coarse resolution, nominally about 25 kilometers, which does not satisfy the requirements of models using higher resolution grids.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  13. Soil moisture content estimation from passive temperature measurements

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  14. Overview of soil moisture measurements with neutrons

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture over Watershed Networks in the U.S.

    E-print Network

    Paris-Sud XI, Université de

    1 Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture over Watershed Networks is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must) Soil Moisture and Ocean Salinity (SMOS) [1, 2] satellite utilizes technology and algorithm approaches

  17. Latest upgrades in the METOP ASCAT Soil Moisture Product

    NASA Astrophysics Data System (ADS)

    Hahn, S.; Melzer, T.; Wagner, W.

    2012-04-01

    The METOP ASCAT Soil Moisture Product will contribute to the most consistent and complete global ECV (essential climate variable) soil moisture data record, which will be based on different active (ERS-1/2 AMI, METOP ASCAT) and passive (SMMR, SSM/I, TMI, AMSR-E, Windsat) microwave sensors. The METOP ASCAT soil moisture product is computed using the current version of the Water Retrieval Package (WARP 5.4), which is based on a semi-empiric change detection method exploiting the multi-incidence angle viewing capabilities of ASCAT. However, an enhanced version (WARP 6.0) will be developed to address weaknesses in the semi-empiric model, e.g. w.r.t. arid environments. The soil moisture product generated with the new version WARP 6.0 will then serve as input in the ECV production system. The aim of the system is to merge the different soil moisture products from the various sources, in order to facilitate long-term studies like trend analysis. This study presents first results of the latest upgrades in WARP, as well as various validations using other soil moisture products (e.g. SMOS, GLDAS, in-situ).

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

    USGS Publications Warehouse

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

    2011-01-01

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

  19. Soil Moisture Prediction Using Support Vector Machines

    NASA Astrophysics Data System (ADS)

    Kashif Gill, M.; Asefa, Tirusew; Kemblowski, Mariush W.; McKee, Mac

    2006-08-01

    Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the "curse of dimensionality." Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  2. Soil Moisture Characterization for Biogenic Emissions Modeling in Texas

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Evaluation of the Soil Moisture Active Passive Mission (SMAP) merged radar-radiometer soil moisture algorithm

    Microsoft Academic Search

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

    2010-01-01

    The Soil Moisture Active Passive (SMAP) mission is recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is under development with a target launch date in late 2014. The SMAP mission will provide high resolution (~9 km) soil moisture product at a global extent. The SMAP instrument architecture incorporates an L-band

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

    NASA Astrophysics Data System (ADS)

    Pan, Feifei; Nieswiadomy, Michael; Qian, Shuan

    2015-05-01

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

  7. Measuring soil moisture with imaging radars

    SciTech Connect

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

    1995-07-01

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

  8. Soil moisture in sessile oak forest gaps

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Soil moisture needs in earth sciences

    NASA Technical Reports Server (NTRS)

    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.

  10. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1973-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  12. Relationships among remotely sensed soil moisture, precipitation and landslide events

    Microsoft Academic Search

    Ram L. Ray; Jennifer M. Jacobs

    2007-01-01

    Landslides are triggered by earthquakes, volcanoes, floods, and heavy continuous rainfall. For most types of slope failure,\\u000a soil moisture plays a critical role because increased pore water pressure reduces the soil strength and increases stress.\\u000a However, in-situ soil moisture profiles are rarely measured. To establish the soil moisture and landslide relationship, a\\u000a qualitative comparison among soil moisture derived from AMSR-E,

  13. Improved Rainfall Runoff Estimates Using Remotely Sensed Soil Moisture

    Microsoft Academic Search

    Jennifer M. Jacobs; David A. Myers; Brent M. Whitfield

    2003-01-01

    Remotely sensed soil moisture data measured during the Southern Great Plains 1997 (SGP97) experiment in Oklahoma were used to characterize antecedent soil moisture conditions for the Soil Conservation Service (SCS) curve number method. The precipitation-adjusted curve number and the soil moisture were strongly related (r2 = 0.70). Remotely sensed soil moisture fields were used to adjust the curve numbers and

  14. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Taylor, C.

    2013-12-01

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

  16. NEUTRON SCATTERING AND SOIL MOISTURE

    Microsoft Academic Search

    C. P. Jr

    1962-01-01

    The history and the state of the art of moisture content and unit weight ; measurement in sotl by radiation techniques is reviewed and an examination made ; of the errors to be expected when using the various types of nuclear devices as ; compared to errors reported by others for tests using conventional techniques. ; No satisfactory mathematical solution

  17. The role of biological soil crusts on soil moisture

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  18. Impact of Soil Moisture Initialization on Seasonal Weather Prediction

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  19. Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks worldwide

    NASA Astrophysics Data System (ADS)

    Brocca, L.; Zucco, G.; Mittelbach, H.; Moramarco, T.; Seneviratne, S. I.

    2014-07-01

    The analysis of the spatial-temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum absolute values, even though in relative terms their temporal patterns are very similar. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250-150,000 km2). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time-invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture only. Overall, we find that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to temporal anomalies or percent of saturation values.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Subpixel variability of remotely sensed soil moisture: an inter-comparison study of SAR and ESTAR

    Microsoft Academic Search

    Rajat Bindlish; Ana P. Barros

    2002-01-01

    The representation of subpixel variability in soil moisture estimates from passive microwave data was investigated through sensitivity analysis and by comparison against the spatial structure of soil moisture fields derived from radar data. This work shows that the subpixel variability not represented in brightness temperature fields is directly associated with the spatial organization of soil hydraulic properties and the spatial

  2. Possible Impacts of Climate Change on Soil Moisture Availability in the Southeast Anatolia Development Project Region (GAP): An Analysis from an Agricultural Drought Perspective

    Microsoft Academic Search

    Ali Umran Komuscu; Ayhan Erkan; Sukriye Oz

    1998-01-01

    This paper presents probable effects of climate change on soil moisture availability in the Southeast Anatolia Development Project (GAP) region of Turkey. A series of hypothetical climate change scenarios and GCM-generated IPCC Business-as-Usual scenario estimates of temperature and precipitation changes were used to examine implications of climate change for seasonal changes in actual evapotranspiration, soil moisture deficit, and soil moisture

  3. Investigation of Soil Moisture - Vegetation Interactions in Oklahoma

    E-print Network

    Ford, Trenton W.

    2013-03-06

    , but not well understood climate factor. This study examines soil moisture-vegetation health interactions using both in situ observations and land surface model simulations. For the observational study, soil moisture is taken from 20 in situ Oklahoma Mesonet...

  4. Radar measurement of soil moisture content

    Microsoft Academic Search

    FAWWAZ T. ULABY

    1974-01-01

    The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-ft truck-mounted boom was used to measure the return at 10 frequency points across the 4-8 GHz band,

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  6. Equivalent steady soil moisture profile and the time compression approximation in water balance modeling

    Microsoft Academic Search

    Guido Daniel Salvucci; Dara Entekhabi

    1994-01-01

    The definition of preevent soil moisture profile and time compression analysis are critical components in water balance models that are based on realistic infiltration\\/exfiltration relations and include profile redistribution of vadose zone moisture. In this paper, detailed analysis of these two fundamental components of water balance modeling is presented. Numerical integration of the governing equations for liquid moisture flow in

  7. SOIL MOISTURE EXPERIMENTS IN 2002 AND 2003

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. The Soil Moisture and Ocean Salinity mission

    Microsoft Academic Search

    Y. H. Kerr; P. Waldteufel; J.-P. Wigneron; M. Berger

    2003-01-01

    Surface soil moisture is a key variable of water and energy exchanges at the land surface\\/atmosphere interface. But currently there are no means to assess it on a global and timely fashion. Similarly, our current knowledge of sea surface salinity is very reduced. One way to overcome this issue would be to use an adequate space-borne instrument. The most promising

  9. Soil Moisture Active Passive Validation Experiment 2008

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. SMAP validation of soil moisture products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. SOIL MOISTURE EXPERIMENTS 2003 (SMEX03)

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Estimating Subcanopy Soil Moisture with RADAR

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  13. On the spatial organization of soil moisture fields

    Microsoft Academic Search

    Ignacio Rodriguez-Iturbe; Gregor K. Vogel; Riccardo Rigon; Dara Entekhabi; Fabio Castelli; Andrea Rinaldo

    1995-01-01

    We examine the apparent disorder which seems to characterize the spatial structure of soil moisture by analyzing large-scale experimental data. Specifically, we address the statistical structure of soil moisture fields under different scales of observation and find unexpected results. The variance of soil moisture follows a power law decay as function of the area at which the process is observed.

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

    NASA Technical Reports Server (NTRS)

    Jackson, R. D. (principal investigator)

    1981-01-01

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

  15. National Airborne Field Experiments for Soil Moisture Remote Sensing

    Microsoft Academic Search

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

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

  16. A microwave scattering model for soil moisture movement

    Microsoft Academic Search

    Mostafa A. Karam; GenCorp Aerojet

    1998-01-01

    A microwave scattering model for soil moisture movement is developed by integrating three models: a moisture profile model, a dielectric constant model, and a soil surface electromagnetic scattering model. As an application, the model is used to assess the impact of moisture infiltration on soil scattering characteristics

  17. Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Overview of the Hydros radar soil moisture algorithm

    NASA Technical Reports Server (NTRS)

    Kim, Yunjin; van Zyl, Jakob

    2005-01-01

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

  19. Microwave soil moisture estimation in humid and semiarid watersheds

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  20. Landslide Susceptibility Mapping using Remotely Sensed Soil Moisture

    Microsoft Academic Search

    Ram L. Ray; Jennifer M. Jacobs

    2008-01-01

    Slope stability analysis using remotely sensed data is routinely conducted throughout the world. This study focuses on rainfall induced landslides and the use of AMSR-E and TRMM satellite data to develop susceptibility maps that can be used to forecast landslides. This research established the first relationships among soil moisture derived from AMSR-E, precipitation from TRMM and major landslide events, respectively,

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  2. Land Surface Emissivity as a Surrogate of Soil Moisture

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Temimi, M.; Khanbilvardi, R.

    2010-12-01

    Soil moisture and fraction of surface water is one of the most uncertain variables in hydrological models, especially in large watersheds. Direct measurement of this parameter at these large scales is not straightforward. The main objective of this work is to demonstrate the potential of using land microwave emissivity as a surrogate for soil moisture and fraction of surface water. First an instantaneous global microwave land emissivity product has been developed using AMSR-E observations. This retrieval utilizes all AMSR-E frequencies and infrared-based data for physical skin temperature. Data sets provided by International Satellite Cloud Climatology Project (ISCCP) were used. Moreover, information on water vapor and air temperature obtained from the ISCCP database (TOVS data) was used to calculate the upwelling and the downwelling atmospheric brightness temperatures as well as the atmospheric transmission. A monthly composite map was developed for each frequency. The analysis of the obtained maps has shown an acceptable agreement with the global pattern of land use/land cover. The difference between V and H polarization emissivity showed an acceptable consistency with soil moisture and fraction of water surface. However, monthly variation of this difference had reasonable agreement with monthly rain rate mostly in less vegetated areas. Moreover, the relation between different frequencies also showed a good potential for predicting the soil moisture since the slope of linear relation between emissivities in different frequencies changes with soil moisture. Fraction of surface water was developed in global scale using land surface emissivity with reasonable agreement with soil moisture except in highly vegetated area. Also, the big difference between day and night in emissivity retrievals was found, as there is a phase lag between infrared and microwave temperature. A technique was developed for resolving this inconsistency using the diurnal cycle variation of skin temperature and microwave brightness temperature.

  3. Tree Species Specific Soil Moisture Patterns and Dynamics

    NASA Astrophysics Data System (ADS)

    Heidbuechel, I.; Dreibrodt, J.; Guntner, A.; Blume, T.

    2014-12-01

    Land use has a major influence on the hydrologic processes that take place in soils. Soil compaction on pastures for example leads to infiltration patterns that differ considerably from the ones observable in forests. It is not clear, however, how different forest stands influence soil infiltration and soil moisture distributions. Factors that that vary amongst different stands and potentially affect soil moisture processes in forests are, amongst others, canopy density, throughfall patterns, the intensity and frequency of stem flow, litter type, root distributions and rooting depth. To investigate how different tree species influence the way soils partition, store and conduct incoming precipitation we selected 15 locations under different tree stands within the TERENO observatory in north-east Germany. The forest stands under investigation were mature oak, young pine, mature pine, young beech and mature beech. At each location we installed 30 FDR soil moisture sensors grouped into five depth profiles (monitoring soil moisture from 10 cm to 200 cm) and 5 additional near surface sensors. The profile locations within each forest stand covered most of the anticipated variability by ranging from minimum to maximum distance to the trees including locations under more and less dense canopy. Supplementary to the FDR sensors, throughfall measurements, tensiometers and groundwater data were available to observe dynamics of tree water availability, water fluxes within the soils and percolation towards the groundwater. To identify patterns in space and time we referred to the statistical methods of wavelet analysis and temporal stability analysis. Finally, we tried to link the results from these analyses to specific hydrologic processes at the different locations.

  4. Preliminary assessment of soil moisture over vegetation

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1986-01-01

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

  5. Effective soil moisture sampling depth of L-band radiometry: A case study M.J. Escorihuela a,

    E-print Network

    Paris-Sud XI, Université de

    Effective soil moisture sampling depth of L-band radiometry: A case study M.J. Escorihuela a, , A radiometry at L-band. The analysis is based on brightness temperature, soil moisture and temperature for the calibration and validation of remote sensing data at L-band. 1. Introduction Soil moisture plays a key role

  6. Improving Estimates of Root-zone Soil Water Content Using Soil Hydrologic Properties and Remotely Sensed Soil Moisture

    NASA Astrophysics Data System (ADS)

    Baldwin, D. C.; Miller, D. A.; Singha, K.; Davis, K. J.; Smithwick, E. A.

    2013-12-01

    Newly defined relationships between remotely sensed soil moisture and soil hydraulic parameters were used to develop fine-scale (100 m) maps of root-zone soil moisture (RZSM) content at the regional scale on a daily time-step. There are several key outcomes from our research: (1) the first multi-layer regional dataset of soil hydraulic parameters developed from gSSURGO data for hydrologic modeling efforts in the Chequemegon Ecosystem Atmospheric Study (ChEAS) region, (2) the operation and calibration of a new model for estimating soil moisture flow through the root-zone at eddy covariance towers across the U.S. using remotely sensed active and passive soil moisture products, and (3) region-wide maps of estimated root-zone soil moisture content. The project links soil geophysical analytical approaches (pedotransfer functions) to new applications in remote sensing of soil moisture that detect surface moisture (~5 cm depth). We answer two key questions in soil moisture observation and prediction: (1) How do soil hydrologic properties of U.S. soil types quantitatively relate to surface-to-subsurface water loss? And (2) Does incorporation of fine-scale soil hydrologic parameters with remotely sensed soil moisture data provide improved hindcasts of in situ RZSM content? The project meets several critical research needs in estimation of soil moisture from remote sensing. First, soil moisture is known to vary spatially with soil texture and soil hydraulic properties that do not align well with the spatial resolution of current remote sensing products of soil moisture (~ 50 km2). To address this, we leveraged new advances in gridded soil parameter information (gSSURGO) together with existing remotely sensed estimates of surface soil moisture into a newly emerging semi-empirical modeling approach called SMAR (Soil Moisture Analytical Relationship). The SMAR model was calibrated and cross-validated using existing soil moisture data from a portion of AMERIFLUX tower sites and the NRCS Soil Climate Analysis Network (SCAN). Our preliminary results show good performance of the SMAR model for predicting RZSM at the site level (root mean square error = 0.04). Second, a calibrated SMAR parameter governing the surface to subsurface rate of water flow was related to soil hydraulic properties at the AMERIFLUX tower sites, and region-wide maps of SMAR parameters were developed for the ChEAS region using gSSURGO information. Finally, region-wide maps of RZSM were developed and validated for the ChEAS region. The RZSM products can be directly incorporated with regional CO2 flux modeling, and the results inform - but are not dependent on - efforts that integrate observed soil moisture data with planned NASA missions (e.g., SMAP).

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S

    Microsoft Academic Search

    Thomas J. Jackson; Rajat Bindlish; Michael H. Cosh; Tianjie Zhao; Patrick J. Starks; David D. Bosch; Mark Seyfried; Mary Susan Moran; David C. Goodrich; Yann H. Kerr; Delphine Leroux

    2012-01-01

    Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn,

  11. Dynamics of deep soil moisture in response to vegetational restoration on the Loess Plateau of China

    NASA Astrophysics Data System (ADS)

    Jia, Yu-Hua; Shao, Ming-An

    2014-11-01

    The limitation of soil water in semiarid regions restricts the formation of a good cover of vegetation. The Loess Plateau in China, well known for its severe soil erosion, has a thick loessial soil that holds substantial volumes of water and provides the basis of a sustainable restoration of vegetation. Our limited understanding of the dynamics of deep soil moisture, however, could lead to the mismanagement of soil-water resources or could even misguide the policies of vegetational reconstruction. To evaluate the temporal response of deep soil moisture in different types of revegetation, we observed soil moisture to a depth of 340 cm in four plots, planted with Korshinsk peashrub (KOP), purple alfalfa (ALF), native plants (natural fallow, NAF), and millet (MIL), on 15 measurement events from 2010 to 2012. Our analysis provided four main conclusions. (1) The quantitative difference of potential evapotranspiration and actual precipitation resulted in natural deficits of soil moisture. The dynamics of deep soil moisture, however, were mainly dominated by the type of vegetation. Deep soils in plots of KOP and ALF became drier than the soil in plots of NAF and MIL. (2) Deep soil moisture in KOP and ALF was weakly variable. Correlations of time series of soil moisture between the upper and lower layers tended not to be significant. Dried soil layer, a special hydrological phenomenon, had formed in the plots. (3) The correlation between variances of soil moisture and the corresponding mean values were not always significantly positive due to the influence of vegetational type, observational depth, and date. (4) Fallow may be the best cover for achieving adequate hydrological sustainability of the soil. These results are expected to help improve the understanding of the response of deep soil moisture to vegetational restoration and to provide insight into the dynamics of deep soil moisture influenced by vegetation on loessial slopes.

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

    NASA Technical Reports Server (NTRS)

    Bolten, John D.; Lakshmi, Venkat

    2009-01-01

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

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

    USGS Publications Warehouse

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, Kurt C.; Coulibaly, Paulin

    2014-04-01

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

  15. Soil moisture dynamics in coastal savanna soils in the tropics under different soil management practices

    Microsoft Academic Search

    E. A. AMPOFO

    2006-01-01

    Soil moisture is important for crop cultivation and its adequacy to meet crop-water requirements is determined by the degree of soil management practised and the quantity of water applied to the soil. This study investigates soil moisture dynamics on three plots: Bare (clean, weeds removed), Weedy (kept weedy), and Mulched (cleared of weeds and fully covered with grass mulch) during

  16. COsmic-ray Soil Moisture Observing System (COSMOS): soil moisture and beyond

    NASA Astrophysics Data System (ADS)

    Zreda, Marek; Shuttleworth, William J.; Zeng, Xubin; Zweck, Chris; Franz, Trenton; Rosolem, Rafael

    2013-04-01

    COSMOS, a project funded by the US National Science Foundation, was designed to measure average soil moisture in the top 10-70 cm of soil over the horizontal footprint of approximately 700 m by measuring cosmic-ray neutrons in air above the ground surface. It is in its fourth, final, year of the feasibility phase in which 60 neutron probes have been installed in the USA to provide continental-scale soil moisture data. The cosmic-ray neutron probe responds to all sources of hydrogen present within the footprint. Therefore, in addition to soil moisture, other pools of hydrogen can be measured; these include atmospheric water vapor, organic matter in soil, water in soil minerals, biomass water (including hydrogen bound in cellulose), and snow on the ground and on the canopy. All these pools of hydrogen form the "total surface moisture" that is measured by COSMOS probes. The first four pools are measured independently (water vapor) or are implicitly included in the probe calibration (water in minerals and organic matter, biomass water). The other two can be separated from one another to produce time series of soil moisture and snow water equivalent. Work is in progress to assimilate neutron data into land-surface models, to produce soil moisture profiles, to validate satellite soil moisture products (the current SMOS mission and the future SMAP mission), to measure temporal variations in biomass, and to measure area-average unsaturated hydraulic properties of soils. Separately, mobile COSMOS probe, called COSMOS rover, is being developed. COSMOS rover can be used to map soil moisture over large areas or along long transects. Cosmic-ray sensing of moisture at the land surface has gained popularity outside of the USA. Approximately 60 probes have been purchased in addition to the 60 probes in the COSMOS project. Funds for additional 80 probes, most of them in Germany, have been secured, and large new proposals will be submitted in the USA and Australia in 2013. These probes form an embryonic global COSMOS network, and an international community of scientists interested in cosmic-ray sensing is emerging. Acknowledgement: The COSMOS project is supported by the US National Science Foundation.

  17. Methods of measuring soil moisture in the field

    USGS Publications Warehouse

    Johnson, A.I.

    1962-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

    2005-01-01

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

  19. Urban soil moisture affecting local air temperature

    NASA Astrophysics Data System (ADS)

    Wiesner, Sarah; Ament, Felix; Eschenbach, Annette

    2015-04-01

    The climate in cities differs from that in the surrounding area due to modified surfaces. Parameters like surface sealing ratio, vegetation and building material are known to be relevant for the intensity of the microclimatic modification. But what about the influence of soil moisture content and availability at the soil surface? Soil acts as a storage and transmitter for water. In doing so, it may have a differently pronounced impact on local climate through distinct evapotranspiration. The actual evapotranspiration rates are determined by water availability at the surface - dependant from soil physical properties and water refill from above or below - and the presence of evapotranspirators, i.e. plants that transpire water from deeper soil areas. The issue of soil hydrological characteristics and water replenishment limiting the local cooling effect of soils is the topic of this contribution. A long-term record (2010-2014) of ongoing measurements in the city of Hamburg, Germany, is evaluated. The data is provided by atmospheric and pedologic measurement sites of the HUSCO network (Hamburg Urban Soil Climate Observatory). They are located within six urban districts: the city core, four suburban districts, featuring different mean groundwater table depths (> 5 m below surface / < 2.5 m below surface), and one industrial area. The temporal evolutions of water content and soil water tension of the suburban soil profiles are found to be very diverse, related to soil substrate, organic matter content and groundwater table depth. Most distinct variations are observed within the upper horizons of suburban soil. Soil hydrological processes show characteristic patterns at each measurement site, including topsoil water content (?) variability. Yet, differences between distinct urban land use types are visible only according to differences in the prevailing soil texture. Impacts of different vegetation types on the soil water dynamics can be identified, while the influence of urban land use is not found to be definite. Air temperature (Ta) anomalies of the suburban sites from the inner city site are analysed for several periods and seasons. During daytime a significant annual mean deviation is observed above unsealed, vegetated surfaces from a sealed site during selected relevant days. Remarkably, about a fifth of the variance of the diurnal Ta span, i.e. increase of Ta during the day, is found to be explained by normalized ? for selected meteorological situations. In this contribution this observed relation between topsoil moisture and air temperature increase during daytime at suburban sites will be presented after describing the local conditions and soil hydrological heterogeneities at the observed urban sites.

  20. Impact of moisture flux convergence and soil moisture on precipitation: a case study for southern U.S. with implications for the globe

    NASA Astrophysics Data System (ADS)

    Wei, J.; Su, H.; Yang, Z.

    2013-12-01

    Interactions between soil moisture, evapotranspiration (ET), atmospheric moisture fluxes and precipitation are complex. It is difficult to attribute the variations of one variable to another. In this study, we investigate the influence of atmospheric moisture fluxes and land surface soil moisture on local precipitation, with a focus on the southern U.S., a region with a strong humidity gradient and intense moisture fluxes. Experiments with the Weather Research and Forecasting (WRF) model show that the variation of moisture flux convergence (MFC) is more important than that of soil moisture for precipitation variation over the southern U.S. Further analyses decompose the precipitation change into several contributing factors and show that MFC exerts a stronger impact on precipitation in wetter regions, where the direct moisture inflow is large. Over transitional zones, the effect of soil moisture variations becomes important, mainly by changing precipitation efficiency. The direct moisture contribution from surface ET is relatively small over all areas. Analysis of global reanalysis data sets shows that similar conclusions apply to other land regions. Although MFC is more important than soil moisture for precipitation over most regions, the impact of soil moisture could be large over certain transitional regions. At the submonthly time scale we analyzed, African Sahel is the only region where soil moisture has greater impact than MFC on precipitation.

  1. Derivation of Soil Moisture Retention Characteristics from Saturated Hydraulic Conductivity

    E-print Network

    Kumar, C.P.

    : Knowledge of the physics of soil water movement is crucial to the solution of many problems in watershed1 Derivation of Soil Moisture Retention Characteristics from Saturated Hydraulic Conductivity C. P systems require knowledge of the relationships between soil moisture content (), soil water pressure (h

  2. A method for estimating soil moisture availability

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1985-01-01

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

  3. Effective soil moisture sampling depth of L-band radiometry

    NASA Astrophysics Data System (ADS)

    Escorihuela, M. J.; Kerr, Y. H.; Chanzy, A.; Wigneron, J. P.

