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Sample records for agricultural soil moisture

  1. 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.

  2. The Temperature Dependence of Soil Moisture Characteristics of Agricultural Soils

    NASA Astrophysics Data System (ADS)

    Salehzadeh, Amir

    1990-01-01

    The temperature dependence of static and dynamic characteristics of four soils: glass beads, Plainfield sand, Plano silt loam, and Elkmound sandy loam were explored. Gain -factor model was employed for quantifying the temperature dependences. The study required novel methods and technologies which were developed and employed for the rapid, and transient measurement of soil-moisture characteristics of these soils. A pressurized 2 cm-high column of soil is sandwiched between two air blocking membranes interfacing outside pressurized water system. Water content (Theta ) is measured with a 2 Curie gamma-ray source combined with a fast detection system giving a statistical accuracy of +/-0.2%. Moisture potential ( Psi) down to -2000 cm was measured with a newly developed "stripper" tensionmeter. While a slowly varying soil-water pressure was imposed on the thin sample through the membranes, firmly held in contact with the soil, water content and moisture -potentials were being monitored in the sample. A plot of water content versus water pressure gave the static characteristics (Theta,Psi ) of soils. An array of tensiometers (between the membranes) allowed measurement of the potential profile; in conjunction with the time-varying water content this permitted measurement of dynamic characteristics, conductivity versus water content (K,Theta). For the (Theta, Psi) characteristics, the measurements indicated that, wholly for glass beads, and largely for sand, the surface tension of pure water governs the temperature response. The temperature dependence of Plano silt loam was largely independent of water content and was roughly five times the temperature dependence of the surface tension of pure water. For Elkmound sandy loam the dependence was complex and not easily explained. Two factors appear to limit further system improvement. (1) A sample thinner than 2 cm faces difficulties of fitting three tensionmeters into the thickness. This limit on the thickness, in turn

  3. Value of Available Global Soil Moisture Products for Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

    2016-04-01

    The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS

  4. Agriculture intensifies soil moisture decline in Northern China

    SciTech Connect

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego; Teuling, Adriann; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; Wang, Liwei; Pan, Xuebiao; Bai, Wei; Niyogi, Dev

    2015-07-09

    Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p<0.01), with a trend of -0.011 to -0.015 m3 m-3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.

  5. Agriculture intensifies soil moisture decline in Northern China.

    PubMed

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego G; Teuling, Adriaan J; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; Wang, Liwei; Pan, Xuebiao; Bai, Wei; Niyogi, Dev

    2015-07-09

    Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983-2012, we find that topsoil (0-50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of -0.011 to -0.015 m(3) m(-3) per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.

  6. Agriculture intensifies soil moisture decline in Northern China

    NASA Astrophysics Data System (ADS)

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego G.; Teuling, Adriaan J.; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; Wang, Liwei; Pan, Xuebiao; Bai, Wei; Niyogi, Dev

    2015-07-01

    Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983-2012, we find that topsoil (0-50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of -0.011 to -0.015 m3 m-3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.

  7. Agriculture intensifies soil moisture decline in Northern China

    DOE PAGES

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; ...

    2015-07-09

    Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p<0.01), with a trend of -0.011 to -0.015 m3 m-3 per decade. Observed discharge declines for the three large river basins are consistentmore » with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.« less

  8. Agriculture intensifies soil moisture decline in Northern China

    PubMed Central

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego G.; Teuling, Adriaan J.; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; Wang, Liwei; Pan, Xuebiao; Bai, Wei; Niyogi, Dev

    2015-01-01

    Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of −0.011 to −0.015 m3 m−3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system. PMID:26158774

  9. Enhancing agricultural forecasting using SMOS surface soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. Classification and soil moisture determination of agricultural fields

    NASA Technical Reports Server (NTRS)

    Vandenbroek, A. C.; Groot, J. S.

    1993-01-01

    During the Mac-Europe campaign of 1991 several SAR (Synthetic Aperature Radar) experiments were carried out in the Flevoland test area in the Netherlands. The test site consists of a forested and an agricultural area with more than 15 different crop types. The experiments took place in June and July (mid to late growing season). The area was monitored by the spaceborne C-band VV polarized ERS-1, the Dutch airborne PHARS with similar frequency and polarization and the three-frequency PP-, L-, and C-band) polarimetric AIRSAR system of NASA/JPL. The last system passed over on June 15, 3, 12, and 28. The last two dates coincided with the overpasses of the PHARS and the ERS-1. Comparison of the results showed that backscattering coefficients from the three systems agree quite well. In this paper we present the results of a study of crop type classification (section 2) and soil moisture determination in the agricultural area (section 3). For these studies we used field averaged Stokes matrices extracted from the AIRSAR data (processor version 3.55 or 3.56).

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

    NASA Astrophysics Data System (ADS)

    Priesack, Eckart; Schuh, Max

    2014-05-01

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

  12. Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

  13. Agricultural terrain scatterometer observations with emphasis on soil moisture variations

    NASA Technical Reports Server (NTRS)

    King, C.

    1973-01-01

    Airborne scatterometer observations were made for agricultural terrain in May and June, 1970 at a NASA test site near Garden City, Kansas. Data from 13.3 GHz and 400 MHz scatterometer were analyzed. It was observed that for incidence angle less than 40 degrees, the 13.3 GHz data showed a difference in backscatter from wet and dry fields of the order of 7 db. The averages of the various crop types were within a spread of only 5 db. Other ground parameters such as cultivation pattern and vegetation row effects showed even less distinguishing characteristics on the backscatter. The 400 MHz data also showed a slight moisture dependency.

  14. Agricultural soil moisture experiment, Colby, Kansas 1978: Measured and predicted hydrological properties of the soil

    NASA Technical Reports Server (NTRS)

    Arya, L. M. (Principal Investigator)

    1980-01-01

    Predictive procedures for developing soil hydrologic properties (i.e., relationships of soil water pressure and hydraulic conductivity to soil water content) are presented. Three models of the soil water pressure-water content relationship and one model of the hydraulic conductivity-water content relationship are discussed. Input requirements for the models are indicated, and computational procedures are outlined. Computed hydrologic properties for Keith silt loam, a soil typer near Colby, Kansas, on which the 1978 Agricultural Soil Moisture Experiment was conducted, are presented. A comparison of computed results with experimental data in the dry range shows that analytical models utilizing a few basic hydrophysical parameters can produce satisfactory data for large-scale applications.

  15. Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural drought is defined as a shortage of moisture in the root zone of plants. Recently available satellite-based remote sensing data have accelerated development of drought early warning system by providing spatially continuous soil moisture information repeatedly at short-term interval. Non...

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

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  18. An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data

    NASA Astrophysics Data System (ADS)

    Carrão, Hugo; Russo, Simone; Sepulcre-Canto, Guadalupe; Barbosa, Paulo

    2016-06-01

    We propose a simple, spatially invariant and probabilistic year-round Empirical Standardized Soil Moisture Index (ESSMI) that is designed to classify soil moisture anomalies from harmonized multi-satellite surface data into categories of agricultural drought intensity. The ESSMI is computed by fitting a nonparametric empirical probability density function (ePDF) to historical time-series of soil moisture observations and then transforming it into a normal distribution with a mean of zero and standard deviation of one. Negative standard normal values indicate dry soil conditions, whereas positive values indicate wet soil conditions. Drought intensity is defined as the number of negative standard deviations between the observed soil moisture value and the respective normal climatological conditions. To evaluate the performance of the ESSMI, we fitted the ePDF to the Essential Climate Variable Soil Moisture (ECV SM) v02.0 data values collected in the period between January 1981 and December 2010 at South-Central America, and compared the root-mean-square-errors (RMSE) of residuals with those of beta and normal probability density functions (bPDF and nPDF, respectively). Goodness-of-fit results attained with time-series of ECV SM values averaged at monthly, seasonal, half-yearly and yearly timescales suggest that the ePDF provides triggers of agricultural drought onset and intensity that are more accurate and precise than the bPDF and nPDF. Furthermore, by accurately mapping the occurrence of major drought events over the last three decades, the ESSMI proved to be spatio-temporal consistent and the ECV SM data to provide a well calibrated and homogenized soil moisture climatology for the region. Maize, soybean and wheat crop yields in the region are highly correlated (r > 0.82) with cumulative ESSMI values computed during the months of critical crop growing, indicating that the nonparametric index of soil moisture anomalies can be used for agricultural drought

  19. Mapping Spatial Moisture Content of Unsaturated Agricultural Soils with Ground-Penetrating Radar

    NASA Astrophysics Data System (ADS)

    Shamir, O.; Goldshleger, N.; Basson, U.; Reshef, M.

    2016-06-01

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

  20. Evaluation of Soil Moisture Derived from Passive Microwave Remote Sensing Over Agricultural Sites in Canada

    NASA Astrophysics Data System (ADS)

    Champagne, C.; McNairn, H.; Berg, A.

    2008-12-01

    Spatial information on soil moisture conditions is a critical agri-environmental variable and can be used alone as a decision support tool for a number of land management decisions, including soil trafficability, seeding options and pesticide applications. Large-area estimations of soil moisture derived from passive microwave sensors are available over Canada from AMSR-E and SSM/I sensors, and in some instances are being used as decision-support tools (AAFC, 2008). These coarse spatial estimates can be used to assess overall conditions on a daily or weekly basis, and potentially be used as a monitoring tool to trigger assessment using higher spatial resolution active microwave sensors. Retrieval algorithms to derive soil moisture from passive microwave brightness temperature produce variable results depending on input frequency and the reliance on ancillary data to estimate vegetation water content and land surface temperature. There is a need to characterize regional errors in these data sets to contextualize their operational use and facilitate integration of these data sets into land surface models. Several soil moisture information products derived from passive microwave remote sensing were evaluated for their potential use in assessing moisture conditions over agricultural regions in Canada. Soil wetness maps derived from SSM/I (Basist et al., 2001), AMSR-E NASA soil moisture products (Njoku, 2008) and two AMSR-E soil moisture products derived using C and X band frequencies using an alternative retrieval algorithm (Owe et al., 2008) were evaluated over agricultural regions in Canada. Evaluations were based on in-situ measurements from sites in Saskatchewan, Manitoba and Ontario for spring and fall periods in 2007 and 2008. Differences in the satellite climatology relative to surface soil moisture observations in Canada will be discussed.

  1. Spatial variability of soil moisture regimes at different scales: implications in the context of precision agriculture.

    PubMed

    Voltz, M

    1997-01-01

    Precision agriculture is based on the concept of soil-specific management, which aims to adapt management within a field according to specific site conditions in order to maximize production and minimize environmental damage. This paper examines how the nature and sources of variation in soil moisture regimes affect our ability to simulate soil water behaviour within a field with adequate precision in order to advise optimal soil-specific management. Field examples of variation in soil moisture regimes are described to illustrate the difficulties involved. A discussion identifies three main points. First, it is recognized that the current modelling approaches to soil moisture regimes do not sufficiently account for local heterogeneities in soil and crop characteristics such as soil morphology and rooting patterns. Second, the estimation of within-field variation of soil hydraulic properties is difficult because of large short-range variation of the properties and general lack of observed data; one way to overcome this problem is to seek new measurement techniques or to find easy-to-measure auxiliary variables spatially correlated to the variables of interest. Last, as pollution impacts often become noticeable to society at scales larger than the scale of agricultural management, hydrological modelling can serve for linking both scales and advising agricultural practices that minimize undesirable pollution effects.

  2. Utilization of vegetation indices to improve microwave soil moisture estimates over agricultural lands

    NASA Technical Reports Server (NTRS)

    Theis, S. W.; Blanchard, B. J.; Newton, R. W.

    1984-01-01

    A technique is presented by means of which visible/near-IR data are used to develop corrections in remotely sensed microwave soil moisture signals, in order to account for vegetation effects. Visible/IR data collected with the NASA NS001 Thematic Mapper Simulator were used to calculate the Perpendicular Vegetation Index (PVI), which was then related to the change of sensitivity of the microwave measurement to surface soil moisture. Effective estimation of soil moisture in the presence of vegetation can be made with L-band microwave radiometers and visible/IR sensors when the PVI is lower than 4.3. This technique offers a means for the estimation of moisture from a space platform over many agricultural areas, without expensive ground data collection.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong

  4. Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale

  5. Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

    2014-01-01

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. 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.

  8. Compressive response of some agricultural soils influenced by the mineralogy and moisture

    NASA Astrophysics Data System (ADS)

    Ajayi, A. E.; Dias Junior, M. S.; Curi, N.; Oladipo, I.

    2013-09-01

    This study aimed to investigate the mineralogy, moisture retention, and the compressive response of two agricultural soils from South West Nigeria. Undisturbed soil cores at the A and B horizons were collected and used in chemical and hydrophysical characterization and confined compression test. X-ray diffractograms of oriented fine clay fractions were also obtained. Our results indicate the prevalence of kaolinite minerals relating to the weathering process in these tropical soils. Moisture retention by the core samples was typically low with pre-compression stress values ranging from50 to 300 kPa at both sites. Analyses of the shape of the compression curves highlight the influence of soil moisture in shifts from the bi-linear to S-shaped models. Statistical homogeneity test of the load bearing capacity parameters showed that the soil mineralogy influences the response to loading by these soils. These observations provide a physical basis for the previous classification series of the soils in the studied area. We showed that the internal strength attributes of the soil could be inferred from the mineralogical properties and stress history. This could assist in decisions on sustainable mechanization in a datapoor environment.

  9. Evaluating the Performance of a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Han, E.; Crow, W. T.; Holmes, T. R.; Bolten, J. D.

    2013-12-01

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, we evaluates a soil moisture assimilation system for agricultural drought monitoring by benchmarking each component of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputs/output) as the full component. Lagged soil moisture/NDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities and/or complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system. First, the non-linear LPRM retrieval algorithm does not appear to add much additional predictive information for future NDVI compared to the simple linear benchmark model comprised of initial AMSR-E observations (horizontally and vertically polarized brightness temperatures and surface temperature). Second, the Palmer model performed worse than the purely linear prognostic model (Antecedent Precipitation Index model) in predicting future vegetation condition. This result points out that the saturation threshold of soil layers in the modern LSMs for runoff generation hinders maximum utilization of meteorological input information for agricultural drought monitoring. As to the assimilation algorithm, better performance of the

  10. 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...

  11. Evaluating the Potential Use of Remotely-Sensed and Model-Simulated Soil Moisture for Agricultural Drought Risk Monitoring

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    Current two datasets provide spatial and temporal resolution of soil moisture at large-scale: the remotely-sensed soil moisture retrievals and the model-simulated soil moisture products. Drought monitoring using remotely-sensed soil moisture is emerging, and the soil moisture simulated using land surface models (LSMs) have been used operationally to monitor agriculture drought in United States. Although these two datasets yield important drought information, their drought monitoring skill still needs further quantification. This study provides a comprehensive assessment of the potential of remotely-sensed and model-simulated soil moisture data in monitoring agricultural drought over the Columbia River Basin (CRB), Pacific Northwest. Two satellite soil moisture datasets were evaluated, the LPRM-AMSR-E (unscaled, 2002-2011) and ESA-CCI (scaled, 1979-2013). The USGS Precipitation Runoff Modeling System (PRMS) is used to simulate the soil moisture from 1979-2011. The drought monitoring skill is quantified with two indices: drought area coverage (the ability of drought detection) and drought severity (according to USDM categories). The effects of satellite sensors (active, passive), multi-satellite combined, length of climatology, climate change effect, and statistical methods are also examined in this study.

  12. Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

    NASA Astrophysics Data System (ADS)

    McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

    2011-12-01

    The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the

  13. A model of the 0.4-GHz scatterometer. [used for agriculture soil moisture program

    NASA Technical Reports Server (NTRS)

    Wu, S. T.

    1978-01-01

    The 0.4 GHz aircraft scatterometer system used for the agricultural soil moisture estimation program is analyzed for the antenna pattern, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principal, system sensitivity, data handling, and resolution cell length requirements are also described. The backscattering characteristics of the agriculture scenes are contained in the form of the functional dependence of the backscattering coefficient on the incidence angle. The substantial gains of the cross-polarization term of the horizontal and vertical antennas have profound effects on the cross-polarized backscattered signals. If these signals are not corrected properly, large errors could result in the estimate of the cross-polarized backscattering coefficient. It is also necessary to correct the variations of the aircraft parameters during data processing to minimize the error in the 0 degree estimation. Recommendations are made to improve the overall performance of the scatterometer system.

  14. Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

    NASA Astrophysics Data System (ADS)

    Cosh, M. H.; Prueger, J. H.; Goodman, F.; Jackson, T. J.

    2009-12-01

    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 requirement a full sky view to be representative of the location. Therefore, these stations are located along field boundaries or in non-representative sites with regards to soil type or soil moisture. Landowners are also less willing to sacrifice productive acreage within their fields for scientific monitoring without compensation. A solution has been developed in the Walnut Creek watershed near Ames, Iowa. Small temporary soil moisture stations are installed within the corn and soybean fields which dominate the landscape. Land owners and operators are able to move the stations if necessary, such as during planting and harvesting or field tillage. This network design results in a non-continuous, but representative watershed average. Begun in 2006, nine stations have been recording the surface soil moisture (~5 cm), which is commonly used in the validation of the AMSR-E instrument. The temporal stability of this network is evaluated and inter-seasonal consistency is addressed. A comparison is also made of the remote sensing products from AMSR-E and the Walnut Creek network during its deployment. It is expected that this network will continue to support soil moisture remote sensing into the future, including the SMOS and SMAP satellite missions.

  15. 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

  16. Agricultural Drought Assessment In Latin America Based On A Standardized Soil Moisture Index

    NASA Astrophysics Data System (ADS)

    Carrao, Hugo; Russo, Simone; Sepulcre, Guadalupe; Barbosa, Paulo

    2013-12-01

    We propose a relatively simple, spatially invariant and probabilistic year-round Standardized Soil Moisture Index (SSMI) that is designed to estimate drought conditions from satellite imagery data. The SSMI is based on soil moisture content alone and is defined as the number of standard deviations that the observed moisture at a given location and timescale deviates from the long- term normal conditions. Specifically, the SSMI is computed by fitting a non-parametric probability distribution function to historical soil moisture records and then trans- forming it into a normal distribution with a mean of zero and standard deviation of one. Negative standard normal values indicate dry conditions and positive values indicate wet conditions. To evaluate the applicability of the SSMI, we fitted empirical and normal cumulative distribution functions (ECDF and nCDF) to 32-years of averaged soil moisture amounts derived from the Essential Climate Variable (ECV) Soil Moisture (SM) dataset, and compared the root-mean-squared errors of residuals. SM climatology was calculated on a 0.25° grid over Latin America at timescales of 1, 3, 6, and 12 months for the long-term period of 1979-2010. Results show that the ECDF fits better the soil moisture data than the nCDF at all timescales and that the negative SSMI values computed with the non-parametric estimator accurately identified the temporal and geographic distribution of major drought events that occurred in the study area.

  17. Improving soil moisture simulation to support Agricultural Water Resource Management using Satellite-based water cycle observations

    NASA Astrophysics Data System (ADS)

    Gupta, Manika; Bolten, John; Lakshmi, Venkat

    2016-04-01

    Efficient and sustainable irrigation systems require optimization of operational parameters such as irrigation amount which are dependent on the soil hydraulic parameters that affect the model's accuracy in simulating soil water content. However, it is a scientific challenge to provide reliable estimates of soil hydraulic parameters and irrigation estimates, given the absence of continuously operating soil moisture and rain gauge network. For agricultural water resource management, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally (Wang and Qu 2009). In the current study, flood irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches below a threshold of 25%, 50% and 75% with respect to the maximum available water capacity (difference between field capacity and wilting point) and applied until the top layer is saturated. An additional important criterion needed to activate the irrigation scheme is to ensure that it is irrigation season by assuming that the greenness vegetation fraction (GVF) of the pixel exceed 0.40 of the climatological annual range of GVF (Ozdogan et al. 2010). The main hypothesis used in this study is that near-surface remote sensing soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately inverted, it would provide field capacity and wilting point soil moisture, which may be representative of that basin. Thus, genetic algorithm inverse method is employed to derive the effective parameters and derive the soil moisture deficit for the root zone by coupling of AMSR-E soil moisture with the physically based hydrological model. Model performance is evaluated using MODIS

  18. A Review of Developments in Agricultural Science Applicable to Military Soil Moisture Prediction Requirements.

    DTIC Science & Technology

    1985-06-01

    horizontally into untapped soil volumes. Resistance to vapor diffusion from leaf stomata is increased as moisture stress increases due to a change of...distributed root, branch, and leaf systems. The roots access water from deeper soil layers than is available for surface evapora- tion, while the

  19. The soil moisture regimes beneath forest and an agricultural crop in southern India--Measurement and modelling

    SciTech Connect

    Harding, R.J.; Hall, R.L.; Swaminath, M.H.; Murthy, K.V.

    1992-12-31

    The environmental effects of plantations of fast growing tree species has been a subject of some controversy in recent years. Extensive soil moisture measurements were made at three sites in Karnataka, southern India. At each site measurements were made beneath a number of vegetation types. These included fast growing tree species (Eucalyptus, Casuarina and Leucaena), degraded natural forest and an agricultural crop (ragi). The measurements indicate that beneath mature forest the available soil water is exhausted towards the end of the dry season, usually by March. The soil only becomes completely wetted if the subsequent monsoon has above average rainfall; during the weak monsoon of 1989 the soil remained approximately 150 mm below field capacity. After the monsoon (and during breaks in the monsoon) soil moisture depletion is between three and five mm per day. This rate decreases as the soil drys out. All the mature forest types show a similar soil water regime. This contrasts strongly with that of the agricultural crop, which shows much smaller changes. A range of soil water accounting models was applied to these data. The most successful are those which use the Penman formulation to estimate the potential evaporation and include a two-layer soil water depletion model. The more general Penman-Monteith formulation was also tested.

  20. Nitrate Distribution in Soil Moisture and Groundwater with Intensive Plantation Management on Abandoned Agricultural Land

    SciTech Connect

    Williams, T.M.

    1998-01-01

    Paper outlines nitrate leaching results of loblolly pine and sweet gum that were grown with irrigation, continuous fertilization and insect pest control on a year old abandoned peanut field. Wells and tension lysimeters were used to measure nitrate in soil moisture and groundwater on three replicate transects for two years. Groundwater nitrate concentration beneath the minimum treatment was much higher than the maximum treatment and old field. All three treatments often exceeded the drinking water standard. Forest and lake edge had low levels while the soil moisture nitrate concentrations in the two plantations treatments were much higher than the old field.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  2. Improving World Agricultural Supply and Demand Estimates by Integrating NASA Remote Sensing Soil Moisture Data into USDA World Agricultural Outlook Board Decision Making Environment

    NASA Astrophysics Data System (ADS)

    Teng, W. L.; de Jeu, R. A.; Doraiswamy, P. C.; Kempler, S. J.; Shannon, H. D.