    2009-04-01

    In the near future two new satellite missions, the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) will be providing for the first time global mapping of surface soil moisture based on radiometric measurements at L-band. For operational applications involving microwave radiometry, soil moisture is generally estimated by inverting a simple model of soil microwave emission. Several field and airborne campaigns have been carried out in order to test, validate and better understand radiative transfer models at L-band. Some of them have shown that in order to accurately model bare soil emission, it was necessary to adjust one parameter as a function of soil moisture. In this way, an exponential and linear dependency of roughness with soil moisture was found by Wigneron et al. 2001 and Escorihuela et al. 2007 respectively. While Schneeberger et al. 2004 fitted a coherent emission model with a transition zone whose thickness depended also in soil moisture. A sensitivity of soil roughness to soil moisture was also find for airborne L-band microwave data during the COSMOS campaign Saleh et al. 2008. This kind of parameterizations pose the problem that are site dependent and thus their application at the satellite scale is not straight forward. Furthermore, they seem to indicate that the actual effective soil moisture sampling depth is somewhat different that the one provided by the field sensors. The aim of this study is thus to analyze the influence of the soil moisture sampling depth in the parameterizations of soil emission in microwave radiometry at L-band. Brightness temperature, soil moisture and temperature profiles were measured over a bare soil. A more detailed profile of surface soil moisture was obtained with a soil heat and water flows mechanistic model. It was found that (1) the effective soil moisture sampling depth is shallower than provided by widely used field moisture sensors, (2) the effective soil moisture sampling depth depended on soil moisture. This conclusions are crucial for the calibration and validation of remote sensing data at L-band. A parameterization for soil moisture sampling depth at L-band is proposed.

  4. Coupling an Inverse Gaussian Model with Artificial Neural Networks to Predict Soil Moisture from Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Zeng, W.; Xu, C.; Huang, J.; Wu, J.; Tuller, M.

    2014-12-01

    Soil moisture is one of the most crucial properties for monitoring and modeling landscape processes. For this study hyperspectral imagery and soil physical properties were collected in both in situ and controlled laboratory experiments to establish predictive capabilities for soil moisture in saline soils. An inverse Gaussian model was first applied to fit the spectral reflectance curves and to derive three curve-specific parameters, namely the inverted amplitude, the distance from the center to the inflection point, and the area under the Gaussian curve. Then both linear regression analysis and artificial neural networks (ANN) were applied to develop soil moisture prediction models. Results indicate that soil salinity greatly affects surface reflectance and thereby prediction of soil moisture. The linear regression model failed to predict soil moisture for all in situ field samples as well as for controlled laboratory samples with moderate salinity levels. It was only able to predict moisture reasonably well when salinity levels were extremely high. Application of ANNs significantly improved prediction accuracy as evidenced by a substantial increase of the correlation coefficient and Nash - Sutcliffe efficiency. Based on obtained results, the coupling of an inverse Gaussian model with artificial neural networks provides practical and accurate means for prediction of soil moisture of saline soils and shows great potential for large-scale soil moisture mapping based on hyperspectral imagery.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

    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 or vegetation cover types are statistically meaningful. The proposed model is applied to the radar images from the Passive Active L-band System (PALS) collected during (SMAPVEX12). SMAPVEX12 lasted for 47 days, during which soil moisture varied significantly. The proposed model was applied to all of the collected images (17 images) during this time span. Optimized sampling site characteristics will be analyzed with surface characteristics and the trade off between the number of samples and estimated sampling error examined.

  7. Sy estimation from paralel soil moisture and water table measurement

    NASA Astrophysics Data System (ADS)

    Gribovszki, Zoltán; Kalicz, Péter

    2015-04-01

    In growing season evapotranspiration induces diurnal signal of soil moisture, and also of water table in shallow water table environments. Diurnal signal of water table was widespreadly used for estimation of groundwater uptake by plants. The limitation of all groundwater signal based methods lies in the difficulty of specific yield (Sy) estimation. This is a soil water storage parameter that strongly depends on both, the unsaturated soil moisture fluxes (recharge and evapotranspiration) and water table elevation. Based on parallel soil moisture profile and water table measurements in a hydrophyte forest of Hidegvíz Valley experimental catchment at the eastern foothills of the Alps subdaily Sy values were calculated. Estimated Sy values are significantly changed along the day. If you want to get accurate Sy value for ET estimation a representative period has to be selected within the day. For analysis Sy values were calculated as a late night average and as a daily average as well. Estimated Sy values were compared to the results of some traditional Sy estimation techniques (particle distribution curve based, moisture characteristic curve based, etc.). Penman-Monteith reference evapotranspiration was used for evaluation of the ET values calculated from different Sy estimations. This research has been supported by the AGRARKLIMA.2 VKSZ_12-1-2013-0034 project.

  8. Uncertainty in SMAP Soil Moisture Measurements Caused by Dew

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Soil moisture detection using KOMPSAT-5 SAR data

    Microsoft Academic Search

    Yisok Oh; Soon-Gu Kwon; Ji-Hwan Hwang

    2010-01-01

    The applicability of the KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR on soil moisture detection is addressed in this paper. At first, the penetration into and reflection from bare soil surfaces at X-band are compared with those at L-band for homogeneous and inhomogeneous moisture profiles. The sensitivities of the X-band radar backscatter on soil moisture are examined for rough bare soil surfaces.

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

    NASA Technical Reports Server (NTRS)

    Waite, W. P. (principal investigator)

    1982-01-01

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

  11. Passive microwave soil moisture downscaling using NLDAS and MODIS data

    NASA Astrophysics Data System (ADS)

    Fang, B.; Lakshmi, V.

    2011-12-01

    The soil moisture retrieved from Advanced Microwave Scanning Radiometer (AMSR-E) is an important variable that has been applied in agriculture, hydrology, climate and weather. However, low spatial resolution (1/4 degree) of AMSR-E derived soil moisture cannot fulfill the requirements of high spatial resolution. In this paper, we studied the relationship between three factors: daily surface temperature range, Normalized Difference Vegetation Index (NDVI) and daily averaged soil moisture, using the 30-year period North America Land Data Assimilation System (NLDAS) Land Surface Temperature (LST) and soil moisture products (1/8 degree); MODIS (Moderate-Resolution Imaging Spectroradiometer) and AVHRR (Advanced Very High Resolution Radiometer) NDVI products (1/20 degree) in Oklahoma. We derived relationships between temperature difference and soil moisture under different vegetation conditions then derived the downscaled soil moisture by comparing the difference between AMSR-E and MODIS retrieved soil moisture. This soil moisture downscaling method not only provides disaggregated soil moisture data for passive microwave sensors, but also for active microwave sensors, such as Soil Moisture Active Passive Mission (SMAP).

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

    NASA Astrophysics Data System (ADS)

    Fang, B.; Lakshmi, V.

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Swenson, Sean; Famiglietti, James; Basara, Jeffrey; Wahr, John

    2008-01-01

    In this study we estimate a time series of regional groundwater anomalies by combining terrestrial water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) satellite mission with in situ soil moisture observations from the Oklahoma Mesonet. Using supplementary data from the Department of Energy's Atmospheric Radiation Measurement (DOE ARM) network, we develop an empirical scaling factor with which to relate the soil moisture variability in the top 75 cm sampled by the Mesonet sites to the total variability in the upper 4 m of the unsaturated zone. By subtracting this estimate of the full unsaturated zone soil moisture anomalies, we arrive at a time series of groundwater anomalies, spatially averaged over a region approximately 280,000 km2 in area. Results are compared to observed well level data from a larger surrounding region, and show consistent phase and relative inter-annual variability.

  14. Concerning the relationship between evapotranspiration and soil moisture

    NASA Technical Reports Server (NTRS)

    Wetzel, Peter J.; Chang, Jy-Tai

    1987-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (principal investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. The Presence of Plants Alters the Effect of Soil Moisture on Soil C Decomposition in Two Different Soil Types

    Microsoft Academic Search

    F. A. Dijkstra; W. Cheng

    2005-01-01

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

  19. Quantifying mesoscale soil moisture with the cosmic-ray rover

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-06-01

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

  20. Non-contact prediction of soil moisture profiles using radio wave reflection

    NASA Astrophysics Data System (ADS)

    Needham, Duane Lee

    Scope and method of study. This study investigated the potential of non-contact measurement of volumetric soil moisture profiles by detecting reflected VHF and UHF radio waves. The investigation included a variability analysis of the dielectric properties of soil, tests to relate volumetric moisture content to dielectric properties, a simulation of radio wave reflection from various profiles, and field trials in which antennas transmitted and received radio waves for detection of the moisture gradient in the soil directly below the instrument. In addition to the measurements, an algorithm was devised to resolve layers of moisture from radio wave reflections of multiple frequencies. Potential applications for such an instrument may include irrigation scheduling, detection of plant stress, and hydrological research. Findings and conclusions. The model that simulated reflection coefficients in the frequency range of 80 MHz to 1 GHz was tested using hypothetical and existent moisture profiles. Results of simulated profiles indicated that reflection coefficients could be used to distinguish between volumetric surface moisture and could detect subsurface moisture to a depth of 45.7 cm. Reflection measurements made in the field trials indicated that linear correlation could be made with volumetric moisture in the top 15.2 cm. The profile restoration algorithm closely predicted simulated surface moisture but had a high failure rate predicting subsurface moisture. Results of the study indicated that reflection coefficients could be used to detect soil moisture at depth, but the restoration algorithm did not effectively resolve moisture layers.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. HIGH RESOLUTION AIRBORNE SOIL MOISTURE MAPPING Jeffrey Walker1

    E-print Network

    Walker, Jeff

    farms [1]. This is the first airborne remote sensing study to provide such high resolution soil moisture microwave remote sensing provides a viable tool for high resolution soil moisture mapping across large areas. #12;Figure 2: Time sequence of remotely sensed (top 2 rows) and ground measured (bottom 2 rows) soil

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Mesoscale Monitoring of Soil Moisture Across a Statewide Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Sensitivity to soil moisture by active and passive microwave sensors

    Microsoft Academic Search

    Yang Du; Fawwaz T. Ulaby; M. Craig Dobson

    1999-01-01

    The backscatter measured by a radar and the emission measured by a radiometer are both very sensitive to the moisture content m, of bare-soil surfaces. Vegetation cover complicates the scattering and emission processes, presumably masking the soil surface and reducing soil-moisture sensitivity. Although researchers generally agree with the preceding statement, numerous claims and counterclaims have been voiced, espousing the superiority

  6. [Research on the method for rapid detection of soil moisture content using spectral data].

    PubMed

    Song, Tao; Bao, Yi-Dan; He, Yong

    2009-03-01

    Spectroscopy technique is one of the qualitative and quantitative analytical techniques developed quickly in recent years. The spectral analysis is a fast and non-destructive method and has been used in many fields such as oil industry, food industry and so on. In the present paper, the spectral band sensitive to soil moisture content was found from the visible/near infrared spectra and a monadic linear regression model based on the data of sensitive spectral band was applied to develop a method for rapid detection of soil moisture content. The spectral data of 52 soil samples were collected by using FieldSpec HandHeld spectroradiometer made by ASD (Analytical Spectral Device) company in the US, and the data of soil moisture content were obtained by experiment. The spectral band sensitive to soil moisture content was achieved by correlation coefficient method. Then, the data of sensitive spectral band were used to build monadic linear regression model of soil moisture content. Finally, the model was employed for the prediction of soil moisture content. Correlation coefficient (r) of prediction and root mean square error of prediction (RMSEP) were used as the evaluation standards. The results indicated that the r and RMSEP for the prediction of soil moisture content were 0.966 5 and 0.012 1 respectively. Thus, it is concluded that the method used in this paper is an available method for the rapid detection of soil moisture content based on the visible/near-infrared spectra. PMID:19455797

  7. Quantifying mesoscale soil moisture with the cosmic-ray rover

    NASA Astrophysics Data System (ADS)

    Chrisman, Bobby B.

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Use of Ultrasonic Technology for Soil Moisture Measurement

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  10. Global Evaluation of Remotely-Sensed Soil Moisture Retrievals

    Microsoft Academic Search

    Wade T. Crow; USDA ARS

    2008-01-01

    To date, limitations in the availability of ground-based soil moisture observations have hampered the large-scale evaluation of remotely-sensed surface soil moisture retrievals. Recently developed evaluation techniques offer the potential to greatly expand the geographic domain over which such retrievals can be evaluated by effectively substituting ground-based rain gauge observations for, less commonly available, ground-based soil moisture observations. Here, we apply

  11. Soil moisture and predicted spells of extreme temperatures in Britain

    Microsoft Academic Search

    B. B. Brabson; D. H. Lister; P. D. Jones; J. P. Palutikof

    2005-01-01

    This paper reports on an analysis of the relationship of soil moisture to extreme temperatures in Britain, taken from the Hadley Centre general circulation model HadCM3 (1860–2099) and validated using the central England temperature extremes from the overlapping period 1878–2000. By 2100, HadCM3 predicts higher average temperatures and a greater variability, asymmetry, and persistence of warm extremes. A generalized extreme

  12. Building the North American Soil Moisture (NASM) Database

    NASA Astrophysics Data System (ADS)

    Quiring, S. M.

    2011-12-01

    Soil moisture is an important variable in the climate system. To date, relatively little work has been done to assemble and homogenize in situ measurements of soil moisture and to utilize these measurements for investigating land-atmosphere interactions. This research addresses the critical need to develop high quality soil moisture datasets from disparate sources and to use these data to improve our understanding of climatic variability on seasonal to interannual timescales. This project will assemble, quality control and harmonize the existing in situ soil moisture observations in the United States (and eventually beyond) and develop a soil moisture database for investigating the nature of land-atmosphere interactions, validating the accuracy of soil moisture simulations in global land surface models, and describing how soil moisture influences climate on seasonal to interannual timescales. These data will be published on a dedicated website and made available to the scientific community to support research efforts such as Decadal and Regional Climate Prediction Using Earth System Models (EaSM), the Soil Moisture and Ocean Salinity (SMOS) satellite recently launched by the European Space Agency and NASA's Soil Moisture Active and Passive (SMAP) mission (planned launch in 2015).

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. A global soil moisture in-situ network for satellite remote sensing of soil moisture

    Microsoft Academic Search

    P. J. van Oevelen

    2009-01-01

    Soil moisture information is critical for understanding the global water and energy cycles, for predicting precipitation, and for advising local water resource managers. Based on theory and experiments to date there is a general agreement that both short and long term improvements in our understanding of the water cycle and our ability to model it should be possible with an

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    Microsoft Academic Search

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

    2011-01-01

    In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation

  18. Large scale measurements of soil moisture for validation of remotely sensed data: Georgia soil moisture experiment of 2003

    Microsoft Academic Search

    D. D. Bosch; V. Lakshmi; T. J. Jackson; M. Choi; J. M. Jacobs

    2006-01-01

    A series of soil moisture experiments were conducted in 2003 (SMEX03) to develop enhanced datasets necessary to improve spatiotemporal characterization of soil moisture and to enhance satellite-based retrievals. One component of this research was conducted in South Central Georgia of the US, from June 17th to July 21st (SMEX03 GA). This study analyzes measurements of soil moisture and temperature collected

  19. A nonlinear coupled soil moisture-vegetation model

    NASA Astrophysics Data System (ADS)

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

    2005-06-01

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

  20. Passive microwaves for soil moisture monitoring

    NASA Astrophysics Data System (ADS)

    Kerr, Yann; Leroux, Delphine; Juglea, Silvia; Gruhier, Claire; Mialon, Arnaud; Cabot, François

    2010-05-01

    Since SMMR launched in 1978) to SMOS (launched in 2009) several missions have attempted describing the soil moisture, an important component of the water cycle. This could be a unique data set to see climatic trends, if coupled with other means as all the sensors (namely SMMR, SSM/I, ERS SCAT, Envisat ASCAT, AMSR, and now SMOS) have different times of over pass, different frequencies and possibluy even different measurement approaches. The rationale here is to inter-calibrate all the sensors available and try to operate a seamless transition correcting all the artifacts. The paper presents our two prong approach. On one hand we intercalibrate using reference targets the SMMR - SSM/I - AMSR series, deriving an empirical adjustment law for time of over pass and slight frequency differences, while, on the other hand we inter-compare over well monitored sites the behaviour of all available sensors and possibly algorithms. Finally, in the framework of the preparation of the SMOS mission we analyse over a reference site different ways to spatialise point information of a smos like pixel. During the oral presentation we will give the results gained through this approach and the problems encountered as well as potential ways to solve them. The results are intercompared with other similar approaches and long term soil moisture evolution shown on different areas.

  1. A strategy for downscaling SMOS-based soil moisture

    NASA Astrophysics Data System (ADS)

    Pan, M.; Sahoo, A. K.; Wood, E. F.

    2010-12-01

    The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission was launched in November 2009, and has been providing 1.4GHz (L-band) observations. A number of ongoing SMOS-related research efforts have been focusing on retrieving top surface soil moisture from the measurements and validation of such measurements and retrievals. For soil moisture detection, the SMOS sensor can only achieve a relatively low spatial resolution of about 50km. But the variability of soil moisture field is still quite high below 50km scale due to land surface heterogeneities like elevation, vegetation cover, soil texture, etc. For this reason, a lot of hydrologic applications, for example, regional land surface modeling and data assimilation studies, are performed at an increasingly finer resolution (down to 1km) and they would expect finer soil moisture fields. So in the long run, the relatively coarse soil moisture retrievals will limit their value in many applications, and spatially downscaled products are very much needed. We propose and test a strategy to downscale the SMOS-based soil moisture products to ~1km or finer. The basic idea is to relate soil moisture to other physical parameters available at higher resolution, for example, elevation, topography, vegetation cover, soil texture, land surface temperature and so on. At places with strong topography, the fine scale soil moisture is primarily controlled by gravity-driven horizontal movement of surface water. In such areas, we can relate soil moisture to topographic features through catchment hydrologic models like the TOPMODEL. In flat areas, soil texture and vegetation properties may pose a greater impact than topography. In this case, we will explore the use of high resolution vegetation information or land surface temperature for downscaling.

  2. Potential of Envisat Asar Observation For Surface Soil Moisture Retrieval

    NASA Astrophysics Data System (ADS)

    Caschili, Alessandro; Mancini, Marco; Troch, Peter A.; Piconi, Claudio

    In March 2002 a new Earth observation satellite will be lunched by ESA. On board is an advanced synthetic aperture radar instrument, called ASAR. It is a C band (5.3 GHz) multipolarized sensor with different incidence angle capabilities and different spatial resolutions. This offers new possibilities for Earth observations and in particular for soil moisture mapping. This paper discusses the potential of ENVISAT ASAR observation for the retrieval of surface soil moisture for bare soil. The data set used in this study was obtained at the European Microwave Signature Laboratory (EMSL), Ispra, Italy, during a dedicated soil moisture experiment (Mancini et al., 1999). Using these data the accuracy of soil moisture retrieval based on ASAR configuration and a surface scattering model is investigated. In Particular the possibilities of using the soil moisture information for assimilation in distributed hydrological models is discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  4. Joint microwave and infrared studies for soil moisture determination

    NASA Technical Reports Server (NTRS)

    Njoku, E. G.; Schieldge, J. P.; Kahle, A. B. (principal investigators)

    1980-01-01

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

  5. Sensitivity of microwave remotely-sensed soil moisture to soil properties

    Microsoft Academic Search

    A. R. Martin; A. Manu; C. A. Laymon; F. Archer

    1999-01-01

    Surface soil moisture is important in a number of disciplines including agricultural scheduling, water resource management, and weather forecasting. While conventional methods of surface soil moisture determination are labor intensive and of limited spatial scale, ground- and aircraft-based microwave remote sensing systems provide repetitive measurements over large areas. However, it is unclear how the remotely-sensed soil moisture reflects the variations

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Satellite remote sensing of soil moisture in Illinois, United States

    Microsoft Academic Search

    Konstantin Y. Vinnikov; Alan Robock; Shuang Qiu; Jared K. Entin; Manfred Owe; Bhaskar J. Choudhury; Steven E. Hollinger; Eni G. Njoku

    1999-01-01

    To examine the utility of using satellite passive microwave observations to measure soil moisture over large regions, we conducted a pilot study using the scanning multichannel microwave radiometer (SMMR) on Nimbus-7, which operated from 1978 to 1987, and actual in situ soil moisture observations from the state of Illinois, United States, which began in 1981. We examined SMMR midnight microwave

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. Mutual interaction of soil moisture state and atmospheric processes

    Microsoft Academic Search

    Dara Entekhabi; Ignacio Rodriguez-Iturbe; Fabio Castelli

    1996-01-01

    The purpose of this paper is to outline the pathways through which soil moisture and meteorological phenomena mutually influence one another at local, regional and global scales. This constitutes two-way land-atmosphere interaction, as meteorological phenomena both act as the forcing and react to the forcing by the soil moisture state. Land surface modification of the atmospheric environment and the atmospheric

  11. The Soil Moisture and Ocean Salinity Mission - An Overview

    Microsoft Academic Search

    Susanne Mecklenburg; Yann Kerr; Achim Hahne

    2008-01-01

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

  12. Estimating soil moisture based on image processing technologies

    Microsoft Academic Search

    Lihua Zheng; Minzan Li; Jianying Sun; Xijie Zhang; Peng Zhao

    2005-01-01

    Soil moisture is a critical factor to crop growth. Due to the facts of drought and less rain in northern China, it is necessary to introduce water controlled irrigating. Therefore, estimating soil moisture distribution rapidly and accurately is very important for decision making of water saving irrigating. This study took a farmland in Beijing as the experiment field. The aerial

  13. Field observations of soil moisture variability across scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study, over 36,000 ground-based soil moisture measurements collected during the SGP97, SGP99, SMEX02, and SMEX03 field campaigns were analyzed to characterize the behavior of soil moisture variability across scales. The field campaigns were conducted in Oklahoma and Iowa in the central USA. ...

  14. SMOS Soil Moisture Validation with Dense and Sparse Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. WindSat Soil Moisture Algorithm and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Statistical characterization of remotely sensed soil moisture images

    Microsoft Academic Search

    Zhenglin Hu; Shafiqul Islam; Yizong Cheng

    1997-01-01

    Using ESTAR (Electronically Scanned Thinned Array Radiometer) passive microwave remotely sensed soil moisture data from the Washita 92 experiment, we examine the appropriateness of several probability density functions as a candidate for soil moisture distribution. Although the normal distribution is found to approximate the data well, it is shown that such a distribution cannot capture the inherent spatial structure of

  18. Airborne GPS bistatic radar soil moisture measurements during SMEX02

    Microsoft Academic Search

    D. Masters; S. Katzberg; P. Axelrad

    2003-01-01

    To further investigate the potential for remotely sensing soil moisture using the L-band GPS bistatic radar concept, a GPS bistatic radar participated for the first time in airborne measurements during the Soil Moisture Experiment 2002 (SMEX02) in Ames, Iowa. A 12 channel GPS navigation receiver was modified to perform bistatic radar measurements and mounted on the JPL PALS instrument. The

  19. L-Band Radar Sensing of Soil Moisture

    Microsoft Academic Search

    Alfred T. C. Chang; Susan G. Atwater; Vincent V. Salomonson; John E. Estes; David S. Simonett; M. Leonard Bryan

    1980-01-01

    The objectives of this experiment were to assess the performance of an L-band, 25-cm wavelength imaging synthetic aperture radar (SAR) for soil moisture determination, and to study the temporal variability of radar returns from a number of agricultural fields. A series of three overflights was accomplished during March 1977 over an agricultural test site in Kern County, CA. Soil moisture

  20. Radar estimates of soil moisture over the Konza Prairie

    Microsoft Academic Search

    S. Gogineni; J. Ampe; A. Budihardjo

    1991-01-01

    Radar backscatter measurements were made as a part of the First International satellite land surface climatology project Field Experiment (FIFE) to estimate soil moisture for use by other investigators. The helicopter-mounted radar was flown along selected transects that coincided with soil moisture measurements. The radar operated at microwave frequencies of 5-3 and 9 6 GHz and at selected incidence angles

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

    NASA Astrophysics Data System (ADS)

    Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

    2014-06-01

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

  2. Dependence of Soil Respiration on Soil Temperature and Soil Moisture in Successional Forests in Southern China

    Microsoft Academic Search

    Xu-Li Tang; Guo-Yi Zhou; Shu-Guang Liu; De-Qiang Zhang; Shi-Zhong Liu; Jiong Li; Cun-Yu Zhou

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in for- ests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three succes- sional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. SMOS Soil moisture Cal val activities

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  5. Quantifying mesoscale soil moisture with the cosmic-ray rover

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-12-01

    Soil moisture governs the surface fluxes of mass and energy and is a major influence on floods and drought. Existing techniques measure soil moisture either at a point or over a large area many kilometers across. To bridge these two scales we used the cosmic-ray rover, an instrument similar to the recently developed COSMOS probe, but bigger and mobile. This paper explores the challenges and opportunities for mapping soil moisture over large areas using the cosmic-ray rover. In 2012, soil moisture was mapped 22 times in a 25 km × 40 km survey area of the Tucson Basin at an average of 1.7 km2 resolution, i.e., a survey area extent comparable to that of a pixel for the Soil Moisture and Ocean Salinity (SMOS) satellite mission. The soil moisture distribution is dominated by climatic variations, notably by the North American monsoon, that results in a systematic increase in the standard deviation, observed up to 0.022 m3 m-3, as a function of the mean, between 0.06 m3 m-3 and 0.14 m3 m-3. Two techniques are explored to use the cosmic-ray rover data for hydrologic applications: (1) interpolation of the 22 surveys into a daily soil moisture product by defining an approach to utilize and quantify the observed temporal stability producing an average correlation coefficient of 0.82 for the soil moisture distributions that were surveyed, and (2) estimation of soil moisture profiles by combining surface moisture from satellite microwave sensors (SMOS) with deeper measurements from the cosmic-ray rover. The interpolated soil moisture and soil moisture profiles allow for basin-wide mass balance calculation of evapotranspiration, which amounted to 241 mm in 2012. Generating soil moisture maps with a cosmic-ray rover at this intermediate scale may help in the calibration and validation of satellite soil moisture data products and may also aid in various large-scale hydrologic studies.