    2009-12-01

    A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by developing monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main objective of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE. Soil moisture is a primary data gap at WAOB. Soil moisture data, generated by the Land Parameter Retrieval Model (LPRM, developed by NASA GSFC and Vrije Universiteit Amsterdam) and customized to WAOB's requirements, will be directly integrated into GLADSE, as well as indirectly by first being integrated into USDA Agricultural Research Service (ARS)'s Environmental Policy Integrated Climate (EPIC) crop model. The LPRM-enhanced EPIC will be validated using three major agricultural regions important to WAOB and then integrated into GLADSE. Project benchmarking will be based on retrospective analyses of WAOB's analog year comparisons. The latter are between a given year and historical years with similar weather patterns. WAOB is the focal point for economic intelligence within the USDA. Thus, improving WAOB's agricultural estimates by integrating NASA satellite observations and model outputs will visibly demonstrate the value of NASA resources and maximize the societal benefits of NASA investments.

  3. Understanding Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Soil moisture modeling review

    NASA Technical Reports Server (NTRS)

    Hildreth, W. W.

    1978-01-01

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

  5. Early Soil Moisture Field Experiments

    NASA Astrophysics Data System (ADS)

    Schmugge, T.

    2008-12-01

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

  6. Soil-moisture sensors and irrigation management

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Joint use of soil moisture and vegetation growth condition by remote sensing on the agricultural drought monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Yang, Siquan; Huang, He; He, Haixia; Li, Suju; Cui, Yan

    2015-12-01

    Remote sensing is one of important methods on the agricultural drought monitoring for its long-term and wide-area observations. The detection of soil moisture and vegetation growth condition are two widely used remote sensing methods on that. However, because of the time lag in the impact of water deficit on the crop growth, it is difficulty to indicate the severity of drought by once monitoring. It also cannot distinguish other negative impact on crop growth such as low temperature or solar radiation. In this paper, the joint use of soil moisture and vegetation growth condition detections was applied on the drought management during the summer of 2013 in Liaoning province, China, in which 84 counties were affected by agricultural drought. MODIS vegetation indices and land surface temperature (LST) were used to extract the drought index. Vegetation Condition Index (VCI), which only contain the change in vegetation index, and Vegetation Supply Water Index (VSWI), which combined the information of vegetation index and land surface temperature, were selected to compare the monitoring ability on drought during the drought period in Liaoning, China in 2014. It was found that VCI could be a good method on the loss assessment. VSWI has the information on the change in LST, which can indicate the spatial pattern of drought and can also be used as the early warning method in the study.

  8. From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture

    NASA Astrophysics Data System (ADS)

    Vico, Giulia; Porporato, Amilcare

    2011-02-01

    With vast regions already experiencing water shortages, it is becoming imperative to manage sustainably the available water resources. As agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements, it is particularly important to develop simple, widely applicable models of irrigation water needs for short- and long-term water resource management. Such models should synthetically provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability. Here we consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. We obtain mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount, and compute water requirements as a function of climate, crop, and soil parameters. These results provide the necessary starting point for a full assessment of irrigation strategies, with reference to sustainability, productivity, and profitability, developed in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and net profit. Adv Water Resour 2011;34(2):272-81].

  9. Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data to Improve USDA's World Agricultural Supply and Demand Estimates

    NASA Technical Reports Server (NTRS)

    Teng, William; Shannon, Harlan; Mladenova, Iliana; Fang, Fan

    2010-01-01

    A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by coordinating monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main goal of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE (See diagram below). Soil moisture is currently a primary data gap at WAOB.

  10. Satellite-based GNSS-R observations from TDS-1 for soil moisture studies in agricultural vegetation landscapes

    NASA Astrophysics Data System (ADS)

    Liu, P. W.; Clarizia, M. P.; Judge, J.; Camps, A.; Ruf, C. S.; Bongiovanni, T. E.

    2015-12-01

    Soil moisture (SM) is a critical factor governing the water and energy fluxes at the land surface that are important for near-term climate forecasting, drought monitoring, crop yield estimation, and better water resources management. Remotely sensed observations at microwave frequencies are the most sensitive to changes of water in the soil. Particularly, frequencies at L-band (1-2 GHz) have been widely used for SM studies under the vegetated land covers because of their minimal atmospheric interference and attenuation by vegetation, allowing observations from the soil surface. In addition to current satellite based microwave sensors, such as the Soil Moisture Active Passive (SMAP) missions, the Global Navigation Satellite System-Reflectometry technique is capable of observing the GNSS signal reflected from the terrain that contains combined information of soil and vegetation characteristics. The technique has recently attracted attention for global SM monitoring because its receiver is small in size and light weight and can be on board the low orbit, small satellites with low power consumption and low cost. Therefore the GNSS-R remote sensing may lead to affordable multi-satellite constellations that enable improved temporal resolution for highly dynamic hydrologic conditions. The current UK Technology Demonstration Satellite (TDS-1) has been providing global GNSS-R observations since September 2014 for experimental purposes and the receiver is accessed and operated for 2 days during every 8-day cycle. In the near future, the NASA Cyclone GNSS (CYGNSS) mission, scheduled to be launched in 2016, will consist of 8 satellites observing GPS L1 signal at a frequency of 1.5754 GHz with a spatial resolution of 10-25 km and a temporal resolution of < 12 hours. The goal of this study is to understand the impacts of SM and characteristics of agricultural vegetation on the forward scattering mechanisms of satellite-based GNSS-R observations. The GNSS-R observations from TDS

  11. Toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus crypticus changes under a global warming perspective: Variations in air temperature and soil moisture content.

    PubMed

    González-Alcaraz, M Nazaret; van Gestel, Cornelis A M

    2016-12-15

    This study aimed to assess how the current global warming perspective, with increasing air temperature (20°C vs. 25°C) and decreasing soil moisture content (50% vs. 30% of the soil water holding capacity, WHC), affected the toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus crypticus. Enchytraeids were exposed for 21d to a dilution series of the agricultural soil with Lufa 2.2 control soil under four climate situations: 20°C+50% WHC (standard conditions), 20°C+30% WHC, 25°C+50% WHC, and 25°C+30% WHC. Survival, reproduction and bioaccumulation of As, Cd, Co, Cu, Fe, Mn, Ni, Pb and Zn were obtained as endpoints. Reproduction was more sensitive to both climate factors and metal(loid) pollution. High soil salinity (electrical conductivity~3dSm(-1)) and clay texture, even without the presence of high metal(loid) concentrations, affected enchytraeid performance especially at drier conditions (≥80% reduction in reproduction). The toxicity of the agricultural soil increased at drier conditions (10% reduction in EC10 and EC50 values for the effect on enchytraeid reproduction). Changes in enchytraeid performance were accompanied by changes in As, Fe, Mn, Pb and Zn bioaccumulation, with lower body concentrations at drier conditions probably due to greater competition with soluble salts in the case of Fe, Mn, Pb and Zn. This study shows that apart from high metal(loid) concentrations other soil properties (e.g. salinity and texture) may be partially responsible for the toxicity of metal(loid)-polluted soils to soil invertebrates, especially under changing climate conditions.

  12. 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.

  13. Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this ...

  14. 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

  15. SOIL moisture data intercomparison

    NASA Astrophysics Data System (ADS)

    Kerr, Yann; Rodriguez-Frenandez, Nemesio; Al-Yaari, Amen; Parens, Marie; Molero, Beatriz; Mahmoodi, Ali; Mialon, Arnaud; Richaume, Philippe; Bindlish, Rajat; Mecklenburg, Susanne; Wigneron, Jean-Pierre

    2016-04-01

    The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. Subsequently, the satellite has been in operation for over 6 years while the retrieval algorithms from Level 1 to Level 2 underwent significant evolutions as knowledge improved. Other approaches for retrieval at Level 2 over land were also investigated while Level 3 and 4 were initiated. In this présentation these improvements are assessed by inter-comparisons of the current Level 2 (V620) against the previous version (V551) and new products either using neural networks or Level 3. In addition a global evaluation of different SMOS soil moisture (SM) products is performed comparing products with those of model simulations and other satellites (AMSR E/ AMSR2 and ASCAT). Finally, all products were evaluated against in situ measurements of soil moisture (SM). The study demonstrated that the V620 shows a significant improvement (including those at level1 improving level2)) with respect to the earlier version V551. Results also show that neural network based approaches can yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved while RFI sources in several areas of the world are significantly reduced. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.

  16. 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.

  17. Microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  18. Passive microwave soil moisture research

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Oneill, P. E.; Wang, J. R.

    1985-01-01

    The AgRISTARS Soil Moisture Project has made significant progress in the quantification of microwave sensor capabilities for soil moisture remote sensing. The 21-cm wavelength has been verified to be the best single channel for radiometric observations of soil moisture. It has also been found that other remote sensing approaches used in conjunction with L-band passive data are more successful than multiple wavelength microwave radiometry in this application. AgRISTARS studies have also improved current understanding of noise factors affecting the interpretability of microwave emission data. The absorption of soil emission by vegetation has been quantified, although this effect is less important than absorption effects for microwave radiometry.

  19. Remote sensing as a tool in assessing soil moisture

    NASA Technical Reports Server (NTRS)

    Carlson, C. W.

    1978-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1980-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Many decisions in agriculture are conditional to soil moisture. For instance in wet conditions, farming operations as soil tillage, organic waste spreading or harvesting may lead to degraded results and/or induce soil compaction. The development of a tool that allows the estimation of soil moisture is useful to help farmers to organize their field work in a context where farm size tends to increase as well as the need to optimize the use of expensive equipments. Soil water transfer models simulate soil moisture vertical profile evolution. These models are highly sensitive to site dependant parameters. A method to implement the mechanistic soil water and heat flow model (the TEC model) in a context of limited information (soil texture, climatic data, soil organic carbon) is proposed [Chanzy et al., 2008]. In this method the most sensitive model inputs were considered i.e. soil hydraulic properties, soil moisture profile initialization and the lower boundary conditions. The accuracy was estimated by implementing the method on several experimental cases covering a range of soils. Simulated soil moisture results were compared to soil moisture measurements. The obtained accuracy in surface soil moisture (0-30 cm) was 0.04 m3/m3. When a few soil moisture measurements are available (collected for instance by the farmer using a portable moisture sensor), significant improvement in soil moisture accuracy is obtained by assimilating the results into the model. Two assimilation strategies were compared and led to comparable results: a sequential approach, where the measurement were used to correct the simulated moisture profile when measurements are available and a variational approach which take moisture measurements to invert the TEC model and so retrieve soil hydraulic properties of the surface layer. The assimilation scheme remains however heavy in terms of computing time and so, for operational purposed fast code should be taken to simulate the soil moisture as with the

  2. Passive microwave soil moisture research

    NASA Technical Reports Server (NTRS)

    Schmugge, T.; Oneill, P. E.; Wang, J. R.

    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, a discussion is provided of 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 interpretability of microwave emission measurements. While determining that a 21-cm wavelength radiometer was the best single sensor for soil moisture research, these studies demonstrated that a multisensor approach will provide more accurate soil moisture information for a wider range of naturally occurring conditions.

  3. Soil Moisture Estimation Using Hyperspectral SWIR Imagery

    NASA Astrophysics Data System (ADS)

    Lewis, D.

    2007-12-01

    The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations

  4. Root-zone soil moisture estimation from assimilation of downscaled Soil Moisture and Ocean Salinity data

    NASA Astrophysics Data System (ADS)

    Dumedah, Gift; Walker, Jeffrey P.; Merlin, Olivier

    2015-10-01

    The crucial role of root-zone soil moisture is widely recognized in land-atmosphere interaction, with direct practical use in hydrology, agriculture and meteorology. But it is difficult to estimate the root-zone soil moisture accurately because of its space-time variability and its nonlinear relationship with surface soil moisture. Typically, direct satellite observations at the surface are extended to estimate the root-zone soil moisture through data assimilation. But the results suffer from low spatial resolution of the satellite observation. While advances have been made recently to downscale the satellite soil moisture from Soil Moisture and Ocean Salinity (SMOS) mission using methods such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh), the assimilation of such data into high spatial resolution land surface models has not been examined to estimate the root-zone soil moisture. Consequently, this study assimilates the 1-km DisPATCh surface soil moisture into the Joint UK Land Environment Simulator (JULES) to better estimate the root-zone soil moisture. The assimilation is demonstrated using the advanced Evolutionary Data Assimilation (EDA) procedure for the Yanco area in south eastern Australia. When evaluated using in-situ OzNet soil moisture, the open loop was found to be 95% as accurate as the updated output, with the updated estimate improving the DisPATCh data by 14%, all based on the root mean square error (RMSE). Evaluation of the root-zone soil moisture with in-situ OzNet data found the updated output to improve the open loop estimate by 34% for the 0-30 cm soil depth, 59% for the 30-60 cm soil depth, and 63% for the 60-90 cm soil depth, based on RMSE. The increased performance of the updated output over the open loop estimate is associated with (i) consistent estimation accuracy across the three soil depths for the updated output, and (ii) the deterioration of the open loop output for deeper soil depths. Thus, the

  5. Derivation of Soil Moisture Patterns from a simple Soil Moisture Index

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Soil moisture and its spatio-temporal pattern is one of the main drivers in complex soil-vegetation-atmosphere exchange processes. In order to observe long-term patterns of surface soil moisture, we analyzed a historical data set of ERS SAR (synthetic aperture radar) data using 85 ERS scenes from 1995-2003 for the Rur catchment (2364 km2) in Western Germany. The ERS satellites operated in C-band and single-channel VV polarization. To derive surface soil moisture from the microwave backscatter intensity, the influence of surface roughness and vegetation biomass on the backscatter must be taken into account. Thus, a simple soil moisture index was developed to retrieve semi-quantitative information about spatial soil moisture patterns with a simple yet robust approach. By using data from all available scenes for each month of the year, histograms of σ0-values for each agricultural land use class (cereals, sugar beet, pasture) were generated. Within each of these histograms, the influence of biomass and surface roughness on backscatter is assumed to be constant. Thus, changes in backscatter intensity are due to changes in surface soil moisture. Since the histograms are based on data from 8 years, we assume that each histogram contains pixels representing the wet and the dry soil moisture state. An index was spanned between high and low backscatter values, identifying wet and dry areas. By using soil texture information of the given location, the qualitative index can be translated into volumetric soil moisture. The resulting soil moisture maps were compared to precipitation data from nearby meteorological stations.

  6. From the sprinkler to satellite: Combining fixed and mobile cosmic-ray neutron probes for realtime multiscale monitoring of soil moisture in agricultural systems

    NASA Astrophysics Data System (ADS)

    Franz, T. E.; Avery, W. A.; Finkenbiner, C. E.

    2015-12-01

    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 various scales by combining fixed and roving cosmic-ray neutron probes at four study sites across an East-West precipitation gradient overtopping the High Plains Aquifer (HPA). Each of the four study sites consisted of coarse scale mapping of the entire ~12 by 12 km domain and detailed mapping of 1 quarter section (0.8 by 0.8 km) agricultural field. By using a simplistic data merging technique we are able to produce a statistical daily soil moisture product at a variety of key spatial scales in support of irrigation water management technology: the individual sprinkler (~102 m2) for variable rate irrigation, the individual pie slice (~103 m2) for variable speed irrigation, and the quarter section (0.64 km2) for uniform rate irrigation. In addition, we are able to provide a daily soil moisture product over the 144 km2 study area at a variety of key remote sensing scales 1, 9, and 144 km2. These products can be used to support SMAP/SMOS through calibration, validation, and value addition by statistical downscaling. Future work could include larger scale monitoring in support of GRACE total water storage calculations in the HPA or other key groundwater resource locations by incorporating existing COSMOS sites or establishment of new networks.

  7. Agriculture: Soils

    EPA Pesticide Factsheets

    Productive soils, a favorable climate, and clean and abundant water resources are essential for growing crops, raising livestock, and for ecosystems to continue to provide the critical provisioning services that humans need.

  8. Correlation of microwave sensor returns with soil moisture

    NASA Technical Reports Server (NTRS)

    Taube, D. W.; Theis, S. W.

    1984-01-01

    Microwave sensor soil data were collected by aircraft over agricultural croplands. Multiple incident angle scatterometer data (13.3, 4.75, 1.6 and 0.4 GHz), passive radiometer data (L and C-band), and soil moisture ground truth measurements were collected coincidentally. Each sensor and angle of incidence was linearly analyzed against the measured soil moisture. For bare agricultural soils, the optimal single sensor for soil moisture preduction is the L-band passive radiometer. The effects of vegetation and differing surface roughness prove significant. When both bare and vegetated surfaces were studied, the masking due to the vegetation renders the single sensor approach ineffective in soil moisture prediction. Multisensor techniques are necessary to remotely measure soil moisture when a priori knowledge of vegetation is not available.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  10. Soil Moisture Monitoring at Watershed Scale in Eastern India

    NASA Astrophysics Data System (ADS)

    Panda, R. K.

    2015-12-01

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

  11. Remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T.

    1976-01-01

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

  12. Estimation of Surface Soil Moisture Using Fractal

    NASA Astrophysics Data System (ADS)

    Chen, Yen Chang; He, Chun Hsuan

    2016-04-01

    This study establishes the relationship between surface soil moisture and fractal dimension. The surface soil moisture is one of important factors in the hydrological cycle of surface evaporation. It could be used in many fields, such as reservoir management, early drought warning systems, irrigation scheduling and management, and crop yield estimations. Soil surface cracks due to dryness can be used to describe drought conditions. Soil cracking phenomenon and moisture have a certain relationship, thus this study makes used the fractal theory to interpret the soil moisture represented by soil cracks. The fractal dimension of surface soil cracking is a measure of the surface soil moisture. Therefore fractal dimensions can also be used to indicate how dry of the surface soil is. This study used the sediment in the Shimen Reservoir to establish the fractal dimension and soil moisture relation. The soil cracking is created under the control of temperature and thickness of surface soil layers. The results show the increase in fractal dimensions is accompanied by a decreases in surface soil moisture. However the fractal dimensions will approach a constant even the soil moisture continually decreases. The sigmoid function is used to fit the relation of fractal dimensions and surface soil moistures. The proposed method can be successfully applied to estimate surface soil moisture. Only a photo taken from the field is needed and is sufficient to provide the fractal dimension. Consequently, the surface soil moisture can be estimated quickly and accurately.

  13. Soil Moisture and Agromet Models

    DTIC Science & Technology

    1981-03-01

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

  14. Soil Moisture Retrieval from Aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Evaluating ESA CCI soil moisture in East Africa

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  16. Soil Moisture State and Hydrologic Process

    NASA Astrophysics Data System (ADS)

    Western, A. W.; Grayson, R. B.; Blöschl, G.; Wilson, D.; Longobardi, A.; Villani, P.; Duncan, M.

    It has long been recognized that soil moisture has a key role in controlling evapo- transpiration during dryer periods, as well as runoff processes, particularly saturation excess runoff. The temporal and spatial variability of moisture can be an important influence on the temporal and spatial characteristics of these processes. More recently, the role of soil moisture in controlling lateral flow processes has re- ceived close attention, with switching between persistent dry and wet states leading to switches between controls on spatial patterns of soil moisture and consequent changes in runoff behaviour. In this paper we will review results on the spatial and temporal variability of soil moisture at the small catchment scale, concentrating in particular on dominant controls and temporal changes in dominant controls. We will discuss the climatic and catchment characteristics under which switching between dominant controls is likely. We will also present results relating spatial soil moisture behaviour to soil moisture state and relating rainfall-runoff response to moisture state: in particular we investi- gated the relationships between the basin soil moisture dynamic and the occurrence of very extreme flood events. The spatial probability density function of soil moisture is bounded by wilting point and porosity. This bounding combined with catchment processes leads to a strong link between spatial variance and spatial mean soil mois- ture, with an initial increase in variance followed by a decrease as mean soil moisture increases from wilting point to saturation. Changes in the spatial control of soil mois- ture and the relationship between soil moisture and terrain also occur as the spatial controls on the soil moisture pattern change in response to mean soil moisture. Strong links between the changes in the spatial characteristics of soil moisture will be demon- strated and the potential of measurements of soil moisture to provide information on catchment state

  17. SMOS CATDS level 3 Soil Moisture products

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    The ESA's (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission, operating since november 2009, is the first satellite dedicated to measuring surface soil moisture and ocean salinity. The CNES (Centre National d'Etudes Spatiales) has developed a ground segment for the SMOS data, known as the CATDS (Centre Aval de Traitement des Données SMOS). Operational since June 2011, it provides data referred to as level 3 products at different time resolutions: daily products, 3 days global products insuring a complete coverage of the Earth surface, 10-days composite products, and monthly averages products. These products are presented in the NetCDF format on the EASE grid (Equal Area Scalable Earth grid) with a spatial resolution of ~ 25*25 km2. Having global maps at different time resolutions is of interest for different applications such as agriculture, water management, climatic events (especially droughts and floods) or climatology. The soil moisture level 3 algorithm is based on ESA's (European Space Agency) level 2 retrieval scheme with the improvement of using several overpasses (3 at most) over a 7-days window. The benefit of using many revisits is expected to improve the retrieved soil moisture. Along with the surface soil moisture, other geophysical parameters are retrieved such as the vegetation optical depth or the dielectric constant of the surface. The aim of this communication is to present the first results from the CATDS dataset and all the different data available. Comparisons with in situ data at different sites will be presented to assess the quality of these data. A comparison with the ESA level 2 SMOS products will also be shown to better understand the difference between these dataset, in terms of quality, coverage, applications and use. We will also present how the CATDS data can capture some special events. For instance, the dataset will be compared with meteorological events (rain events), or extreme events such as droughts or

  18. The Temperature in Microwave Soil Moisture Retrieval

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Research on the Spatial Variability of Soil Moisture

    NASA Astrophysics Data System (ADS)

    Zhang, Changli; Liu, Shuqiang; Zhang, Xianyue; Tan, Kezhu

    China is a country seriously suffering from the lack of water resource, especially the north of China (a dense area) where there are more agricultural production than other places in China. Therefore, some have become most important problems which should be settled down right now for precision agriculture: saving the water of agriculture, optimizing the water for cropland as well as making use of soil moisture effectively. To realise the potential of soil-moisture, protect the water source , strengthen the management of the soil moisture of farm, design the irrigation and drainage, monitor the soil-moisture, etc. ,the data collection of soil moisture and the study on how to could provide the far-reaching and academic significance of guidance together with higher regional and practical use value. The IDW, Spline and Kriging in the Spatial Analyst of ArcGIS 9.0 are applied on drawing the distributing map of soil moisture and it also offers the theoretical foundation for the connection between studying soil moisture and enhancing the yield.