  6. USING SOIL MOISTURE TO DETERMINE WHEN TO SUBSOIL

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission

    Microsoft Academic Search

    Yann H. Kerr; Philippe Waldteufel; Jean-Pierre Wigneron; Jean-Michel Martinuzzi; Michael Berger

    2001-01-01

    Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility

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

    USGS Publications Warehouse

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

    1996-01-01

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

  10. Soil moisture estimation in a semiarid watershed using RADARSAT-1 satellite imagery and genetic programming

    NASA Astrophysics Data System (ADS)

    Makkeasorn, Ammarin; Chang, Ni-Bin; Beaman, Mark; Wyatt, Chris; Slater, Charles

    2006-09-01

    Soil moisture is a critical element in the hydrological cycle especially in a semiarid or arid region. Point measurement to comprehend the soil moisture distribution contiguously in a vast watershed is difficult because the soil moisture patterns might greatly vary temporally and spatially. Space-borne radar imaging satellites have been popular because they have the capability to exhibit all weather observations. Yet the estimation methods of soil moisture based on the active or passive satellite imageries remain uncertain. This study aims at presenting a systematic soil moisture estimation method for the Choke Canyon Reservoir Watershed (CCRW), a semiarid watershed with an area of over 14,200 km2 in south Texas. With the aid of five corner reflectors, the RADARSAT-1 Synthetic Aperture Radar (SAR) imageries of the study area acquired in April and September 2004 were processed by both radiometric and geometric calibrations at first. New soil moisture estimation models derived by genetic programming (GP) technique were then developed and applied to support the soil moisture distribution analysis. The GP-based nonlinear function derived in the evolutionary process uniquely links a series of crucial topographic and geographic features. Included in this process are slope, aspect, vegetation cover, and soil permeability to compliment the well-calibrated SAR data. Research indicates that the novel application of GP proved useful for generating a highly nonlinear structure in regression regime, which exhibits very strong correlations statistically between the model estimates and the ground truth measurements (volumetric water content) on the basis of the unseen data sets. In an effort to produce the soil moisture distributions over seasons, it eventually leads to characterizing local- to regional-scale soil moisture variability and performing the possible estimation of water storages of the terrestrial hydrosphere.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  15. Sensitivity to soil moisture by active and passive microwave sensors

    Microsoft Academic Search

    Yang Du; Fawwaz T. Ulaby; M. Craig Dobson

    2000-01-01

    The backscatter measured by radar and the emission measured by a radiometer are both very sensitive to the moisture content mυ of bare-soil surfaces. Vegetation cover complicates the scattering and emission processes, and it has been presumed that the addition of vegetation masks the soil surface, thereby reducing the radiometric and radar soil-moisture sensitivities. Even though researchers working in the

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

    USGS Publications Warehouse

    Georgakakos, Konstantine P.; Smith, Diane E.

    2000-01-01

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

  17. Geophysical mapping of variations in soil moisture

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (principal investigator)

    1977-01-01

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

  19. A Time Series Approach for Soil Moisture Estimation

    NASA Technical Reports Server (NTRS)

    Kim, Yunjin; vanZyl, Jakob

    2006-01-01

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

  20. Response of grassland ecosystems to prolonged soil moisture deficit

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  1. The Effects of Wildfire on Soil Moisture Dynamics

    NASA Astrophysics Data System (ADS)

    Kanarek, M.; Cardenas, M.

    2013-12-01

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

  2. High-resolution soil moisture mapping in Afghanistan

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  4. Is soil moisture initialization important for seasonal to decadal predictions?

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2014-05-01

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

  5. The moisture retention characteristic of four soils from Niger 

    E-print Network

    Landeck, Jonathon Keith

    1984-01-01

    (Ustoxic Quartzipsamment), and a footslope phase of Labucheri sand (Psammentic Paleustalf). Laboratory measurement revealed that total porosity ranges from 32. 5X (Dayobu) to 43. 4X (Labucheri). Volumetric moisture at 0. 1 bar tension ranged from 22. 9... of tension for all soils. Following three days of drainage and profile dessication, soil moisture is retained at about 1. 0 bar of tension. To seven days of profile drying, &2-3X volumetric moisture is lost from the sub-horizons of the investigated soils...

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

    NASA Astrophysics Data System (ADS)

    Zribi, Mehrez; Baghdadi, Nicolas

    2015-04-01

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

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

    NASA Technical Reports Server (NTRS)

    Entekhabi, Dara; Nijoku, Eni G.; ONeill, Peggy E.; Kellogg, Kent H.; Crow, Wade T.; Edelstein, Wendy N.; Entin, Jared K.; Goodman, Shawn D.; Jackson, Thomas J.; Johnson, Joel; Kimball, John; Piepmeier, Jeffrey R.; Koster, Randal D.; McDonald, Kyle C.; Moghaddam, Mahta; Moran, Susan; Reichle, Rolf; Shi, J. C.; Spencer, Michael W.; Thurman, Samuel W.; Tsang, Leung; VanZyl, Jakob

    2009-01-01

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

  8. Assessment of Potential AMSR-E Soil Moisture Disaggregation Using Scatterometer Observations

    NASA Astrophysics Data System (ADS)

    Lakshmi, V.; Mladenova, I. E.; Jackson, T.; Long, D.

    2007-12-01

    Advanced Microwave Scanning Radiometer (AMSR-E) on the NASA's Aqua platform has been providing land surface variables such as soil moisture in near real-time since 2002. A fundamental ongoing issue with the satellite estimates, as with any satellite passive microwave sensor, is their coarse spatial scale and how to downscale them to spatial resolutions compatible with a wider range of applications. Disaggregation techniques based on a synergism between passive and active microwave observations have shown promising results. However the available radar systems have limited temporal and spatial coverage in the mid-latitudes where soil moisture is important. Most of the disaggregation methodologies are based on temporal change detection in soil moisture. Another alternative is the QuikSCAT scatterometer, which offers daily observations with a 2.225km ground pixel size for the enhanced backscattering coefficient product. This may be a desirable option that offers a long-term data set with high temporal resolution for developing downscaling technique for disaggregation of radiometer derived soil moisture estimates (i.e. AMSR-E). QuikSCAT backscatter sensitivity to soil moisture was studied over the National Airborne Field Experiment 2006 (NAFE"06) area located in the south-eastern part of Australia. The domain encompasses a wide range of ground conditions including flood irrigation. Point comparisons between QuikSCAT backscattering coefficients and AMSR-E soil moisture revealed the greatest sensitivity of QuikSCAT backscatter to soil moisture over the Kyeamba study area, which was mostly grazing land. North-south and east-west oriented transect lines for a variety soil moisture conditions were also examined. Overall, the QuikSCAT backscatter and AMSR-E soil moisture show similar trends. However the larger variability of the backscatter values was evident in more of the transect lines. As a result, further analysis of the impact of NDVI and vegetation type is needed. The proposed assimilation of radiometer and scatterometer obtained observations will result into high temporal and fine spatial resolution soil moisture product. Aquarius, due for launch in 2009, carries on board both instruments. On that way exploring the possibility of combining AMSR-E and QuikSCAT observations can be beneficial for Aquarius by building more knowledge on the soil moisture temporal and spatial variability and by improving the available soil moisture and disaggregation algorithms.

  9. Radar backscatter sensitivity of soil moisture in vegetation covered areas

    Microsoft Academic Search

    Faisal Karim; Susan Steele-Dunne; Nick van de Giesen

    2010-01-01

    Radar backscatter is sensitive to the water content of bare soil surface. Vegetation cover masks the soil surface, reducing the sensitivity of the radar backscatter to soil moisture. The water-cloud model is used to account for vegetation effects on the copolarized backscatter coefficient in C and L band. In this sensitivity study, two different models for opacity are compared to

  10. SOIL MOISTURE AND ABSORPTION OF WATER BY TREE ROOTS1

    Microsoft Academic Search

    T. T. Kozlowski

    1987-01-01

    Shade trees undergo periodic dehydration because the rate of absorption of soil water lags behind the rate of transpirational water loss from tree crowns. The rate of absorption of water from wet, warm, and well-aerated soil is controlled largely by the rate of transpiration . However, ab- sorption of water often is impeded by low soil moisture con- tent, a

  11. Data Assimilation of Cosmic-ray Derived Soil Moisture

    NASA Astrophysics Data System (ADS)

    Rosolem, R.; Shuttleworth, W. J.; Arellano, A. F.; Hoar, T. J.; Zeng, X.; Zreda, M.; Franz, T. E.

    2012-12-01

    Soil moisture predicted by numerical models plays a key role in weather and seasonal climate projections. Nevertheless, intermediate-scale soil moisture measurements have been difficult to obtain due to small-scale heterogeneity of soil water content, making upscaling measurements to areas comparable to land surface model (LSM) grid size problematic. Real-time integrated soil moisture measurements at spatial scales of a few hundreds of meters and effective depth of tens of centimeters are now available from the COsmic-ray Soil Moisture Observing System (COSMOS). This paper describes the initial efforts to implement the data assimilation framework of COSMOS observations applied to LSMs. A physically-based and analytic model that calculates the above-ground fast neutron intensity from LSM-derived soil moisture profiles is introduced here. The COsmic-ray Soil Moisture Interaction Code (COSMIC) includes a description of (a) degradation of the incoming high energy neutron flux, (b) creation of fast neutrons at each depth in the soil, and (c) degradation of the resulting fast neutrons before they reach the soil surface. COSMIC has been implemented into the Data Assimilation Research Testbed (DART) in order to update the soil moisture status of the NOAH LSM given COSMOS fast neutron intensity measurements. Preliminary results show the soil water dynamics in NOAH being improved when compared to a network of 180 point-scale sensors placed within the COSMOS sensor footprint for a site near Tucson (Arizona). Comparison of surface energy and water fluxes are also shown for a number of selected COSMOS sites co-located with Ameriflux towers.

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

    USGS Publications Warehouse

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

    2009-01-01

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

  13. Soil moisture downscaling across climate regions and its emergent properties

    NASA Astrophysics Data System (ADS)

    Mascaro, Giuseppe; Vivoni, Enrique R.; Deidda, Roberto

    2011-11-01

    Land surface models of water and energy fluxes can benefit from the characterization of soil moisture variability provided by robust downscaling algorithms over a wide range of climatic settings. In this study, we present the application of a multifractal-based statistical downscaling scheme using 800 m aircraft-derived soil moisture data collected during three field campaigns in contrasting climatic regimes. The disaggregation scheme was tested in a previous work using data of the Southern Great Plains experiment in 1997 (SGP97) in a temperate region in Oklahoma. Here, we explore its capability on different climates by using data from two other campaigns: Soil Moisture Experiment in 2002 (SMEX02), in an agricultural region with subhumid climate in Iowa, and Soil Moisture Experiment in 2004 (SMEX04), conducted in two semiarid areas in Arizona and Sonora (Mexico). We first demonstrate the presence of multifractality in soil moisture fields over the scale range from 0.8 km (aircraft footprint) to 25.6 km (satellite footprint) over most wetness conditions. Next, we identify an empirical regional calibration relation linking model parameters with the spatial mean soil moisture and coarse-scale predictors that account for topography, soil texture, and land cover in each site. The downscaling model shows good performance in a broad range of conditions, except for a few cases where specific physiographic features introduce relevant spatial nonhomogeneity in the soil moisture field. The calibrated downscaling model is then applied to study the relation between spatial variability and mean soil moisture across the different climate settings. In such a way, we explain the diverse shapes presented in previous studies and suggest possible physical explanations for intraregional and interregional differences.

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.; Owe, M.; Schmugge, T. J. (principal investigators)

    1981-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil Moisture Active/Passive (SMAP) Mission is one of the first satellites being developed by NASA in response to the National Research Council’s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed Central

    Dente, Laura; Su, Zhongbo; Wen, Jun

    2012-01-01

    The validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture products is a crucial step in the investigation of their inaccuracies and limitations, before planning further refinements of the retrieval algorithm. Therefore, this study intended to contribute to the validation of the SMOS soil moisture products, by comparing them with the data collected in situ in the Maqu (China) and Twente (The Netherlands) regions in 2010. The seasonal behavior of the SMOS soil moisture products is generally in agreement with the in situ measurements for both regions. However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data. Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m3/m3 for the Maqu region and 0.17 m3/m3 for the Twente region for ascending pass data. Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter. Improving the RFI filtering method and the quality of the retrieval algorithm inputs, such as land surface temperature and land cover, would certainly improve the accuracy of the retrieved soil moisture. PMID:23112582

  18. Measurement of soil moisture trends with airborne scatterometers

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J. (principal investigator)

    1978-01-01

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

  19. SMOS CP34 soil moisture and ocean salinity maps

    Microsoft Academic Search

    C. Gabarro; J. Ballabrera; A. Turiel; J. Martinez; M. Umbert; F. Perez; N. Hoareau; M. Portabella; V. Gonzalez; J. Gourrion; S. Guimbard; M. Piles; A. Camps; M. Vall-llossera

    2012-01-01

    This paper presents the soil moisture and ocean salinity maps from the SMOS mission generated operationally by the Spanish SMOS Level 3 and 4 data processing center (CP34) and experimentally by the SMOS Barcelona Expert Center (SMOS-BEC).

  20. Integrating soil moisture and groundwater into climate models

    E-print Network

    Krakauer, Nir Y.

    Integrating soil moisture and groundwater into climate models Nir Krakauer nkrakauer and climate Groundwater and climate Planned directions #12;The parable of the mammoth How did mammoths just mammoths... Freshwater and moderate climate ­ like other resources ­ are equally vulnerable

  1. A quantitative comparison of soil moisture inversion algorithms

    Microsoft Academic Search

    Jakob J. van Zyl; Yunjin Kim

    2001-01-01

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

  2. A quantitative comparison of soil moisture inversion algorithms

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Soil moisture initialization for climate prediction: Assimilation of scanning multifrequency microwave radiometer

    E-print Network

    Ni-Meister, Wenge

    Soil moisture initialization for climate prediction: Assimilation of scanning multifrequency microwave radiometer soil moisture data into a land surface model Wenge Ni-Meister,1 Paul R. Houser,2 soil moisture state initialization. However, initial soil moisture state prediction skill can

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

    Microsoft Academic Search

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

    2011-01-01

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

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

    Microsoft Academic Search

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

    2011-01-01

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

  7. Can Your Global Climate Modeling Project Use a Global Soil Moisture Data Set?

    Microsoft Academic Search

    T. P. Ferre; M. P. Whitaker; B. Nijssen; J. Washburne

    2002-01-01

    Soil moisture is a critical component of the hydrological cycle and plays an important role in determining land surface \\/ atmosphere interactions. However, scientists currently lack sufficient observational data to characterize large scale soil moisture distributions. The GLOBE Soil Moisture Project aims to mobilize the global K-12 with the larger scientific community to participate in periodic, near-surface, gravimetric soil moisture

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

    Ochsner, T.; Venterea, R. T.

    2009-12-01

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

  12. The NASA Soil Moisture Active Passive (SMAP) mission: Overview

    Microsoft Academic Search

    Peggy O'Neill; Dara Entekhabi; Eni G. Njoku; Kent H. Kellogg

    2010-01-01

    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. 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

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

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Holmes, Thomas

    2015-04-01

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

  14. The moisture retention characteristic of four soils from Niger

    E-print Network

    Landeck, Jonathon Keith

    1984-01-01

    THE MOISTURE RETENTION CHARACTERISTIC OF FOUR SOILS FROM NIGER A Thesis by JONATHON KEITH LANDECK Submitted to the Graduate College of Texas ASN University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE.... A. St, out (Member) E. C. A. Runge (Head of Department) December 1984 ABSTRACT The Moisture Retention Characteristic of Four Soils from Niger. (December 1984) Jonathon Keith Landeck, B. S. , Michigan State University Chairman of Advisory...

  15. A ground validation problem of remotely sensed soil moisture data

    Microsoft Academic Search

    C. Yoo

    2002-01-01

    .  ?As the use of space-based sensors to observe soil moisture is becoming more plausible, it is becoming necessary to validate\\u000a the remotely sensed soil moisture retrieval algorithms. In this paper, measurements of point gauges on the ground are analyzed\\u000a as a possible ground-truth source for the comparison with remotely sensed data. The design compares a sequence of measurements\\u000a taken on

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

    PubMed

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

    2013-02-01

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

  17. Soil Moisture Feedbacks on Convection Triggers: The Role of SoilPlant Hydrodynamics MARIO SIQUEIRA

    E-print Network

    Katul, Gabriel

    Soil Moisture Feedbacks on Convection Triggers: The Role of Soil­Plant Hydrodynamics MARIO SIQUEIRA, and Departamento de Engenharia Meca^nica, Universidade de Brasi´lia, Brasi´lia, Brazil GABRIEL KATUL Nicholas form 13 August 2008) ABSTRACT The linkages between soil moisture dynamics and convection triggers

  18. Effect of ambient gases and soil moisture regimes on carbohydrate translocation in kidneybean plants grown in pots in Riyadh, KSA

    Microsoft Academic Search

    Fahad Al-Qurainy

    This study designated to examine the effect of elevated gases in four localities of Riyadh City on carbohydrate for parts of kidneybean plants (Phaseolous vulgaris L.) grown in pots under two soil moisture regimes (well-watered vs. restricted water). Carbohydrate analysis results showed increases in kidneybean samples under well-watered conditions compared to restricted soil moisture. Most kidneybean samples at Embasses site

  19. SCAT/ASCAT Soil Moisture Data: Enhancements in the TU Wien Method for Soil Moisture Retrieval From ERS and METOP Scatterometer Observations

    NASA Astrophysics Data System (ADS)

    Naeimi, V.; Wagner, W.; Bartalis, Z.

    2009-05-01

    Active microwave remote sensing observations of the scatterometers onboard the European Remote Sensing (ERS) and METeorological OPerational (METOP) satellites have been proven to be valuable for monitoring surface soil moisture globally using the so-called TU Wien change detection method. The METOP satellite series carrying ASCAT (Advanced Scatteromer) instrument for the next 15 years will ensure the continuity of soil moisture retrieval from scatterometers' data for more than 30 years considering the available ERS-1&2 Scatterometer (SCAT) observations dataset. With the aim of implementing a near real-time system for operational soil moisture remote sensing at EUMETSAT, the Institute of Photogrammetry and Remote Sensing at Vienna University of Technology (TU Wien) has developed an improved soil moisture retrieval algorithm to cope with some of the limitations found in the earlier method. The new algorithm has been implemented on a discrete global grid with 12.5 km quasi-equal grid spacing and includes a correction method to reduce azimuthal anisotropy of backscatter signal, new techniques for calculation of the model parameters and incorporates a comprehensive error modeling. The error analysis provides not only the quality information about the product but also facilitates accurate determination of historically driest/wettest conditions during the retrieval process. Enhancements made in the TU Wien retrieval algorithm result in a more uniform performance of the model and, consequently, a spatially consistent soil moisture product with a better spatial resolution.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Kunkel, Kenneth E.

    1990-11-01

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

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

    NASA Astrophysics Data System (ADS)

    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 prevailing in this area. Main input data were percentage of granularity categories I to IV according to Kopecky method, reduced volume weight (?d) and measured humidity for potentials hw = -2.5; -56, -209, -558, -976, -3060, -15300 cm specified in laboratory in the overpressure equipment for testing the regression made with abovementioned methods. To compare the results between measured and modeled data by various data driven methods, was accomplished an analysis using correlation coefficient and other statistical characteristics. This evaluation revealed most accurate results by using hybrid SOM-SVM model, in comparison with a conventional multi-layer artificial neural networks, multi-linear regression and standalone SVM model. Greater stability and need of less time devoted to calculations was observed in computation using SVM methodology, since the MLP training sometimes stuck in a local minimum so the training process has to be reset and run many times. This work was supported by the Slovak Research and Development Agency under the contract No. LPP-0319-09.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  4. Soil moisture disaggregation using multiplicative random cascade theory

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Soil moisture is an important parameter that is used in many different applications. In recent years, many efforts have been done to estimate soil moisture by using passive microwave satellite data. Soil Moisture and Ocean Salinity (SMOS) satellite carries an innovative passive microwave radiometer that is widely used to map soil moisture. This satellite has demonstrated that it can provide valuable soil moisture data. However, the spatial resolution of SMOS is 35km-50km and to be able to use its data for regional scale studies, it is necessary to use disaggregation methods to derive soil moisture map in higher spatial resolution. The disaggregation methods that are used to improve the SMOS data are generally based on using a higher spatial resolution satellite data. These methods are encountered with some limitations such as it is necessary that both of the low and high resolution sensors acquire an image from the study area simultaneously. In this research, we are used multiplicative random cascade method to derive higher spatial resolution soil moisture map. The random cascade method is a statistical disaggregation method and it does not need to integrate the reference data with any higher spatial resolution data. To assess the accuracy of this method, ground soil moisture data that were collected during the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) field campaign is used. The range of soil moisture amounts of this data set is 0.27 m3/m3-0.36 m3/m3. The spatial resolution of the data is improved from 80 km to 40 km, 20 km, 10 km and 5 km. In each level of disaggregation, the accuracies are assessed. The Root Mean Square Error (RMSE) of 0.0041 m3/m3, 0.0053 m3/m3, 0.0111 m3/m3 and 0.0135 m3/m3 are obtained for each level, respectively. These low RMSE values are due to the low range of soil moisture measurements during CanEX-SM10. To have more confidence in the method, it is applied to Soil Moisture Experiment 2003 (SMEX03) data set too. The range of soil moisture amounts is 0.01 m3/m3-0.26 m3/m3. The spatial resolution of the data is improved from 80 km to 40 km, 20 km, 10 km and 5 km. The RMSE values of 0.0191 m3/m3, 0.0383 m3/m3, 0.0517 m3/m3 and 0.0630 m3/m3 are obtained for each level respectively. It seems that the difference between RMSE values of the two data sets is related to their different ranges of soil moisture. However, the accuracy assessment of both data sets shows that the random cascade method is an appropriate method to disaggregate low spatial resolution soil moisture data.

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

    SciTech Connect

    Luo, Yan [I.M. Systems Group at NOAA/NCEP/EMC; Feng, Xia [George Mason University; Houser, Paul [George Mason University; Anantharaj, Valentine G [ORNL; Fan, Xingang [Western Kentucky University, Bowling Green; De Lannoy, Gabrielle [Ghent University, Belgium; Zhan, Xiwu [NOAA/NESDIS Center for Satellite Applications and Research; Dabbiru, Lalitha [Mississippi State University (MSU)

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  8. Does soil moisture overrule temperature dependence of soil respiration in Mediterranean riparian forests?

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the ? = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, ?, and powered to an exponent ? > 0 (? =1: linear model; ? ? 1: power model). Both soil moisture data the satellite retrieved (? = ?sat) and the estimates (? = ?est) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was always the lowest; the accuracy in estimating the event soil loss of a models with er

  12. Aircraft scatterometer observations of soil moisture on rangeland watersheds

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  13. The dynamic interplay between roots and soil moisture

    NASA Astrophysics Data System (ADS)

    Garre, Sarah; Vanderborght, Jan; Javaux, Mathieu; Vereecken, Harry

    2010-05-01

    Although water uptake by roots in the soil has been investigated in numerous studies, it is still not clear which is the main factor controlling the uptake, especially under non-uniform soil moisture distribution or intermediately wet soil. Root activity or root compensation factors are frequently used to adjust 1-D root water uptake models to observations. However, they are fitting parameters, which do not rely on real observations and can probably hardly be extrapolated to other boundary conditions. Experiments incorporating more information on the root architecture and on the 3-D soil moisture distributions are therefore needed to better circumvent the interactions between plants, soil structure and boundary conditions and to understand how plant root water uptake affects the flow field variability and vice-versa. We investigated the role root water uptake on soil moisture in an unsaturated, undisturbed soil column (orthic Luvisol) subject to known boundary conditions and cropped with summer barley. We monitored soil moisture in the monolith during 11 weeks using a noninvasive measurement method: time-lapse electrical resistivity tomography (ERT). Additionally, time domain reflectometry probes (TDR), tensiometers and temperature probes were installed at several depths to monitor local soil water content and electrical conductivity. Minirhizotron tubes were inserted in the lysimeters to monitor root growth and root length density (RLD) in the different soil layers. The 3-D ERT images allowed us to characterize the root space and time water depletion distribution during the growing season. Combined with the root monitoring method, it gave us a better insight in the way plants take up water in the soil and how they adapt there root system to changing soil moisture conditions.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Ancell, Brian; Nauert, Christian

    2014-05-01

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

  16. Large-Area Soil Moisture Estimation Using Multi-Incidence-Angle RADARSAT-1 SAR Data

    Microsoft Academic Search

    Hari Shanker Srivastava; Parul Patel; Yamini Sharma; Ranganath R. Navalgund

    2009-01-01

    The sensitivity of synthetic aperture radar (SAR) backscatter to soil moisture has been adequately established. However, monitoring of soil moisture over large agricultural areas is still difficult because SAR backscatter is also sensitive to other target properties like surface roughness, crop cover, and soil texture (soil type), along with its strong sensitivity to soil moisture. Hence, to develop a methodology

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

    Microsoft Academic Search

    Feike A. Dijkstra; Weixin Cheng

    2007-01-01

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

  18. Evaluation of microwaves soil moisture products based on two years of ground measurements over a Sahelian region.

    NASA Astrophysics Data System (ADS)

    Gruhier, C.; de Rosnay, P.; Kerr, Y.; Kergoat, L.

    2008-12-01

    Microwaves remote sensing is a promising approach to measure soil moisture values and variations. Soil moisture is a very important variable which strongly interacts with soil-vegetation-atmosphere fluxes. This is particularly true in Sahelian region with monsoon climatic system. From active or passive microwaves measurements of backscatter coefficients or brightness temperatures, soil moisture products are derived. Soil moisture products evaluation is essential to improve algorithm and inform users on the products quality (eg quality of soil moisture products variability or absolutes). This study aims to evaluate and to intercompare five soil moisture products from active and passive microwaves sensors. The study is performed for 2005-2006, for a 1 x 3 degrees longitude-latitude window located in Sahel (14-17N and 0-1W). In addition an accurate validation is conducted for specific locations based on ground measurements available in this region. It uses the Gourma (Mali) soil moisture measurements network installed in the framework of the African Monsoon Multidisciplinary Analysis (AMMA) program. The soil moisture network has been organized in order to validate remotely sensed soil moisture for the future Soil Moisture an Ocean Salinity (SMOS) mission. Three stations located on sandy dune systems have been selected according to their location along the North-South climatic gradient. They provide continuous soil moisture measurements at 15-minute time step and at 5-cm depth for 2005-2006. Five soil moisture products provided by three different sensors are considered. 1) From the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E), two soil moisture products are used: the National Snow and Ice Data Center product and the Amsterdam University product. 2) From the Wind Scatterometer, on European Remote Sensing (ERS) satellite, two soil moisture products are evaluated: the Vienna University of Technology and the Zribi et al 2007 products. 3) The soil moisture product obtained by the Amsterdam University from the Tropical Rainfall Measuring Mission satellite mission (TMI sensor -TRMM Microwave Imager) is also evaluated. AMSR-E and TRMM/TMI are passive microwave sensors while ERS/SCAT is an active microwave sensor. Soil moisture product comparison and evaluation investigates both spatial and temporal variations of soil moisture as well as absolutes values. Consistency of soil moisture spatial distributions between the products is addressed. It is shown that there is generally a good agreement, in term of spatial distribution of soil moisture over the considered region, between the products during the monsoon season. In contrast products consistency is poorer during the dry season. Statistical correlations between ground measurements and satellite products are significant for all products, (best results is R2=0.85 for the AMSR-E university of Amsterdam product). But all the soil moisture products considered over-estimate absolute soil moisture values, particularly during the dry season. Mean RMSE is around 5% in volumetric soil moisture content. Important differences between products based on data from same sensor are also highlighted in this study.

  19. Microbial soil respiration and its dependency on carbon inputs, soil temperature and moisture

    E-print Network

    Silver, Whendee

    Microbial soil respiration and its dependency on carbon inputs, soil temperature and moisture J . C on the results obtained. Soil respiration was periodically measured at an oak savanna woodland and a ponderosa in the modeling framework. Keywords: climate change, soil organic matter, decomposition, soil respiration Received

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  1. Active and passive microwave remote sensing of soil moisture

    Microsoft Academic Search

    Rajat Bindlish

    2000-01-01

    This study focuses on the development of a consistent methodology for soil moisture inversion from Synthetic Aperture Radar (SAR) data using the Integral Equation Model (Fung et al., 1992) without the need to prescribe time-varying land-surface attributes as constraining parameters. Specifically, the dependence of backscatter coefficient on the soil dielectric constant, surface roughness height and correlation length was investigated. The

  2. Soils âField Characterization, Collection, and Laboratory Analysis

    NSDL National Science Digital Library

    Abir Biswas

    Field characterization of soil profiles in coniferous and deciduous settings; sample collection of soils from different horizons; laboratory analysis of soil moisture, soil organic carbon (by loss on ignition), and grain size distribution (by sieving)

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

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

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

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

    Microsoft Academic Search

    J. E. Hipp

    1974-01-01

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

  5. Field-Scale Soil Moisture Sensing Using GPS Reflections: Description of the PBO H2O Soil Moisture Product

    NASA Astrophysics Data System (ADS)

    Chew, C. C.; Small, E. E.; Larson, K. M.

    2014-12-01

    Data from NSF's EarthScope Plate Boundary Observatory (PBO), and similar GPS networks worldwide, can be used to monitor the terrestrial water cycle. GPS satellites transmit L-band microwave signals, which are affected by water at Earth's surface. GPS signals take two paths: (1) the "direct" signal travels from the satellite to the antenna; (2) the "reflected" signal interacts with the Earth's surface before travelling to the antenna. The direct signal is used by geophysicists to measure position of the antenna, while the effects of reflected signals are generally ignored. Recently, our group has developed a technique to retrieve terrestrial water cycle variables from GPS reflections. The sensing footprint is intermediate in scale between in situ and remote sensing observations. Soil moisture, snow depth, and an index of vegetation water content are estimated from data collected at over 400 PBO sites. The products are updated daily and are available online. This presentation provides a description of the soil moisture product. Near-surface soil moisture is estimated at more than 100 sites in the PBO H2O network. At each site, a geodetic-quality GPS antenna records the interference pattern between the direct and ground-reflected GPS signals in signal-to-noise ratio (SNR) interferograms. The ground-reflected GPS signal is altered by changes in the permittivity of the ground surface, which is primarily a function of its water content. Temporal changes in the SNR interferogram, primarily its phase, are indicative of changes in soil moisture. SNR phase data are converted to soil moisture using relationships determined using an electrodynamic model. Soil moisture is not retrieved when there is snow or significant vegetation (> ~1 kg m-2 of vegetation water), as both affect SNR phase. When there is moderate vegetation, a correction is applied to the phase data before conversion to soil moisture. The effect of vegetation on SNR phase and the exact relationship between SNR phase and soil moisture are the primary sources of error. At sites where seasonal variations in vegetation water content are < 0.5 kg m-2, validation surveys show that the RMSE between in situ and GPS soil moisture estimates is < 0.04 cm3 cm-3. Therefore, soil moisture data from these sites could be utilized for satellite validation and other applications.

  6. Establishing a Multi-Spatial Wireless Sensor Network to Monitor Nitrate Concentrations in Soil Moisture

    E-print Network

    2004-01-01

    Wireless Sensor Network to Monitor Nitrate Concentrations inSensors for measuring temperature, precipitation, moisture, nitrate.sensors to measure temperature, precipitation, and soil moisture and nitrates.

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  8. Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

    NASA Astrophysics Data System (ADS)

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

    1999-01-01

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

  9. Soil moisture estimation in cereal fields using multipolarized SAR data

    NASA Astrophysics Data System (ADS)

    Alvarez-Mozos, J.; Izagirre, A.; Larrañaga, A.

    2012-04-01

    The retrieval of soil moisture from remote sensing data is an extremely active research topic with applications on a wide range of disciplines. Microwave observations represent the most viable approach due to the influence of soils' dielectric constant (and thus soil moisture) on both the emission and backscatter of waves in this region of the spectrum. Passive observations provide higher temporal resolutions, whereas active (SAR) observations have a higher spatial detail. Even if operational moisture products, based on passive data, exist, retrieval algorithms using active observations still face several problems. Surface roughness and vegetation cover are probably the disturbing factors most affecting the accuracy of soil moisture retrievals. In this communication the influence of vegetation cover is investigated and a retrieval technique based on multipolarized C band SAR observations is proposed. With this aim a dedicated field campaign was carried out in La Tejería watershed (north of Spain) from January to August 2010. Eight RADARSAT-2 Fine-Quadpol scenes were acquired in order to investigate the role of vegetation cover on the retrieval of soil moisture, as well as the sensitivity of different polarimetric parameters to vegetation cover condition. Coinciding with image acquisitions soil moisture, plant density and crop height measurements were acquired in eight control fields (cultivated with barley and wheat crops). The sensitivity of backscatter coefficients (in HH, HV and VV polarizations) and backscatter ratios (p=HH/VV and q=HV/VV) to soil moisture and crop condition were evaluated and the semi-empirical Water Cloud Model was fitted to the observations. The results obtained showed that the contribution of the cereal vegetation cover was minimal in HH and HV polarizations, whereas the VV channel appeared to be significantly attenuated by the cereal cover, so its value decreased as the crops grew. As a result, the ratios p and q showed a very good correlation with vegetation condition and resulted to be almost insensitive to soil moisture variations. These ratios were next used to parameterize cereal vegetation cover on a retrieval scheme based on the Water Cloud Model. Results were best on VV polarization where the correlation coefficients obtained were above 0.7. The approach proposed is very promising from an operational point of view since it corrects the influence of vegetation cover in the retrieval without requiring external information to describe it. Besides, the low variability of the empirical coefficients obtained for different fields, suggests that differences in surface roughness at this stage do not significantly affect soil moisture retrievals.

  10. Distribution of soil and leaf water potentials of mature grapefruit trees under three soil moisture regimes

    E-print Network

    Prathapar, Sanmugam Ahembaranathan

    1982-01-01

    DISTRIBUTION OF SOIL AND LEAF WATER POTENTIALS OF MATURE GRAPEFRUIT TREES UNDER THREE SOIL MOISTURE REGIMES A Thesis by SANMUGAM AHEMBARANATHAN PRATHAPAP, Submitted to the Graduate College of Texas A&M University in partial fulfillment... of the requirement for the degree of MASTER OF SCIENCE May 1982 Major Subject; Agricultural Engineering DISTRIBUTION OF SOIL AND LEAF WATER POTENTIALS OF MATURE GRAPEFRUIT TREES UNDER THREE SOIL MOISTURE REGIMES A Thesis by SANMUGAM AHEMBARANATHAN PRATHAPAR...

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  12. Soil moisture modeling by means of Landsat-5 TM data over a Mediterranean mountain catchment

    NASA Astrophysics Data System (ADS)

    Cristóbal, Jordi; Llorens, Pilar; Latron, Jérôme

    2010-05-01

    Soil moisture has important implications on the hydrological cycle and its monitoring is relevant for the assessment of environmental stress that affects forest and agricultural ecosystems. Nowadays, radiometric measurements provided by Remote Sensing are the technologies used to model soil moisture at regional scales in a feasible way. In this study we present a preliminary estimation of the daily soil moisture, for the period 2002-2009, using a set of 30 Landsat images (22 Landsat-5 TM and 8 Landsat-7 ETM+), for several locations in the Vallcebre research catchments (42° 12'N, 1° 49'E). This area is located in the NE of the Iberian Peninsula at 1100m a.s.l., and is characterized by a sub-Mediterranean climate with marked water deficit in summer. Mean annual temperature is 9.1°C and mean annual precipitation is 862 ± 206 mm, with a mean of 90 rainy days per year. Mean annual reference evapotranspiration is 823 ± 26 mm. Landsat-7 ETM+ and Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital Elevation Model, obtaining an RMSE less than 30 m. Radiometric correction of Landsat non-thermal bands has been done following the methodology proposed by Pons and Solé (1994), which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Atmospheric correction of Landsat thermal band has been carried out by means of a single-channel algorithm improvement developed by Cristóbal et al. (2009) and the land surface emissivity computed by means of the methodology proposed by Sobrino and Raissouni (2000). Soil water content has been modeled through a multiple regression analysis between soil moisture data and several vegetation indexes - NDVI, EVI, Greenness - and wetness indexes - NDWI, Wetness and the land surface temperature. In order to select the variables before performing the multiple regression analysis a model's predictors have been computed on the basis of Mallows' Cp. Models have been validated through surface soil moisture measurements obtained in 10 TDR profiles covering a wide range of soil moisture conditions in different topographic locations and over different types of vegetation: grassland, Scots pines (Pinus sylvestris) and Pubescent oaks (Quercus humilis). Preliminary results show a good agreement between soil moisture multiple regression models obtained using remote sensing data and field soil moisture data. Keywords: Soil moisture, Landsat-5 TM, multiple regression analysis, Mediterranean region.

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

    Microsoft Academic Search

    Alexander Loew; Wolfram Mauser

    2008-01-01

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

  14. Soil moisture modeling and scaling using passive microwave remote sensing 

    E-print Network

    Das, Narendra N.

    2007-04-25

    based on soil texture (i.e., pedo transfer functions) are 17 commonly used in hydrologic models. In this study, the average values for selected soil water retention and hydraulic conductivity parameters for the major soil textural classes... is the air density, cp is the specific heat capacity of the air at the constant pressure, ra is aerodynamic resistance of evaporating surface, where = dm0 /dT, m0 is the specific moisture content of air saturated with water vapor...

  15. Soil Moisture Sensing Using Reflected GPS Signals: Description of the GPS Soil Moisture Product.

    NASA Astrophysics Data System (ADS)

    Larson, Kristine; Small, Eric; Chew, Clara

    2015-04-01

    As first demonstrated by the GPS reflections group in 2008, data from GPS networks can be used to monitor multiple parameters of the terrestrial water cycle. The GPS L-band signals take two paths: (1) the "direct" signal travels from the satellite to the antenna, which is typically located 2-3 meters above the ground; (2) the reflected signal interacts with the Earth's surface before traveling to the antenna. The direct signal is used by geophysicists and surveyors to measure the position of the antenna, while the effects of reflected signals are a source of error. If one focuses on the reflected signal rather than the positioning observables, one has a method that is sensitive to surface soil moisture (top 5 cm), vegetation water content, and snow depth. This method - known as GPS Interferometric Reflectometry (GPS-IR) - has a footprint of ~1000 m2 for most GPS sites. This is intermediate in scale to most in situ and satellite observations. A significant advantage of GPS-IR is that data from existing GPS networks can be used without any changes to the instrumentation. This means that there is a new source of cost-effective instrumentation for satellite validation and climate studies. This presentation will provide an overview of the GPS-IR methodology with an emphasis on the soil moisture product. GPS water cycle products are currently produced on a daily basis for a network of ~500 sites in the western United States; results are freely available at http://xenon.colorado.edu/portal. Plans to expand the GPS-IR method to the network of international GPS sites will also be discussed.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

    Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  18. Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System

    SciTech Connect

    Buckley, R.

    2001-06-27

    Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

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

    NASA Astrophysics Data System (ADS)

    Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

    2014-05-01

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

  20. Geophysical mapping of variations in soil moisture

    Microsoft Academic Search

    Dumitru Ioane; Daniel Scradeanu; Florina Chitea; George Garbacea

    2010-01-01

    The geophysical investigation of soil characteristics is a matter of great actuality for agricultural, hydrogeological, geotechnical or archaeological purposes. The geophysical mapping of soil quality is subject of a recently started scientific project in Romania: \\

  1. Concerning the Relationship between Evapotranspiration and Soil Moisture.

    NASA Astrophysics Data System (ADS)

    Wetzel, Peter J.; Chang, Jy-Tai

    1987-01-01

    Evapotranspiration observations have traditionally been scaled by potential evapotranspiration as a means of unifying the soil moisture-evapotranspiration relationship under a variety of meteorological conditions. However, this scaling alone does not unify the relationship during the drying. supply-limited phase. In this paper, a second scaling parameter is identified which applies to this phase of evapotranspiration. The parameter is a maximum sustainable, or threshold evapotranspiration, which occurs in vegetation-covered surfaces just before leaf stomata close, and occurs when surface tension begins to significantly restrict the moisture release from bare soil pores. Simple expressions for this parameter are presented for the cases of vegetation cover and bare soil. The number of input variables required in these expressions is rather small.We examine the effect of natural soil heterogeneities on evapotranspiration as computed from the proposed model. It is shown that the observed natural variability in soil moisture resulting from these heterogeneities is large enough to seriously alter the relationship between regional evapotranspiration and the area average soil moisture when compared to the point or homogeneous relationship. The implications for remote sensing and grid point numerical models are discussed. As a consequence of these results, we propose some key elements of a very simple parameterization for regional evapotranspiration for use in numerical models.

  2. Results of soil moisture flights during April 1974

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Blanchard, B. J.; Burke, W. J.; Paris, J. F.; Swang, J. R.

    1976-01-01

    The results presented here are derived from measurements made during the April 5 and 6, 1974 flights of the NASA P-3A aircraft over the Phoenix, Arizona agricultural test site. The purpose of the mission was to study the use of microwave techniques for the remote sensing of soil moisture. These results include infrared (10-to 12 micrometers) 2.8-cm and 21-cm brightness temperatures for approximately 90 bare fields. These brightness temperatures are compared with surface measurements of the soil moisture made at the time of the overflights. These data indicate that the combination of the sum and difference of the vertically and the horizontally polarized brightness temperatures yield information on both the soil moisture and surface roughness conditions.

  3. Radar estimates of soil moisture over the Konza Prairie

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  4. Sensitivity of Microwave Backscatter to Soil Moisture under Bare Soil Conditions

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  5. Downscaling of seasonal soil moisture forecasts using satellite data

    NASA Astrophysics Data System (ADS)

    Schneider, S.; Jann, A.; Schellander-Gorgas, T.

    2014-08-01

    A new approach to downscaling soil moisture forecasts from the seasonal ensemble prediction forecasting system of the ECMWF (European Centre for Medium-Range Weather Forecasts) is presented in this study. Soil moisture forecasts from this system are rarely used nowadays, although they could provide valuable information. Weaknesses of the model soil scheme in forecasting soil water content and the low spatial resolution of the seasonal forecasts are the main reason why soil water information has hardly been used so far. The basic idea to overcome some of these problems is the application of additional information provided by two satellite sensors (ASCAT and Envisat ASAR) to improve the forecast quality, mainly to reduce model bias and increase the spatial resolution. Seasonal forecasts from 2011 and 2012 have been compared to in situ measurement sites in Kenya to test this two-step approach. Results confirm that this downscaling is adding skill to the seasonal forecasts.

  6. Estimation of soil moisture conditions with Landsat TM in Guangzhou

    NASA Astrophysics Data System (ADS)

    Sun, Q.; Tan, J.; Chen, S.

    2008-10-01

    As useful indicators for land surface characteristics, Land Surface Temperature (LST) and Normal Different Vegetation Index (NDVI) can provide information on vegetation and moisture conditions at the surface. In this study, Qin's monowindow algorithm and Temperature-Vegetation Dryness Index (TVDI) were employed to study LST and soil moisture conditions in Guangzhou. Landsat TM image dated on November 23, 2005 was used to retrieve the LST and TVDI. A geospatial model was designed and processed for getting LST and soil moisture status. The result images reveal that, the areas with high land surface temperatures mainly appeared in the centers of urban. On 23 November, 2005, areas with high land surface temperatures took up 26.15%, while urban heat island areas with higher land surface temperatures took up 11.6% in Guangzhou. Except water and urban or built-up land, humid and normal areas took up 22.05%, slight drought areas took up 60.75%, drought areas took up 17.01%, and heavy drought areas took up 0.16%.Compare to the real status of soil moisture, the result indicate that the TVDI index can provide a powerful tool to assess the soil moisture conditions for large scale areas in Guangzhou.

  7. Effect of Soil Moisture on Fumigant Emissions from a Loam Soil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Emissions of soil fumigants must be minimized in order to protect air quality in California. Soil moisture is an important factor that can be managed at a relatively low cost prior to soil fumigation to reduce emissions. A previous study indicated that increasing soil water content up to field capac...

  8. Coupled stochastic dynamics of water table and soil moisture in bare soil conditions

    Microsoft Academic Search

    L. Ridolfi; P. D'Odorico; F. Laio; S. Tamea; I. Rodriguez-Iturbe

    2008-01-01

    The soil water content plays a fundamental role in a number of important environmental processes, including those involved in the water cycle, vegetation dynamics, soil biogeochemical cycles, and land-atmosphere interactions. Despite the recent efforts spent in the analytical modeling of the stochastic soil moisture dynamics in dryland ecosystems, the probabilistic characterization of the soil water balance in groundwater dependent environments

  9. Implications of complete watershed soil moisture measurements to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

    1983-01-01

    A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

  10. Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

    NASA Astrophysics Data System (ADS)

    Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

    2006-05-01

    Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

  11. Foliar anatomical and morphological variation in Nothofagus pumilio seedlings under controlled irradiance and soil moisture levels.

    PubMed

    Ivancich, Horacio S; Lencinas, María V; Pastur, Guillermo J Martínez; Esteban, Rosina M Soler; Hernández, Luis; Lindstrom, Ivone

    2012-05-01

    Foliar anatomy and morphology are strongly related to physiological performance; therefore, phenotypic plasticity in leaves to variations in environmental conditions, such as irradiance and soil moisture availability, can be related to growth rate and survivorship, mainly during critical growth phases, such as establishment. The aim of this work was to analyze changes in the foliar internal anatomy (tissue proportions and cell dimensions) and external morphology (leaf length, width and area) of Nothofagus pumilio (Poepp. et Endl.) Krasser seedlings growing in a greenhouse under controlled irradiance (three levels) and soil moisture (two levels) during one growing season (measured three times), and to relate them to physiological traits. Three irradiance levels (4, 26 and 64% of the natural incident light) and two soil moisture levels (40 and 80% soil capacity) were evaluated during November, January and March. Internal foliar anatomy of seedlings was analyzed using digital photographs of histological cuttings, while leaf gross morphology was measured using digital calipers and image analysis software. Most internal anatomical variables presented significant differences under different irradiance levels during the growing season, but differences were not detected between soil moisture levels. Palisade parenchyma was the tissue most sensitive to irradiance levels, and high irradiance levels (64% natural incident light) produced greater values in most of the internal anatomical variables than lower irradiance levels (4-24% natural incident light). Complementarily, larger leaves were observed in medium and low irradiance levels, as well as under low soil moisture levels (40% soil capacity). The relationship of main results with some eco-physiological traits was discussed. Foliar internal anatomical and external morphological plasticity allows quick acclimation of seedlings to environmental changes (e.g., during harvesting). These results can be used to propose new forest practices that consider soil moisture and light availability changes to maintain high physiological performance of seedlings. PMID:22499597

  12. A Particle Batch Smoother for soil moisture determination by assimilating soil temperatures

    NASA Astrophysics Data System (ADS)

    Dong, Jianzhi; Steele-Dunne, Susan; van de Giesen, Nick

    2015-04-01

    Soil moisture plays a pivotal role in hydrological modeling. Information on soil moisture spatial variability is difficult to obtain using either traditional point scale, or footprint scale remote sensing measurements. This challenge limits both hydrological model performance and the utility of soil moisture products. Distributed temperature sensing (DTS) is an innovative tool for making high resolution temperature measurements (spatial < 1m, and temporal < 1min), along cables which can be up to several kilometers in length. Previous studies demonstrated the feasibility of estimating soil moisture by assimilating temperature observations at shallow layers in a sequential data assimilation system. In this study, we propose a smoothing approach developed from the particle filter, in which series of temperature observations rather than instantaneous observations are assimilated. The evolution of soil temperature in time contains more information of soil moisture than instantaneous observation points. Compared with the standard particle filter, our particle smoothing approach provides improved estimates using same amount of temperature information. It is particularly beneficial for inferring root zone soil moisture. The smoothing approach here may provide a viable tool for determining distributed soil moisture information from DTS observations.

  13. Alberta Soil Moisture Analyses using CaLDAS

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  14. Vegetation and Roughness Controls on Field Scale Soil Moisture Variability

    NASA Astrophysics Data System (ADS)

    Adams, J. R.; Berg, A. A.; Toth, B.; Magagi, R.

    2009-05-01

    Downscaling of satellite-based passive microwave soil moisture products such as those to be derived from the Soil Moisture and Ocean Salinity (SMOS) mission requires enhanced understanding of controls of field scale soil moisture variability. A RADARSAT 2 field validation campaign was conducted in July 2008 to measure soil conditions, crop parameters and surface roughness over a six day period, at a network of 10 agricultural sites in Saskatchewan (N 50° - N 51°; W 105° - W 106°). Four crop types are analysed: pulse crops, cereals, oilseeds, and fallow fields, with a sample area of 2.1 km2 per site. From this data set we evaluate the impact of vegetation type and surface roughness on field scale soil moisture variability using parametric and non-parametric statistical approaches. Our results demonstrate the importance of both field scale roughness and vegetation type on field scale variability. Of significance, field scale roughness can be measured from satellite platforms such as RADARSAT-2 and vegetation type is available from optical sensors.