  20. 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.

  1. NASA Soil Moisture Active Passive (SMAP) Applications

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  2. Role of soil moisture in maintaining droughts

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  3. Modeling soil moisture memory in savanna ecosystems

    NASA Astrophysics Data System (ADS)

    Gou, S.; Miller, G. R.

    2011-12-01

    Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants

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

    NASA Astrophysics Data System (ADS)

    Kanniah, Kasturi; Siang, Kang Chuen

    2016-07-01

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

  5. Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  6. 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), ...

  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. Studying dynamics of soil moisture patterns

    NASA Astrophysics Data System (ADS)

    Balcerak, Ernie

    2012-11-01

    Soil moisture variations in space and time are important to the hydrological cycle. To better understand the dynamics of the various factors affecting soil moisture patterns, Rosenbaum et al. conducted a comprehensive study in the small Wüstebach catchment in Germany, using a wireless sensor network to monitor soil moisture with high temporal and spatial resolution and broad coverage. They found large variations in spatial soil moisture patterns, which depended on soil depth and catchment wetness. Soil moisture patterns also changed seasonally and during single wetting and drying episodes. The authors showed how soil moisture variations are controlled by a wide range of factors including soil properties, topography, vegetation, groundwater, and rainfall. (Water Resources Research, doi:10.1029/2011WR011518, 2012)

  9. Microwave Soil Moisture Retrieval Under Trees

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  10. Depression of soil moisture freezing point

    SciTech Connect

    Fedorov, V.I.

    1996-12-01

    Certain criteria for freezing temperature of clay soil have been found which are a relative moisture content at the soil liquid limit (W/W{sub L}) and maximum hydroscopic moisture (W/W{sub h}). On the strength of test data it has been established that the relative moisture content at the soil liquid limit (W/W{sub L}) may also serve as a criterion on compression pressure and resistance against shearing for soil paste with no structural binding. Linear correlation between the moisture content of natural soil and its paste -- the equation of moisture balance -- has been found which specifies a thermodynamic balance condition. The equation of moisture balance represents a whole set of properties for a certain type of soil, such as strength and compressibility. In this respect, it may be considered as a ``Soil equation`` which allows for further prognosis of its properties.

  11. 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.

  12. GNSSProbe, penetrating GNSS signals for measuring soil moisture

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Field scale spatio-temporal soil moisture variability for trafficability and crop water availability

    NASA Astrophysics Data System (ADS)

    Carranza, Coleen; van der Ploeg, Martine; Ritsema, Coen

    2016-04-01

    Spatio-temporal patterns of soil moisture have been studied mostly for inputs in land surface models for weather and climate predictions. Remote sensing techniques for estimation of soil moisture have been explored because of the good spatial coverage at different scales. Current available satellite data provide surface soil moisture as microwave systems only measure soil moisture content up to 5cm soil depth. The OWAS1S project will focus on estimation of soil moisture from freely available Sentinel-1 datasets for operational water management in agricultural areas. As part of the project, it is essential to develop spatio-temporal methods to estimate root zone soil moisture from surface soil moisture. This will be used for crop water availability and trafficability in selected agricultural fields in the Netherlands. A network of single capacitance sensors installed per field will provide continuous measurements of soil moisture in the study area. Ground penetrating radar will be used to measure soil moisture variability within a single field for different time periods. During wetter months, optimal conditions for traffic will be assessed using simultaneous soil strength and soil moisture measurements. Towards water deficit periods, focus is on the relation (or the lack thereof) between surface soil moisture and root zone soil moisture to determine the amount of water for crops. Spatio-temporal distribution will determine important physical controls for surface and root zone soil moisture and provide insights for root-zone soil moisture. Existing models for field scale soil-water balance and data assimilation methods (e.g. Kalman filter) will be combined to estimate root zone soil moisture. Furthermore, effects of root development on soil structure and soil hydraulic properties and subsequent effects on trafficability and crop water availability will be investigated. This research project has recently started, therefore we want to present methods and framework of

  14. Microwave radiometric measurements of soil moisture in Italy

    NASA Astrophysics Data System (ADS)

    Macelloni, G.; Paloscia, S.; Pampaloni, P.; Santi, E.; Tedesco, M.

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

  15. [Quantification of Agricultural In-Situ Surface Soil Moisture Content Using Near Infrared Diffuse Reflectance Spectroscopy: A Comparison of Modeling Methods].

    PubMed

    Wu, Yong-feng; Dong, Yi-wei; Hu, Xin; Lu, Guo-hua; Ren, De-chao; Song, Ji-qing

    2015-12-01

    At field scale, surface soil had special characteristics of volumetric moisture content (VMC) with a relatively little difference and spatial heterogeneity induced by physical and chemical properties, roughness, straw residues, etc. It has been a great challenge for near infrared diffuse reflectance spectroscopy (NIR-DRS) measurement of surface soil moisture in situ. In this study, exonential decay models based on seven water-related wavelengths (1200, 1400, 1450, 1820, 1940, 2000 and 2250 nm), linear models of normalized difference soil moisture index (NSMI) and relative absorption depth (RAD) based on wave-length combinations, linear or quadratic model of width of the inflection (σ), center amplitude of the function (Rd) and area under the Gaussian curve (A) from soil moisture Gaussian model (SMGM), and partial least square (PLS) regression models based on bands were used to quantify VMC. The results indicated that (1) of all the single wavelengths, 2 000 nm showed the best validation result, indicated by the lowest RMSEp (2.463) and the highest RPD value (1.060). (2) Comparing with RAD, the validation of NSMI was satisfactory with higher R² (0.312), lower RMSEp (2.133) and higher RPD value (1.224). (3) In the validation results of SMGM parameters and PLS fitting, Rd was found to produce the best fitting quality identified by the highest R² (0.253), the lowest RMSEp (2.222), and the highest RPD value (1.175). (4) Comprehensively, a linear model based on NSMI showed the highest validation accuracy of all the methods. What is more, its calculation process is simple and easy to operate, and therefore become the preferred method to quantify surface soil moisture content in situ.

  16. Soil moisture and evapotranspiration predictions using Skylab data

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  17. 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...

  18. 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...

  19. Evaluation of Deterministic Models for Near Surface Soil Moisture Prediction

    DTIC Science & Technology

    1988-05-01

    probabilities for selected sites across Canada’, Agrometeorology Section. Research Branch. Agriculture Canada. Ottawa. Ontario. Technical Bulletin 86. i Dyer...J.A., (1980) ’Fall field workdays in Canada’, Agrometeorology Section. Research Branch, Agriculture Canada. Ottawa, Ontario, Technical Bulletin 92...Dyer, J.A. and A.R. Mack, (1984)’The versatile soil moisture budget - version three’, Agrometeorology Section. Research Branch. Agriculture Canada

  20. Using ARM observations to test soil moisture dynamics in climate models

    NASA Astrophysics Data System (ADS)

    Sun, S.; Cook, D. R.; Drewniak, B. A.; Stein, M.; Collis, S. M.; Moyer, E. J.

    2015-12-01

    Potential changes in soil moisture may have significant societal impacts, as soil moisture directly influences agriculture. Soil moisture is also a critical factor in climate simulations as it is the moisture source for evapotranspiration over land. Climate model projections generally show reduced soil moisture in future warmer climate conditions, and the scale of potential adverse impacts means that validation of those projections is a science priority. Our understanding of soil moisture dynamics is hampered by limited suitable observational data, but the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site offers a unique resource for this purpose, with over a decade of simultaneous measurements of soil moisture profiles and measurements of moisture fluxes and aboveground variables. In this work we use stations across SGP to identify statistical relationships in drivers of soil moisture dynamics. We also compare observed soil moisture dynamics to those in the Community Land Model version 4 (CLM4), running CLM4 in an offline mode with observationally derived atmospheric forcing, to identify similarities and discrepancies in resulting soil moisture evolution in observations and model. Preliminary comparison of metrics such as soil moisture characteristic time, soil moisture infiltration rate, etc. suggests that the governing hydrological and/or biophysical processes in models need improvements. The spatial heterogeneity of the SGP measurement stations also provides insight into the role of sub-grid scale features and the role of spatial resolution in producing accurate representations of soil moisture in climate models.

  1. Soil moisture by extraction and gas chromatography

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  2. Survey of methods for soil moisture determination

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  3. 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.

  4. SMAP and SMOS soil moisture validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SMOS and SMAP satellite missions each produce global soil moisture products using L-band radiometry. Both missions begin with the same fundamental equations in developing their soil moisture retrieval algorithm but implement it differently due to design differences of the instruments. SMOS with ...

  5. Passive microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Kondratyev, K. Y.; Melentyev, V. V.; Rabinovich, Y. I.; Shulgina, E. M.

    1977-01-01

    The theory and calculations of microwave emission from the medium with the depth-dependent physical properties are discussed; the possibility of determining the vertical profiles of temperature and humidity is considered. Laboratory and aircraft measurements of the soil moisture are described; the technique for determining the productive-moisture content in soil, and the results of aircraft measurements are given.

  6. Measuring soil moisture with imaging radars

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  7. [Soil moisture estimation model based on multiple vegetation index].

    PubMed

    Wu, Hai-long; Yu, Xin-xiao; Zhang, Zhen-ming; Zhang, Yan

    2014-06-01

    Estimating soil moisture conveniently and exactly is a hot issues in water resource monitoring among agriculture and forestry. Estimating soil moisture based on vegetation index has been recognized and applied widely. 8 vegetation indexes were figured out based on the hyper-spectral data measured by portable spectrometer. The higher correlation indexes among 8 vegetation indexes and surface vegetation temperature were selected by Gray Relative Analysis method (GRA). Then, these selected indexes were analyzed using Multiple Linear Regression to establish soil moisture estimation model based on multiple vegetation indexes, and the model accuracy was evaluated. The accuracy evaluation indicated that the fitting was satisfied and the significance was 0.000 (P < 0.001). High correlation was turned out between estimated and measured soil moisture with R2 reached 0.636 1 and RMSE 2.149 9. This method introduced multiple vegetation indexes into soil water content estimating over micro scale by non-contact measuring method using portable spectrometer. The exact estimation could be an appropriate replacement for remote sensing inversion and direct measurement. The model could estimate soil moisture quickly and accurately, and provide theory and technology reference for water resource management in agriculture and forestry.

  8. Soil moisture variability within remote sensing pixels

    SciTech Connect

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

    1992-11-30

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

  9. Downscaling soil moisture using multisource data in China

    NASA Astrophysics Data System (ADS)

    An, Ru; Wang, Hui-Lin; You, Jia-jun; Wang, Ying; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballardd, Jonathan Arthur; Chen, Yuehong

    2016-10-01

    Soil moisture plays an important role in the water cycle within the surface ecosystem and it is the basic condition for the growth and development of plants. Currently, the spatial resolution of most soil moisture data from remote sensing ranges from ten to several tens of kilometres whilst those observed in situ and simulated for watershed hydrology, ecology, agriculture, weather and drought research are generally less than 1 kilometre. Therefore, the existing coarse resolution remotely sensed soil moisture data needs to be down-scaled. In this paper, a universal soil moisture downscaling model through stepwise regression with moving window suitable for large areas and multi temporal has been established. Datasets comprise land surface, brightness temperature, precipitation, soil and topographic parameters from high resolution data, and active/passive microwave remotely sensed soil moisture data from Essential Climate Variables (ECV_SM) with 25 km spatial resolution were used. With this model, a total of 288 soil moisture maps of 1 km resolution from the first ten-day of January 2003 to the last tenth-day of December 2010 were derived. The in situ observations were used to validate the down-scaled ECV_SM for different land cover and land use types and seasons. In addition, various errors comparative analysis was also carried out for the down-scaled ECV_SM and original one. In general, the down-scaled soil moisture for different land cover and land use types is consistent with the in situ observations. The accuracy is relatively high in autumn and winter. The validation results show that downscaled soil moisture can be improved not only on spatial resolution, but also on estimation accuracy.

  10. Soil moisture retrieval from Sentinel-1 satellite data

    NASA Astrophysics Data System (ADS)

    Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo

    2016-04-01

    Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal

  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

  12. On-irrigator pasture soil moisture sensor

    NASA Astrophysics Data System (ADS)

    Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian

    2017-02-01

    In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of  ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements.

  13. Development of an Objective High Spatial Resolution Soil Moisture Index

    NASA Astrophysics Data System (ADS)

    Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

    2015-12-01

    Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective

  14. U.S National cropland soil moisture monitoring using SMAP

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop condition information is critical for public and private sector decision making that concerns agricultural policy, food production, food security, and food commodity prices. Crop conditions change quickly due to various growing condition events, such as temperature extremes, soil moisture defic...

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

    NASA Technical Reports Server (NTRS)

    Wilheit, T. T.

    1978-01-01

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

  16. Soil moisture monitoring for crop management

    NASA Astrophysics Data System (ADS)

    Boyd, Dale

    2015-07-01

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

  17. Integrating Microwave and Optical Data for Monitoring Soil Moisture

    NASA Astrophysics Data System (ADS)

    Morgan, R. S.; Abd El-Hady, M.; Rahim, I. S.; Silva, J.; Berg, A.

    2016-08-01

    In arid regions, such as Egypt, irrigation is the main source of water consumption and freshwater resources are getting scarcer. Therefore, the development of an appropriate irrigation water practices becomes a necessity. Soil moisture, in particular, plays a key role in any efficient water use strategy for agriculture. This study aims at suggesting a protocol for processing microwave data (Sentinel-1) supported by optical data (Landsat 8) with and without ancillary data and utilizing Artificial Neural Network (ANN) to provide repeatable, reliable and accurate estimation of soil moisture content and at a practical interval. The results of this study suggested two approaches for soil moisture predictions using Sentienl-1 data. The first approach depended totally on remote sensing data with a correlation of 0.76. The second approach is more suitable when accurate detailed field survey of soil field capacity is available and reached a correlation of about 0.98.

  18. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1996-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  1. 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 ...

  2. 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.

  3. 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.

  4. 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.

  5. High Energy Moisture Characteristics: Linking Between Soil Physical Processes and Structure Stability

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Water storage and flow in soils is usually complicated by the intricate nature of and changes in soil pore size distribution (PSD) due to modifications in soil structure following changes in agricultural management. The paper presents the Soil High Energy Moisture Characteristic (Soil-HEMC) method f...

  6. Radar for Measuring Soil Moisture Under Vegetation

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  7. Soil Moisture Retrieval from Co-Polarized ALOS PALSAR Backscattering in the Zwalm and Alzette Catchments

    NASA Astrophysics Data System (ADS)

    Lievens, H.; Vernieuwe, H.; Verhoest, N. E. C.; De Baets, B.; Matgen, P.; Montanari, M.; Hoffmann, L.; Mattia, F.

    2008-11-01

    It is well known that Synthetic Aperture Radar (SAR) sensors have a large potential for observing soil moisture. However, the sensitivity of L-band sensors to real world soil moisture data has not been discussed to a large extent. Therefore, different agricultural fields in the Zwalm catchment (Belgium) and the Alzette basin (Luxembourg) have been selected to investigate the potential of PALSAR HH-polarized imagery for monitoring soil moisture. Both sites have been extensively sampled with respect to soil moisture, soil roughness, and vegetation parameters during several field campaigns. Soil moisture is retrieved using a possibilistic inversion scheme, through which the accuracy of soil moisture retrieval with respect to uncertainty in soil roughness characterization is assessed.

  8. HCMM satellite follow-on investigation no. 25. Soil moisture and heat budget evalution in selected European zones of agricultural and environmental interest (TELLUS project)

    NASA Technical Reports Server (NTRS)

    1980-01-01

    A simple procedure to evaluate actual evaporation was derived by linearizing the surface energy balance equation, using Taylor's expansion. The original multidimensional hypersurface could be reduced to a linear relationship between evaporation and surface temperature or to a surface relationship involving evaporation, surface temperature and albedo. This procedure permits a rapid sensitivity analysis of the surface energy balance equation as well as a speedy mapping of evaporation from remotely sensed surface temperatures and albedo. Comparison with experimental data yielded promising results. The validity of evapotranspiration and soil moisture models in semiarid conditions was tested. Wheat was the crop chosen for a continuous measurement campaign made in the south of Italy. Radiometric, micrometeorologic, agronomic and soil data were collected for processing and interpretation.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

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

  11. Remote sensing of soil moisture with microwave radiometers

    NASA Technical Reports Server (NTRS)

    Schmugge, T.; Wilheit, T.; Webster, W., Jr.; Gloerson, P.

    1976-01-01

    Results are presented that were derived from measurements made by microwave radiometers during the March 1972 and February 1973 flights of National Aeronautics and Space Administration (NASA) Convair-9900 aircraft over agricultural test sites in the southwestern part of United States. The purpose of the missions was to study the use of microwave radiometers for the remote sensing of soil moisture. The microwave radiometers covered the 0.8- to 21-cm wavelength range. The results show a good linear correlation between the observed microwave brightness temperature and moisture content of the 0- to 1-cm layer of the soil. The results at the largest wavelength (21 cm) show the greatest sensitivity to soil moisture variations and indicate the possibility of sensing these variations through a vegetative canopy. The effect of soil texture on the emission from the soil was also studied and it was found that this effect can be compensated for by expressing soil moisture as a percent of field capacity for the soil. The results were compared with calculations based on a radiative transfer model for layered dielectrics and the agreement is very good at the longer wavelengths. At the shorter wavelengths, surface roughness effects are larger and the agreement becomes poorer.

  12. Estimating Sahelian and East African soil moisture using the Normalized Difference Vegetation Index

    NASA Astrophysics Data System (ADS)

    McNally, A.; Funk, C.; Husak, G. J.; Michaelsen, J.; Cappelaere, B.; Demarty, J.; Pellarin, T.; Young, T. P.; Caylor, K. K.; Riginos, C.; Veblen, K. E.

    2013-06-01

    Rainfall gauge networks in Sub-Saharan Africa are inadequate for assessing Sahelian agricultural drought, hence satellite-based estimates of precipitation and vegetation indices such as the Normalized Difference Vegetation Index (NDVI) provide the main source of information for early warning systems. While it is common practice to translate precipitation into estimates of soil moisture, it is difficult to quantitatively compare precipitation and soil moisture estimates with variations in NDVI. In the context of agricultural drought early warning, this study quantitatively compares rainfall, soil moisture and NDVI using a simple statistical model to translate NDVI values into estimates of soil moisture. The model was calibrated using in-situ soil moisture observations from southwest Niger, and then used to estimate root zone soil moisture across the African Sahel from 2001-2012. We then used these NDVI-soil moisture estimates (NSM) to quantify agricultural drought, and compared our results with a precipitation-based estimate of soil moisture (the Antecedent Precipitation Index, API), calibrated to the same in-situ soil moisture observations. We also used in-situ soil moisture observations in Mali and Kenya to assess performance in other water-limited locations in sub Saharan Africa. The separate estimates of soil moisture were highly correlated across the semi-arid, West and Central African Sahel, where annual rainfall exhibits a uni-modal regime. We also found that seasonal API and NDVI-soil moisture showed high rank correlation with a crop water balance model, capturing known agricultural drought years in Niger, indicating that this new estimate of soil moisture can contribute to operational drought monitoring. In-situ soil moisture observations from Kenya highlighted how the rainfall-driven API needs to be recalibrated in locations with multiple rainy seasons (e.g., Ethiopia, Kenya, and Somalia). Our soil moisture estimates from NDVI, on the other hand, performed

  13. Small-scale soil moisture determination with GPR

    NASA Astrophysics Data System (ADS)

    Igel, Jan; Preetz, Holger

    2010-05-01

    The knowledge of topsoil moisture distribution is an important input for modelling water flow and evapotranspiration which are essential processes in hydrology, meteorology, and agriculture. All these processes involve non-linear effects and thus the small-scale variability of input parameters play an important role. Using smoothed interpolations instead can cause significant biases. Lateral soil moisture distribution can be sensed by different techniques at various scales whereby geophysical methods provide spatial information which closes the gap between point measurements by classical soil scientific methods and measurements on the field or regional scale by remote sensing. Ground-penetrating radar (GPR) can be used to explore soil moisture on the field scale as propagation of electromagnetic waves is correlated to soil water content. By determining the velocity of the ground wave, which is a guided wave travelling along the soil surface, we can sense soil water content. This method has been applied to determine topsoil moisture for several years. We present a new groundwave technique which determines the velocity in between two receiving antennas which enables a higher lateral resolution (approx. 10 cm) compared to classical groundwave technique (half meter and more). We present synthetic data from finite-differences (FD) calculations as well as data from a sandbox experiment carried out under controlled conditions to demonstrate the performance of this method. Further, we carried out field measurements on two sites on a sandy soil which is used as grassland. The measurements were carried out in late summer at dry soil conditions. Soil moisture on the first site shows an isotropic pattern with correlation lengths of approx. 35 cm. We think this natural pattern is governed by rout distribution within the soil and the water uptake of vegetation. On the second site, soil moisture distribution shows a regular stripe pattern. As the land has been used as

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

    Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

  15. Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.

    1985-01-01

    Because of the large contrast between the dielectric constant of liquid water and that of dry soil at microwave wavelength, there is a strong dependence of the thermal emission and radar backscatter from the soil on its moisture content. This dependence provides a means for the remote sensing of the moisture content in a surface layer approximately 5 cm thick. The feasibility of these techniques is demonstrated from field, aircraft and spacecraft platforms. The soil texture, surface roughness, and vegetative cover affect the sensitivity of the microwave response to moisture variations with vegetation being the most important. It serves as an attenuating layer which can totally obscure the surface. Research indicates that it is possible to obtain five or more levels of moisture discrimination and that a mature corn crop is the limiting vegetation situation.

  16. Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

    NASA Astrophysics Data System (ADS)

    Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

    2012-04-01

    Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture

  17. Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

    NASA Technical Reports Server (NTRS)

    Bolten, John; Crow, Wade

    2012-01-01

    The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  19. Agriculture, forestry, range, and soils, chapter 2, part C

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The feasibility of using microwave systems in agriculture, forestry, range, and soil moisture measurements was studied. Theory and preliminary results show the feasibility of measuring moisture status in the soil. For vegetational resources, crop identification for inventory and for yield and production estimates is most feasible. Apart from moisture- and water-related phenomena, microwave systems are also used to record structural and spatial data related to crops and forests.