  15. Influence of Soil Moisture on Microbial Activity in a Primary Acidification of Pyritic Soils

    NASA Astrophysics Data System (ADS)

    Ueno, K.; Adachi, T.

    2004-12-01

    Soil moisture had a grate influence on soil acidification in pyritic soils. The acidification was occurred by chemical and bacterial processes of pyrite oxidation. It was reported that the bacterial oxidation was accelerated by soil moisture at near the condition of plastic limited. We investigated the accelerated soil moisture condition by matric potential and changes of bacterial activity using a soil taken from polder land of the Lake Nakaumi. Six levels of soil moisture conditions were prepared by drying. The samples were incubated at 30oC with keeping these moistures, and populations of Gram-positive and -negative bacteria (GPB and GNB) and Thiobacillus ferrooxidans (total, adsorbed and free forms) were determined. Soil acidification was accelerated at the moisture range from -6.0kPa to -35kPa while drying at 5.4g/h of evaporation rate. Samples drying at 12.0g/h ceased acidifying over -35kPa. On the other hand, a drop of pH value was accelerated at -35kPa when the samples was kept under their moisture conditions. The moisture condition seemed to be suitable for bacterial oxidation. The major bacteria under most of the moisture conditions were GPB, but T. ferrooxidans, one of GNB, was predominated at -35kPa. Under this moisture condition, the growth rate of T. ferrooxidans was highest and the population of GPB decreased during the exponential growth stage of T. ferrooxidans. Acidification of the soil seemed to be depending on proliferation of T. ferrooxidans not on the cell number of T. ferrooxidans. The growth rate of both absorbed and free forms of T. ferrooxidans was highest at -35kPa of all soil moisture conditions. The survival rate of T. ferrooxidans was highest at -3.5kPa and that of the free forms decreased at -35kPa. At -3,000kPa the absorbed forms of T. ferrooxidans had very small population and then decreased. The free forms were not detected. These data indicated that growth habitat of T. ferrooxidans were influenced by soil moisture. The accelerated moisture condition of -35kPa had a uniqueness on the bacterial populations and was suitable for proliferation of T. ferrooxidans. These results showed that high growth rate of T. ferrooxidans had a great influence on high rate of acidification in pyritic soils. The mechanism supposed to be that motility of the bacteria was influenced by shrinkage level of soil matrix and also that the environment was suitable for getting their energy to keep them alive.

  16. De-noising of microwave satellite soil moisture time series

    NASA Astrophysics Data System (ADS)

    Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew; Wagner, Wolfgang

    2013-04-01

    The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of Technology) ASCAT data sets to identify two types of errors that are spectrally distinct. Based on a semi-empirical model of soil moisture dynamics, we consider possible digital filter designs to improve the accuracy of their soil moisture products by reducing systematic periodic errors and stochastic noise. We describe a methodology to design bandstop filters to remove artificial resonances, and a Wiener filter to remove stochastic white noise present in the satellite data. Utility of these filters is demonstrated by comparing de-noised data against in-situ observations from ground monitoring stations in the Murrumbidgee Catchment (Smith et al., 2012), southeast Australia. Albergel, C., de Rosnay, P., Gruhier, C., Muñoz Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y. H., & Wagner, W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226. Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters, 35, L24403. Smith, A. B., Walker, J. P., Western, A. W., Young, R. I., Ellett, K. M., Pipunic, R. C., Grayson, R. B., Siriwardena, L., Chiew, F. H. S., & Richter, H. (2012). The Murrumbidgee soil moisture network data set. Water Resources Research, 48, W07701. Su, C.-H., Ryu, D., Young, R., Western, A. W., & Wagner, W. (2012). Inter-comparison of microwave satellite soil moisture retrievals over Australia. Submitted to Remote Sensing of Environment.

  17. Understanding of accuracy on calculated soil moisture field for the study of land-atmosphere interaction

    NASA Astrophysics Data System (ADS)

    Yorozu, K.; Tanaka, K.; Nakakita, E.; Ikebuchi, S.

    2007-12-01

    Understanding the state of soil moisture is effective to enhance climate predictability on inter-seasonal or annual time scales. Thus, the Global Soil Wetness Project (GSWP) has been implemented as an environmental modeling research activity. The SiBUC (Simple Biosphere including Urban Canopy) land surface model is one of the participants of the 2nd GSWP, and it uses mosaic approach to incorporate all kind of land-use. In order to estimate the global soil moisture field as accurately as possible and to utilize the products of GSWP2 simulation more efficiently, SiBUC is run with irrigation scheme activated. Integration of one-way uncoupled SiBUC model from 1986 to 1995 have produced global soil moisture field. Both the model and forcing data may contain uncertainty. However, the SiBUC model is one of the few models which can consider irrigation effect. And also, the advantage of the meteorological forcing data provided from GSWP2 is hybridization among reanalysis products, observation data and satellite data. In this sense, it is assumed that GSWP2 products is the most accurate global land surface hydrological data set in available. Thus, these global products should be applied to land-atmosphere interaction study, if possible. To do this, it is important to understand inter-annual or much higher time scale accuracy on calculated soil moisture filed. In this study, calculated soil moisture field are validated with observation of soil moisture in five regions (Illinois:USA, China, India, Mongolia, Russia). The Russian data has two types data: one is located in spring wheat and another is located in winter wheat. These observation data are provided from Global Soil Moisture Data Bank (GSMDB). To understand the time scale accuracy on soil moisture field, three correlation coefficients are calculated between calculated soil moisture and observed soil moisture: inter-annual, inter-seasonal and monthly mean correlation, respectively. As a result, if the median value in each region is focused on, high monthly correlation are shown in Illinois (0.83) and India (0.75). In these regions, inter-seasonal correlation is also high, but inter-annual correlation becomes lower. On the other hand, in China or Mongolia, all median value of correlation is low. And, both types of monthly correlation in Russia are relatively high (0.69, 0.65). In addition, inter-seasonal and inter-annual correlation are almost same as monthly correlation. From the result, from the viewpoint of regional scale, calculated soil moisture field in Illinois and India have high accuracy on monthly and inter-seasonal time scales. In Russia, calculated soil moisture field has relatively high accuracy on any time scales. Low accuracy on monthly time scale in China and Mongolia correspond to the result of multi-model analysis and validation (Guo et al., 2007). From this concurrent result, it is assumed that it is difficult to estimate the soil moisture field in China and Mongolia for any models or meteorological forcing data have some uncertainty. Nevertheless these reason should be investigated.

  18. Assimilation of streamflow and soil moisture observations in a distributed physically-based hydrological model

    NASA Astrophysics Data System (ADS)

    Trudel, M.; Leconte, R.; Paniconi, C.

    2012-04-01

    Data assimilation techniques not only enhance model simulations and predictions, they also give the opportunity to pose a diagnostic on both model and observations used in the assimilation process. The goal of this research is to assimilate streamflow and soil moisture in a distributed physically-based hydrological model, CATHY (CATchment HYdrology). The study site is the des Anglais Watershed, a 690-km2 river basin located in southern Québec, Canada. An ensemble Kalman filter was used to assimilate streamflow observations at the basin outlet and at interior locations, as well as soil moisture at different depths (15, 45, and 90 cm) measured with probes (6 stations) and surface soil moisture estimated from radar remote sensing. The use of a Latin hypercube sampling instead of the Monte Carlo method to generate the ensemble reduced the size of ensemble, and therefore the calculation time. An important issue in data assimilation is the estimation of error covariance matrices. Different post-assimilation diagnostics, based on innovations (observation-minus-background), analysis residuals (observation-minus-analysis) and analysis increments (analysis-minus-background) were used to evaluate assimilation optimality. A calibration approach was performed to determine the standard deviation of model parameters, forcing data and observations that lead to optimal assimilations. The analysis of innovations showed a lag between the model prediction and the observation during rainfall events. The assimilation of streamflow observations (outlet or interior locations) corrected this discrepancy. The assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) at both outlet and interior point locations. The structure of the state vector used in this study allowed the assimilation of outlet streamflow observations to have an impact over streamflow simulations at interior point locations. Indeed, the state vector contains the outlet streamflow (Qout) and the incoming streamflow (Qin), since both these informations are used by the Muskingum-Cunge surface routing equation in CATHY. However, assimilation of streamflow observations increased systematically the soil moisture values simulated at 15 and 45 cm. The combined assimilation of outlet streamflow and soil moisture improved the NSE of streamflow without degrading the simulation of soil moisture. Moreover, the assimilation of streamflow and soil moisture observations from one station (at 45 cm depth) appeared to have a similar impact on soil moisture simulations compared to a combined assimilation of streamflow and soil moisture observations from five stations. Finally, it was found that the frequency of the assimilation of soil moisture observations has a greater impact on the results than the spatial coverage of the assimilation: assimilation of daily soil moisture measured with probes at six stations gives better results than the assimilation of surface soil moisture estimated from radar remote sensing 8 times over the course of a summer season.

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

    NASA Astrophysics Data System (ADS)

    Kolassa, Jana; Aires, Filipe

    2013-04-01

    A neural network algorithm has been developed for the retrieval of Soil Moisture (SM) from global satellite observations. The algorithm estimates soil moisture from a synergy of passive and active microwave, infrared and visible satellite observations in order to capture the different SM variabilities that the individual sensors are sensitive to. The advantages and drawbacks of each satellite observation have been analysed and the information type and content carried by each observation have been determined. A global data set of monthly mean soil moisture for the 1993-2000 period has been computed with the neural network algorithm (Kolassa et al., in press, 2012). The resulting soil moisture retrieval product has then been used in an inter-comparison study including soil moisture from (1) the HTESSEL model (Balsamo et al., 2009), (2) the WACMOS satellite product (Liu et al., 2011), and (3) in situ measurements from the International Soil Moisture Network (Dorigo et al., 2011). The analysis showed that the satellite remote sensing products are well-suited to capture the spatial variability of the in situ data and even show the potential to improve the modelled soil moisture. Both satellite retrievals also display a good agreement with the temporal structures of the in situ data, however, HTESSEL appears to be more suitable for capturing the temporal variability (Kolassa et al., in press, 2012). The use of this type of neural network approach is currently being investigated as a retrieval option for the SMOS mission. Our soil moisture retrieval product has also been used in a coherence study with precipitation data from GPCP (Adler et al., 2003) and inundation estimates from GIEMS (Prigent et al., 2007). It was investigated on a global scale whether the three observation-based datasets are coherent with each other and show the expected behaviour. For most regions of the Earth, the datasets were consistent and the behaviour observed could be explained with the known hydrological processes. In addition, a regional analysis was conducted over several large river basins, including a detailed analysis of the time-lagged correlations between the three datasets and the spatial propagation of observed signals. Results appear consistent with the knowledge of the hydrological processes governing the individual basins. References Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, and P. Arkin (2003), The Version 2 Global Precipita- tion Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present).J. Hydrometeor., 4,1147-1167. Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. and Scipa,l K. (2009) A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrol., 10, 623-643 Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T. (2011), The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675-1698 Kolassa, J., Aires, F., Polcher, J., Prigent, C., and Pereira, J. (2012), Soil moisture Retrieval from Multi-instrument Observations: Information Content Analysis and Retrieval Methodology (2012), J. Geophys. Res., Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.(2011), Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425-436. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews (2007), Global inundation dy- namics inferred from multiple satellite observations, 1993-2000, J. Geophys. Res., 112, D12107, doi:10.1029/2006JD007847.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  1. Potential application of satellite radar to monitor soil moisture

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.; Bradley, G. A.; Dobson, M. C.

    1981-01-01

    The microwave backscattering characteristics of soils as a function of moisture content are reviewed as a basis for the evaluation of the applicability of satellite radar to soil moisture determinations. Results of experiments showing the dependence of the complex dielectric constant, power reflection coefficient and backscattering coefficient of soil on its volumetric moisture content are presented. Results of a research program using the truck-mounted University of Kansas microwave active spectrometer to determine if, by the proper choice of sensor frequency, polarization and incidence, the sensor dynamic range in response to moisture variations may be greater than its response to other variations are considered in detail, and the optimum conditions of frequency (between 4 and 5 GHz), angular incidence (between 7 and 20 deg from nadir) and polarization (HH) obtained are indicated. An empirical model for the backscattering coefficient as a function of gravimetric moisture content derived on the basis of the experimental data is presented, and it is noted that available airborne and spaceborne data confirm the results of the ground-based sensors.

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

    NASA Astrophysics Data System (ADS)

    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 in order to ensure consistency between both instruments. The corresponding soil moisture retrievals from AMSR-E and AMSR2 demonstrated reasonable agreement relative to in situ data. A detailed discussion that focuses on this analysis as well as possible approaches for removing the observed bias in the brightness temperature observations will be presented.

  3. Evaluation of an agro--ecosystem model using cosmicray neutron soil moisture

    NASA Astrophysics Data System (ADS)

    Carr, Benjamin David

    The properties of the land surface affect the interaction of the surface and the atmosphere. The partitioning of absorbed shortwave radiation into emitted radiation, sensible heat flux, latent heat flux, and soil heat flux is determined by the presence of soil moisture. When the land surface is dry, there will be higher sensible heat flux, emitted radiation and soil heat flux. However, when liquid water is present, latent energy will be used to change the phase of water from solid to liquid and liquid to gas. This latent heat flux moves water and energy to a different part of the atmosphere. A contributing factor to soil moisture available for latent heat flux is the water table. With a shallow water table (< 5 m), plant roots are able to extract water for growth and generally an increase in latent heat flux is seen. In the Midwest U.S., the management of fields changes the latent heat flux through different crop choices, planting and harvest date, fertilizer application, and tile drainage. Therefore, land surface models, like Agro--IBIS, need to be simulated and evaluated at the field--scale. Agro--IBIS is an agroecosystem model that is able to incorporate changes in vegetation growth as well as management practices, which in turn impact soil moisture available for latent heat flux. Agro--IBIS has been updated with the soil physics of HYDRUS--1D in order to accurately simulate the impact of the water table. In measuring soil moisture, a consistent challenge is the representative scale of the instrument, which is often a point. A newer method of obtaining soil moisture over the field--scale is using a cosmic--ray neutron detector, which is sensitive to a diameter of 700 m and to a depth of ˜ 20 cm. I used soil moisture observed by the cosmic--ray neutron detector in an agricultural field to evaluate estimates made with the Agro--IBIS model over a growing season of maize and a growing season of soybean. Because of the large area observed by the cosmic-ray neutron detector, a soil texture sensitivity analysis was performed using Agro--IBIS to determine the texture that would produce the best hydraulic properties and therefore the best estimate of soil moisture. The maize year results show Agro--IBIS with silt loam soil texture with a RMSE of 0.037 cm3 cm-33 and bias of -0.02 cm3 cm3 cm--3 and the updated Agro--IBIS (AgroIBIS--VSF) had a RMSE of 0.033 cm3 cm--3 and bias of -0:006 cm3 cm-3 compared to the cosmic--ray neutron soil moisture. In the soybean year, sandy clay loam with Agro--IBIS had a RMSE of 0.028 cm3 cm --3 and bias of -0.014 cm3 cm--3 and AgroIBIS--VSF had a RMSE of 0.028 cm3 cm --3 and bias of 0.023 cm3 cm--3. These low values for RMSE and bias demonstrate that the models are in good agreement with the field--scale observation of soil moisture for the growing season in 2011 (maize) and 2012 (soybean). Adding a water table did not improve AgroIBIS--VSF's accuracy against the observed cosmic--ray neutron soil moisture in the top 20 cm, except with the sandy clay loam soil texture simulations. The original version of Agro--IBIS conserved water to within 1% of total precipitation, but the water balance for AgroIBIS--VSF lost close to 10%. Both the original and new version of Agro--IBIS performed poorly during the 2012 drought year as shown by their inconsistency with observed yield and the change in soil moisture storage, as well as expected LAI and canopy height.

  4. Inferring soil moisture and vegetation parameters from airborne and spaceborne radar data

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

    Most of the emphasis in active remote sensing of soil moisture has focused on higher resolution SAR data. We critically examine the existing soil moisture algorithms, and compare the performance of the different algorithms.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  6. Modeling and application of soil moisture at varying spatial scales with parameter scaling

    E-print Network

    Das, Narendra Narayan

    2009-05-15

    The dissertation focuses on characterization of subpixel variability within a satellite-based remotely sensed coarse-scale soil moisture footprint. The underlying heterogeneity of coarse-scale soil moisture footprint is masked by the area...

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

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1975-01-01

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

  8. Comparative analysis of drought based on precipitation and soil moisture indices in Haihe basin of North China during the period of 1960-2010

    NASA Astrophysics Data System (ADS)

    Qin, Yue; Yang, Dawen; Lei, Huimin; Xu, Kai; Xu, Xiangyu

    2015-07-01

    Drought severity not only depends on weather anomaly, but is also related to terrestrial hydrological condition to a large extent. In this study, we analyzed droughts using indices based on precipitation and soil moisture during the period of 1960-2010 in Haihe basin, which is a typical drought-prone region in North China. The Soil Moisture Drought Severity (SMDS) and Standardized Precipitation Index (SPI) are used to evaluate drought severity. SMDS is calculated based on the monthly soil moisture of upper 50 cm from the simulation by Community Land Model (CLM 4.0) and SPI is calculated based on gridded precipitation at 0.05° resolution (5 km × 5 km approximately), which is spatially interpolated from observations. During the last 51 years, 36 severe drought events (affecting areas greater than 20,000 km2 and durations longer than 3 months) have been identified based on SMDS, and 41 drought events identified based on SPI. Results derived from SMDS indicate that there is a significant increasing trend in the drought affected area, and that the drought event occurred in 1999 has the largest affected area. Compared with the drought events derived from SMDS, the events derived from SPI have shorter durations but larger affected areas on average. Although the mean NDVI of the whole basin has been increasing since the 1980s, the two declining periods of 1992-1994 and 1999-2003 show fairly good agreement with the drought events identified in the same periods. The Anomaly of Normalized Difference Vegetation Index (A-NDVI) is introduced as NDVI anomaly from its trend line, thus the negative value of A-NDVI can reflect the drought impact on vegetation reasonably. Result indicates that both the SMDS and SPI are significantly correlated with A-NDVI, and correlation between annual SMDS and A-NDVI is higher than that of SPI.

  9. Effects of roughness on the radar response to soil moisture of bare ground

    NASA Technical Reports Server (NTRS)

    Batlivala, P. P.; Ulaby, F. T.

    1975-01-01

    The radar response to soil moisture content was experimentally determined for three different bare fields with considerably different surface roughnesses at eight frequencies in the 2 to 8 GHz band and for Horizontal transmit-Horizontal receive (HH) and Vertical transmit-Vertical receive (VV) polarizations. Analysis of the data indicated that the effect of roughness on the radar backscattering coefficient can be minimized by proper choice of the radar parameters. If, in addition, sensitivity to soil moisture variations and system design constraints are considered, the following radar parameters for an operational soil moisture mapper are recommended: frequency= 4 GHz, angle of incidence range= 7 deg to 15 deg and either HH or VV polarization. The corresponding sensitivity is about 0.25 db/ 0.01 gram/cubic cm.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  11. Soil Moisture and Vegetation Effects on GPS Reflectivity From Land

    NASA Astrophysics Data System (ADS)

    Torres, O.; Grant, M. S.; Bosch, D.

    2004-12-01

    While originally designed as a navigation system, the GPS signal has been used to achieve a number of useful scientific measurements. One of these measurements utilizes the reflection of the GPS signal from land to determine soil moisture. The study of GPS reflections is based on a bistatic configuration that utilizes forward reflection from the surface. The strength of the GPS signal varies in proportion to surface parameters such as soil moisture, soil type, vegetation cover, and topography. This paper focuses on the effects of soil water content and vegetation cover on the surface based around a reflectivity. A two-part method for calibrating the GPS reflectivity was developed that permits the comparison of the data with surface parameters. The first part of the method relieves the direct signal from any multipath effects, the second part is an over-water calibration that yields a reflectivity independent of the transmitting satellite. The sensitivity of the GPS signal to water in the soil is shown by presenting the increase in reflectivity after rain as compared to before rain. The effect of vegetation on the reflected signal is also presented by the inclusion of leaf area index as a fading parameter in the reflected signal from corn and soy bean fields. The results are compared to extensive surface measurements made as part of the Soil Moisture Experiment 2002 (SMEX 2002) in Iowa and SMEX 2003 in Georgia.

  12. TRMM Microwave Imager soil moisture mapping and flooding during CLASIC

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Passive microwave remote sensing has the potential to contribute to flood risk and impact assessment through the direct relationship between emissivity and soil moisture/standing water. Lower frequencies have greater potential because the impacts of atmospheric and vegetation attenuation are minimiz...

  13. Combined Passive Active Soil Moisture Observations During CLASIC

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An important issue in advancing higher spatial resolution and better accuracy in soil moisture remote sensing is the integration of active and passive observations. In an effort to address these questions an airborne passive/active L-band system (PALS) was flown as part of CLASIC in Oklahoma over th...

  14. Introduction to Soil Moisture Experiments 2004 (SMEX04)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Land surface antecedent boundary conditions may control the onset and intensity of the summer monsoon rainfall in the southwestern U.S. and northern Mexico. The influence of the land surface is relayed through surface evaporation and associated surface cooling (dependent on soil moisture), terrain, ...

  15. ESTIMATION OF GROUND WATER RECHARGE USING SOIL MOISTURE BALANCE APPROACH

    E-print Network

    Kumar, C.P.

    ESTIMATION OF GROUND WATER RECHARGE USING SOIL MOISTURE BALANCE APPROACH C. P. Kumar* ABSTRACT The amount of water that may be extracted from an aquifer without causing depletion is primarily dependent upon the ground water recharge. Thus, a quantitative evaluation of spatial and temporal distribution

  16. A comparison of soil moisture sensors for space flight applications

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  17. The soil moisture active passive (SMAP) mission and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) satellite will be launched by the National Aeronautics and Space Administration in October 2014. This satellite is the culmination of basic research and applications development over the past thirty years. During most of this period, research and development o...

  18. WindSat Global Soil Moisture Retrieval and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A physically based six-channel land algorithm is developed to simultaneously retrieve the global soil moisture, vegetation water content and land surface temperature. The algorithm is based on a maximum-likelihood estimation and uses WindSat passive microwave data at 10, 18.7 and 37 GHz. The global ...

  19. Overview of the NASA soil moisture active/passive mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active Passive (SMAP) Mission is currently in design Phase C and scheduled for launch in October 2014. Its mission concept is based on combined L-band radar and radiometry measurements obtained from a shared, rotating 6-meter antennae. These measurements will be used to retrie...

  20. Using microwave radar for soil moisture inversion under soybean canopies

    Microsoft Academic Search

    Roger D. De Roo; Fawwaz T. Ulaby; M. Craig Dobson

    1998-01-01

    The successful radar mapping of soil moisture under vegetation canopies would be a boon to agriculture, global climate change studies, water resource management and other areas. Toward this end, a series of polarimetric radar measurements of soybeans over the entire growing season of 1996 were made at L and C-band at the Long Term Ecological Research site at the Kellogg

  1. Active Radar Soil Moisture Products for Water use Efficiency Estimation

    Microsoft Academic Search

    M. Doubkova; W. Wagner; C. Kuenzer; Z. Bartalis; S. Hasenauer

    2007-01-01

    The protection of water resources becomes more important with the increasing number of climate hazards. In order to protect water resources we have to fully understand the relationships between carbon and hydrological cycles and how these alter with increasing frequency of climate hazards. Numerous methods have been developed in order to monitor absorbed carbon, evapotranspiration, and soil moisture. Here, methods

  2. Initializing a regional climate model with satellite-derived soil moisture

    Microsoft Academic Search

    B. Bisselink; E. van Meijgaard; A. J. Dolman; R. A. M. de Jeu

    2011-01-01

    Regional climate simulations over Europe were initialized with soil moisture derived from the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) in order to assess the model accuracy in predicting soil moisture and other components of the hydrological cycle. The AMSR-E soil moisture initially showed systematic differences with model-predicted soil moisture. For proper initialization the AMSR-E product had to be rescaled

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

    The Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the AMSR-E provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated AMSR-E channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the AMSR-E soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of AMSR-E derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European Centre for Medium-Range Weather Forecasts. The results of this research will contribute to a better characterization of the low biases and discrepancies currently observed in the AMSR-E soil moisture product.

  4. Radon diffusion coefficients in soils of varying moisture content

    NASA Astrophysics Data System (ADS)

    Papachristodoulou, C.; Ioannides, K.; Pavlides, S.

    2009-04-01

    Radon is a naturally occurring radioactive gas that is generated in the Earth's crust and is free to migrate through soil and be released to the atmosphere. Due to its unique properties, soil gas radon has been established as a powerful tracer used for a variety of purposes, such as exploring uranium ores, locating geothermal resources and hydrocarbon deposits, mapping geological faults, predicting seismic activity or volcanic eruptions and testing atmospheric transport models. Much attention has also been given to the radiological health hazard posed by increased radon concentrations in the living and working environment. In order to exploit radon profiles for geophysical purposes and also to predict its entry indoors, it is necessary to study its transport through soils. Among other factors, the importance of soil moisture in such studies has been largely highlighted and it is widely accepted that any measurement of radon transport parameters should be accompanied by a measurement of the soil moisture content. In principle, validation of transport models in the field is encountered by a large number of uncontrollable and varying parameters; laboratory methods are therefore preferred, allowing for experiments to be conducted under well-specified and uniform conditions. In this work, a laboratory technique has been applied for studying the effect of soil moisture content on radon diffusion. A vertical diffusion chamber was employed, in which radon was produced from a 226Ra source, was allowed to diffuse through a soil column and was finally monitored using a silicon surface barrier detector. By solving the steady-state radon diffusion equation, diffusion coefficients (D) were determined for soil samples of varying moisture content (m), from null (m=0) to saturation (m=1). For dry soil, a D value of 4.1×10-7 m2s-1 was determined, which increased moderately by a factor of ~3 for soil with low moisture content, i.e. up to m ~0.2. At higher water fractions, a decrease in D was initiated and became particularly pronounced approaching complete saturation; at m =0.9, D was as low as 2×10-9 m2s-1. A series of field experiments has also been conducted using alpha-track CR-39 detectors to follow the moisture-dependence of radon diffusion through soil under natural conditions. Diffusion coefficients were determined as a function of surface soil moisture assuming a one-dimensional diffusive radon transport model. Comparison between results obtained by the two methods showed that laboratory studies may provide a good indication of radon diffusion coefficients to be expected in the field. However, values determined in the field were systematically lower than those assessed in the laboratory. This finding could be attributed to soil-dependent parameters, such as differences in pore space geometry between the soil used in laboratory experiments and the undisturbed soil. In the latter case, the higher degree of compaction imposes a more tortuous pathway to soil gas, while at the same time the diffusive gas flux is hindered by local-scale zones of higher bulk density or water content.

  5. The COsmic-ray Soil Moisture Observing System (COSMOS): a non-invasive, intermediate scale soil moisture measurement network

    NASA Astrophysics Data System (ADS)

    Zreda, Marek; Shuttleworth, W. James; Zweck, Chris; Zeng, Xubin; Ferre, Ty

    2010-05-01

    Soil moisture at a horizontal scale of ca. 600 m averaged over depths of 15-70 cm can be inferred from measurements of cosmic-ray neutrons that are generated within air and soil, moderated mainly by hydrogen atoms in the soil, and emitted back to the atmosphere where they are measured. These neutrons are sensitive to water content changes, largely insensitive to soil chemistry, and their intensity is inversely correlated with hydrogen content of the soil. The measurement with a neutron detector placed above the ground takes minutes to hours, permitting high-resolution, long-term monitoring of undisturbed soil moisture. The ability to provide non-invasive, precise, rapid and continuous measurements over a large footprint make the method suitable for calibration and validation (cal/val) of satellite microwave instruments, such as SMOS and SMAP. We envision three types of cal/val activities. In the first, multiple probes would be installed over the satellite microwave footprint to provide average soil moisture continuously. Given the disparity between the microwave footprint (40 km) and the cosmic-ray footprint (0.6 km), this approach would require a large number of probes, and may be too expensive. The second approach would use a smaller number of stationary probes that would be relocated every hour or so, or probes mounted on moving vehicles, to cover a microwave pixel within a short time. This approach would provide snapshots of soil moisture rather than continuous coverage, but would require a small number of probes and be inexpensive. The third approach would utilize the COsmic-ray Soil Moisture Observing System (COSMOS), which comprises initially a network of 50 probes (to provide a proof of concept) and subsequently 500 probes distributed across the contiguous USA. Additional COSMOS probes are also being deployed on an experimental basis in Australia, Europe, and China. SMOS data could be compared with the changing spatio-temporal pattern of continental soil moisture as sampled by initially 50, subsequently 500 COSMOS probes, ultimately providing a continental scale validation mechanism.

  6. Is Europe getting dryer? Soil moisture depletion observed from GRACE

    NASA Astrophysics Data System (ADS)

    Andersen, O. B.; Hinderer, J.; Linage, C. D.

    2006-12-01

    One of the most poorly observed components of the climate system is continental-scale water storage and its variations on annual to inter-annual scales. Indeed, available ground observations are generally of very small spatial or temporal scope and models driven with observed forcing seldom agree on simulated terrestrial water storage. GRACE has the capability of detecting mean seasonal variations of terrestrial water storage for large river basins like Europe. We will demonstrate here the skill of GRACE data in detecting inter-annual variability in terrestrial water storage by jointly analyzing observations from GRACE compared with hydrological model to asses the accuracy of the observations. We will also include gravity field variations from in situ observations by the GGP stations in Europe, and asses the accuracy by combining with observations from hydrological models. During 2002-2005 GRACE observes overall soil moisture depletion in Europe peaking during the heat wave in 2003. In order to validate and access local conditions the water storage changes are corroborated with indirect estimates of soil water changes based on atmospheric analysis and with in-situ observations of gravity changes using super-conducting gravimeters in Europe

  7. Online Vegetation Parameter Estimation in Passive Microwave Regime for Soil Moisture Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing observations in the passive microwave regime can be used to estimate surface soil moisture over land at global and regional scales. Soil moisture is important to applications such as weather forecasting, climate and agriculture. One approach to estimating soil moisture from remote sen...

  8. Evaluation of SMOS Soil Moisture products over continental US using the SCAN/SNOTEL network

    E-print Network

    Boyer, Edmond

    ) satellite has opened the era of soil moisture products from passive L-Band observations. In this study, but differences are observed over many sites and need to be addressed. Index Terms--microwave, soil moisture,L-Band results [11]. Many studies have showed the utility of passive L-Band observation for soil moisture ([12

  9. Circular Polarization for L-band Radiometric Soil Moisture Roger D. De Roo, Anthony W. England

    E-print Network

    De Roo, Roger

    Circular Polarization for L-band Radiometric Soil Moisture Retrieval Roger D. De Roo, Anthony W retrievals of surface soil moisture at L-band, the preferred polarization is hori- zontal polarization, because it has higher sensitivity to the soil moisture than does vertical polarization. However, L- band

  10. Calibration and validation of the COSMOS rover for surface soil moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...

  11. On the comparison between the LISFLOOD modelled and the ERS\\/SCAT derived soil moisture estimates

    Microsoft Academic Search

    G. Laguardia; S. Niemeyer

    2008-01-01

    In order to evaluate the reliability of the soil moisture product obtained by means of the LISFLOOD hydrological model (De Roo et al., 2000), we compare it to soil moisture estimates derived from ERS scatterometer data (Wagner et al., 1999). Once calculated the root mean square error and the correlation between the two soil moisture time series on a pixel

  12. In situ validation issues in the soil moisture active passive (SMAP) satellite mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    SMAP is a new NASA mission scheduled for 2014 that will provide a number of soil moisture and freeze/thaw products. The soil moisture products will span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data fr...

  13. In situ validation of the soil moisture active passive (SMAP) satellite mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    SMAP is a new NASA mission proposed for 2014 that would provide a number of soil moisture and freeze/thaw products. The soil moisture products span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data from th...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

  16. Survival of endophytic diazotrophic bacteria in soil under different moisture levels

    Microsoft Academic Search

    André L. M. Oliveira; Erineudo L. Canuto; Edmilson E. Silva; Veronica M. Reis; José I. Baldani

    2004-01-01

    The effects of soil moisture on the survival of three diazotrophic bacteria species (Azospirillum amazonense, Gluconacetobacter diazotrophicus and Azospirillum brasilense) were tested. Soil moisture had little influence on the survival of A. brasilense, which is considered a free-living species. On the other hand, increased soil moisture extended the survival of the endophytes A. amazonense and G. diazotrophicus. These results indicate

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. An analytical method for predicting surface soil moisture from rainfall observations

    E-print Network

    Pan, Feifei

    .g., Hornberger et al., 2001; Houser, 1996]. The important roles of soil moisture in Earth system dynamics include, irrigation, pest detection and control are all related to soil moisture information [e.g., Dinar et al., 1986 and forest fire prediction; (5) civil engineering, where soil moisture is useful in hazardous

  19. GROUND-BASED SOIL MOISTURE OBSERVATIONS WITHIN SATELLITE FOOTPRINTS DURING SMEX02

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Experiment 2002 (SMEX02) was held in a 50 km by 100 km region surrounding Ames, Iowa, USA, between June 24 and July 12, 2002. The experiment had several objectives, including aircraft testing of new soil moisture sensor technologies, extension of soil moisture inversion algorithms ...

  20. Canadian experiment for soil moisture in 2010 (CanEx-SM10): Overview and preliminary results

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to the Soil Moisture and Ocean Salinity (SMOS) mission validation and the pre-launch assessment of the proposed Soil Moisture and ...

  1. Soil moisture estimation using WindSat based passive microwave polarimetric observations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Global soil moisture estimates are critical to study its role in weather and climate. Microwave remote sensing is the most feasible technique for large-scale soil moisture observations. Efforts have been made towards the goal of obtaining accurate satellite-based soil moisture products. Low frequenc...

  2. Dry-end surface soil moisture variability during NAFE'06 A. J. Teuling,1,2

    E-print Network

    Walker, Jeff

    of the surface soil moisture field can lead to improved sampling, retrieval, validation, and downscaling. [3Dry-end surface soil moisture variability during NAFE'06 A. J. Teuling,1,2 R. Uijlenhoet,1 R-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical

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

    Microsoft Academic Search

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

    2010-01-01

    Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However,

  4. Scaling characteristics of spatial patterns of soil moisture from distributed modelling

    Microsoft Academic Search

    Salvatore Manfreda; Matthew F. McCabe; Mauro Fiorentino; Ignacio Rodríguez-Iturbe; Eric F. Wood

    2007-01-01

    Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the

  5. Catchment Monitoring for Scaling and Assimilation of Soil Moisture and Streamflow

    E-print Network

    Walker, Jeff

    component includes the validation of remotely sensed near-surface soil moisture data (25km 25km spatial in areas of low vegetation. Keywords: Soil moisture; Streamflow; Data assimilation; Remote Sensing; Scaling that drive temporal and spatial variability in soil moisture. Satellite remote sensing offers some potential

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

    Microsoft Academic Search

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

    2010-01-01

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

  7. A new Multi-Scale Data Assimilation Algorithm to Downscale Satellite-Based Soil Moisture Data

    Microsoft Academic Search

    N. N. Das; B. P. Mohanty; Y. Efendiev

    2008-01-01

    The study focuses on downscaling of soil moisture from coarse remote sensing footprints to finer scales. Two approaches are proposed for soil moisture downscaling. The first approach provides the probability distribution functions at the finer scales with no information about the spatial organization of soil moisture fields. The second approach implements a multiscale ensemble Kalman filter (EnKF) that assimilates remotely

  8. An improved algorithm for disaggregating microwave-derived soil moisture based on red,

    E-print Network

    Boyer, Edmond

    , the resolution at which current and near-future remotely sensed soil moisture data are avail- able is in general of 0.012 vol./vol.. Key words: disaggregation, downscaling, soil moisture, evaporation, nonlinear, SMOSAn improved algorithm for disaggregating microwave-derived soil moisture based on red, near

  9. The potential of assimilating remotely sensed soil moisture into land surface models

    Microsoft Academic Search

    H. Gao; M. Pan; E. F. Wood; C. D. Michele

    2004-01-01

    Assimilation of remote sensing data into hydrological modeling has the potential to improve forecasting accuracy; with space-borne, low frequency microwave observations being especially interesting because of its sensitivity to surface soil moisture and its change. However, in conveying the soil moisture information to land surface models, both the brightness temperature and the retrieved soil moisture product suffer from errors introduced

  10. SMOS/SMAP synergy for SMAP level 2 soil moisture algorithm evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil Moisture Active Passive (SMAP)satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the sup...

  11. The SMAP In Situ Soil Moisture Sensor Testbed: Comparing in situ sensors for satellite validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One of the most valuable tools in validating satellite based soil moisture estimates, such as those from the Soil Moisture Active Passive (SMAP) mission are large scale in situ networks. Global validation involves networks operated by many different organizations. Existing in situ soil moisture netw...

  12. Evaluation of Hyperspectral, Infrared Temperature and Radar Measurements for Monitoring Surface Soil Moisture

    Microsoft Academic Search

    Ross Bryant; David Thoma; Susan Moran; Chandra Holifield; David Goodrich; Tim Keefer; Ginger Paige

    Remote sensing techniques for monitoring soil moisture were tested by comparing hyperspectral reflectance and spectral indexes; surface temperature (Ts) and thermal indexes; and normalized radar backscatter to soil moisture. A laboratory study indicated that hyperspectral reflectance and Ts were sensitive to surface soil moisture (r2 range from 0.72

  13. Radar based surface soil moisture retrieval through the combined use of two backscattering models

    Microsoft Academic Search

    Jesús Álvarez-Mozos; Niko E. C. Verhoest; Javier Casali; María González-Audícana

    2005-01-01

    Radar based surface soil moisture retrieval has been subject of intense research during the last decades. However, several difficulties hamper the operational estimation of soil moisture based on actually available space borne sensors. The main difficulty experienced so far consists of the parameterization of other surface characteristics, mainly roughness, which strongly influences the backscattering coefficient and harms the soil moisture

  14. The objectives and rationale of the Soil Moisture and Ocean Salinity (SMOS) mission

    Microsoft Academic Search

    Yann H. Kerr; Philippe Waldteufel; Jean-Pierre Wigneron; M. Berger

    2001-01-01

    This paper will describe the SMOS concept in terms of instrument (characteristics) investigates the main aspects of the retrieval capabilities of the 2D microwave interferometer for monitoring soil moisture, vegetation biomass and surface temperature. The analysis is based on model inversion taking into account the instrument characteristics. The standard error of estimate of the surface variables is computed as a

  15. Applications of remote sensing and GIS in surface hydrology: Snow cover, soil moisture and precipitation

    Microsoft Academic Search

    Xianwei Wang

    2008-01-01

    Studies on surface hydrology can generally be classified into two categories, observation for different components of surface water, and modeling their dynamic movements. This study only focuses on observation part of surface water components: snow cover, soil moisture, and precipitation. Moreover, instead of discussion on the detailed algorithm and instrument technique behind each component, this dissertation pours efforts on analysis

  16. Continental-Scale Evaluation of Assimilated Soil Moisture Retrievals From the Advanced Microwave Scanning Radiometer

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is a fundamental data source used in crop growth stage and crop stress models developed by the USDA Foreign Agriculture Service for global crop estimation. USDA’s International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA). Currently, the PECAD DSS utiliz...

  17. Effects of roughness on the radar response to soil moisture of bare ground

    Microsoft Academic Search

    P. P. Batlivala; F. T. Ulaby

    1975-01-01

    The radar response to soil moisture content was experimentally determined for three different bare fields with considerably different surface roughnesses at eight frequencies in the 2 to 8 GHz band and for Horizontal transmit-Horizontal receive (HH) and Vertical transmit-Vertical receive (VV) polarizations. Analysis of the data indicated that the effect of roughness on the radar backscattering coefficient can be minimized

  18. Sensitivity of the radar signal to soil moisture: variation with incidence angle, frequency, and polarization

    Microsoft Academic Search

    I. Champion; R. Faivre

    1997-01-01

    This study focuses on the variations of the radar sensitivity to soil moisture (d?o\\/dmυ) with the radar configuration parameters (frequency, polarization, and angle). An analysis of variance shows that only the polarization significantly influences d?o\\/dmυ, which is larger at cross-polarization than at like-polarized configurations

  19. Is the PDO or AMO the climate driver of soil moisture in the Salmon River Basin, Idaho?

    NASA Astrophysics Data System (ADS)

    Tang, Chunling; Chen, Dong; Crosby, Benjamin T.; Piechota, Thomas C.; Wheaton, Joseph M.

    2014-09-01

    Current droughts and increasing water demands are straining water resources in the Salmon River Basin (SRB) and are anticipated to continue in the future. As a robust drought indictor, soil moisture plays an important role in characterizing prolonged droughts. The current study investigates the impacts of two oceanic-atmospheric patterns, i.e. the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO), on soil moisture and identify the most complete driver (PDO/AMO) of soil moisture in the SRB. Using wavelet analysis tools, we found that: 1) soil moisture in both Stanley station (a snow-dominated region) and White Bird station (a rain-dominated region) in the SRB are linked to the variations of the PDO and AMO; 2) both the PDO and AMO have less significant impacts on soil moisture in Stanley station; and 3) the PDO produces, with respect to AMO, a stronger correlation with soil moisture in the SRB. Given the importance of the soil moisture to the drought, the results could allow an estimation of drought availability under forecasted oceanic-atmospheric patterns, which will provide useful information for water resources management in the SRB.

  20. Zinc movement in sewage-sludge-treated soils as influenced by soil properties, irrigation water quality, and soil moisture level

    USGS Publications Warehouse

    Welch, J.E.; Lund, L.J.

    1989-01-01

    A soil column study was conducted to assess the movement of Zn in sewage-sludge-amended soils. Varables investigated were soil properties, irrigation water quality, and soil moisture level. Bulk samples of the surface layer of six soil series were packed into columns, 10.2 cm in diameter and 110 cm in length. An anaerobically digested municipal sewage sludge was incorporated into the top 20 cm of each column at a rate of 300 mg ha-1. The columns were maintained at moisture levels of saturation and unsaturation and were leached with two waters of different quality. At the termination of leaching, the columns were cut open and the soil was sectioned and analyzed. Zinc movement was evaluated by mass balance accounting and correlation and regression analysis. Zinc movement in the unsaturated columns ranged from 3 to 30 cm, with a mean of 10 cm. The difference in irrigation water quality did not have an effect on Zn movement. Most of the Zn applied to the unsaturated columns remained in the sludge-amended soil layer (96.1 to 99.6%, with a mean of 98.1%). The major portion of Zn leached from the sludge-amended soil layer accumulated in the 0- to 3-cm depth (35.7 to 100%, with a mean of 73.6%). The mean final soil pH values decreased in the order: saturated columns = sludge-amended soil layer > untreated soils > unsaturated columns. Total Zn leached from the sludge-amended soil layer was correlated negatively at P = 0.001 with final pH (r = -0.85). Depth of Zn movement was correlated negatively at P = 0.001 with final pH (r = -0.91). Multiple linear regression analysis showed that the final pH accounted for 72% of the variation in the total amounts of Zn leached from the sludge-amended soil layer of the unsaturated columns and accounted for 82% of the variation in the depth of Zn movement among the unsaturated columns. A significant correlation was not found between Zn and organic carbon in soil solutions, but a negative correlation significant at P = 0.001 was found between pH and Zn (r = -0.61).

  1. SOIL MOISTURE NEUTRON PROBE CALIBRATION AND USE IN FIVE SOILS OF UZBEKISTAN

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The soil moisture neutron probe (SMNP) is a key tool in measurements of crop water use, necessary for accurate irrigation and minimization of salinization; but it is not useful in all soils. We showed that the SMNP could be accurately field calibrated at five locations in Uzbekistan, in soils rangin...

  2. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions ? i.e., Brooks and Corey (1964) (BC), Campbell (19...

  3. Dielectric properties of soils as a function of moisture content

    NASA Technical Reports Server (NTRS)

    Cihlar, J.; Ulaby, F. T.

    1974-01-01

    Soil dielectric constant measurements are reviewed and the dependence of the dielectric constant on various soil parameters is determined. Moisture content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as soil dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric soil water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three soil textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and soil texture.

  4. Influence of radar frequency on the relationship between bare surface soil moisture vertical profile and radar backscatter

    E-print Network

    Paris-Sud XI, Université de

    Influence of radar frequency on the relationship between bare surface soil moisture vertical on the relationship between surface soil moisture and the nature of radar backscatter over bare soils. In an attempt the operational use of radar signals for the estimation of soil moisture. In this context, when the soil moisture

  5. Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio

    NASA Astrophysics Data System (ADS)

    Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J.

    2014-12-01

    Urban impervious surfaces lead to increases in stormwater runoff. Green infrastructure, like bioretention cells, is being used to mitigate negative impacts of runoff by disconnecting impervious surfaces from storm water systems and redirecting flow to decentralized treatment areas. While bioretention soil characteristics are carefully designed, little research is available on soil moisture dynamics within the cells and how these might relate to inter-storm variability in performance. Bioretentions have been installed along a residential street in Parma, Ohio to determine the impact of green infrastructure on the West Creek watershed, a 36 km2 subwatershed of the Cuyahoga River. Bioretentions were installed in two phases (Phase I in 2013 and Phase II in 2014); design and vegetation density vary slightly between the two phases. Our research focuses on characterizing soil moisture dynamics of multiple bioretentions and assessing their impact on stormwater runoff at the street scale. Soil moisture measurements were collected in transects for eight bioretentions over the course of one summer. Vegetation indices of canopy height, percent vegetative cover, species richness and NDVI were also measured. A flow meter in the storm drain at the end of the street measured storm sewer discharge. Precipitation was recorded from a meteorological station 2 km from the research site. Soil moisture increased in response to precipitation and decreased to relatively stable conditions within 3 days following a rain event. Phase II bioretentions exhibited greater soil moisture and less vegetation than Phase I bioretentions, though the relationship between soil moisture and vegetative cover is inconclusive for bioretentions constructed in the same phase. Data from five storms suggest that pre-event soil moisture does not control the runoff-to-rainfall ratio, which we use as a measure of bioretention performance. However, discharge data indicate that hydrograph characteristics, such as lag time and peak flow, are altered relative to a control street. This analysis suggests that street-scale implementation of bioretention can reduce the impact of impervious surface on stormflows, but more information is needed to fully understand how soil moisture of the bioretentions affects inter-storm variability in performance.

  6. Root Zone Soil Moisture Assessment Using Passive Microwave Remote Sensing and Distributed Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Das, N. N.; Mohanty, B.

    2004-12-01

    Soil moisture is a fundamental state variable and it varies spatially due to topography, soil, precipitation variability and landuse-landcover, and temporally, due to difference in hydrologic characteristics and controls. Estimation of profile soil moisture using remotely sensed land surface moisture data with the combination of forward soil hydrologic modeling is very promising. This integrated method may become resourceful solution to the problem for profile soil moisture estimation and its transient behavior. In a preliminary attempt to understand soil moisture land surface dynamics, an effort is being made to assess soil moisture on the watershed scale. A method has been implemented to combine hydrologic model and passive microwave land surface soil moisture observation to predict root zone soil moisture. The prime focus of this work is to combine HYDRUS-1D model with Soil Survey Geographic (SSURGO) Database (30 x 30 meters), NEXRAD based precipitation, LANDSAT7 landcover classification and ESTAR derived surface soil moisture in a GIS platform. We applied and tested this integrated approach in the Little Washita watershed during SGP97 using ground and remotely sensed data set for a month period. The integrated model facilitates to identify the critical parameters that control the spatio-temporal variability of the soil moisture fields and a good assessment of soil moisture in the root zone.

  7. A hydrometeorological approach for probabilistic simulation of monthly soil moisture under bare and crop land conditions

    NASA Astrophysics Data System (ADS)

    Das, Sarit Kumar; Maity, Rajib

    2015-04-01

    This study focuses on the probabilistic estimation of monthly soil moisture variation by considering (a) the influence of hydrometeorological forcing to model the temporal variation and (b) the information of Hydrological Soil Groups (HSGs) and Agro-Climatic Zones (ACZs) to capture the spatial variation. The innovative contributions of this study are: (i) development of a Combined Hydro-Meteorological (CHM) index to extract the information of different influencing hydrometeorological variables, (ii) consideration of soil-hydrologic characteristics (through HSGs) and climate regime-based zoning for agriculture (through ACZs), and (iii) quantification of uncertainty range of the estimated soil moisture. Usage of Supervised Principal Component Analysis (SPCA) in the development of the CHM index helps to eliminate the "curse of dimensionality," typically arises in the multivariate analysis. The usage of SPCA also ensures the maximum possible association between the developed CHM index and soil moisture variation. The association between these variables is modeled through their joint distribution which is obtained by using the theory of copula. The proposed approach is also spatially transferable, since the information on HSGs and ACZs is considered. The "leave-one-out" cross-validation (LOO-CV) approach is adopted for stations belong to a particular HSG to examine the spatial transferability. The simulated soil moisture values are also compared with a few existing soil moisture data sets, derived from different Land Surface Models (LSMs) or retrieved from different satellite-based missions. The potential of the proposed approach is found to be promising and even applicable to crop land also, though with a lesser degree of efficiency as compared to bare land conditions.

  8. The Potential of Remotely Sensed Evapotranspiration and Soil Moisture Retrievals in Calibrating Land Surface Models

    NASA Astrophysics Data System (ADS)

    Ryu, D.; Kunnath Poovakka, A.; Renzullo, L. J.; George, B.