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

    NASA Astrophysics Data System (ADS)

    Fontes, Adan Fimbres

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

  1. Scaling and calibration of a core validation site for the soil moisture active passive mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The calibration and validation of soil moisture remote sensing products is complicated due to the logistics of installing a long term soil moisture monitoring network in an active landscape. It is more efficient to locate these stations along agricultural field boundaries, but unfortunately this oft...

  2. SMOS disaggregated soil moisture product at 1 km resolution: processor overview and first validation results

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM...

  3. Extending the soil moisture record of the climate reference network with machine learning

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ...

  4. 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...

  5. Evaluation of soil moisture sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    USGS Publications Warehouse

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-08-01

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

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  11. Microstrip Ring Resonator for Soil Moisture Measurements

    NASA Technical Reports Server (NTRS)

    Sarabandi, Kamal; Li, Eric S.

    1993-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  17. Use of TRMM Microwave Imager (TMI) to characterize soil moisture for the Little River Watershed

    NASA Astrophysics Data System (ADS)

    Cashion, J. E.; Lakshmi, V.; Bosch, D.

    2003-12-01

    Soil moisture plays a critical role in many hydrological processes including infiltration, evaporation, and runoff. Additionally, soil moisture has a direct effect on weather patterns. Satellite based passive microwave sensors offer an effective way to observe soil moisture data over vast areas, and there are currently several satellite systems that detect soil moisture. Long-term in situ (field) measurements of soil moisture are collected in the Little River Watershed (LRWS) located in Tifton, Georgia and compared with the remotely sensed data collected over the watershed. The LRWS has been selected by the United States Department of Agriculture (USDA) to represent the south eastern costal plains region of North America. The LRWS is composed primarily of sandy soils and has a flat topography with meandering streams. The in-situ measurements were collected by stationary soil moisture probes attached to rain gage stations throughout the LRWS for the period 2000-2002. The remotely sensed data was acquired by two satellites viz. - the Tropical Rainfall Measurement Mission Microwave Imager (TMI) for soil moisture and the Moderate Resolution Imaging Spectroradiometer (MODIS) for vegetation. The TMI is equipped with a passive vertically and horizontally polarized 10.65GHz sensor that is capable of detecting soil moisture. Soil moisture collected in the field is related to the TMI brightness temperatures. However, vegetation has a strong affect on the 10.65GHz brightness temperature. The Normalized Difference Vegetation Index (NDVI) data, provided by the (MODIS), are used to evaluate the effect of vegetation on soil microwave emission.

  18. State of the art in large-scale soil moisture monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is an essential climate variable influencing land-atmosphere interactions, an essential hydrologic variable impacting rainfall-runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large...

  19. Surface Roughness Parameter Uncertainties on Radar Based Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

    Joseph, A. T.; vanderVelde, R.; O'Neill, P. E.; Lang, R.; Su, Z.; Gish, T.

    2012-01-01

    Surface roughness variations are often assumed to be negligible for the retrieval of sol moisture. Although previous investigations have suggested that this assumption is reasonable for natural vegetation covers (i.e. Moran et al. 2002), in-situ measurements over plowed agricultural fields (i.e. Callens et al. 2006) have shown that the soil surface roughness can change considerably due to weathering induced by rain.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Inference of Soil Hydrologic Parameters from Soil Moisture Monitoring Records

    NASA Astrophysics Data System (ADS)

    Chandler, D. G.; Seyfried, M. S.; McNamara, J. P.; Hwang, K.

    2015-12-01

    Soil moisture is an important control on hydrologic function, as it governs flux through the soil and responds to and determines vertical fluxes from and to the atmosphere, groundwater recharge and lateral fluxes through the soil. Most physically based hydrologic models require parameters to represent soil physical properties governing flow and retention of vadose water. The presented analysis compares four methods of objective analysis to determine field capacity, plant extraction limit (or permanent wilting point) and field saturated soil moisture content from decadal records of volumetric water content. These values are found as either data attractors or limits in the VWC records and may vary with interannual moisture availability. Results are compared to values from pedotransfer functions and discussed in terms of historic methods of measurement in soil physics.

  2. Soil Moisture Variability Beneath a Melting Snowpack

    NASA Astrophysics Data System (ADS)

    Webb, R.; Fassnacht, S. R.

    2013-12-01

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

  3. 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 ...

  4. Soil moisture and temperature algorithms and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  6. 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...

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

    NASA Astrophysics Data System (ADS)

    Qiu, Jianxiu; Crow, Wade T.; Nearing, Grey S.; Mo, Xingguo; Liu, Suxia

    2014-07-01

    Using a decade of ground-based soil moisture observations acquired from the United States Department of Agriculture's Soil Climate Analysis Network (SCAN), we calculate the mutual information (MI) content between multiple soil moisture variables and near-future vegetation condition to examine the existence of emergent drought information in vertically integrated (surface to 60 cm) soil moisture observations (θ0-60 [cm]) not present in either superficial soil moisture observations (θ5 [cm]) or a simple low-pass transformation of θ5. Results suggest that while θ0-60 is indeed more valuable than θ5 for predicting near-future vegetation anomalies, the enhanced information content in θ0-60 soil moisture can be effectively duplicated by the low-pass transformation of θ5. This implies that, for drought monitoring applications, the shallow vertical penetration depth of microwave-based θ5 retrievals does not represent as large a practical limitation as commonly perceived.

  8. Drought monitoring using downscaled soil moisture through machine learning approaches over North and South Korea

    NASA Astrophysics Data System (ADS)

    Park, S.; Im, J.; Rhee, J.; Park, S.

    2015-12-01

    Soil moisture is one of the most important key variables for drought monitoring. It reflects hydrological and agricultural processes because soil moisture is a function of precipitation and energy flux and crop yield is highly related to soil moisture. Many satellites including Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity sensor (SMOS), and Soil Moisture Active Passive (SMAP) provide global scale soil moisture products through microwave sensors. However, as the spatial resolution of soil moisture products is typically tens of kilometers, it is difficult to monitor drought using soil moisture at local or regional scale. In this study, AMSR-E and AMSR2 soil moisture were downscaled up to 1 km spatial resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) data—Evapotranspiration, Land Surface Temperature, Leaf Area Index, Normalized Difference Vegetation Index, Enhanced Vegetation Index and Albedo—through machine learning approaches over Korean peninsula. To monitor drought from 2003 to 2014, each pixel of the downscaled soil moisture was scaled from 0 to 1 (1 is the wettest and 0 is the driest). The soil moisture based drought maps were validated using Standardized Precipitation Index (SPI) and crop yield data. Spatial distribution of drought status was also compared with other drought indices such as Scaled Drought Condition Index (SDCI). Machine learning approaches were performed well (R=0.905) for downscaling. Downscaled soil moisture was validated using in situ Asia flux data. The Root Mean Square Errors (RMSE) improved from 0.172 (25 km AMSR2) to 0.065 (downscaled soil moisture). The correlation coefficients improved from 0.201 (25 km AMSR2) to 0.341 (downscaled soil moisture). The soil moisture based drought maps and SDCI showed similar spatial distribution that caught both extreme drought and no drought. Since the proposed drought monitoring approach based on the downscaled

  9. SoilNet - A Zigbee based soil moisture sensor network

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  10. 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.

  11. A numerical simulation of soil temperature and moisture variations for a bare field

    NASA Technical Reports Server (NTRS)

    Schieldge, J. P.; Kahle, A. B.; Alley, R. E.

    1982-01-01

    The diurnal variations of soil temperature and moisture content were simulated for a bare agricultural field in the San Joaquin Valley in California. The simulation pertained to the first 72 hours of drying, from saturation, of a sandy, clay loam soil. The results were compared with measurements of soil temperature and moisture content made at the field. Calculated and measured values of soil temperature trends agreed in general, but model results of moisture trends did not replicate observed diurnal effects evident at depths 4 centimeters or more below the surface.

  12. NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.

    2013-01-01

    Water in the soil, both its amount (soil moisture) and its state (freeze/thaw), plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

  13. First soil moisture values from SMOS over a Sahelian region.

    NASA Astrophysics Data System (ADS)

    Gruhier, Claire; Kerr, Yann; de Rosnay, Patricia; Pellarin, Thierry; Grippa, Manuela

    2010-05-01

    Soil moisture is a crucial variable which influences the land surface processes. Numerous studies shown microwaves at low frequency are particularly performed to access to soil moisture values. SMOS (Soil Moisture and Ocean Salinity), launched the November 2th 2009, is the first space mission dedicated to soil moisture observations. Before SMOS, several soil moisture products were provided, based on active or passive microwaves measurements. Gruhier et al. (2010) analyse five of them over a Sahelian area. The results show that the range of volumetric soil moisture values obtained over Sahel is drastically different depending on the remote sensing approach used to produce soil moisture estimates. Although microwave bands currently available are not optimal, some products are in very good agreement with ground data. The main goal of this study is to introduce the first soil moisture maps from SMOS over West Africa. A first analyse of values over a Sahelian region is investigated. The study area is located in Gourma region in Mali. This site has been instrumented in the context of the AMMA project (African Monsoon Multidisciplinary Analysis) and was specifically designed to address the validation of remotely sensed soil moisture. SMOS soil moisture values was analysed with ground knowledge and placed in the context of previous soil moisture products. The high sensitivity of the L-band used by SMOS should provide very accurate soil moisture values.

  14. Downscaled soil moisture from SMAP evaluated using high density observations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...

  15. 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.

  16. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at p<0.01) with the amount of measured precipitation. In this study we analyze the role of other crucial atmospheric parameters (i.e., temperature, relative humidity, global solar radiation, and wind speed and wind direction) in the intraanual evolution of soil moisture; focussing our analyses on the soil moisture discharge episodes. Here we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). Key Words: Soil Moisture Discharges

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

    NASA Astrophysics Data System (ADS)

    Rahmani, Abdolaziz; Golian, Saeed; Brocca, Luca

    2016-06-01

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

  18. Estimating Soil Moisture from Satellite Microwave Observations

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

    Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data

  19. On the identification of representative in situ soil moisture monitoring stations for the validation of SMAP soil moisture products in Australia

    NASA Astrophysics Data System (ADS)

    Yee, Mei Sun; Walker, Jeffrey P.; Monerris, Alessandra; Rüdiger, Christoph; Jackson, Thomas J.

    2016-06-01

    The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in situ monitoring stations. Therefore, a standard methodology for selecting the most representative stations for the purpose of validating satellites and land surface models is essential. Based on temporal stability and geostatistical studies using long-term soil moisture records, intensive ground measurements and airborne soil moisture products, this study investigates the representativeness of soil moisture monitoring stations within the Yanco study area for the validation of NASA's Soil Moisture Active Passive (SMAP) products at 3 km for radar, 9 km for radar-radiometer and 36 km for radiometer pixels. This resulted in the identification of a number of representative stations according to the different scales. Although the temporal stability method was found to be suitable for identifying representative stations, stations based on the mean relative difference (MRD) were not necessarily the most representative of the areal average. Moreover, those identified from standard deviation of the relative difference (SDRD) may be dry-biased. It was also found that in the presence of heterogeneous land use, stations should be weighted based on proportions of agricultural land. Airborne soil moisture products were also shown to provide useful a priori information for identifying representative locations. Finally, recommendations are made regarding the design of future networks for satellite validation, and specifically the most representative stations for the Yanco area.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. 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...

  2. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  4. Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

    NASA Astrophysics Data System (ADS)

    Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

    2011-12-01

    Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

  5. Quantifying Shrink Swell Capacity of Soil Using Soil Moisture Isotherms

    NASA Astrophysics Data System (ADS)

    Rivera, L. D.; Cobos, D. R.; Campbell, C. S.; Morgan, C.

    2013-12-01

    Vertisols, soils instinctively known for their expansive clays that cause them to have a high shrink swell potential, cover 2.4% of the earths ice-free land. In the United States these expansive soils can cause upwards of 6 billion in damages to pavements, foundations, and utility lines annually (Brady & Weil, 2010). Because of this, it is especially important that a soils ability to shrink and swell is well characterized when making engineering decisions. One traditional method for measuring a soil's expansive potential, the Coefficient of Linear Extensibility (COLE), can take weeks to months to complete (Grossman et al., 1968; Schafer and Singer, 1976b). Use of soil moisture isotherms, or the Soil Moisture Characteristic Curve (SMCC), in recent research has shown that the slope of the SMCC is related to a soils swelling potential (McKeen, 1992). The goal of this research is to evaluate the robustness of the relationship between the SMCC and COLE for a set of well-characterized test soils with COLE ranging from 0 to 0.176. If expansive potential can be reliably predicted from the SMCC, then data from recently developed automatic soil moisture isotherm generators could be used to characterize expansive potential with a fraction of the time and effort necessary for traditional techniques.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These

  8. 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.

  9. Traditional and microirrigation with stochastic soil moisture

    NASA Astrophysics Data System (ADS)

    Vico, Giulia; Porporato, Amilcare

    2010-03-01

    Achieving a sustainable use of water resources, in view of the increased food and biofuel demand and possible climate change, will require optimizing irrigation, a highly nontrivial task given the unpredictability of rainfall and the numerous soil-plant-atmosphere interactions. Here we theoretically analyze two different irrigation schemes, a traditional scheme, consisting of the application of fixed water volumes that bring soil moisture to field capacity, and a microirrigation scheme supplying water continuously in order to avoid plant water stress. These two idealized irrigation schemes are optimal in the sense that they avoid crop water stress while minimizing water losses by percolation and runoff. Furthermore, they cover the two extremes cases of continuous and fully concentrated irrigation. For both irrigation schemes, we obtain exact solutions of the steady state soil moisture probability density function with random timing and amounts of rainfall. We also give analytical expressions for irrigation frequency and volumes under different rainfall regimes, evaporative demands, and soil types. We quantify the excess volumes required by traditional irrigation, mostly lost in runoff and deep infiltration, as a function of climate, soil, and vegetation parameters.

  10. Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

    NASA Technical Reports Server (NTRS)

    Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M; Gherboudj, Imen; Colliander, A.; Cosh, M.; Belanger, John; Burgin, M.; Fisher, J.; Kim, S.; Rousseau, L-P B.; Djamai, N.; Shang, J.; Merzouki, A.

    2011-01-01

    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 Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture.

  11. Assimilation of Passive and Active Microwave Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  12. Estimation of soil moisture from diurnal surface temperature observations

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

    A coupled heat and moisture balance model was used to determine the thermal inertia of a grass covered top soil under different meteorological conditions. Relations between thermal inertia and soil moisture were established using the De Vries models for thermal conductivity and heat capacity to relate soil moisture and thermal inertia as a function of soil type. A sensitivity study of the surface roughness length and thermal inertia on diurnal surface temperature shows the necessity of focusing on the night time surface temperature rather than on the day time surface temperature, in order to estimate the soil moisture content of the top soil.

  13. 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...

  14. 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

  15. [Soil moisture dynamics under artificial Caragana microphylla shrub].

    PubMed

    Alamusa; Jiang, Deming; Fan, Shixiang; Luo, Yongming

    2002-12-01

    Applying the methods of deducing time series from vegetation space alignment, we analyzed the spatial and temporal variation features of soil moisture under artificial Caragana microphylla shrubs built in 1984, 1987, 1995, 1999. The results showed that affected by mechanical composition of mobile sandy dunes, the soil of sandy land was mainly composed of sandy particle, and the particles of > 0.01 mm were accounted for 97%. The withered moisture was 1.55%. The field waterhold capacity was 5.5%, and the available moisture storage was 3.95%. With the increase of the dominance of fix-sand vegetation, the moisture content of soil under artificial Caragana microphylla shrubs was decreased. The soil moisture of vegetation built in 1984 was lower than that built in 1999. The soil moisture conditions of four stages vegetation were continued depressing from April to June in a year, the lowest point presenced in June, and then gradually increased from July to October. The vertical change of soil moisture showed the tendency of increasing with soil depth. The soil moisture decreased by the degrees of early built vegetation (1984, 1987). Especially in 70 cm soil depth, the moisture content of soil decreased obviously. Caragana microphylla shrubs absorbed water and aggravated the shortage of soil moisture content near the root system, which affected the component of vegetation in Caragana microphylla shrubs. The species of herbaceous plants and annual plants increased during the growth of Caragana microphylla shrub.

  16. Microbiology and Moisture Uptake of Desert Soils

    NASA Astrophysics Data System (ADS)

    Kress, M. E.; Bryant, E. P.; Morgan, S. W.; Rech, S.; McKay, C. P.

    2005-12-01

    We have initiated an interdisciplinary study of the microbiology and water content of desert soils to better understand microbial activity in extreme arid environments. Water is the one constituent that no organism can live without; nevertheless, there are places on Earth with an annual rainfall near zero that do support microbial ecosystems. These hyperarid deserts (e.g. Atacama and the Antarctic Dry Valleys) are the closest terrestrial analogs to Mars, which is the subject of future exploration motivated by the search for life beyond Earth. We are modeling the moisture uptake by soils in hyperarid environments to quantify the environmental constraints that regulate the survival and growth of micro-organisms. Together with the studies of moisture uptake, we are also characterizing the microbial population in these soils using molecular and culturing methods. We are in the process of extracting DNA from these soils using MoBio extraction kits. This DNA will be used as a template to amplify bacterial and eukaryotic ribosomal DNA to determine the diversity of the microbial population. We also have been attempting to determine the density of organisms by culturing on one-half strength R2A agar. The long-range goal of this research is to identify special adaptations of terrestrial life that allow them to inhabit extreme arid environments, while simultaneously quantifying the environmental parameters that enforce limits on these organisms' growth and survival.

  17. Soil Moisture Measurements and their Applications at the Savannah River Site

    SciTech Connect

    Buckley, R.

    2000-09-26

    Soil moisture is a very important component of the land-atmosphere exchange. Practically, it is valuable in both the agricultural and meteorological industries. Farmers require soil moisture for crop yields, while the atmospheric numerical modeling community has found soil moisture to be extremely important in generating realistic forecasts. Physically, the soil moisture not only provides water vapor for precipitation through evapotranspiration and controls the splitting of net radiation into sensible and latent heat components, but it also provides thermal inertia to the climate through heat storage and release from large water reservoirs (Famiglietti et al. 1998). Quantification of soil moisture is challenging since the range of spatial scale varies from centimeters to thousands of kilometers, while temporal scales vary from minutes to months. In the short term, soil moisture is influenced by topography, soil type, texture, and vegetation and affects the infiltration of water into and through the soil, as well as how much water will be held within the soil. In the long term, soil moisture is impacted by atmospheric forcing and affects the amount of water available to the soil through rain (or snowmelt), as well as removal by evapo-transpiration (Entin et al. 2000). Due to the expense and difficulty of measuring soil moisture, few extensive data sets currently exist. Exceptions include those found in Russia (dating back to the 1930s), Mongolia (1973-1995), China (1981-1991), India (1987-1995), and the US (Illinois, Iowa and Oklahoma, from the early 1980s to the present), (Robock et al. 2000). Most of these data were taken several times per month and do not provide high-frequency variations in time. A real-time, operational monitoring network for soil moisture detection has very important ramifications in the satellite industry, where such measures could serve as a ground truth. This paper discusses a real-time soil monitoring station that has been established at

  18. Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

    USGS Publications Warehouse

    McNally, Amy; Gregory J. Husak,; Molly Brown,; Mark Carroll,; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

    2015-01-01

    The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

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

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  20. Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring.

    PubMed

    Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

    2013-01-01

    Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

  1. Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

    NASA Astrophysics Data System (ADS)

    Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

    2013-01-01

    Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  3. Capacitive Soil Moisture Sensor for Plant Watering

    NASA Astrophysics Data System (ADS)

    Maier, Thomas; Kamm, Lukas

    2016-04-01

    How can you realize a water saving and demand-driven plant watering device? To achieve this you need a sensor, which precisely detects the soil moisture. Designing such a sensor is the topic of this poster. We approached this subject with comparing several physical properties of water, e.g. the conductivity, permittivity, heat capacity and the soil water potential, which are suitable to detect the soil moisture via an electronic device. For our project we have developed a sensor device, which measures the soil moisture and provides the measured values for a plant watering system via a wireless bluetooth 4.0 network. Different sensor setups have been analyzed and the final sensor is the result of many iterative steps of improvement. In the end we tested the precision of our sensor and compared the results with theoretical values. The sensor is currently being used in the Botanical Garden of the Friedrich-Alexander-University in a long-term test. This will show how good the usability in the real field is. On the basis of these findings a marketable sensor will soon be available. Furthermore a more specific type of this sensor has been designed for the EU:CROPIS Space Project, where tomato plants will grow at different gravitational forces. Due to a very small (15mm x 85mm x 1.5mm) and light (5 gramm) realisation, our sensor has been selected for the space program. Now the scientists can monitor the water content of the substrate of the tomato plants in outer space and water the plants on demand.

  4. 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.

  5. Effects of soil moisture content on upland nitrogen loss

    NASA Astrophysics Data System (ADS)

    Ouyang, Wei; Xu, Xueting; Hao, Zengchao; Gao, Xiang

    2017-03-01

    In recent years, nitrogen (N) loss from upland fields has become one of the most important sources for agricultural nonpoint source (NPS) pollution. Understanding the relationships between soil hydrological processes and N loss in NPS pollution is vital for controlling the agricultural NPS pollution in upland fields. The objective of this study was to analyze the interaction of N loss with different moisture conditions in the freeze-thaw zone. The semi-distributed hydrologic model Soil and Water Assessment Tool (SWAT) was used in this study to simulate runoff and different forms of N loss, which provided a basis for analyzing characteristics of N loss in the study region. Results showed that the soil moisture content was an important factor affecting N loss in the study region. Different forms of N loss were also analyzed and it was found that N loss occurred primarily in the form of organic-N, which is likely due to the dominant role of erosion-induced pollution. This study provides useful information for preventing NPS pollution within the study region.

  6. 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.

  7. Improved forecasting of global vegetation conditions using remotely-sensed surface soil moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Timely and accurate monitoring of anomalies in root-zone soil water availability is essential for assessing global agricultural crop conditions. Root-zone soil moisture estimates are particularly important for obtaining forecasts of end-of-season crop yield fluctuations provided by the United States...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil

  9. The prototype SMOS soil moisture Algorithm

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, to be launched in September 2007. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 will consists mainly of angular brightness temperatures while level 2 will consist of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The consortium of institutes preparing the Soil moisture algorithm is led by CESBIO (Centre d'Etudes Spatiales de la BIOsphère) and Service d'Aéronomie and consists of the institutes represented by the authors. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric

  10. 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.