    2014-12-01

    Model calibration is frequently limited by the availability, quality, quantity and the nature of ground observations. Remotely sensed soil moisture and evapotranspiration (ET) provide an alternative source of hydrological information to inform models. In this study, microwave soil moisture retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily estimates of ET from CSIRO MODIS ReScaled potential ET (CMRSET) model are adopted to calibrate a land surface model using 15 different objective functions considering various combinations of bias and correlation of ET and soil moisture. The Shuffled Complex Evolution (SCE) calibration algorithm is used to calibrate a grid-based land surface model modified from the Australian Water Resource Assessment - Landscape (AWRA-L) model. The study catchments are located in south Australia with ground observations of ET and soil moisture for validation. Parameters for calibration are selected based on the results from variance-based Sobols' sensitivity analysis. The efficacy of each calibration is assessed mainly based on the streamflow predictability of the calibrated model. Calibration schemes with a greater emphasis on ET provide good estimates of ET but the streamflow predictions are comparatively poor. It is found that the streamflow predictions improve when higher importance is given to soil moisture derived objective functions. The optimized parameter values exhibit wide variations for different objective functions even though they provide similar values for streamflow, ET and soil moisture. Lastly, we discuss about the reasons for poor performance of the ET-based calibration and the impact of physical properties of the catchment on the calibration. This study has important implications to the optimal use of remotely sensed observations for hydrological modeling at large catchments with sparse or no gauging.

  9. Microwave Remote Sensing of Soil Moisture for Estimation of Soil Properties

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    Surface soil moisture dynamics was derived using microwave remote sensing, and employed to estimate soil physical and hydraulic properties. The L-band ESTAR radiometer was employed in an airborne campaign over the Little Washita watershed, Oklahoma during June 10-18, 1992. Brightness temperature (TB) data were employed in a soil moisture inversion algorithm which corrected for vegetation and soil effects. Analyses of spatial TB and soil moisture dynamics during the dry-down period revealed a direct relationship between changes in TB, soil moisture and soil texture. Extensive regression analyses were carried out which yielded statistically significant quantitative relationships between ratio of percent sand to percent clay (RSC, a term derived to quantify soil texture) and saturated hydraulic conductivity (Ksat) in terms of change components of TB and surface soil moisture. Validation of results indicated that both RSC and Ksat can be estimated with reasonable accuracy. These findings have potential applications for deriving spatial distributions of RSC and Ksat over large areas.

  10. Modeling Soil Moisture in the Mojave Desert

    USGS Publications Warehouse

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

    2008-01-01

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

  11. Soil moisture estimation by airborne active and passive microwave remote sensing: A test-bed for SMAP fusion algorithms

    NASA Astrophysics Data System (ADS)

    Montzka, Carsten; Bogena, Heye; Jagdhuber, Thomas; Hajnsek, Irena; Horn, Ralf; Reigber, Andreas; Hasan, Sayeh; Rüdiger, Christoph; Jaeger, Marc; Vereecken, Harry

    2014-05-01

    The objective of the NASA Soil Moisture Active & Passive (SMAP) mission is to provide global measurements of soil moisture and its freeze/thaw state. The SMAP launch is currently planned for 2014-2015. The SMAP measurement approach is to integrate L-band radar and L-band radiometer as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. The radar and radiometer measurements can be effectively combined to derive soil moisture maps that approach the accuracy of radiometer-only retrievals, but with a higher resolution (being able to approach the radar resolution under some conditions). Aircraft and tower-based instruments will be a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment in Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer (PLMR2) and the active L-band system DLR F-SAR were flown on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e. all types of land cover and experimental monitoring sites. These data are used as a test-bed for the analysis of existing and development of new active-passive fusion techniques. A synergistic use of the two signals can help to decouple soil moisture effects from the effects of vegetation (or roughness) in a better way than in the case of a single instrument. In this study, we present and evaluate three approaches for the fusion of active and passive microwave records for an enhanced representation of the soil moisture status: i) estimation of soil moisture by passive sensor data and subsequent disaggregation by active sensor backscatter data, ii) disaggregation of passive microwave brightness temperature by active microwave backscatter and subsequent inversion to soil moisture, and iii) fusion of two single-source soil moisture products from radar and radiometer.

  12. Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations

    NASA Astrophysics Data System (ADS)

    Albergel, C.; de Rosnay, P.; Gruhier, C.; Munoz-Sabater, J.; Hasenauer, S.; Isaksen, L.; Kerr, Y.; Wagner, W.

    2012-04-01

    In situ soil moisture data collected from more than 200 stations located in various biomes and climate (Africa, Australia, Europe and the United States) are used to determine the reliability of three soil moisture products, (i) one analysis from the ECMWF (European Centre for Medium-Range Weather Forecasts) numerical weather prediction system (SM-DAS-2) and two remotely sensed soil moisture products, namely (ii) ASCAT (Advanced Scatterometer) and (iii) SMOS (Soil Moisture Ocean Salinity). SM-DAS-2 is produced offline at ECMWF and relies on an advanced surface data assimilation system Extended Kalman Filter) used to optimally combine conventional observations with satellite measurements. ASCAT remotely sensed surface soil moisture is provided in near real time by EUMETSAT. At ECMWF, ASCAT is used for soil moisture analyses in SM-DAS-2, also. Finally the SMOS remotely sensed soil moisture data level two product developed at CESBIO is used. Evaluation of the times series as well as of the anomaly values, shows good performances of the three products to capture surface soil moisture annual cycle as well as its short term variability. Correlation values with in situ data are very satisfactory over most of the investigated sites located in contrasted biomes and climate conditions with averaged values of 0.70 for SM-DAS-2, 0.53 for ASCAT and 0.54 for SMOS. Although radio frequency interference disturbs the natural microwave emission of the Earth observed by SMOS in several parts of the world, hence the soil moisture retrieval, performances of SMOS over Australia are very encouraging.

  13. Emission and distribution of fumigants as affected by soil moistures in three different textured soils.

    PubMed

    Qin, Ruijun; Gao, Suduan; Ajwa, Husein

    2013-01-01

    Water application is a low-cost strategy to control emissions of soil fumigant to meet the requirements of the stringent environmental regulations and it is applicable for a wide range of commodity groups. Although it is known that an increase in soil moisture reduces emissions, the range of soil moisture for minimizing emissions without risking pest control, is not well defined for various types of soils. With two column studies, we determined the effect of different soil moisture levels on emission and distribution of 1,3-dichloropropene and chloropicrin in three different textured soils. Results on sandy loam and loam soils showed that by increasing soil moisture from 30% to 100% of field capacity (FC), peak fluxes were lowered by 77-88% and their occurrences were delayed 5-15 h, and cumulative emissions were reduced 24-49%. For the sandy soil, neither peak fluxes nor the cumulative emissions were significantly different when soil moisture increased from 30% to 100% FC. Compared to the drier soils, the wetter soils retained consistently higher fumigant concentrations in the gas-phase, suggesting efficacy may not be impacted in these soils. The air-filled porosity positively and linearly correlated with the cumulative emission loss across all soil types indicating that it may serve as a good indicator for estimating emissions. These laboratory findings can be further tested under field conditions to conclude what irrigation regime should be used for increasing soil water content before fumigant application that can achieve maximum emission reduction and uniform fumigant distribution with high exposure index values. PMID:23137872

  14. Upscaling of soil moisture measurements in NW Italy

    NASA Astrophysics Data System (ADS)

    Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Brunod, Christian; Ratto, Sara; Cauduro, Marco

    2015-04-01

    There is large mismatch in spatial scale between the climate and meteorological model grid, and the scale of soil and vegetation measurements. Remote sensing data can help to fit the model scale, but they cannot provide rootzone data. In this work some soil moisture datasets are analysed for the sake of providing larger scale estimation of soil moisture and water and energy fluxes. The first dataset refers to a plain site near Torino, where measurements are taken since 1997 (Baudena et al., 2012), and a mountain site close to the town. The second one is a dataset in the mountains of Valle d'Aosta (Brocca et al., 2013), where 4 years of data are available. The use of digital elevation models and vegetation maps is shown in this work. Some soil processes (e.g. Whalley et al., 2012) are usually disregarded, but in this work their possible impact is considered. References L. Brocca, A. Tarpanelli, T. Moramarco, F. Melone, S.M. Ratto, M. Cauduro, S. Ferraris, N. Berni, F. Ponziani, W. Wagner, T. Melzer (2013). Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations VADOSE ZONE JOURNAL, vol. 8-2, p. 1-10, doi:10.2136/vzj2012.0102 M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). Soil water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009 W.R. Whalley, G.P. Matthews, S. Ferraris (2012). The effect of compaction and shear deformation of saturated soil on hydraulic conductivity. SOIL & TILLAGE RESEARCH, vol. 125, p. 23-29, ISSN: 0167-1987

  15. Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency

    Microsoft Academic Search

    Olivier Merlin; Jeffrey P. Walker; Abdelghani Chehbouni; Yann Kerr

    2008-01-01

    A deterministic approach for downscaling ?40 km resolution Soil Moisture and Ocean Salinity (SMOS) observations is developed from 1 km resolution MODerate resolution Imaging Spectroradiometer (MODIS) data. To account for the lower soil moisture sensitivity of MODIS surface temperature compared to that of L-band brightness temperature, the disaggregation scale is fixed to 10 times the spatial resolution of MODIS thermal data (10 km).

  16. Thermal performance of underground power cables with constant and cyclic currents in presence of moisture migration in the surrounding soil

    SciTech Connect

    Freitas, D.S.; Prata, A.T. [Federal Univ. of Santa Catarina, Florianopolis, Santa Catarina (Brazil). Dept. of Mechanical Engineering] [Federal Univ. of Santa Catarina, Florianopolis, Santa Catarina (Brazil). Dept. of Mechanical Engineering; Lima, A.J. de [CEQC-PIRELLI S.A., Santo Andre, Sao Paulo (Brazil). Cable Div.] [CEQC-PIRELLI S.A., Santo Andre, Sao Paulo (Brazil). Cable Div.

    1996-07-01

    A numerical methodology for thermal analysis of buried power cables in presence of heat and moisture migration in the surrounding soil is presented. The governing equations are solved via a finite volume methodology and both cable and soil are incorporated in the problem formulation. The developed program is versatile and user-friendly, and was implemented in a personal computer. Results are presented for constant and cyclic loads, stressing the importance of moisture migration in power cable design.

  17. Synergy between passive (SMOS) and active (RADARSAT-2) microwave soil moisture over Berambadi, India

    NASA Astrophysics Data System (ADS)

    Tomer, Sat Kumar; Bitar, Ahmad Al; Sekhar, Muddu; Merlin, Olivier; Bandyopadhyay, Soumya; Kerr, Yann

    2013-04-01

    This study presents comparison and analysis towards blending of the SMOS derived soil moisture and RADARSAT-2 derived soil moisture over the Berambadi watershed, South India. SMOS (Soil Moisture and Ocean Salinity) satellite from ESA has a passive microwave L-Band sensor providing acquisition at ~40 km resolution and less than 3 days temporal resolution. RADARSAT-2 is an active microwave sensor from (CSA) operating in C-Band at a decametric spatial resolution and 24 days temporal resolution. Both satellites are all-weather satellites. SMOS is less impacted by roughness effects as it operates in passive mode at L-Band compared to RADARSAT-2, which on the other hand has a significantly higher spatial resolution. Twenty four images of RADARSAT-2 and SMOS-L2UDP soil moisture product, along with extensive field data collected in field campaigns during 2010-2012 in the framework of the ongoing AMBHAS (Assimilation of Multi-satellite data at Berambadi watershed for Hydrology And land Surface experiment) project were used in the analysis. A non parametric algorithm based on the CDF transformation method was developed to retrieve the soil moisture from RADARSAT-2 backscatter coefficient at a spatial resolution of 100 m. This product is validated using a random sampling procedure to divide the data into calibration and validation set each one consisting of 12 images. The developed algorithm provided a good estimate of the surface soil moisture with a RMSE of 0.05 m3 m-3. Then the validated RADARSAT-2 soil moisture maps were upscaled to compare with the SMOS data. Eight upscaling strategies were considered, taking into account the surface heterogeneity in terms of texture (clay sand), surface cover (forest, land cover) and SMOS mean antenna pattern. The strategies use linear combination of the different parameters. Significant differences were observed between the eight strategies. The RMSE and coefficient of determination of the different strategies varied between 0.06-0.09 m3 m-3 and 0.3-0.9 respectively. The best comparisons with a RMSE of 0.06 m3 m-3 and a coefficient of determination of 0.7 were obtained for upscaling strategies that include land cover effect. This result was used in the development of a downscaling procedure to merge the spatial information from RADARSAT-2 with the temporal dynamics from SMOS acquisitions. In order to implement this method the persistence of the spatial patterns in the RADARSAT-2 soil moisture map were evaluated by inspecting the spatiotemporal correlation coefficient across the two years, which was approximately 0.55. The impact of rain and farming activities were also taken into consideration in the analysis of the spatial heterogeneity. This study shows the potential synergy between the use of active/passive microwave soil moisture retrievals for spatial and temporal down-scaling of soil moisture. This study also shows the potential synergies between SMOS and SMAP (Soil Moisture Active Passive) mission from NASA due to launch in 2015 since SMAP will make active L-band acquisitions.

  18. Evaluation of ERS scatterometer soil moisture products over a half-degree region in southwestern France

    NASA Astrophysics Data System (ADS)

    Pellarin, Thierry; Calvet, Jean-Christophe; Wagner, Wolfgang

    2006-09-01

    This paper investigates the ERS Scatterometer soil moisture products precision over a half-degree region in Southwestern France. Based on a high resolution soil moisture simulation (1 km2) validated at the local scale, the ERS-scat product is assessed at its own resolution (about 50 × 50 km2). The study points out the suitable quality of the surface soil moisture product (root mean square error equal to 0.06 m3.m-3 for a 4-year period) and assesses the retrieved root-zone soil moisture accuracy provided by a semi-empirical methodology exclusively based on surface soil moisture products.

  19. Relationship Between Rainfall and Soil Moisture Based on AMSR-E Data

    NASA Technical Reports Server (NTRS)

    Jin, Kyoung-Wook; Njoku, Eni; Chan, Steven

    2006-01-01

    Rainfall over land is a primary uncertainty source and limitation for the soil moisture retrieval. Discerning the signal emitted by the surface from emission of a raining atmosphere is extremely complicated. Results show some insights of the relationship between precipitation and soil moisture according to spatio-temporal scales We are working on investigating consistency between the retrieved soil moisture data and the model data (NARR) to study how satellite-based soil moisture observations can contribute to simulate improved large-scale soil moisture estimation through data assimilation.

  20. The Soil Moisture Active Passive Mission: Geophysical Products and Algorithm Development

    NASA Astrophysics Data System (ADS)

    Njoku, E. G.; Entekhabi, D.; O'Neill, P. E.; Jackson, T. J.; Bindlish, R.; Chan, S.; Colliander, A.; Das, N. N.; Dunbar, S.; Kim, S.; Kimball, J. S.; McDonald, K. C.; Mahta, M.; Reichle, R. H.

    2012-12-01

    NASA's Soil Moisture Active Passive (SMAP) mission, scheduled for launch in October 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of importance in flood prediction and drought monitoring. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. SMAP utilizes an L-band radar and an L-band radiometer sharing a rotating 6-meter mesh reflector antenna. The radar and radiometer instruments will operate onboard the SMAP spacecraft in a 685 km Sun-synchronous near-polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. The algorithms and data products for SMAP are being developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors (PALS, UAVSAR, SMOS and Aquarius). The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). Key components of the Cal/Val Plan are the characterization and instrumentation of core and contributing validation sites, as well as analysis approaches that can be used to calibrate and validate the science data products. In this presentation we report on the development status of the SMAP data products and algorithms.

  1. Examining Soil Moisture Variability and Field Mean Estimation Methods using Nested Observations

    NASA Astrophysics Data System (ADS)

    Peterson, A.; Helgason, W.; Ireson, A. M.

    2014-12-01

    Information about soil moisture is typically required at the field scale. Direct measurements of soil moisture at this scale are not possible, though there are a number of promising indirect methods (e.g. remote sensing methods and cosmic-ray neutrons). Methods for obtaining point scale measurements of soil moisture are well established. However, variability of soil moisture, in both space and time, makes accurately determining field scale soil moisture from point measurements difficult. Understanding sub-field scale variability is a key step in determining how to upscale point measurements, and in particular to identify the minimum number of point measurements necessary to represent field scale mean soil moisture. Objectives of this study are to: (1) examine the spatial variability of soil moisture with time, and (2) compare field scale soil moisture estimation methods. Nested soil moisture measurements provided observations covering a 5002m2 area within a semi-arid prairie pasture site in southern Saskatchewan, Canada. Complementary measurements of the water balance were measured using meteorological and flux instrumentation. Spatial variability of surface and root zone soil moisture were examined using data from gridded dielectric water content probe surveys and a neutron probe array. Field scale surface soil moisture was measured at the site using a cosmic-ray neutron probe. The field scale estimation methods compared are: (1) water balance, (2) upscaling by averaging point scale measurements, (3) upscaling by identification of average representative time stable sites, and (4) extrapolation of shallow soil moisture measured by cosmic-ray neutron probe. Variability of surface soil moisture was found to be smallest under extreme dry and wet conditions, and largest during intermediate moisture conditions. Large spatial variability was found in the root zone, with soil moisture being most temporally variable closer to the surface.

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

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface soil moisture. Validation of results using field measured values and soil texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.

  3. Remote sensing of soil moisture using Loran-C signals

    NASA Astrophysics Data System (ADS)

    Feng, Yi; Astin, Ivan

    2014-05-01

    Accurate knowledge of wide-area soil moisture is essential for atmospheric and hydrological studies. In recent years, efforts worldwide have focused on the use of microwave imaging sensors on-board satellites such as SMOS to derive this information from the interpreted brightness temperature of the Earth. However, the frequency of data retrieved this way is often limited by the revisit period of the remote sensing platforms. In this study, we explore the feasibility of using 100 kHz Loran-C radio navigation signals, transmitted continuously from ground-based stations, for the estimation of soil moisture on wide-areas. This technique is based on the measured time delay of the surface wave component, which is influenced by land surface and atmospheric dynamics. It was found that variations in the propagation time of Loran-C surface waves may be representative of short-term ground electrical conductivity changes along the propagation path, which are believed to have a direct link with soil properties. Using Loran-C time delays measured at the University of Bath, it has been shown that the proposed method, combined with model data, can be used for the remote sensing of soil moisture where improved temporal sampling is required. This allows for further validation and improvement.

  4. SMAP Mission Multiresolution Soil Moisture data for Understanding Geophysical Process Dynamics at Different Scales (Invited)

    NASA Astrophysics Data System (ADS)

    Das, N. N.

    2013-12-01

    Knowledge of soil moisture evolution at various spatiotemporal resolutions is vital to understand dynamic geophysical processes pertaining to hydrology, ecology, weather and climate. Therefore measuring soil moisture at different spatiotemporal resolution from in situ to kilometers scale at field- to global-extent is essential. Various in situ soil moisture measuring instruments (~meter spatial resolution) forming functional networks are deployed across the world, however, are mostly localized. Satellite sensors e.g., AMSR-E (2002 - 2011) and SMOS (2009 - present) have been providing soil moisture estimate at very coarse spatial resolution of >40 km. In between these ~meter-scale and ~40 km soil moisture measurements, there is lack of availability of any consistent, spatially and temporally continuous soil moisture measurements. NASA's SMAP mission that has a target launch date in late 2014 will provide multiresolution (36-, 9-, and 3-km) and frequent revisit (2-3 days) soil moisture measurements at a global-extent. SMAP data will facilitate numerous studies without need of upscaling or downscaling soil moisture measurement, and hence improve the dynamic geophysical processes understanding. The data will also provide fresh perspective of soil moisture evolution and scaling over different hydroclimatic regions and landcover. The presentation will introduce the scientific community on the SMAP suite of soil moisture products by especially focusing on expected product accuracy, retrieval characteristics, flags, retrieval thresholds and masks. Potential studies emanating from multiresolution soil moisture measurements will also be discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    A prototype soil moisture monitoring, prediction and reporting system is being developed for Australia, with the Murrumbidgee catchment as the demonstration catchment. The system will provide current and future soil moisture information and its uncertainty at 1km resolution, by combining weather, climate and land surface model predictions with soil moisture data from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite; the first-ever dedicated microwave soil moisture mission. A major aspect of this project is developing and testing the soil moisture retrieval algorithms to be used for SMOS and verifying SMOS data for Australian conditions, through a number of airborne campaigns. The key elements of this project will develop and test innovative techniques for monitoring, prediction and reporting of 1km resolution soil moisture content from ground-, air- and space-based measurements for Australian conditions. The ground based and air-borne data will be used for: (i) calibration/validation of the SMOS satellite; (ii) development and verification of surface soil moisture retrieval algorithm components of the SMOS Simulator; (iii) development and verification of soil hydraulic property estimation; and (iv) verification of 1km moisture from MoistureMap. The Murrumbidgee catchment is an 80,000km2 watershed located in south-eastern Australia, with a large diversity in climatic, topographic and land cover characteristics making it an excellent demonstration test-bed for SMOS Simulator and MoistureMap developments. The Murrumbidgee River Catchment has been instrumented and monitored for soil moisture and supporting data for more than 7 years. The existing network of monitoring sites, data management systems, data sets, and detailed knowledge of the catchment provide an ideal basis for the field work and data requirements of this study. The soil moisture prediction model to be used is CSIRO Atmosphere Biosphere Land Exchange (CABLE), a column model based on Richards’ equation that simulates water and energy fluxes between a vertical profiles, land surface, vegetation and the atmosphere. This model is ideally suited to the assimilation requirements of this project due to its prediction of hydrological and thermal states soil and vegetation states, which are necessary for radiance and thermal data assimilation via ensemble CABLE simulations. In this presentation, we discuss the initial simulations with the land surface model (CABLE) and also the established data assimilation scheme. Moreover, we present the results from the first airborne campaigns to Central Australia and the Murrumbidgee River catchment. Finally, the progress of the developments of the different projects is presented, providing a first idea of the information that can be obtained from the SMOS data sets.

  6. Assessing Landscape-Scale Soil Moisture Distribution Using Auxiliary Sensing Technologies and Multivariate Geostatistics

    NASA Astrophysics Data System (ADS)

    Landrum, C.; Castrignanò, A.; Mueller, T.; Zourarakis, D.; Zhu, J.

    2013-12-01

    It is important to assess soil moisture to develop strategies to better manage its availability and use. At the landscape scale, soil moisture distribution derives from an integration of hydrologic, pedologic and geomorphic processes that cause soil moisture variability (SMV) to be time, space, and scale-dependent. Traditional methods to assess SMV at this scale are often costly, labor intensive, and invasive, which can lead to inadequate sampling density and spatial coverage. Fusing traditional sampling techniques with georeferenced auxiliary sensing technologies, such as geoelectric sensing and LiDAR, provide an alternative approach. Because geoelectric and LiDAR measurements are sensitive to soil properties and terrain features that affect soil moisture variation, they are often employed as auxiliary measures to support less dense direct sampling. Georeferenced proximal sensing acquires rapid, real-time, high resolution data over large spatial extents that is enriched with spatial, temporal and scale-dependent information. Data fusion becomes important when proximal sensing is used in tandem with more sparse direct sampling. Multicollocated factorial cokriging (MFC) is one technique of multivariate geostatistics to fuse multiple data sources collected at different sampling scales to study the spatial characteristics of environmental properties. With MFC sparse soil observations are supported by more densely sampled auxiliary attributes to produce more consistent spatial descriptions of scale-dependent parameters affecting SMV. This study uses high resolution geoelectric and LiDAR data as auxiliary measures to support direct soil sampling (n=127) over a 40 hectare Central Kentucky (USA) landscape. Shallow and deep apparent electrical resistivity (ERa) were measured using a Veris 3100 in tandem with soil moisture sampling on three separate dates with ascending soil moisture contents ranging from plant wilting point to field capacity. Terrain features were produced from 2010 LiDAR returns collected at ?1 m nominal pulse spacing. Exploratory statistics revealed 12 variables that best associate with soil moisture including slope, elevation, calcium, organic matter, clay, sand and geoelectric measurements (ERa for each date). A linear combination of basic variogram functions, called the linear model of coregionalization (LMC), was fitted using a matrix of direct and cross experimental variograms constituting the 12 different variables studied. The LMC consisted of 3 basic components: nugget, spherical (short range scale=40m) and exponential (long range scale=250m) where each component explained 17%, 22% and 60% of the total measured variation, respectively. Applying principal component analysis to the coregionalization matrix at each spatial scale produced a set of regionalized factors summarizing the variation at that spatial scale. Mapping regionalized factors decomposes the total measured system variation into scale-dependent synthetic homogeneous zones that lend insight into the properties influencing SMV. Results suggest that soil texture and OM drive the soil moisture variation under the soil moisture regimes observed. This study shows the potential for using ERa and multivariate statistics to develop soil moisture management strategies under water stressed conditions.

  7. Soil Moisture Transit Times on a Steep Hillslope

    NASA Astrophysics Data System (ADS)

    Kim, S.; Jnag, E.; Jeong, J.