  11. The Soil Moisture Active Passive Marena Oklahoma In Situ Sensor Testbed (SMAP-MOISST): Design and initial results

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In situ soil moisture monitoring networks are critical to the development of soil moisture remote sensing missions as well as agricultural and environmental management, weather forecasting and many other endeavors. These in situ networks are composed of a variety of sensors and installation practic...

  12. Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  14. Remote sensing of vegetation and soil moisture

    NASA Technical Reports Server (NTRS)

    Kong, J. A.; Shin, R. T. (Principal Investigator)

    1983-01-01

    Progress in the investigation of problems related to the remote sensing of vegetation and soil moisture is reported. Specific topics addressed include: (1) microwave scattering from periodic surfaces using a rigorous modal technique; (2) combined random rough surface and volume scattering effects; (3) the anisotropic effects of vegetation structures; (4) the application of the strong fluctuation theory to the the study of electromagnetic wave scattering from a layer of random discrete scatterers; and (5) the investigation of the scattering of a plane wave obliquely incident on a half space of densely distributed spherical dielectric scatterers using a quantum mechanical potential approach.

  15. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  16. 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.

  17. 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

  18. 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).

  19. Soil moisture impacts on convective precipitation in Oklahoma

    NASA Astrophysics Data System (ADS)

    Ford, Trenton W.

    Soil moisture is vital to the climate system, as root zone soil moisture has a significant influence on evapotranspiration rates and latent and sensible heat exchange. Through the modification of moisture flux from the land surface to the atmosphere, soil moisture can impact regional temperature and precipitation. Despite a wealth of studies examining land-atmosphere interactions, model and observation-driven studies show conflicting results with regard to the sign and strength of soil moisture feedback to precipitation, particularly in the Southern Great Plains of the United States. This research provides observational evidence for a preferential dry (or negative) soil moisture feedback to precipitation in Oklahoma. The ability of soil moisture to impact the location and occurrence of afternoon convective precipitation is constrained by synoptic-scale atmospheric circulation and resulting mid- and low-level wind patterns and sensible and latent heat flux. Overall, the preference for precipitation initiation over dry soils is enhanced when regional soil moisture gradients exhibit a weakened east to west, wet to dry pattern. Based on these results, we conclude that soil moisture can modify atmospheric conditions potentially leading to convective initiation. However, the land surface feedback signal is weak at best, suggesting that regional-scale circulation is the dominant driver of warm season precipitation in the Southern Great Plains.

  20. BOREAS HYD-1 Volumetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-1 team made measurements of volumetric soil moisture at the Southern Study Area (SSA) and Northern Study Area (NSA) tower flux sites in 1994 and at selected tower flux sites in 1995-97. Different methods were used to collect these measurements, including neutron probe and manual and automated Time Domain Reflectometry (TDR). In 1994, the measurements were made every other day at the NSA-OJP (Old Jack Pine), NSA-YJP (Young Jack Pine), NSA-OBS (Old Black Spruce), NSA-Fen, SSA-OJP, SSA-YJP, SSA-Fen, SSA-YA (Young Aspen), and SSA-OBS sites. In 1995-97, when automated equipment was deployed at NSA-OJP, NSA-YJP, NSA-OBS, SSA-OBS, and SSA-OA (Old Aspen), the measurements were made as often as every hour. The data are stored in tabular ASCII files. The volumetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  1. 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.

  2. Soil moisture sensing with aircraft observations of the diurnal range of surface temperature

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Blanchard, B.; Anderson, A.; Wang, V.

    1977-01-01

    Aircraft observations of the surface temperature were made by measurements of the thermal emission in the 8-14 micrometers band over agricultural fields around Phoenix, Arizona. The diurnal range of these surface temperature measurements were well correlated with the ground measurement of soil moisture in the 0-2 cm layer. The surface temperature observations for vegetated fields were found to be within 1 or 2 C of the ambient air temperature indicating no moisture stress. These results indicate that for clear atmospheric conditions remotely sensed surface temperatures are a reliable indicator of soil moisture conditions and crop status.

  3. Scaling surface soil moisture in the Walnut Gulch Experimental Watershed

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    The estimation of surface soil moisture in semi-arid and arid regions is complicated by the inherent heterogeneous precipitation patterns and ephemeral surface water characteristics. Large-scale sampling is inefficient for long term monitoring of surface soil moisture, especially with the goal of calibration of a satellite soil moisture product such as that generated by the AMSR-E instrument for example. Statistical methods of accurately monitoring and scaling point and watershed estimates to satellite scale moisture values are explored. The location for this study is the Walnut Gulch Experimental Watershed in Tombstone, Arizona, which is also the location of the Soil Moisture Experiment in 2004 (SMEX04). The variability of radiometric temperature brightness data is also examined for its relationships to land surface parameters, climate variables, and insitu soil moisture measurements. Variability assessment is also evaluated for consistency and persistence over a three-year period.

  4. Evaluation and Application of Remotely Sensed Soil Moisture Products

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  5. Temporal observations of surface soil moisture using a passive microwave sensor

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; O'Neill, P.

    1987-01-01

    A series of 10 aircraft flights was conducted over agricultural fields to evaluate relationships between observed surface soil moisture and soil moisture predicted using passive microwave sensor observations. An a priori approach was used to predict values of surface soil moisture for three types of fields: tilled corn, no-till corn with soybean stubble, and idle fields with corn stubble. Acceptable predictions were obtained for the tilled corn fields, while poor results were obtained for the others. The source of error is suspected to be the density and orientation of the surface stubble layer; however, further research is needed to verify this explanation. Temporal comparisons between observed, microwave predicted, and soil water-simulated moisture values showed similar patterns for tilled well-drained fields. Divergences between the observed and simulated measurements were apparent on poorly drained fields. This result may be of value in locating and mapping hydrologic contributing areas.

  6. Validation of Satellite Soil Moisture Retrievals using Precipitation Records in India

    NASA Astrophysics Data System (ADS)

    Karthikeyan, L.; Nagesh Kumar, D.

    2014-11-01

    Soil moisture plays crucial role in influencing the components of hydrologic cycle and thus used for large range of applications such as climate predictions, agriculture management and flood/drought modelling. The current work focuses on establishing a measure to check the performance of passive microwave satellite soil moisture data using rainfall information over India. The measure is developed based on the concepts of information theory and copulas. Two soil moisture products developed by, VUA-NASA (jointly by Vrije Universiteit Amsterdam and NASA) and university of Montana are tested with the proposed measure using IMD rainfall data at 0.25° latitude-longitude spatial resolution. The measure conveyed that soil moisture product by university of Montana has outperformed over its counterpart. Further analysis concluded that under moderate climate conditions, Montana product could be used for analysis whereas for study in extreme weather conditions it may be necessary to check the usefulness of VUA-NASA product.

  7. Soil moisture retrieval in the Oberpfaffenhofen testsite using MAC Europe AIRSAR data

    NASA Technical Reports Server (NTRS)

    Wever, Tobias; Henkel, Jochen

    1993-01-01

    Soil moisture content is an important parameter in many disciplines of science like hydrology, meteorology, agriculture and others. Microwave remote sensing technique has a high potential in measuring the dielectric constant of soils, which is strongly governed by the soil moisture. Much excellent work has been done on investigating the relationship between backscattering coefficient and soil moisture. Most of these studies are measured in a laboratory or are carried out with a multitemporal data set. This means, that the variation in the backscattering coefficient is only related to the soil moisture because all other parameters influencing the backscattering like surface roughness, vegetation cover, plant geometry, phenology of plants and row direction are kept constant. In this study the sensitivity of the backscattering coefficient to soil moisture of corn fields is investigated. In the framework of the MAC-Europe Campaign in June 1991, the NASA/JPL three-frequency polarimetric AIRSAR system collected data over the test site Oberpfaffenhofen. The AIRSAR campaign in Oberpfaffenhofen was complemented with intensive ground truth measurements. The sampled corn fields are nearly in the range of the same incidence angle (approximately 20 deg) and belong to different soil types. The evaluation was carried out at a single data set. The results show that the backscattering, measured at P-band, can be described with only two parameters very well. The main parameter influencing the backscattering is the soil moisture content; the second subordinated parameter is the row direction.

  8. Validation of two gridded soil moisture products over India with in-situ observations

    NASA Astrophysics Data System (ADS)

    Unnikrishnan, C. K.; George, John P.; Lodh, Abhishek; Maurya, Devesh Kumar; Mallick, Swapan; Rajagopal, E. N.; Mohandas, Saji

    2016-07-01

    Surface level soil moisture from two gridded datasets over India are evaluated in this study. The first one is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation system based on Extended Kalman Filter method (EKF), which make use of satellite observation of Advanced Scatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Second dataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) using passive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations of soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil moisture products. The difference between these datasets over India is minimum in the non-monsoon months and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMO soil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellite soil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 and UKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in all seasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probability distribution of IMD soil moisture observation peaks at 0.25 m3/m3, NRSC at 0.15 m3/m3, AMSR-2 at 0.25 m3/m3 and UKMO at 0.35 m3/m3 during June-September period. Validation results show UKMO analysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets. The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soil moisture during monsoon season over India in NRSC data suggests the necessity of incorporating the actual vegetation for a better soil moisture retrieval using passive microwave sensors. Both products have good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf tree and

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

    USGS Publications Warehouse

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

    2017-01-01

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

  10. Evaluation of soil moisture downscaling using a simple thermal based proxy - the REMEDHUS network (Spain) example

    NASA Astrophysics Data System (ADS)

    Peng, J.; Niesel, J.; Loew, A.

    2015-08-01

    Soil moisture retrieved from satellite microwave remote sensing normally has spatial resolution in the order of tens of kilometers, which are too coarse for many regional hydrological applications such as agriculture monitoring and drought predication. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of the simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over a dense soil moisture observational network (REMEDHUS) in Spain. Firstly, the optimized VTCI was determined through sensitivity analyses of VTCI to surface temperature, vegetation index, cloud, topography and land cover heterogeneity, using data from MODIS and MSG SEVIRI. Then the downscaling scheme was applied to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture observations, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The accuracy level is comparable to other downscaling methods that were also validated against REMEDHUS network. Furthermore, slightly better performance of MSG SEVIRI over MODIS was observed, which suggests the high potential of applying geostationary satellite for downscaling soil moisture in the future. Overall, considering the simplicity, limited data requirements and comparable accuracy level to other complex methods, the VTCI downscaling method can facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

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

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  13. 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.

  14. Estimating daily root-zone soil moisture in snow-dominated regions using an empirical soil moisture diagnostic equation

    NASA Astrophysics Data System (ADS)

    Pan, Feifei; Nieswiadomy, Michael

    2016-11-01

    Soil moisture in snow-dominated regions has many important applications including evapotranspiration estimation, flood forecasting, water resource and ecosystem services management, weather prediction and climate modeling, and quantification of denudation processes. A simple and robust empirical approach to estimate root-zone soil moisture in snow-dominated regions using a soil moisture diagnostic equation that incorporates snowfall and snowmelt processes is suggested and tested. A five-water-year dataset (10/1/2010-9/30/2015) of daily precipitation, air temperature, snow water equivalent and soil moistures at three depths (i.e., 5 cm, 20 cm, and 50 cm) at each of 12 Snow Telemetry (SNOTEL) sites across Utah (37.583°N-41.883°N, 110.183°W-112.9°W), is applied to test the proposed method. The first three water years are designated as the parameter-estimation period (PEP) and the last two water years are chosen as the model-testing period (MTP). Applying the estimated soil moisture loss function parameters and other empirical parameters in the soil moisture diagnostic equation in the PEP, soil moistures in three soil columns (0-5 cm, 0-20 cm, and 0-50 cm) are estimated in the MTP. The relatively accurate soil moisture estimations compared to the observations at 12 SNOTEL sites (RMSE ⩽ 6.23 (%V/V), average RMSE = 4.28 (%V/V), correlation coefficient ⩾0.75, average correlation coefficient =0.89, the Nash-Sutcliffe efficient coefficient Ec ⩾ 0.24, average Ec = 0.72) indicate that the soil moisture diagnostic equation is capable of accurately estimating soil moisture in snow-dominated regions after the snowfall and snowmelt processes are included in the soil moisture diagnostic equation.

  15. Joint microwave and infrared studies for soil moisture determination

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

  16. 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

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

    NASA Astrophysics Data System (ADS)

    Coates, Victoria; Pattison, Ian; Sander, Graham

    2016-04-01

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

  18. An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

    NASA Astrophysics Data System (ADS)

    Wang, J. R.

    1992-11-01

    Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were conducted by a group of investigators over a 15-km by 15-km test site south of Manhattan, Kansas, during the First ISLSCP Field Experiment (FIFE) in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several active and passive microwave sensors as well as a gamma radiation device. The calculations were based on a catchment-scale water balance model that is driven by spatially interpolated rainfalls and estimated potential evaporation. The results of this group effort are presented in the five papers in this section. They include discussions on the statistics of soil moisture variability within a pixel of a remote sensor, soil moisture measurements by impedance probes, the comparison of active and passive microwave sensing of surface soil moisture, the statistics of soil moisture estimation by a gamma-radiation technique, and the comparison of the calculated and measured latent heat fluxes at the catchment scale (4 km by 4 km).

  19. Soil moisture determination study. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1979-01-01

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

  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. Soil moisture remote sensing: State of the science

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Use of soil moisture sensors for irrigation scheduling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Various types of soil moisture sensing devices have been developed and are commercially available for water management applications. Each type of soil moisture sensors has its advantages and shortcomings in terms of accuracy, reliability, and cost. Resistive and capacitive based sensors, and time-d...

  4. Challenges in Interpreting and Validating Satellite Soil Moisture Information

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...

  5. 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 ...

  6. Assessment of the SMAP level 2 passive soil moisture product

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on Jan 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days using an L-band (active) radar and an L-band (passive) radiometer. SMAP provides ...

  7. The global distribution and dynamics of surface soil moisture

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each

  10. Influence of soil moisture on linear alkylbenzene sulfonate-induced toxicity in ammonia-oxidizing bacteria.

    PubMed

    Nielsen, Klaus B; Brandt, Kristian K; Jacobsen, Anne-Marie; Mortensen, Gerda K; Sørensen, Jan

    2004-02-01

    Moisture affects bioavailability and fate of pollutants in soil, but very little is known about moisture-induced effects on pollutant toxicity. We here report on a modifying effect of moisture on degradation of linear alkylbenzene sulfonates (LASs) and on their toxicity towards ammonia-oxidizing bacteria (AOB) in agricultural soil. In soil spiked with two LAS levels (250 or 1,000 mg/kg) and incubated at four different moisture levels (9-100% of water-holding capacity), degradation was strongly affected by both soil moisture and initial LAS concentration, resulting in degradation half-lives ranging from 13 to more than 160 d. Toxicity towards AOB assessed by a novel Nitrosomonas europaea luxAB-reporter assay was correlated to total LAS concentration, indicating that LAS remained bioavailable over time without accumulation of toxic intermediates. Toxicity towards indigenous AOB increased with increasing soil moisture. The results indicate that dry soil conditions inhibit LAS degradation and provide protection against toxicity within the indigenous AOB, thus allowing for a rapid recovery of this population when LAS degradation is resumed and completed after rewetting. We propose that the protection of microbial populations against toxicity in dry soil may be a general phenomenon caused primarily by limited diffusion and thus a low bioavailability of the toxicant.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  13. [Effects of soil thickness on spatiotemporal pattern of soil moisture in catchment level].

    PubMed

    Chen, Jia; Shi, Zhi-Hua; Li, Lu; Luo, Xuan

    2009-07-01

    Based on the fixed-spot observation, this paper analyzed the effects of soil thicknesses on the spatiotemporal pattern of soil moisture in the Wulongchi catchment of Danjiangkou, China. The soil moisture content increased soon after precipitation events, followed by a decline as the soil dried down, whilst its spatial heterogeneity exhibited an opposite pattern. The profile-averaged soil moisture content differed significantly with soil thickness. The soil with a thickness of 20 cm had lower profile-averaged moisture content whose variation trend was similar to that of precipitation and varied obviously among seasons; medium thickness (20-40 cm) soil had medium level of profile-averaged moisture content whose seasonal variation was moderately and affected by the characteristics of precipitation; while the soil with a thicknesses of > 40 cm had higher profile-averaged moisture content whose seasonal variation was relatively small. The profile distribution pattern of soil moisture was determined by the integrated effects of precipitation, evapotranspiration, and leakage, exhibiting increasing-type at semi-humid stage, waving-type at humid stage, and both of the two types at arid stage. There was a significant positive correlation between profile-averaged soil moisture content and soil thickness, and the correlation coefficient was 0.630-0.855. The moisture content in 0-15 cm soil layer had less correlation with soil thickness, but the moisture content in 20-55 cm soil layer was significantly correlated with soil thickness.

  14. Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

    NASA Astrophysics Data System (ADS)

    Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

    2016-04-01

    Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico

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

    NASA Astrophysics Data System (ADS)

    Goodchild, Martin; Kühn, Karl; Jenkins, Dick

    2014-05-01

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

  16. Application of Modular Modeling System to Predict Evaporation, Infiltration, Air Temperature, and Soil Moisture

    NASA Technical Reports Server (NTRS)

    Boggs, Johnny; Birgan, Latricia J.; Tsegaye, Teferi; Coleman, Tommy; Soman, Vishwas

    1997-01-01

    Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  19. 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

  20. 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...

  1. 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.

  2. The Soil Moisture Active Passive (SMAP) Applications Activity

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Moran, Susan; Escobar, Vanessa; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni

    2011-01-01

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP measurements will allow global and high-resolution mapping of soil moisture and its freeze/thaw state at resolutions from 3-40 km. These measurements will have high value for a wide range of environmental applications that underpin many weather-related decisions including drought and flood guidance, agricultural productivity estimation, weather forecasting, climate predictions, and human health risk. In 2007, NASA was tasked by The National Academies to ensure that emerging scientific knowledge is actively applied to obtain societal benefits by broadening community participation and improving means for use of information. SMAP is one of the first missions to come out of this new charge, and its Applications Plan forms the basis for ensuring its commitment to its users. The purpose of this paper is to outline the methods and approaches of the SMAP applications activity, which is designed to increase and sustain the interaction between users and scientists involved in mission development.

  3. The Capability of Microwave Radiometers In Retrieving Soil Moisture Profiles Using A Neural Networks

    NASA Astrophysics Data System (ADS)

    Macelloni, G.; Paloscia, S.; Santi, E.; Tedesco, M.

    Hydrological models require the knowledge of land surface parameters like soil mois- ture and snow properties with a large spatial distribution and high temporal frequency. Whilst conventional methods are unable to satisfy the constraints of space and time estimation of these parameters, the use of remote sensing data represents a real im- provement. In particular the potential of data collected by microwave radiometers at low frequencies to extract soil moisture has been clearly demonstrated in several pa- pers. However, the penetration power into the soil depends on frequency and, whereas L-band is able to estimate the moisture of a relatively thick soil layer, higher frequen- cies are only sensitive to the moisture of soil layer closer to the surface. This remark leads to the hypothesis that multifrequency observations could be able to retrieve a soil moisture profile. In several experiments carried out both on agricultural fields and on samples of soil in a tank, by using the IROE multifrequency microwave radiometers, the effect of moisture and surface roughness on different frequencies was studied. From this experiments the capability of L-band in measuring the moisture of a soil layer of several centimeters, in the order of the wavelength, was confirmed, as well the sensitivity to the moisture of the first centimeters layer at C- and X-bands, and the one of the very first layer of smooth soil at Ka-band. Using an electromagnetic model (Integral Equation Model, IEM) the brightness temperatures as a function of the in- cidence angle were computed at 1.4, 6, 10, and 37 GHz for different soil moisture profiles and different surface roughness. A particular consideration was dedicated to the latter parameter, since, especially at Ka band, surface roughness strongly affects the emission and masks the effect of moisture. Different soil moisture profiles have been tested: increasing and decreasing with depth and also constant for sandy and sandy-loam soils. After this

  4. Remotely sensed soil moisture input to a hydrologic model

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  5. Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

    NASA Technical Reports Server (NTRS)

    Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

    2014-01-01

    Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  7. 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.

  8. Soil moisture and the persistence of North American drought

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Hales, T.; Ford, C. R.

    2011-12-01

    Climate change will alter the amount, type (i.e., snow vs. rain), and timing of precipitation that controls many hazardous Earth surface processes, including debris flows. Most GCMs agree that as climate warms the frequency of extreme precipitation will increase across the globe. Debris flow events triggered by heavy precipitation will likely also increase. Precipitation also affects the resistance to debris flow initiation by controlling belowground plant hydraulic architecture (e.g. root frequency, diameter distribution, tensile strength). Quantifying the links between precipitation, below ground properties, and the processes that initiate debris flows are therefore critical to understanding future hazard. To explore these links, we conducted a field experiment in the Coweeta Hydrologic Laboratory by excavating 12 soil pits (~1 m3), from two topographies (noses, hollows), and two tree species (Liriodendron tulipifera and Betula lenta). For each species and topography, we collected all biomass from five soil depths and measured soil moisture at 30, 60, and 90cm depth. For each depth we also measured root tensile strength, root cellulose content. Where we collected soil moisture data, we also measured root and soil hydraulic conductivity. Our data show a link between soil moisture content and root biomass distribution; root biomass is more evenly distributed through the soil column in hollows compared to noses. This relationship is consistent with the hypothesis that more consistent soil moisture in hollows allows plant roots to access resources from deeper within the soil column. This physiologic control has a significant effect on root cohesion, with trees on noses (or lower average soil moisture) providing greater root cohesion close to the surface, but considerably less cohesion at depth. Root tensile strength correlated with local daily soil moisture rather than the long term differences represented by noses and hollows. Daily soil moisture affected the amount

  10. Integration of soil moisture and geophysical datasets for improved water resource management in irrigated systems

    NASA Astrophysics Data System (ADS)

    Finkenbiner, Catherine; Franz, Trenton E.; Avery, William Alexander; Heeren, Derek M.

    2016-04-01

    Global trends in consumptive water use indicate a growing and unsustainable reliance on water resources. Approximately 40% of total food production originates from irrigated agriculture. With increasing crop yield demands, water use efficiency must increase to maintain a stable food and water trade. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Fixed and roving cosmic-ray neutron probes were combined in order to characterize the spatial and temporal patterns of soil moisture at three study sites across an East-West precipitation gradient in the state of Nebraska, USA. A coarse scale map was generated for the entire domain (122 km2) at each study site. We used a simplistic data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler (˜102m2) for variable rate irrigation, the individual wedge (˜103m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. Additionally, we were able to generate a daily soil moisture product over the entire study area at various key modeling and remote sensing scales 12, 32, and 122 km2. Our soil moisture products and derived soil properties were then compared against spatial datasets (i.e. field capacity and wilting point) from the US Department of Agriculture Web Soil Survey. The results show that our "observed" field capacity was higher compared to the Web Soil Survey products. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depth and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of this non-contact and pragmatic geophysical method into current irrigation practices across the state and globe has the

  11. Effects of recurrent rolling/crimping operations on cover crop termination, soil moisture, and soil strength for conservation organic systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rolling/crimping technology has been utilized to mechanically terminate cover crops in conservation agriculture. In the southeastern United States, to eliminate competition for valuable soil moisture, three weeks are typically required after rolling to plant a cash crop into the desiccated cover cro...

  12. Aqua AMSR-E soil moisture retrieval: Evaluation and potential Algorithm improvement

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Global estimates of soil moisture derived from the Advanced Microwave Scanning Radiometer on Aqua (AMSR-E) have been an invaluable resource over the past decade for a broad spectrum of research and applications that include global hydrology, agriculture, and climate and weather forecasting. NASA, as...

  13. Validation of the Soil Moisture Active Passive mission using USDA-ARS experimental watersheds

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The calibration and validation program of the Soil Moisture Active Passive mission (SMAP) relies upon an international cooperative of in situ networks to provide ground truth references across a variety of landscapes. The USDA Agricultural Research Service operates several experimental watersheds wh...

  14. Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An increase in abnormal climate change patterns and unsustainable irrigation in uplands cause drought and affect agricultural water security, crop productivity, and price fluctuations. In this study, we developed a soil moisture model to project irrigation requirements (IR) for upland crops under cl...

  15. Mapping soil moisture across an irrigated field using electromagnetic conductivity imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The ability to measure and map volumetric soil water theta quickly and accurately is important in irrigated agriculture. However, the traditional approach of using thermogravimetric moisture (w) and converting this to theta using measurements of bulk density (theta – cm3/cm3) is laborious and time c...

  16. A comparison between two algorithms for the retrieval of soil moisture using AMSR-E data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A comparison between two algorithms for estimating soil moisture with microwave satellite data was carried out by using the datasets collected on the four Agricultural Research Service (ARS) watershed sites in the US from 2002 to 2009. These sites collectively represent a wide range of ground condit...

  17. Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

  18. 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...

  19. Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remo...

  20. Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Estimation of soil moisture has received considerable attention in the areas of hydrology, agriculture, meteorology and environmental studies because of its role in the partitioning water and energy at the land surface. In this study, the Ensemble Kalman Filter (EnKF), a popular data assimilation te...

  1. Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for non-linear systems was applied to the Root Zone Water Quality Model. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were us...

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  3. 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.

  4. Soil moisture downscaling using a simple thermal based proxy

    NASA Astrophysics Data System (ADS)

    Peng, Jian; Loew, Alexander; Niesel, Jonathan

    2016-04-01

    Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

  5. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

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

  6. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

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

  7. 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.

  8. Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Within the Soil Erosion and Degradation Research Group Experimental Stations, soil moisture is being researched as a key factor of the soil hydrology and soil erosion (Cerdà, 1995; Cerda, 1997; Cerdà 1998). This because under semiarid conditions soil moisture content plays a crucial role for agriculture, forest, groundwater recharge and soil chemistry and scientific improvement is of great interest in agriculture, hydrology and soil sciences. Soil moisture has been seeing as the key factor for plant photosynthesis, respiration and transpiration in orchards (Schneider and Childers, 1941) and plant growth (Veihmeyer and Hendrickson, 1950). Moreover, soil moisture determine the root growth and distribution (Levin et al., 1979) and the soil respiration ( Velerie and Orchard, 1983). Water content is expressed as a ratio, ranging from 0 (dry) to the value of soil porosity at saturation (wet). In this study we present 1-year of soil moisture measurements at two experimental sites in the Valencia region, Eastern Spain: one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). The EC-5 soil moisture smart sensor S-SMC-M005 integrated with the field-proven ECH2O™ Sensor and a 12-bit A/D has been choosen for measuring soil water content providing ±3% accuracy in typical soil conditions. Soil moisture measurements were carried out at 5-minute intervals from January till December 2012. In addition, soil moisture was measured at two depths in each landscape: 2 and 20 cm depth - in order to retrieve a representative vertical cross-section of soil moisture. Readings are provided directly from 0 (dry) to 0.450 m3/m3 (wet) volumetric water content. The soil moisture smart sensor is conected to a HOBO U30 Station - GSM-TCP which also stored 5-minute temperature, relative humidity, dew point, global solar radiation, precipitation, wind speed and wind direction

  9. Estimating root zone soil water content using limited soils information and surface soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Heathman, Gary Claude

    2001-10-01

    The various hydrologic processes of infiltration, redistribution, drainage, evaporation, and water uptake by plants are strongly interdependent, as they occur sequentially or simultaneously. An important state variable that strongly influences the magnitude to which these rate processes occur is the amount of water present within the root zone, and in particular, the top few centimeters near the soil surface. Traditionally, measurements of soil moisture have been limited to point measurements made in the field. In general, averages of point measurements are used to characterize the soil moisture of an area, but these averages seldom yield information that is adequate to characterize large scale hydrologic processes. Recent advancements in remote sensing now make it possible to obtain areal estimates of surface soil moisture. The use of remotely sensed data to estimate surface soil moisture, combined with soil water and hydrologic modeling, provides a unique opportunity to advance our understanding of hydrologic processes at a much larger scale. Standard techniques for measuring soil moisture have been well documented, with commercial instrumentation being widely available. Various computer models have been developed to estimate soil moisture in the root and vadose zone, although their application over large scales is limited due to varying spatial and temporal field conditions. It is the combination of ground-based data (in-situ measurements), near-surface soil moisture data, and modeling that form the basis for this research. The interactive use of field research, remote sensing ground truth data, and integrated systems modeling is used to describe surface and profile soil moisture conditions at several locations within a large watershed. Successful application of this approach should improve our capabilities for estimating soil hydraulic properties and to better estimate water and chemical transport in the root zone, thus enhancing water use efficiency and plant

  10. 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

  11. 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

  12. Microbial destruction of chitin in soils under different moisture conditions

    NASA Astrophysics Data System (ADS)

    Yaroslavtsev, A. M.; Manucharova, N. A.; Stepanov, A. L.; Zvyagintsev, D. G.; Sudnitsyn, I. I.

    2009-07-01

    The most favorable moisture conditions for the microbial destruction of chitin in soils are close to the total water capacity. The water content has the most pronounced effect on chitin destruction in soils in comparison with other studied substrates. It was found using gas-chromatographic and luminescent-microscopic methods that the maximum specific activity of the respiration of the chitinolytic community was at a rather low redox potential with the soil moisture close to the total water capacity. The range of moisture values under which the most intense microbial transformation of chitin occurred was wider in clayey and clay loamy soils as compared with sandy ones. The increase was observed due to the contribution of mycelial bacteria and actinomycetes in the chitinolytic complex as the soil moisture increased.

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  15. Remote monitoring of soil moisture using airborne microwave radiometers

    NASA Technical Reports Server (NTRS)

    Kroll, C. L.

    1973-01-01

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

  16. Spatial distribution of soil moisture in precision farming using integrated soil scanning and field telemetry data

    NASA Astrophysics Data System (ADS)

    Kalopesas, Charalampos; Galanis, George; Kalopesa, Eleni; Katsogiannos, Fotis; Kalafatis, Panagiotis; Bilas, George; Patakas, Aggelos; Zalidis, George

    2015-04-01

    Mapping the spatial variation of soil moisture content is a vital parameter for precision agriculture techniques. The aim of this study was to examine the correlation of soil moisture and conductivity (EC) data obtained through scanning techniques with field telemetry data and to spatially separate the field into discrete irrigation management zones. Using the Veris MSP3 model, geo-referenced data for electrical conductivity and organic matter preliminary maps were produced in a pilot kiwifruit field in Chrysoupoli, Kavala. Data from 15 stratified sampling points was used in order to produce the corresponding soil maps. Fusion of the Veris produced maps (OM, pH, ECa) resulted on the delineation of the field into three zones of specific management interest. An appropriate pedotransfer function was used in order to estimate a capacity soil indicator, the saturated volumetric water content (θs) for each zone, while the relationship between ECs and ECa was established for each zone. Validation of the uniformity of the three management zones was achieved by measuring specific electrical conductivity (ECs) along a transect in each zone and corresponding semivariograms for ECs within each zone. Near real-time data produced by a telemetric network consisting of soil moisture and electrical conductivity sensors, were used in order to integrate the temporal component of the specific management zones, enabling the calculation of time specific volumetric water contents on a 10 minute interval, an intensity soil indicator necessary to be incorporated to differentiate spatially the irrigation strategies for each zone. This study emphasizes the benefits yielded by fusing near real time telemetric data with soil scanning data and spatial interpolation techniques, enhancing the precision and validity of the desired results. Furthermore the use of telemetric data in combination with modern database management and geospatial software leads to timely produced operational results

  17. A statistical retrieval algorithm for root zone soil moisture

    NASA Astrophysics Data System (ADS)

    Lindau, Ralf; Simmer, Clemens

    2014-11-01

    An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.

  18. Inversion algorithms for the microwave remote sensing of soil moisture. Experiments with swept frequency microwaves

    NASA Technical Reports Server (NTRS)

    Hancock, G. D.; Waite, W. P.

    1984-01-01

    Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.

  19. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  20. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    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 during SMEX03 GA. A network of in situ soil moisture measurement devices, established to provide validation data for the satellite collections and for long-term estimation of soil moisture conditions throughout the region, provided continuous measurements at 19 sites. Additional soil moisture and temperature validation data were collected daily from 49 field sites. These sites represented a diversity of land covers including forest, cotton, peanut, and pasture. Precipitation that occurred prior to June 22nd and from June 29th through July 2nd produced drying conditions from June 23rd to June 28th and gradual wetting from June 29th through July 2nd. Soil moisture in the top 0-1 cm of the soil was found to be more responsive to precipitation and to have greater variability than soil moisture at the 0-3 or 3-6 cm layers. Within different land covers, soil moisture followed the same trends, but varied with land use. Pasture sites were consistently the wettest while row-crop sites were normally the driest. Good agreement was observed between soil moisture measurements collected with the in situ network and the 49 SMEX sites. For the study period, soil moisture across the entire 50 km by 75 km region and five of the six 25 km by 25 km EASE-Grids demonstrated time stable characteristics. Time stability analysis and statistical tests demonstrated the in situ stations had a small dry bias as compared to the SMEX03 GA measurements. These results indicate that the in situ network will be a good resource for long-term calibration of remotely sensed soil moisture and provide

  3. Soil Moisture Retrievals Using L-band Radiometer Observations in SMEX02: Successes and Challenges

    NASA Astrophysics Data System (ADS)

    Crosson, W. L.; Limaye, A. S.; Laymon, C. A.

    2004-05-01

    Measurements at L-band are widely considered to be optimal for soil moisture remote sensing, taking into account emitting depth and complications arising from roughness and vegetation. Although there is no operational satellite-borne L-band radiometer today, plans are underway to deploy one by the end of the decade. During the Soil Moisture Experiments in 2002 (SMEX02), the Passive and Active L and S-band (PALS) instrument was flown over the Walnut Creek Watershed in Iowa. This agricultural region was selected to facilitate testing of microwave remote sensing algorithms under conditions of highly variable and sometimes dense vegetation cover. L-band brightness temperature observations from PALS were used to retrieve near-surface soil moisture for conditions representative of the dominant corn and soybean land covers in the watershed. Sensitivities of the retrieved soil moisture to surface temperature, surface roughness and the vegetation B parameter have been evaluated for both crops. Retrievals for corn were found to be highly sensitive to the vegetation B parameter, while retrievals for soybeans were most sensitive to surface roughness. The vegetation water content of approximately 4 kg/m2 for the corn sites appears to be high enough to make soil moisture retrievals problematic, but retrievals appear relatively robust for soybeans with a vegetation water content of 0.3-0.7 kg/m2. For both corn and soybeans there is considerable overlap in the parameter spaces (combinations of surface roughness and vegetation B parameter) that yield accurate moisture retrievals for three wet days analyzed, but these parameter values do not translate well to dry conditions. This may indicate potential deficiencies in the roughness and vegetation correction algorithms for agricultural areas and raises concerns about global operational soil moisture retrieval from satellite-borne microwave sensors.

  4. Improving the Operability of the Cosmic-ray Neutron Soil Moisture Method: Estimation of Soil Calibration Parameters Using Global Datasets

    NASA Astrophysics Data System (ADS)

    Finkenbiner, C. E.; Avery, W. A.; Franz, T. E.; Munoz-Arriola, F.; Rosolem, R.

    2014-12-01

    Despite its critical importance to global food security, approximately 60% of water used for agriculture is wasted each year through inadequate water conservation, losses in distribution, and inefficient irrigation. Therefore, in order to coordinate a strategy to accomplish the agricultural demands in the future we must maintain a stable global food and water trade while increasing crop yield and efficiency. This research aims to improve the operability of the novel cosmic-ray neutron method used for estimating field scale soil moisture. The sensor works by passively counting the above ground low-energy neutrons which correlates to the amount of water in the measurement volume (a circle with radius of ~300 m and vertical depth of ~30 cm). Because the sensor responds to different forms of water (sources of hydrogen), estimates of background water in the mineral soil and soil organic matter must be accounted in order to minimize measurement error. Here we compared field-scale estimates of soil mineral water and soil organic matter with readily available global datasets. Using the newly compiled 1 km resolution Global Soil Dataset (GSDE), we investigate the correlation between (1) soil mineral water and clay content and (2) in-situ soil organic material. Preliminary results of in-situ samples from forty study sites around the globe suggest the GSDE dataset has sufficiently low bias and uncertainty (~ within 0.01 g/g of water equivalent) to better isolate the soil moisture signal from the neutron count information. Incorporation of this dataset will allow for real-time soil moisture mapping of hundreds of center-pivots using the mobile cosmic-ray sensor without the need of time-consuming in-situ soil sampling. The incorporation of this novel technique for soil moisture management has the potential to increase the efficiency of irrigation water use.

  5. Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

    NASA Technical Reports Server (NTRS)

    Yang, Wenli; Pham, Long; Zhao, Peisheng; Kempler, Steve; Wei, Jennifer

    2016-01-01

    Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

  6. Synergistic use of active and passive microwave in soil moisture estimation

    NASA Technical Reports Server (NTRS)

    O'Neill, P.; Chauhan, N.; Jackson, T.; Saatchi, S.

    1992-01-01

    Data gathered during the MACHYDRO experiment in central Pennsylvania in July 1990 have been utilized to study the synergistic use of active and passive microwave systems for estimating soil moisture. These data sets were obtained during an eleven-day period with NASA's Airborne Synthetic Aperture Radar (AIRSAR) and Push-Broom Microwave Radiometer (PBMR) over an instrumented watershed which included agricultural fields with a number of different crop covers. Simultaneous ground truth measurements were also made in order to characterize the state of vegetation and soil moisture under a variety of meteorological conditions. A combination algorithm is presented as applied to a representative corn field in the MACHYDRO watershed.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Fate of 14C-labeled dissolved organic matter in paddy and upland soils in responding to moisture.

    PubMed

    Chen, Xiangbi; Wang, Aihua; Li, Yang; Hu, Lening; Zheng, Hua; He, Xunyang; Ge, Tida; Wu, Jinshui; Kuzyakov, Yakov; Su, Yirong

    2014-08-01

    Soil organic matter (SOM) content in paddy soils is higher than that in upland soils in tropical and subtropical China. The dissolved organic matter (DOM) concentration, however, is lower in paddy soils. We hypothesize that soil moisture strongly controls the fate of DOM, and thereby leads to differences between the two agricultural soils under contrasting management regimens. A 100-day incubation experiment was conducted to trace the fate and biodegradability of DOM in paddy and upland soils under three moisture levels: 45%, 75%, and 105% of the water holding capacity (WHC). (14)C labeled DOM, extracted from the (14)C labeled rice plant material, was incubated in paddy and upland soils, and the mineralization to (14)CO2 and incorporation into microbial biomass were analyzed. Labile and refractory components of the initial (14)C labeled DOM and their respective half-lives were calculated by a double exponential model. During incubation, the mineralization of the initial (14)C labeled DOM in the paddy soils was more affected by moisture than in the upland soils. The amount of (14)C incorporated into the microbial biomass (2.4-11.0% of the initial DOM-(14)C activity) was less affected by moisture in the paddy soils than in the upland soils. At any of the moisture levels, 1) the mineralization of DOM to (14)CO2 within 100 days was 1.2-2.1-fold higher in the paddy soils (41.9-60.0% of the initial DOM-(14)C activity) than in the upland soils (28.7-35.7%), 2) (14)C activity remaining in solution was significantly lower in the paddy soils than in the upland soils, and 3) (14)C activity remaining in the same agricultural soil solution was not significantly different among the three moisture levels after 20 days. Therefore, moisture strongly controls DOM fate, but moisture was not the key factor in determining the lower DOM in the paddy soils than in the upland soils. The UV absorbance of DOM at 280 nm indicates less aromaticity of DOM from the paddy soils than from the

  9. Multi-polarization C-band SAR for soil moisture estimation

    NASA Technical Reports Server (NTRS)

    Brown, R. J.; Brisco, B.

    1991-01-01

    Previous studies of synthetic aperture radar (SAR) imagery have shown qualitative relationships between radar backscatter and soil moisture. However, to be able to use these data in operational programs it will be necessary to establish quantitatively how the radar return is related to soil moisture and the effects of surface roughness, soil type, and vegetation cover and growth stage, as a function of frequency and polarization. To this end, a multi-year experiment began in 1990 as a cooperative venture amongst the Canada Center (Agriculture Canada), and the Universities of Guelph, Sherbrooke, Laval, and Waterloo. During 1990, SAR imagery was acquired during two periods (May and Jun.) to correspond to times of minimal and substantial vegetation cover. SAR data were acquired on three days in May and on four days in Jul. to cover different soil moisture conditions. This unique comprehensive data set is used to investigate the relationships between soil moisture and radar backscatter. The experiment and data collected are described, and a preliminary qualitative interpretation of the relationship between soil moisture and image tone is provided.

  10. Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

  11. Evaluating Soil Moisture Status Using an e-Nose

    PubMed Central

    Bieganowski, Andrzej; Jaromin-Glen, Katarzyna; Guz, Łukasz; Łagód, Grzegorz; Jozefaciuk, Grzegorz; Franus, Wojciech; Suchorab, Zbigniew; Sobczuk, Henryk

    2016-01-01

    The possibility of distinguishing different soil moisture levels by electronic nose (e-nose) was studied. Ten arable soils of various types were investigated. The measurements were performed for air-dry (AD) soils stored for one year, then moistened to field water capacity and finally dried within a period of 180 days. The volatile fingerprints changed during the course of drying. At the end of the drying cycle, the fingerprints were similar to those of the initial AD soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that e-nose results can be used to distinguish soil moisture. It was also shown that different soils can give different e-nose signals at the same moistures. PMID:27338404

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

    NASA Technical Reports Server (NTRS)

    Welker, J. E.

    1984-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  14. 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.

  15. 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.

  16. Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

    NASA Astrophysics Data System (ADS)

    Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

    2017-03-01

    Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has

  17. [Priming Effects of Soil Moisture on Soil Respiration Under Different Tillage Practices].

    PubMed

    Zhang, Yan; Liang, Ai-zhen; Zhang, Xiao-ping; Chen, Sheng-long; Sun, Bing-jie; Liu, Si-yi

    2016-03-15

    In the early stage of an incubation experiment, soil respiration has a sensitive response to different levels of soil moisture. To investigate the effects of soil moisture on soil respiration under different tillage practices, we designed an incubation trial using air-dried soil samples collected from tillage experiment station established on black soils in 2001. The tillage experiment consisted of no-tillage (NT), ridge tillage (RT), and conventional tillage (CT). According to field capacity (water-holding capacity, WHC), we set nine moisture levels including 30%, 60%, 90%, 120%, 150%, 180%, 210%, 240%, 270% WHC. During the 22-day short-term incubation, soil CO₂ emission was measured. In the early stage of incubation, the priming effects occurred under all tillage practices. There were positive correlations between soil respiration and soil moisture. In addition to drought and flood conditions, soil CO₂ fluxes followed the order of NT > RT > CT. We fitted the relationship between soil moisture and soil CO₂ fluxes under different tillage practices. In the range of 30%-270% WHC, soil CO₂ fluxes and soil moisture fitted a quadratic regression equation under NT, and linear regression equations under RT and CT. Under the conditions of 30%-210% WHC of both NT and RT, soil CO₂ fluxes and soil moisture were well fitted by the logarithmic equation with fitting coefficient R² = 0.966 and 0.956, respectively.

  18. Assimilation of Satellite Soil Moisture observation with the Particle Filter-Markov Chain Monte Carlo and Geostatistical Modeling

    NASA Astrophysics Data System (ADS)

    Moradkhani, Hamid; Yan, Hongxiang

    2016-04-01

    Soil moisture simulation and prediction are increasingly used to characterize agricultural droughts but the process suffers from data scarcity and quality. The satellite soil moisture observations could be used to improve model predictions with data assimilation. Remote sensing products, however, are typically discontinuous in spatial-temporal coverages; while simulated soil moisture products are potentially biased due to the errors in forcing data, parameters, and deficiencies of model physics. This study attempts to provide a detailed analysis of the joint and separate assimilation of streamflow and Advanced Scatterometer (ASCAT) surface soil moisture into a fully distributed hydrologic model, with the use of recently developed particle filter-Markov chain Monte Carlo (PF-MCMC) method. A geostatistical model is introduced to overcome the satellite soil moisture discontinuity issue where satellite data does not cover the whole study region or is significantly biased, and the dominant land cover is dense vegetation. The results indicate that joint assimilation of soil moisture and streamflow has minimal effect in improving the streamflow prediction, however, the surface soil moisture field is significantly improved. The combination of DA and geostatistical approach can further improve the surface soil moisture prediction.