    2014-12-01

    Field monitoring of isotopes and isotope analyses have been used to approximate water travel time at hillslope scales. This paper introduces an alternate method for estimating a point-scaled transit time in a soil layer, namely hydrometric transit time (HTT). HTT uses hydrometric measurements to address both matrix flow and bypass flow. Soil matrix flux is approximated through integration of continuous soil moisture profiles and soil water computations. Free surface film modeling of unsaturated flow is used to estimate bypass flow. This flux and storage estimation scheme is applied to a steep hillslope using hydrometric measurements that were estimated over an 8-month period using a continuous daily approximation of soil moisture profiles. Transit times at several designated points are also evaluated using isotope analyses. Results show that rainfall strongly controls temporal fluctuations. This work highlights the potential role of HTT in revealing the spatial and seasonal variations in the transit time probability density function (PDF) along transects. Mean transit time does not sufficiently characterize transit time variations on a hillslope scale. Accumulated flux distributions identify distinct hydrologic contributions and efficient redistribution of soil water in the downslope area of the hillside.

  8. Investigating Land-Atmosphere Interactions using the North American Soil Moisture (NASM) Database

    NASA Astrophysics Data System (ADS)

    Quiring, S. M.; Ford, T. W.

    2013-12-01

    The North American Soil Moisture Database (soilmoisture.tamu.edu) is a new high-quality observational soil moisture database that contains soil moisture data from >1700 stations in Canada and the United States. Here we provide an overview of how the in situ soil moisture observations were assembled, quality controlled and harmonized prior to being incorporated in the NASMD. The soil moisture database will facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper describes some of our early findings regarding the nature of land-atmosphere interactions in the U.S. Great Plains.

  9. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

    Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological, phenological, geological, agronomic, and socio-economic variables are also considered to extend the model in order to reveal the proper causal relation. First results show that dry as well as wet extremes of SMI have a negative impact on crop yield for winter wheat. This indicates that soil moisture has at least a limiting affect on crop production.

  10. Spatial Variations in Soil Properties at the University of Mississippi Soil Moisture Observatory

    NASA Astrophysics Data System (ADS)

    Holland, J. V.; Fancher, C. W.; Sleep, M. D.; Twombly, J. E.; Aufman, M. S.; Holt, R. M.; Kuszmaul, J. S.

    2004-05-01

    Geophysical and remote sensing technologies are being increasingly used to investigate the properties of shallow soils. Nearly all of the soil physical properties important to geophysical and remote sensing technologies, including electrical conductivity, electromagnetic properties, thermal properties, acoustic properties, and vapor phase transport processes, are controlled by soil mineralogy, soil structure, and the distribution of soil moisture. Spatial and temporal variations in these controls conspire to confound sensor observations and complicate data reduction and inversion by producing non-unique sensor signatures. To provide a facility for detailed study of soil - geophysical interactions, we are constructing a Soil Moisture Observatory (SMO) at the University of Mississippi (UM). The 5 acre SMO is located in a former agricultural field at the UM Biological Field Station, a 740 acre tract of land located 11 miles from the UM campus in Oxford, Mississippi. The soils present at the SMO consist of silty and sandy loam. Our preliminary activities at the site included collecting 60 continuous soil cores using a direct-push sampling probe and the installation of neutron access tubes along two intersecting transects. Continuous soil samples were taken to a depth of 1.5 m and analyzed for particle size distribution, porosity, bulk density, iron content, moisture content. Variograms of these data show that most soil properties have a horizontal correlation length of greater than 10 m. The horizontal correlation length for moisture content increases with depth from about 12 m near the soil surface to approximately 24 m at a depth of 1 m. Vertical variograms of soil moisture show evidence of a small-scale structure with a correlation length of 0.6 m.

  11. Distributed Hydrological Model with New Soil Water Parameterization for Integrating Remotely Sensed Soil Moisture at Watershed Scale

    Microsoft Academic Search

    Zhang Wanchang; Chen Jiongfeng

    2008-01-01

    Detailed vertical soil moisture profile is essential for hydrological modeling and is also often used as important diagnostic information for better understanding the surface-atmospheric interactions. This paper presents a modified ESSI distributed hydrological model that is suitable for comparing and assimilating the remotely sensed soil moisture by integrating a soil water parameterization scheme which is able to numerically calculates soil

  12. Diurnal and seasonal variation in the control of soil temperature and moisture on soil CO2 efflux during secondary succession

    NASA Astrophysics Data System (ADS)

    Dunker, S. L.; Epstein, H. E.

    2012-12-01

    The carbon sink activity of the eastern United States over the last several decades has been attributed to secondary succession1. The extent of this sink activity depends on the balance between gross primary production and ecosystem respiration (RE), i.e. net ecosystem production (NEP). Because soil CO2 efflux, a component of RE, can influence the magnitude or sign of NEP, constraining the dynamics of soil CO2 efflux and its controls over diurnal, seasonal and decadal time scales is important. The aims of this study were twofold. (1) To examine the influence of soil temperature and moisture on soil CO2 efflux in abandoned agricultural fields undergoing secondary succession. (2) To investigate whether the soil CO2 efflux - soil temperature and moisture relationship varied diurnally, seasonally, or among successional stages. To test these questions, we employed a chronosequence approach at Blandy Experimental Farm near Boyce, VA. Six study fields, ranging in age from 6 to >100 years, were classified as early, mid or late successional. Each pair of fields in the same successional stage was closely age-matched. We concurrently measured soil CO2 efflux, soil temperature at 5 cm, and soil volumetric water content (VWC) to 12 cm (%) year round for two years both during the day (1000-1400) and at night (2200-0200). Soil samples to 15 cm from each study plot were collected and analyzed in the laboratory to determine bulk density (?B) and particle density (?P). Soil porosity (?) was calculated as (1 - ?B / ?P)*100. Soil water filled pore space (WFPS) was calculated as VWC/?. A stepwise multiple regression of soil CO2 efflux against soil temperature and WFPS showed that temperature and WFPS significantly affected soil CO2 efflux (p<0.0001; R2=0.41; Flux = 0.42(Temp) + 5.72(WFPS) - 4.18). An analysis of covariance with season, chronosequence, successional stage and time of day as independent variables, and a new principle component derived from soil temperature and WFPS as a covariate showed that while soil CO2 efflux did vary by season (p<0.0001) and by chronosequence (p=0.040), it did not vary by successional stage (p=0.970) or by time of day (p=0.129). The soil CO2 efflux - soil temperature and moisture relationship varied seasonally (p<0.0001), but did not vary between the two chronosequences (p=0.299), between day and night (p=0.139) or among successional stages (p=0.052). The similarity in the soil CO2 efflux - soil temperature and moisture relationship between the two chronosequences, despite the difference in soil CO2 efflux magnitude, suggests that while land use history can impact the amount of CO2 released by the soil, the influence of environmental drivers remains the same. Notably, there was no difference between daytime and nighttime in the amount of CO2 released by soil, nor in the soil CO2 efflux - soil temperature and moisture relationship. This suggests that extrapolations of nighttime estimates of RE by eddy covariance systems to total daily RE are reasonable. 1Albani et al.. 2006. Global Change Biology 12:2370-2390.

  13. Soil moisture variability: a comparison between detailed field measurements and remote sensing measurement techniques

    Microsoft Academic Search

    PETER J. VAN OEVELEN

    Surface soil moisture, defined here as the volumetric soil water content in the top 10 cm of the soil, shows a great deal of variability. The variance observed within a square metre can be as large as for a whole field. For that reason alone, point measurements in low quantities cannot be representativ e for the average soil moisture of

  14. Soil moisture variability: a comparison between detailed field measurements and remote sensing measurement techniques

    Microsoft Academic Search

    PETER J. VAN OEVELEN

    1998-01-01

    Surface soil moisture, defined here as the volumetric soil water content in the top 10 cm of the soil, shows a great deal of variability. The variance observed within a square metre can be as large as for a whole field. For that reason alone, point measurements in low quantities cannot be representative for the average soil moisture of a

  15. Active and passive microwave measurements of soil moisture in FIFE

    NASA Technical Reports Server (NTRS)

    Wang, J. R.; Gogineni, S. P.; Ampe, J.

    1992-01-01

    During the intensive field campaigns of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in May-October of 1987, several nearly simultaneous measurements were made with low-altitude flights of the L-band radiometer and C- and X-band scatterometers over two transects in the Konza Prairie Natural Research Area, some 8 km south of Manhattan, Kansas. These measurements showed that although the scatterometers were sensitive to soil moisture variations in most regions under the flight path, the L-band radiometer lost most of its sensitivity in regions unburned for many years. The correlation coefficient derived from the regression between the radar backscattering coefficient and the soil moisture was found to improve with the increase in antenna incidence angle. This is attributed to a steeper falloff of the backscattering coefficient as a function of local incidence at angles near nadir than at angles greater than 30 deg.

  16. Soil Moisture Sensing via Swept Frequency Based Microwave Sensors

    PubMed Central

    Pelletier, Mathew G.; Karthikeyan, Sundar; Green, Timothy R.; Schwartz, Robert C.; Wanjura, John D.; Holt, Greg A.

    2012-01-01

    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 SFI instrument over a range of soil types, at varying levels of moisture. This testing protocol was developed to provide the best possible comparison between SFI to TDT than would otherwise be possible by using soil moisture as the bench mark, due to variations in soil density between soil water content levels which are known to impact the calibration between TDR’s estimate of soil water content from the measured propagation delay which is converted to an apparent permittivity measurement. This experimental decision, to compare propagation delay of TDT to FDT, effectively removes the errors due to variations in packing density from the evaluation and provides a direct comparison between the SFI instrument and the time domain technique of TDT. The tests utilized three soils (a sand, an Acuff loam and an Olton clay-loam) that were packed to varying bulk densities and prepared to provide a range of water contents and electrical conductivities by which to compare the performance of the SFI technology to TDT measurements of propagation delay. For each sample tested, the SFI instrument and the TDT both performed the measurements on the exact same probe, thereby both instruments were measuring the exact same soil/soil-probe response to ensure the most accurate means to compare the SFI instrument to a high-end TDT instrument. Test results provided an estimated instrumental accuracy for the SFI of +/?0.98% of full scale, RMSE basis, for the precision delay lines and +/?1.32% when the SFI was evaluated on loam and clay loam soils, in comparison to TDT as the bench-mark. Results from both experiments provide evidence that the low-cost SFI approach is a viable alternative to conventional TDR/TDT for high accuracy applications. PMID:22368494

  17. Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

    NASA Astrophysics Data System (ADS)

    Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

    2015-04-01

    Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico SemiDistribuito in continuo") continuous hydrological model is used for flood simulation. The Ensemble Kalman Filter (EnKF) is employed as data assimilation technique for its flexibility and good performance in a number of previous applications. Different components are involved in the developed data assimilation procedure. For the correction of the bias between satellite and modelled soil moisture data three different techniques are considered: mean-variance matching, Cumulative Density Function (CDF) matching and least square linear regression. For properly generating the ensembles of model states, required in the application of EnKF technique, an exhaustive search of the model error parameterization and structure is carried out, differentiated for each study catchments. A number of scores and statistics are employed for the evaluation the reliability of the ensemble. Similarly, different configurations for the observation error are investigated. Results show that for four out six catchments the assimilation of the ASCAT soil moisture product improves discharge simulation in the validation period 2010-2013, mainly during flood events. The two catchments in which the assimilation does not improve the results are located in the mountainous part of the region where both MISDc and satellite data perform worse. The analysis on the data assimilation choices highlights that the selection of the observation error seems to have the largest influence on discharge simulation. Finally, the bias correction approaches have a lower effect and the selection of linear techniques is preferable. The assessment of all the components involved in the data assimilation procedure provides a clear understanding of results and it is advised to follow a similar procedure in this kind of studies.

  18. Soil moisture mapping in a semi-arid region, based on ASAR/Wide Swath satellite data

    E-print Network

    Paris-Sud XI, Université de

    .1002/2012WR013405 #12;Keywords: moisture mapping, radar, Envisat ASAR 1. Introduction Soil moisture is a key the soil moisture at a high spatial resolution. The radar signal backscattered by bare soil strongly the understanding of radar signal behavior, as a function of surface parameters and soil moisture in particular

  19. Impact of Soil Moisture Dynamics on ASAR ?o Signatures and Its Spatial Variability Observed over the Tibetan Plateau

    PubMed Central

    van der Velde, Rogier; Su, Zhongbo; Ma, Yaoming

    2008-01-01

    This paper reports on the analysis of a 2.5 year-long time series of ASAR wide swath mode (WSM) observations for characterizing the soil moisture dynamics. The employed ASAR WSM data set consists of 152 VV-polarized scenes acquired in the period between April 2005 and September 2007 over the Naqu river basin located on the Tibetan Plateau. For four different spatial domains, with areas of 30×30 km2, 5×5 km2 and (two domains of) 1×1 km2, the mean backscatter (?o) and the standard deviation (stdev) have been computed for each ASAR acquisition. Comparison of the mean ?o values with the stdev values results in a specific triangular distribution of data points for all spatial domains. Analysis of the mean ?o and stdev with respect to in-situ soil moisture measurements demonstrates that this triangular shaped distribution can be explained by soil moisture dynamics during monsoon and winter periods. This shows that the relationship between the spatial mean soil moisture and variability is not uniquely defined and may change throughout seasons. Downscaling of coarse resolution soil moisture products should, therefore, be ideally based on additional near real time data sources. In this context, the presented results could form a basis for the development of SAR-based soil moisture downscaling methodologies.

  20. Spatiotemporal characterization of soil moisture fields in agricultural areas using cosmic-ray neutron probes and data fusion

    NASA Astrophysics Data System (ADS)

    Franz, Trenton; Wang, Tiejun

    2015-04-01

    Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE USA. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 12 by 12 km study domain also contained three stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong relationship between the mean and variance of soil moisture at several averaging scales. The relationships between the mean and higher order moments were not significant. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. In addition, we combined the data from the three stationary cosmic-ray neutron probes and mobile surveys using linear regression to derive a daily soil moisture product at 1, 3, and 12 km spatial resolutions for the entire growing season. The statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide daily center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

  1. L-band radar sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Chang, A. T. C.; Salomonson, V. V.; Atwater, S. G.; Estes, J. E.; Simonett, D. S.; Bryan, M. L.

    1980-01-01

    The objectives of the experiment were to assess the performance of an L-band, 25-cm wavelength imaging synthetic aperture radar (SAR) for soil moisture determination, and to study the temporal variability of radar returns from a number of agricultural fields. A series of overflights was accomplished during March 1977 over an agricultural test site in Kern County, Calif. Soil moisture samples were collected from bare fields at nine sites at depths of 0-2, 2-5, 5-15, and 15-30 cm. These gravimetric measurements were converted to percent of field capacity for correlation to the radar return signal. The initial signal film was optically correlated and scanned to produce image data numbers. These numbers were then converted to relative return power by linear interpolation of the noise power wedge which was introduced in 5-dB steps into the original signal film before and after each data run. Results of correlations between the relative return power and percent of field capacity demonstrate that the relative return power from this imaging radar system is responsive to the amount of soil moisture in bare fields. The signal returned from dry and wet fields where furrowing is parallel to the radar beam differs by about 15 dB. Before this technique can be operationally employed, adequate calibration of the radar system is required to insure comparability of data both from area to area within a single flight and between different flights.

  2. GPS-R L1 interference signal processing for soil moisture estimation: an experimental study

    NASA Astrophysics Data System (ADS)

    Yan, Songhua; Li, Zhengyong; Yu, Kegen; Zhang, Kefei

    2014-12-01

    Global positioning system reflectometry (GPS-R) is an emerging area of GPS applications in microwave remote sensing using multipath reflected signals. Soil moisture estimation is one of the many potential applications of the GPS-R technique. The focus of this study is on investigating the feasibility of soil moisture estimation based on GPS L1 band interference signals which can be readily captured using a low-cost off-the-shelf L1-band GPS receiver. The theoretical background is studied, and the field experiments conducted are described. Power spectrum analysis is performed on the received interference signals to determine the interference signal frequency variation, and cosine similarity is applied to identify the initial phase change. Data collected at a number of continuously operating GPS stations are also analyzed. The results demonstrate that both interference signal frequency and phase have changed significantly after rainfalls occurred. That is, it is possible to estimate soil moisture by analyzing the frequency change and phase shift. However, it is also observed that the phase shift is inconsistent in some cases. Ongoing work will focus on figuring out the source of the inconsistency so that reliable estimation of soil moisture can be achieved.

  3. Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling

    NASA Technical Reports Server (NTRS)

    Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf

    2012-01-01

    Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

  4. Soil moisture's underestimated role in climate change impact modelling in low-energy systems.

    PubMed

    le Roux, Peter Christiaan; Aalto, Juha; Luoto, Miska

    2013-10-01

    Shifts in precipitation regimes are an inherent component of climate change, but in low-energy systems are often assumed to be less important than changes in temperature. Because soil moisture is the hydrological variable most proximally linked to plant performance during the growing season in arctic-alpine habitats, it may offer the most useful perspective on the influence of changes in precipitation on vegetation. Here we quantify the influence of soil moisture for multiple vegetation properties at fine spatial scales, to determine the potential importance of soil moisture under changing climatic conditions. A fine-scale data set, comprising vascular species cover and field-quantified ecologically relevant environmental parameters, was analysed to determine the influence of soil moisture relative to other key abiotic predictors. Soil moisture was strongly related to community composition, species richness and the occurrence patterns of individual species, having a similar or greater influence than soil temperature, pH and solar radiation. Soil moisture varied considerably over short distances, and this fine-scale heterogeneity may contribute to offsetting the ecological impacts of changes in precipitation for species not limited to extreme soil moisture conditions. In conclusion, soil moisture is a key driver of vegetation properties, both at the species and community level, even in this low-energy system. Soil moisture conditions represent an important mechanism through which changing climatic conditions impact vegetation, and advancing our predictive capability will therefore require a better understanding of how soil moisture mediates the effects of climate change on biota. PMID:23749628

  5. Growth of three species of Bidens under different levels of soil moisture content

    Microsoft Academic Search

    Kiyokazu Suehiro; Kazuo Hozumi; Kichiro Shinozaki

    1984-01-01

    By the assumption that both soil moisture and soil air affect plant growth as linear factor, the relationship between mean\\u000a plant dry weight and soil moisture content was newly formulated. Its applicability to actual growth data was tested by growing\\u000a three species ofBidens under different levels of soil moisture content. The growth data ofBidens well satisfied the new formula. The

  6. Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS-2

    Microsoft Academic Search

    Jeffrey P. Walker; Paul R. Houser; Garry R. Willgoose

    2003-01-01

    Active microwave remote sensing observations of backscattering, such as C-band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS-2) satellite, have the potential to measure moisture content in a near-surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from

  7. Airborne time-series measurement of soil moisture using terrestrial gamma radiation

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

    Terrestrial gamma radiation data and independent ground-based core soil moisture data are analyzed. They reveal the possibility of using natural terrestrial gamma radiation collected from a low-flying aircraft to make reliable real-time soil moisture measurements for the upper 20 cm of soil. The airborne data were compared to the crude ground-based soil moisture data set collected at the core sites.

  8. Microbial biomass and activity in soils with different moisture content heated at high temperatures

    NASA Astrophysics Data System (ADS)

    Barreiro, Ana; Lombao, Alba; Martin, Angela; Cancelo-González, Javier; Carballas, Tarsy; Díaz-Raviña, Montserrat

    2015-04-01

    It is well known that soil properties determining the thermal transmissivity (moisture, texture, organic matter, etc.) and the duration and temperatures reached during soil heating are key factors driving the fire-induced changes in soil microbial communities. However, despite its interest, the information about this topic is scarce. The aim of the present study is to analyze, under laboratory conditions, the impact of the thermal shock (infrared lamps reaching temperatures of 100 °C, 200 °C and 400 °C) on microbial communities of three acid soils under different moisture level (0 %, 25 % and 50 % per soil volume). Soil temperature was measured with thermocouples and the impact of soil heating was evaluated by means of the analysis of the temperature-time curves calculating the maximum temperature reached (Tmax) and the degree-hours (GH) as an estimation of the amount of heat supplied to the samples (fire severity). The bacterial growth (leucine incorporation) and the total microbial biomass (PLFA) were measured immediately after the heating and one month after the incubation of reinoculated soils. The results showed clearly the importance of moisture level in the transmission of heat through the soil and hence in the further direct impact of high temperatures on microorganisms living in soil. In general, the values of microbial parameters analyzed were low, particularly immediately after soil heating at higher temperatures; the bacterial activity measurements (leucine incorporation technique) being more sensitive to detect the thermal shock showed than total biomass measurements (PLFA). After 1 month incubation, soil microbial communities tend to recover due to the proliferation of surviving population using as substrate the dead microorganisms (soil sterilization). Thus, time elapsed after the heating was found to be decisive when examining the relationships between the microbial properties and the soil heating parameters (GH, Tmax). Analysis of results also showed that the measurement of the heat supplied to the soil (GH) rather than Tmax is a useful parameter to interpret microbial changes induced by soil heating. Acknowledgements. This work was supported by Spanish Ministry of Economy and Competitiveness (AGL2012-39686-C02-01) and for the for the MAPFRE foundation. A. Barreiro and A. Lombao are recipients of FPU grant from Spanish Ministry of Education. Keywords: Degree-hour, soil heating, leucine incorporation, total PLFA biomass

  9. Detecting causation mechanisms of soil moisture patterns in Germany

    NASA Astrophysics Data System (ADS)

    Samaniego, Luis; Kumar, Rohini; Zink, Matthias; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2013-04-01

    Detecting trends, feedbacks, and causation mechanisms in hydrometeorologic variables such as soil moisture is a challenging task because of the nonlinear dynamics of the atmosphere-land-vegetation system, the assimilation of noisy observations, and the structural and parametric uncertainty of land surface models (LSM). Quite often, wrong conclusions can be drawn because uncorrelated variables may be assumed to have no causal relationship with presupposed predictors. The main goal of this study is to test whether a significant "Granger causality" (Granger 1969) exist between monthly soil moisture fields over Germany and large-scale circulation patterns, characterized by anomalies of sea level pressure over the Northern Hemisphere or geopotential height and atmospheric humidity over Europe. The advantage of this testing framework stems from the fact that it is based on predictability instead of correlation to identify causation, as it is the case with standard correlation-based approaches. Two contrasting modeling paradigms, the land surface NOAH model and the process-based hydrologic model mHM (Samaniego et al. 2012) are employed to estimate daily soil moisture over Germany during the period from 1989 to 2009. WRF/NOAH was forced with ERA-Interim data at the boundary of the EURO-CORDEX Region (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11°. To ease comparison, mHM was also forced with daily precipitation and temperature fields generated by WRF during the same period at 4×4 km resolution. Main physiographic characteristics in NOAH such as land cover and soil texture are represented with a 1×1 km MODIS data set and a single horizon, coarse resolution FAO soil map with 16 soil texture classes, respectively. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) embedded in mHM allows to estimate effective model parameters based on detailed input data (100×100 m) obtained from Corine land cover and soil texture fields for various horizons comprising 72 classes. mHM global parameters, in contrast with those of NOAH, were obtained by closing the water balance in major German river basins. For the "Granger causality" test, variables such as sea level pressure or geopotential height at 500 hPa (dss.ucar.edu/datasets/ds010.0/, data-portal.ecmwf.int/data/d/interim_daily) are used as predictor fields including the lagged values of these variables. Results indicate that the subgrid variability of the land surface properties and the parametrization schemes have greater influence on soil moisture simulations. Mann-Kendall tests performed with mHM data indicated the existence of a negative trend (p-value 5%) in soil moisture during summer months which is the consequence of observed downward trend in precipitation and upward trend in temperature. On the contrary, soil moisture simulations in winter months did not exhibited significant trends. The Granger-causation mechanisms of these trends are under investigation.

  10. Downscaling and assimilating remotely sensed soil moisture data for the TOPLATS model

    NASA Astrophysics Data System (ADS)

    Pan, F.; Peters-Lidard, C.

    2001-05-01

    The sub-grid-scale or sub-field-scale (i.e., <100 meter) soil moisture information can be important for numerical simulation of grid-scale energy and water fluxes and proper representation of runoff generation processes. Recent research suggests that a promising approach to estimate sub-grid scale soil moisture is assimilation of remotely sensed data into fine resolution hydrologic models. Airborne L-band passive microwave sensors flown during recent field campaigns, e.g., Washita'92, Southern Great Plains Hydrology Experiment (SGP)'97, and SGP'99, provide soil moisture products at spatial resolutions of order 100s of meters, which is coarser than the typical fine resolution of hydrologic models such as TOPLATS (e.g., 30m). Future satellite-based soil moisture products will have spatial resolutions of order 10 km; therefore, how to downscale or interpolate coarser resolution data to a finer grid for hydrologic models will become very important. In this talk, we will present three different approaches to deal with this problem: (1) Match the hydrologic model resolution to that of the remotely sensed soil moisture products; (2) Spatially interpolate the remotely sensed soil moisture products to the finer grid of the models; and (3) Match the mean of the modeled soil moisture to the mean of the remotely sensed soil moisture product, preserving the high moments of the modeled soil moisture, without spatial interpolation. For the second method, besides the spatial correlation of soil moisture, we incorporate the correlations between soil moisture and other variables (e.g., precipitation, radiation, land cover, soil, and topography) into our spatial interpolation of remotely sensed soil moisture. Previous studies of soil moisture scaling characteristics by the authors and others are incorporated into the downscaling methodologies. The performance of each approach is evaluated over Washita '92 and SGP97 regions.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The diversity of in situ soil moisture network protocols and instrumentation led to the development of a testbed for comparing in situ soil moisture sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each statio