  19. Influence of Surface Roughness Spatial Variability and Temporal Dynamics on the Retrieval of Soil Moisture from SAR Observations

    PubMed Central

    Álvarez-Mozos, Jesús; Verhoest, Niko E.C.; Larrañaga, Arantzazu; Casalí, Javier; González-Audícana, María

    2009-01-01

    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 currently available spaceborne sensors. The main difficulty experienced so far results from the strong influence of other surface characteristics, mainly roughness, on the backscattering coefficient, which hinders the soil moisture inversion. This is especially true for single configuration observations where the solution to the surface backscattering problem is ill-posed. Over agricultural areas cultivated with winter cereal crops, roughness can be assumed to remain constant along the growing cycle allowing the use of simplified approaches that facilitate the estimation of the moisture content of soils. However, the field scale spatial variability and temporal variations of roughness can introduce errors in the estimation of soil moisture that are difficult to evaluate. The objective of this study is to assess the impact of roughness spatial variability and roughness temporal variations on the retrieval of soil moisture from radar observations. A series of laser profilometer measurements were performed over several fields in an experimental watershed from September 2004 to March 2005. The influence of the observed roughness variability and its temporal variations on the retrieval of soil moisture is studied using simulations performed with the Integral Equation Model, considering different sensor configurations. Results show that both field scale roughness spatial variability and its temporal variations are aspects that need to be taken into account, since they can introduce large errors on the retrieved soil moisture values. PMID:22389611

  20. Soil moisture at local scale: Measurements and simulations

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio

    2014-08-01

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

  1. SMOS CATDS Level 3 products, Soil Moisture and Brightness Temperature

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Choi, Minha; Jacobs, Jennifer M.

    2007-04-01

    Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0-6, 5-11, 15-21, and 25-31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed. As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.

  3. Root Zone Soil Moisture Forecasting Using Multivariate Relevance Vector Machines

    NASA Astrophysics Data System (ADS)

    Zaman, B.; McKee, M.

    2009-12-01

    Root zone soil moisture at depths of 1 and 2 meters are forecasted four days into the future. Prediction of soil moisture can be of paramount importance owing to its applicability in soil water balance calculations, modeling of various hydrometeorological, ecological, and biogeochemical factors, and initialization of various land-atmosphere models. In this study, we propose a new multivariate output prediction approach for forecasting root zone soil moisture using learning machine models. These models are known for their robustness, efficiency, and sparseness, and provide a statistically sound approach to solving the inverse problems and thus to building statistical models. The multivariate relevance vector machine (MVRVM) is used to build a model that predicts future soil state based upon current soil moisture and soil temperature conditions. The predicting function learns the input-output response pattern from the training dataset. Soil moisture measurements acquired by the Soil Climate Analysis Network (SCAN) site at Rees Center, Texas are used for this study. The methodology combines the data at different depths from 5 cm to 50 cm, the largest of which corresponds to the depth at which the soil moisture sensors are generally operational, to produce soil moisture predictions at larger depths. The MVRVM model demonstrates superior performance. The results for soil moisture predictions at 1 m and 2 m depth for the fourth day are excellent, with RMSE = 0.0125 m3water/m3soil; IoA = 0.96; CoE = 0.88 at 1 m depth, and RMSE = 0.0021 m3/m3; IoA = 0.98; CoE = 0.93 for 2 m depth. The statistics indicate good model generalization capability and computations show good agreement with the actual soil moisture measurements with R2 = 0.89 and R2 = 0.94 for 1 m and 2 m depths on fourth day, respectively. The MVRVM produces good results for all four days with a reduced computational complexity and more suitable real-time implementation. Bootstrapping is used to check over

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

    SciTech Connect

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

    2010-11-01

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

  5. Predicting root zone soil moisture using surface data

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  6. 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.

  7. Improving the vegetation parametrization in the ASCAT soil moisture retrieval

    NASA Astrophysics Data System (ADS)

    Hahn, Sebastian; Wagner, Wolfgang

    2016-04-01

    The TU Wien soil moisture retrieval algorithm is based upon a backscatter model designed to exploit the multi-angle viewing capabilities of space-borne fan-beam scatterometers. In the beginning the backscatter model has been developed for the scatterometers on-board ERS-1 and ERS-2 and later successfully applied on the successor instrument ASCAT (Advanced Scatterometer) on-board the series of Metop satellites. The soil moisture retrieval algorithm represents a physically motivated change detection method, which requires model parameters derived along the way to the final soil moisture estimates. The computation of the model parameters needs to be done in the time domain and is computationally expensive. However, not all model parameters are computationally estimated from the backscatter measurements, but rather defined by empirical observations. The cross-over angles belong to this group of model parameters, which unlike other model parameters, remain spatially and temporally constant on a global scale. This study investigates the possibility to optimize the cross-over angles, which are important parameters for the vegetation correction in the TU Wien soil moisture retrieval algorithm. The optimization is carried out with various cost functions and compared against soil moisture values from land surface models. First results indicate that spatially varying cross-over angles help to improve the mean annual cycle of soil moisture.

  8. A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

    NASA Astrophysics Data System (ADS)

    Pradhan, N. R.

    2015-12-01

    Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

  9. Operational Irrigation Scheduling for Citrus Trees with Soil Moisture Data Assimilation and Weather Forecast

    NASA Astrophysics Data System (ADS)

    Han, Xujun; Hendricks Franssen, Harrie-Jan; Martínez Alzamora, Fernando; Ángel Jiménez Bello, Miguel; Chanzy, André; Vereecken, Harry

    2015-04-01

    Agricultural areas in the Mediterranean are expected to face more drought stress in the future due to climate change and human activities. Irrigation scheduling is necessary to allocate the optimal water amount at the right time period to avoid unnecessary water losses. An operational data assimilation framework was set-up to combine model predictions and soil moisture measurements in an optimal way for characterizing the soil water status of the root zone. Irrigation amounts for the next days are optimized on the basis of the soil water status of the root zone and meteorological ensemble predictions. In these experiments, the uncertainties of atmospheric forcings and soil properties were considered. The uncertain model forcings were taken from an ensemble of weather forecasts by ECMWF, and delivered by MeteoFrance in this project. The improved soil moisture profile was used to calculate the irrigation requirement taking into account the root distribution of citrus trees in the subsurface. The approach was tested operationally for the experimental site near Picassent, Valencia, Spain. Three fields were irrigated according to our approach in the years 2013 and 2014. Three others were irrigated traditionally, based on FAO-criteria. Soil moisture was measured by FDR probes at 10 cm and 30 cm depth at various fields and these real time data were assimilated by the Local Ensemble Transform Kalman Filter (LETKF) into the Community Land Model (CLM) to improve the estimation of the soil moisture profile. The measured soil moisture was assimilated five times per day before the start of the next drip irrigation. The final results (total amount of irrigated water, stem water potential and citrus production) show that our strategy resulted in significantly less irrigated water compared to the FAO-irrigated fields, but without indications of increased water stress. Soil moisture contents did not decline over time in our approach, stem water potential measurements did not

  10. ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management

    NASA Astrophysics Data System (ADS)

    Mecklenburg, S.; Kerr, Y. H.

    2015-12-01

    The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the

  11. Comparing soil moisture memory in satellite observations and models

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

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

  12. Evaluation of the validated soil moisture product from the SMAP radiometer

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...

  13. 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...

  14. Evaluation of SMAP radiometer level 2 soil moisture algorithms using four years of SMOS data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objectives of the SMAP (Soil Moisture Active Passive) mission include global measurements of soil moisture at three different spatial resolutions. SMAP will provide soil moisture with a 3-day revisit time at an accuracy of 0.04 m3/m3 The 36 km gridded soil moisture product (L2_SM_P) is primar...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    For several years passive microwave observations have been used to retrieve soil moisture from the Earth’s surface. Low frequency observations have the most sensitivity to soil moisture, therefore the modern Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) ...

  16. Comparing and Combining Surface Soil Moisture Products from AMSR2

    NASA Astrophysics Data System (ADS)

    Parinussa, R.; Kim, S.; Liu, Y.; Johnson, F.; Sharma, A.

    2015-12-01

    Soil moisture is an important variable in hydrological systems as its part of the water cycle in the atmosphere, the land surface and subsurface. Microwave remote sensing is a viable tool to monitor global soil moisture conditions at regular time intervals. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is a sensor onboard the Global Change Observation Mission 1 - Water that was launched in May 2012. Multiple soil moisture products from AMSR2 observations exist; these were compared and combined with special emphasis to the global scale. The first product is retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm, the other uses the Land Parameter Retrieval Model (LPRM). These two products were compared against each other and evaluated against COSMOS data over the United States, Australia, Europe and Africa. The temporal correlations highlight differences in the representation of the seasonal cycle of soil moisture. It is hypothesized that four factors, physical surface temperatures, surface roughness, vegetation and ground soil wetness conditions, affect the quality of soil moisture retrievals. The complementary between the products led to the opportunity to combine them into a superior one that benefits from the strengths of both algorithms.These soil moisture algorithms share the same background in the radiative transfer model, but each algorithm applies different approaches to reflect various external conditions. As a result, the performance of the products is complementary in many locations in terms of bias, RMSE and, most importantly temporal correlation coefficients. Here, we present a methodology that combines the two AMSR2 based soil moisture products into a single product, which improves the overall performance by leveraging the strengths of the individual products. The new product is combined by applying an optimal weighting factor, calculated based on variance and correlation coefficients against a reference dataset. The complementary

  17. Soil Respiration in Different Agricultural and Natural Ecosystems in an Arid Region

    PubMed Central

    Lai, Liming; Zhao, Xuechun; Jiang, Lianhe; Wang, Yongji; Luo, Liangguo; Zheng, Yuanrun; Chen, Xi; Rimmington, Glyn M.

    2012-01-01

    The variation of different ecosystems on the terrestrial carbon balance is predicted to be large. We investigated a typical arid region with widespread saline/alkaline soils, and evaluated soil respiration of different agricultural and natural ecosystems. Soil respiration for five ecosystems together with soil temperature, soil moisture, soil pH, soil electric conductivity and soil organic carbon content were investigated in the field. Comparing with the natural ecosystems, the mean seasonal soil respiration rates of the agricultural ecosystems were 96%–386% higher and agricultural ecosystems exhibited lower CO2 absorption by the saline/alkaline soil. Soil temperature and moisture together explained 48%, 86%, 84%, 54% and 54% of the seasonal variations of soil respiration in the five ecosystems, respectively. There was a significant negative relationship between soil respiration and soil electrical conductivity, but a weak correlation between soil respiration and soil pH or soil organic carbon content. Our results showed that soil CO2 emissions were significantly different among different agricultural and natural ecosystems, although we caution that this was an observational, not manipulative, study. Temperature at the soil surface and electric conductivity were the main driving factors of soil respiration across the five ecosystems. Care should be taken when converting native vegetation into cropland from the point of view of greenhouse gas emissions. PMID:23082234

  18. New DEMs may stimulate significant advancements in remote sensing of soil moisture

    NASA Astrophysics Data System (ADS)

    Nolan, Matt; Fatland, Dennis R.

    From Napoleon's defeat at Waterloo to increasing corn yields in Kansas to greenhouse gas flux in the Arctic, the importance of soil moisture is endemic to world affairs and merits the considerable attention it receives from the scientific community. This importance can hardly be overstated, though it often goes unstated.Soil moisture is one of the key variables in a variety of broad areas critical to the conduct of societies' economic and political affairs and their well-being; these include the health of agricultural crops, global climate dynamics, military trafficability planning, and hazards such as flooding and forest fires. Unfortunately the in situ measurement of the spatial distribution of soil moisture on a watershed-scale is practically impossible. And despite decades of international effort, a satellite remote sensing technique that can reliably measure soil moisture with a spatial resolution of meters has not yet been identified or implemented. Due to the lack of suitable measurement techniques and, until recently digital elevation models (DEMs), our ability to understand and predict soil moisture dynamics through modeling has largely remained crippled from birth [Grayson and Bloschl, 200l].

  19. Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

    1998-01-01

    The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

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

    PubMed

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

    2011-06-01

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

  1. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

    NASA Astrophysics Data System (ADS)

    DY, C. Y.; Fung, J. C. H.

    2016-08-01

    A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

  2. Indirect Measurement of Evapotranspiration from Soil Moisture Depletion

    NASA Astrophysics Data System (ADS)

    Li, M.; Chen, Y.

    2007-12-01

    Direct and in situ measurement of evapotranspiration (ET), such as the eddy covariance (EC) method, is often expensive and complicated, especially over tall canopy. In view of soil water balance, depletion of soil moisture can be attributed to canopy ET when horizontal soil moisture movement is negligible and percolation ceases. This study computed the daily soil moisture depletion at the Lien-Hua-Chih (LHC) station (23°55'52"N, 120°53'39"E, 773 m elevation) from July, 2004 to June, 2007 to estimate daily ET. The station is inside an experimental watershed of a natural evergreen forest and the canopy height is about 17 m. Rainfall days are assumed to be no ET. For those days with high soil moisture content, normally 2 to 3 days after significant rainfall input, ET is estimated by potential ET. Soil moistures were measured by capacitance probes at -10 cm, - 30 cm, -50 cm, -70 cm, and -90 cm. A soil heat flux plate was placed at -5 cm. In the summer of 2006, a 22 m tall observation tower was constructed. Temperature and relative humidity sensors were placed every 5 m from ground surface to 20 m for inner and above canopy measurements. Net radiation and wind speed/directions were also installed. A drainage gauge was installed at -50 cm to collect infiltrated water. Continuous measurements of low response instruments were recorded every 30-minute averaged from 10-minute samplings. A nearby weather station provides daily pan evaporation and precipitation data. Since the response of soil water variations is relatively slow to the fluctuations of atmospheric forcing, only daily ET is estimated from daily soil moisture depletion. The annual average precipitation is 2902 mm and the annual average ET is 700 mm. The seasonal ET patterns of the first two water years are similar. The third year has a higher ET because soil moisture was recharged frequently by rainfall In order to examine the applicability of this approach, an EC system, including a 3-D sonic anemometer (Young

  3. Validation and Upscaling of Soil Moisture Satellite Products in Romania

    NASA Astrophysics Data System (ADS)

    Sandric, I.; Diamandi, A.; Oana, N.; Saizu, D.; Vasile, C.; Lucaschi, B.

    2016-06-01

    The study presents the validation of SMOS soil moisture satellite products for Romania. The validation was performed with in-situ measurements spatially distributed over the country and with in-situ measurements concentrated in on small area. For country level a number of 20 stations from the national meteorological observations network in Romania were selected. These stations have in-situ measurements for soil moisture in the first 5 cm of the soil surface. The stations are more or less distributed in one pixel of SMOS, but it has the advantage that covers almost all the country with a wide range of environmental conditions. Additionally 10 mobile soil moisture measurements stations were acquired and installed. These are spatially concentrated in one SMOS pixel in order to have a more detailed validation against the soil type, soil texture, land surface temperature and vegetation type inside one pixel. The results were compared and analyzed for each day, week, season, soil type, and soil texture and vegetation type. Minimum, maximum, mean and standard deviation were extracted and analyzed for each validation criteria and a hierarchy of those were performed. An upscaling method based on the relations between soil moisture, land surface temperature and vegetation indices was tested and implemented. The study was financed by the Romanian Space Agency within the framework of ASSIMO project http://assimo.meteoromania.ro.

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

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

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

  5. Calibration of the Root Zone Water Quality Model and Application of Data Assimilation Techniques to Estimate Profile Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Estimation of soil moisture has received considerable attention in the areas of hydrology, agriculture, meteorology and environmental studies because of its role in the partitioning water and energy at the land surface. In this study, the USDA, Agricultural Research Service, Root Zone Water Quality ...

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

    NASA Astrophysics Data System (ADS)

    Tran, Phuong; Vanclooster, Marnik; Lambot, Sébastien

    2013-04-01

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

  7. The Role of Evapotranspiration on Soil Moisture Depletion in a Small Alaskan Subarctic Farm

    NASA Astrophysics Data System (ADS)

    Ruairuen, W.; Fochesatto, G. J.; Sparrow, E. B.; Schnabel, W.; Zhang, M.

    2013-12-01

    At high latitudes the period for agriculture production is very short (110 frost-free days) and strongly depends on the availability of soil water content for vegetables to grow. In this context the evapotranspiration (ET) cycle is key variable underpinning mass and energy balance modulating therefore moisture gradients and soil dryness. Evapotranspiration (ET) from field-grown crops water stress is virtually unknown in the subarctic region. Understanding ET cycles in high latitude agricultural ecosystem is essential in terms of water management and sustainability and projection of agricultural activity. To investigate the ET cycle in farming soils a field experiment was conducted in the summer of 2012 and 2013 at the University of Alaska Fairbanks Agricultural and Forestry Experiment Station combining micrometeorological and hydrological measurements. In this case experimental plots of lettuce (Lactuca sativa) plants were grown. The experiment evaluated several components of the ET cycle such as actual evapotranspiration, reference evaporation, pan evaporation as well as soil water content and temperature profiles to link them to the vegetable growing functions. We investigated the relationship of soil moisture content and crop water use across the growing season as a function of the ET cycle. Soil water depletion was compared to daily estimates of water loss by ET during dry and wet periods. We also investigated the dependence of ET on the atmospheric boundary layer flow patterns set by the synoptic large scale weather patterns.

  8. Effect of soil moisture on pesticide toxicity to an enchytraeid worm, Enchytraeus sp.

    PubMed

    Puurtinen, H M; Martikainen, E A

    1997-07-01

    The aim of the study was to find out whether soil moisture affects toxicity of organic pesticides to an enchytraeid worm. Laboratory experiments were carried out with dimethoate and benomyl, using a small Enchytraeus sp. as the test species. Substrate was natural agricultural field soil cultivated without pesticides for several years. Experimental design consisted of three soil moistures (40, 55, and 70% of water holding capacity) and five pesticide concentrations, plus controls. Measured parameters were survival, size of the parent worms and number and size of juveniles produced. Dimethoate was relatively non-toxic to this species. Dimethoate did not decrease survival, but sublethal effects on adult size and number of juveniles were observed. Adverse conditions in dry soil masked these effects; dimethoate appeared to be less toxic in dry soil than in moist soil. Benomyl caused significant mortality and the effects were very abrupt. Toxicity of benomyl decreased with increasing soil moisture content; in moist soil the worms survived at higher benomyl concentrations than in drier soils.

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

    NASA Astrophysics Data System (ADS)

    Dijkstra, F. A.; Cheng, W.

    2005-12-01

    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 85% of field capacity in a greenhouse experiment. We continuously labeled plants with depleted 13C, which allowed us to separate plant-derived CO2-C from original soil-derived CO2-C in soil respiration measurements. We observed an overall increase in soil-derived CO2-C efflux in the presence of plants (priming effect) in both soils with on average a greater priming effect in the high soil moisture treatment (60% increase in soil-derived CO2-C compared to control) than in the low soil moisture treatment (37% increase). Greater plant biomass in the high soil moisture treatment contributed to greater priming effects, but priming effects remained significantly higher after correcting for plant biomass. Possibly, root exudation of labile C may have increased more than plant biomass and may have become more effective in stimulating microbial decomposition in the higher soil moisture treatment. Our results indicate that changing soil moisture conditions can significantly alter rhizosphere effects on soil C decomposition.

  10. Soil moisture monitoring methods: Strengths and limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Upscaling sparse, irregularly spaced in situ soil moisture measurements for calibration and validation of SMAP soil moisture products

    NASA Astrophysics Data System (ADS)

    Whitcomb, J.; Clewley, D.; Moghaddam, M.; Akbar, R.; Silva, A. R. D.

    2015-12-01

    There is a large difference in the footprints over which remote sensing instruments, such as the Soil Moisture Active Passive (SMAP) mission, retrieve soil moisture and that of in situ networks. Therefore a method for upscaling in situ measurements is required before they can be used to validate remote sensing instruments. The upscaling problem is made more difficult when measurements are sparse and irregularly spaced within the footprint. To address these needs, we have developed a method for producing upscaled estimates of soil moisture based on a network of in situ soil moisture measurements and airborne P-band SAR data, and utilizing a Random Forests-based regression algorithm. Sites within the SoilSCAPE network, for which the technique was developed, typically contains sensors at ~30 locations, with each location sampled at multiple depths. Measurements are taken at 20 minute intervals and averaged over a selectable time interval, thereby supporting near-real time generation of soil moisture maps. The collected measurements are automatically uploaded to a central database from which they can be accessed for use in the regression algorithm. Our regression-based approach works well with irregularly-spaced sensors by incorporating a set of data layers that correlate well with soil moisture. The layers include thematic land cover, elevation, slope, aspect, flow accumulation, clay fraction, air temperature, precipitation, and P-Band HH, VV, and HV backscatter. Values from these data layers are extracted for each sensor location and applied to train the Random Forests algorithm. The decision trees generated are then applied to estimate soil moisture at a 100 m spacing throughout the network region, after which the evenly-spaced values are averaged to accord with the 3-, 9-, and 36-km SMAP measurement grids. The resulting set of near-real time soil moisture estimates suitable for SMAP calibration and validation is placed online for use by the SMAP Cal/Val team

  12. 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

  13. Using electromagnetic conductivity imaging to generate time-lapse soil moisture estimates.

    NASA Astrophysics Data System (ADS)

    Huang, Jingyi; Scuderio, Elia; Corwin, Dennis; Triantafilis, John

    2015-04-01

    Irrigated agriculture is crucial to the agricultural productivity of the Moreno valley. To maintain profitability, more will need to be done by irrigators with less water, owing to competing demands from rapidly expanding urbanisation in southern California. In this regard, irrigators need to understand the spatial and temporal variation of soil moisture to discern inefficiencies. However, soil moisture is difficult to measure and monitor, unless a large bank of soil sensors are installed and at various depths in the profile. In order to value add to the limited amount of information, geophysical techniques, such as direct current resisivity (DCR) arrays are used to develop electrical resistivity images (ERI). Whilst successful the approach is time consuming and labour intensive. In this research we describe how equivalent data can be collected using a proximal sensing electromagnetic (EM) induction instrument (i.e. DUALEM-421) and inversion software (EM4Soil) to generate EM conductivity images (EMCI). Figure 1 shows the EMCI generated from DUALEM-421 data acquired at various days of a time-lapse experiment and including; day a) 0, b) 1, c) 2, d) 3, e) 5, f) 7 and g) 11. We calibrate the estimates of true electrical conductivity (sigma - mS/m) with volumetric moisture content and show with good accuracy the spatial and temporal variation of soil moisture status and over 12 day period. The results show clearly that the pivot sprinkler irrigation system is effective at providing sufficient amounts of water to the top 0.5 m of a Lucerne crop (i.e. red shaded areas of high sigma). However, in some places faulty sprinklers are evident owing to the lack of wetting (i.e. blue shaded areas of low sigma). In addition, and over time, our approach shows clearly the effect the Lucerne crop has in drying the soil profile and using the soil moisture.

  14. Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor

    PubMed Central

    Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

    2016-01-01

    Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10–14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m3·m−3 in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m3·m−3, as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation. PMID:27537881

  15. Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor.

    PubMed

    Kojima, Yuki; Shigeta, Ryo; Miyamoto, Naoya; Shirahama, Yasutomo; Nishioka, Kazuhiro; Mizoguchi, Masaru; Kawahara, Yoshihiro

    2016-08-15

    Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10-14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m³·m(-3) in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m³·m(-3), as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation.

  16. On the disaggregation of satellite based passive microwave estimates of soil moisture: current status and future challenges

    NASA Astrophysics Data System (ADS)

    Chehbouni, A.; Merlin, O.

    2007-05-01

    Soil moisture is a fundamental state variable that controls several earth surface related processes, i.e. hydrology, meteorology, climate modelling, and agricultural management. However, the spatial and temporal dynamic of soil moisture dynamic is very complex since it depends on several factors such as weather condition, land cover/land use, soil type, topography, geology. Capturing such dynamic requires a dense network of continuous observation of soil moisture which is not feasible. The only realistic possibility for derive continuous spatially distributed soil moisture is through satellite observations. In this regard Passive microwave sensors, especially those operating at low frequencies (L bands) present an interesting potential for monitoring soil moisture. However, the use of coarse spatial resolution of instrument such as SMOS in the field of hydrology is not straightforward. Indeed, the scale at which most hydrological processes occur is approximately 1km or less. It is thus of crucial importance to develop procedures to disaggregate passive microwave based soil moisture from its nominal scale to that needed for hydrological application and/or watershed management. The objective of this presentation is to provide an overview of existing and newly developed techniques for disaggregating soil moisture from coarse scale to scale relevant for hydrological application. Ground and aircraft data collected at the Walnut Gulch experimental watershed are used to discuss the performance and the limitation of these approaches.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-10-01

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

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  1. Assessment of the SMAP Passive Soil Moisture Product

    NASA Technical Reports Server (NTRS)

    Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey; Yueh, Simon; Entekhabi, Dara; Cosh, Michael H.; Caldwell, Todd; Walker, Jeffrey; Wu, Xiaoling; Berg, Aaron; Rowlandson, Tracy; Pacheco, Anna; McNairn, Heather; Thibeault, Marc; Martinez-Fernandez, Jose; Gonzalez-Zamora, Angel; Seyfried, Mark; Bosch, David; Starks, Patrick; Goodrich, David; Prueger, John; Palecki, Michael; Small, Eric E.; Zreda, Marek; Calvet, Jean-Christophe; Crow, Wade T.; Kerr, Yann

    2016-01-01

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

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

    USGS Publications Warehouse

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

    2006-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  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

  6. 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

  7. Soil Moisture Prediction in the Soil, Vegetation and Snow (SVS) Scheme

    NASA Astrophysics Data System (ADS)

    Alavi, Nasim; Bélair, Stéphane; Fortin, Vincent; Zhang, Shunli; Husain, Syed; Carrera, Marco; Abrahamowicz, Maria

    2016-04-01

    A new land surface scheme has been developed at Environment of Canada to provide surface fluxes of momentum, heat and moisture for the Global Environmental Multiscale (GEM) atmospheric model. In this study, the performance of the soil, vegetation and snow (SVS) scheme in estimating surface and root-zone soil moisture is evaluated against the ISBA (Interactions between Surface, Biosphere, and Atmosphere) scheme currently used operationally within GEM for numerical weather prediction. In addition, the sensitivity of SVS soil moisture results to soil texture and vegetation data sources (type and fractional coverage) has been explored. The performance of SVS and ISBA was assessed against a large set of in situ as well as brightness temperature data from the Soil Moisture and Ocean Salinity (SMOS) satellite over North America. The results indicate that SVS estimates the time evolution of soil moisture more accurately, and compared to ISBA results in higher correlations with observations and reduced errors. The sensitivity tests carried out during this study revealed that SVS soil moisture results are not affected significantly by the soil texture data from different sources. The vegetation data source, however, has a major impact on the soil moisture results predicted by SVS, and accurate specification of vegetation characteristics is crucial for accurate soil moisture prediction.

  8. Developing Soil Moisture Profiles Utilizing Remotely Sensed MW and TIR Based SM Estimates Through Principle of Maximum Entropy

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field

  9. 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.

  10. Influence of Antecedent Soil Moisture Conditions and Substrate Quality on the Magnitude and Timing of N2O Emissions From Riparian Soil

    NASA Astrophysics Data System (ADS)

    Owens, J. L.; Macrae, M. L.; Bourbonniere, R. A.; Petrone, R. M.; Schiff, S. L.

    2009-05-01

    Nitrous oxide (N2O) is a greenhouse gas with a large global warming potential. Consequently there is concern over increased concentrations of atmospheric N2O. Denitrification and nitrification are the primary sources of N2O emissions from agricultural soils and riparian wetlands within these systems. These processes are regulated by soil moisture, oxygen levels in soil pores, soil substrate/nutrient supply (e.g. carbon (C) and nitrogen (N)), pH, and temperature. Soil moisture history may also be a key determinant of N2O flux timing and magnitude through its influence on soil turnover processes and therefore available nutrient pools. However, the linkages between these controls as well as their relative influence on N2O fluxes are poorly understood. This research uses an experimental approach to examine the combined influences of soil moisture and nutrient availability (as affected by soil antecedent moisture history) on N2O fluxes from riparian soil. Soil cores were collected from both an upland (loam soil) location and a lowland (organic soil) location in an agricultural riparian wetland in Southern Ontario for this experiment. In the laboratory, intact soil cores were subject to moisture cycles (wet-dry-wet; dry-wet-dry) over a six-week period to examine how N2O fluxes and soil available nutrient pools changed throughout different types of moisture cycles. Preliminary results indicate that antecedent soil moisture influences the timing and magnitude of N2O flux due to its influence on both soil available nutrient content and likely O2 availability; however, these relationships differ for the two soil types. Larger N2O fluxes were observed from upland soils on a drying trend as opposed to a wetting trend. In contrast, larger N2O fluxes were observed from soils on a wetting trend rather than a drying trend from lowland soil. In addition, the timing of the onset and cessation of N2O fluxes differed both with soil type and the direction of the moisture cycle (i

  11. The Effect of Vegetation on Soil Moisture Retrievals from GPS Signal-to-Noise Ratio Data

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    GPS-Interferometric Reflectometry (GPS-IR) is a method of environmental monitoring that relates changes in ground-reflected (multipath) GPS signals to changes in surface soil moisture and vegetative state for an area of approximately 1000 m2 surrounding a GPS antenna. GPS-IR operates as a bi-static radar: L2C frequency signals transmitted by GPS satellites and subsequent reflections (multipath) are measured by antennas at permanent GPS stations. Changes in multipath signals are seen in signal-to-noise ratio (SNR) interferograms, which are recorded by the GPS receiver. Results from previous field studies have shown that shallow soil moisture can be estimated from SNR phase for bare soil conditions or when vegetation is sparse. Vegetation surrounding a GPS antenna affects the phase shift, amplitude, and frequency/apparent reflector height of SNR oscillations. Therefore, it is necessary to quantify the vegetation conditions, for example vegetation height or water content, that preclude retrieval of soil moisture estimates using GPS-IR. We use both field data and an electrodynamic model that simulates SNR interferograms for variable soil and vegetation conditions to: 1. Determine how changes in vegetation height, biomass, and water content affect GPS phase, amplitude, and apparent reflector height and 2. Quantify the amount of vegetation that obscures the soil moisture signal in SNR data. We report results for rangeland and agricultural sites. At the rangeland sites, vegetation water content only varies between 0 and 0.6 kg/m2. Both observed and simulated SNR data from these sites show that apparent reflector height is nearly constant. Therefore, SNR interferograms are strongly affected by permittivity at the soil surface, and thus soil moisture can be retrieved. Even though reflector height does not change, SNR phase shift and amplitude are affected by fluctuations in rangeland vegetation and must be accounted for in soil moisture retrievals. At several agricultural

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

    NASA Astrophysics Data System (ADS)

    Moyano, F. E.; Vasilyeva, N.; Bouckaert, L.; Cook, F.; Craine, J.; Curiel Yuste, J.; Don, A.; Epron, D.; Formanek, P.; Franzluebbers, A.; Ilstedt, U.; Kätterer, T.; Orchard, V.; Reichstein, M.; Rey, A.; Ruamps, L.; Subke, J.-A.; Thomsen, I. K.; Chenu, C.

    2012-03-01

    Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects and moisture interaction effects of soil texture, organic carbon content and bulk density. When compared to other functions currently used in different soil biogeochemical models, we observe that our results can correct biases and reconcile differences within and between such functions. Ultimately, accurate predictions of the response of soil carbon to future climate scenarios will require the integration of soil-dependent moisture-respiration functions coupled with realistic representations of soil water dynamics.

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

    NASA Astrophysics Data System (ADS)

    Moyano, F. E.; Vasilyeva, N.; Bouckaert, L.; Cook, F.; Craine, J.; Curiel Yuste, J.; Don, A.; Epron, D.; Formanek, P.; Franzluebbers, A.; Ilstedt, U.; Kätterer, T.; Orchard, V.; Reichstein, M.; Rey, A.; Ruamps, L.; Subke, J.-A.; Thomsen, I. K.; Chenu, C.

    2011-12-01

    Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4 % in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main and moisture interaction effects of soil texture, organic carbon content and bulk density. When compared to other functions currently used in different soil biogeochemical models, we observe that our results can correct biases and reconcile differences within and between such functions. Ultimately, accurate predictions of the response of soil carbon to future climate scenarios will require the integration of soil-dependent moisture-respiration functions coupled with realistic representations of soil water dynamics.

  14. Improving soil moisture profile prediction from ground-penetrating radar data: a maximum likelihood ensemble filter approach

    NASA Astrophysics Data System (ADS)

    Tran, A. P.; Vanclooster, M.; Lambot, S.

    2013-02-01

    The vertical profile of root zone soil moisture plays a key role in many hydro-meteorological and agricultural applications. We propose a closed-loop data assimilation procedure based on the maximum likelihood ensemble filter algorithm to update the vertical soil moisture profile from time-lapse ground-penetrating radar (GPR) data. A hydrodynamic model is used to propagate the system state in time and a radar electromagnetic model to link the state variable with the observation data, which enables us to directly assimilate the GPR data. Instead of using the surface soil moisture only, the approach allows to use the information of the whole soil moisture profile for the assimilation. We validated our approach by a synthetic study. We constructed a synthetic soil column with a depth of 80 cm and analyzed the effects of the soil type on the data assimilation by considering 3 soil types, namely, loamy sand, silt and clay. The assimilation of GPR data was performed to solve the problem of unknown initial conditions. The numerical soil moisture profiles generated by the Hydrus-1D model were used by the GPR model to produce the "observed" GPR data. The results show that the soil moisture profile obtained by assimilating the GPR data is much better than that of an open-loop forecast. Compared to the loamy sand and silt, the updated soil moisture profile of the clay soil converges to the true state much more slowly. Increasing update interval from 5 to 50 h only slightly improves the effectiveness of the GPR data assimilation for the loamy sand but significantly for the clay soil. The proposed approach appears to be promising to improve real-time prediction of the soil moisture profiles as well as to provide effective estimates of the unsaturated hydraulic properties at the field scale from time-lapse GPR measurements.

  15. Improving soil moisture profile reconstruction from ground-penetrating radar data: a maximum likelihood ensemble filter approach

    NASA Astrophysics Data System (ADS)

    Tran, A. P.; Vanclooster, M.; Lambot, S.

    2013-07-01

    The vertical profile of shallow unsaturated zone soil moisture plays a key role in many hydro-meteorological and agricultural applications. We propose a closed-loop data assimilation procedure based on the maximum likelihood ensemble filter algorithm to update the vertical soil moisture profile from time-lapse ground-penetrating radar (GPR) data. A hydrodynamic model is used to propagate the system state in time and a radar electromagnetic model and petrophysical relationships to link the state variable with the observation data, which enables us to directly assimilate the GPR data. Instead of using the surface soil moisture only, the approach allows to use the information of the whole soil moisture profile for the assimilation. We validated our approach through a synthetic study. We constructed a synthetic soil column with a depth of 80 cm and analyzed the effects of the soil type on the data assimilation by considering 3 soil types, namely, loamy sand, silt and clay. The assimilation of GPR data was performed to solve the problem of unknown initial conditions. The numerical soil moisture profiles generated by the Hydrus-1D model were used by the GPR model to produce the "observed" GPR data. The results show that the soil moisture profile obtained by assimilating the GPR data is much better than that of an open-loop forecast. Compared to the loamy sand and silt, the updated soil moisture profile of the clay soil converges to the true state much more slowly. Decreasing the update interval from 60 down to 10 h only slightly improves the effectiveness of the GPR data assimilation for the loamy sand but significantly for the clay soil. The proposed approach appears to be promising to improve real-time prediction of the soil moisture profiles as well as to provide effective estimates of the unsaturated hydraulic properties at the field scale from time-lapse GPR measurements.

  16. 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

  17. 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

  18. Physically plausible prescription of land surface model soil moisture

    NASA Astrophysics Data System (ADS)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  19. 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

  20. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  2. Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

    NASA Astrophysics Data System (ADS)

    Peichl, Michael; Thober, Stephan; Schwarze, Reimund; Meyer, Volker; Samaniego, Luis

    2016-04-01

    Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results

  3. Shallow Subsurface Soil Moisture Dynamics in the Root-Zone and Bulk Soil of Sparsely Vegetated Land Surfaces as Impacted by Near-Surface Atmospheric State

    NASA Astrophysics Data System (ADS)

    Trautz, A.; Illangasekare, T. H.; Tilton, N.

    2015-12-01

    Soil moisture is a fundamental state variable that provides the water necessary for plant growth and evapotranspiration. Soil moisture has been extensively studied in the context of bare surface soils and root zones. Less attention has focused on the effects of sparse vegetation distributions, such as those typical of agricultural cropland and other natural surface environments, on soil moisture dynamics. The current study explores root zone, bulk soil, and near-surface atmosphere interactions in terms of soil moisture under different distributions of sparse vegetation using multi-scale laboratory experimentation and numerical simulation. This research is driven by the need to advance our fundamental understanding of soil moisture dynamics in the context of improving water conservation and next generation heat and mass transfer numerical models. Experimentation is performed in a two-dimensional 7.3 m long intermediate scale soil tank interfaced with a climate-controlled wind tunnel, both of which are outfitted with current sensor technologies for measuring atmospheric and soil variables. The soil tank is packed so that a sparsely vegetated soil is surrounded by bulk bare soil; the two regions are separated by porous membranes to isolate the root zone from the bulk soil. Results show that in the absence of vegetation, evaporation rates vary along the soil tank in response to longitudinal changes in humidity; soil dries fastest upstream where evaporation rates are highest. In the presence of vegetation, soil moisture in the bulk soil closest to a vegetated region decreases more rapidly than the bulk soil farther away. Evapotranspiration rates in this region are also higher than the bulk soil region. This study is the first step towards the development of more generalized models that account for non-uniformly distributed vegetation and land surfaces exhibiting micro-topology.

  4. Push broom microwave radiometer observations of surface soil moisture in Monsoon '90

    NASA Astrophysics Data System (ADS)

    Schmugge, T.; Jackson, T. J.; Kustas, W. P.; Roberts, R.; Parry, R.; Goodrich, D. C.; Amer, S. A.; Weltz, M. A.

    1994-05-01

    The push broom microwave radiometer (PBMR) was flown on six flights of the NASA C-130 to map the surface soil moisture over the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed in southeastern Arizona. The PBMR operates at a wavelength of 21 cm and has four horizontally polarized beams which cover a swath of 1.2 times the aircraft altitude. By flying a series of parallel flight lines it was possible to map the microwave brightness temperature (TB), and thus the soil moisture, over a large area. In this case the area was approximately 8 by 20 km. The moisture conditions ranged from very dry, <2% by volume, to quite wet, >15%, after a heavy rain. The rain amounts ranged from less than 10 mm to more than 50 mm over the area mapped with the PBMR. With the PBMR we were able to observe the spatial variations of the rain amounts and the temporal variation as the soil dried. The TB values were registered to a Universal Transverse Mercator grid so that they could be compared to the rain gage readings and to the ground measurements of soil moisture in the 0- to 5-cm layer. The decreases in TB were well correlated with the rainfall amounts, R2 = 0.9, and the comparison of Tg with soil moisture was also good with an R2 of about 0.8. For the latter, there was some dependence of the relation on location, which may be due to soil or vegetation variations over the area mapped. The application of these data to runoff forecasts and flux estimates will be discussed.

  5. Soil moisture and strength index for earthwork construction quality control

    NASA Astrophysics Data System (ADS)

    Sawangsuriya, A.; Wachiraporn, S.; Sramoon, W.

    2015-09-01

    This paper presents the implementation of soil moisture and strength index measurements for earthwork construction quality control as well as a link between the in situ testing and structural property of earthen materials. Use of the convenient Dynamic Cone Penetrometer (DCP) in conjunction with conventional moisture-density measurements enhances quality control by achieving acceptable level of compaction, more uniform structural properties, and aids developing a controlled design parameter during the earthwork construction. Soil strength in term of DCP index normalized by the deviation of compaction moisture content from the optimum moisture content is proposed as performance criteria for a variety of engineered earth fills and special engineering assessment, prevention, and mitigation of geohazards e.g. earthen flood defense embankments.

  6. 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

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

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Stacke, Tobias

    2013-04-01

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

  8. Soil Moisture Time Stability in Two Hydro-climatic Regions

    NASA Astrophysics Data System (ADS)

    Mohanty, B. P.; Joshi, C.; Jacobs, J. M.

    2009-12-01

    In this study we present time stability analyses of soil moisture at different spatial measurement support scales (point-scale and airborne remote sensing footprint-scale 800 m X 800 m) in two different hydro-climatic regions. The data used in the analyses consist of in-situ and passive microwave remotely sensed soil moisture data from Southern Great Plains hydrology experiments 1997 and 1999 (SGP97 and SGP99) conducted in Little Washita (LW) watershed, Oklahoma, and Soil Moisture Experiments 2002 and 2005 (SMEX02 and SMEX05) in Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percentage clay, percentage sand, and soil texture), and topography (elevation and slope) are significant physical controls jointly affecting the spatio-temporal evolution and time stability of soil moisture at both point- and footprint-scale. In Iowa, using point scale soil moisture measurements, WC11 field having higher %clay and lower %sand content was found to be more time stable than the WC12 field. The common time stable points using data across the 3-year period (2002-2005) were mostly located at moderate to high elevations in both the fields. Drainage features and cropping practices also affected the field-scale soil moisture variability in the WC fields. At the remote sensing footprint-scale, the ANOVA tests show that the percentage clay and percentage sand are better able to discern the time stable features of the footprints compared to the soil texture in Iowa. Further, the footprints with steep slopes exhibited the best time stable characteristics in Iowa. On the other hand, in Oklahoma, ANOVA results show that the footprints with sandy clay and loam soil texture are better indicators of the time stability phenomena. In terms of the hill slope position, depressions (0-0.93%) followed by mild slopes (0.93-1.85%) are the best indicators of time stable footprints. Also, at both point- and footprint-scale in both the regions, land use

  9. Estimating field scale root zone soil moisture using the cosmic-ray neutron probe

    NASA Astrophysics Data System (ADS)

    Peterson, A. M.; Helgason, W. D.; Ireson, A. M.

    2015-12-01

    Many practical hydrological, meteorological and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to "field scale", integrated over the entire root zone. The cosmic-ray neutron probe is a promising instrument to provide field scale areal coverage, but these observations are shallow and require depth scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a two year period. Area-averaged soil moisture was assessed using a cosmic-ray neutron probe. Root zone soil moisture was measured at 21 locations within the 5002 m2 area, using a down-hole neutron probe. The cosmic-ray neutron probe was found to provide accurate estimates of field scale surface soil moisture, but accounted for less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (1) the coupling of the cosmic-ray neutron probe with a time stable neutron probe monitoring location, (2) coupling the cosmic-ray neutron probe with a representative landscape unit monitoring approach, and (3) convolution of the cosmic-ray neutron probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.004 cm3 cm-3), followed by the exponential filter (RMSE = 0.012 cm3 cm-3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. It is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray neutron probe data.

  10. Estimating field-scale root zone soil moisture using the cosmic-ray neutron probe

    NASA Astrophysics Data System (ADS)

    Peterson, Amber M.; Helgason, Warren D.; Ireson, Andrew M.

    2016-04-01

    Many practical hydrological, meteorological, and agricultural management problems require estimates of soil moisture with an areal footprint equivalent to field scale, integrated over the entire root zone. The cosmic-ray neutron probe is a promising instrument to provide field-scale areal coverage, but these observations are shallow and require depth-scaling in order to be considered representative of the entire root zone. A study to identify appropriate depth-scaling techniques was conducted at a grazing pasture site in central Saskatchewan, Canada over a 2-year period. Area-averaged soil moisture was assessed using a cosmic-ray neutron probe. Root zone soil moisture was measured at 21 locations within the 500 m × 500 m study area, using a down-hole neutron probe. The cosmic-ray neutron probe was found to provide accurate estimates of field-scale surface soil moisture, but measurements represented less than 40 % of the seasonal change in root zone storage due to its shallow measurement depth. The root zone estimation methods evaluated were: (a) the coupling of the cosmic-ray neutron probe with a time-stable neutron probe monitoring location, (b) coupling the cosmic-ray neutron probe with a representative landscape unit monitoring approach, and (c) convolution of the cosmic-ray neutron probe measurements with the exponential filter. The time stability method provided the best estimate of root zone soil moisture (RMSE = 0.005 cm3 cm-3), followed by the exponential filter (RMSE = 0.014 cm3 cm-3). The landscape unit approach, which required no calibration, had a negative bias but estimated the cumulative change in storage reasonably. The feasibility of applying these methods to field sites without existing instrumentation is discussed. Based upon its observed performance and its minimal data requirements, it is concluded that the exponential filter method has the most potential for estimating root zone soil moisture from cosmic-ray neutron probe data.

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

    NASA Astrophysics Data System (ADS)

    Tawfik, Ahmed B.

    The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate

  12. BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  13. Assessing the impact of soil moisture initialization on seasonal predictions using the NCEP AGCM

    NASA Astrophysics Data System (ADS)

    Lu, C.; Mitchell, K.

    2002-12-01

    Due to the lack of long-term consistent soil moisture analysis, numerical studies of the impact of soil moisture on medium to seasonal range forecasts are often based on extreme or idealized conditions. In this study, the atmospheric predictability at seasonal scale is investigated using soil moisture analyses that are more realistic and model consistent. This is accomplished using the Air Force Weather Agency (AFWA) Agricultural Meteorology modeling system (AGRMET), an operational global database of land surface states and energy/water fluxes, and the NCEP Global Forecast System (GFS), a state-of-the-art general circulation model. AFWA incorporated the NCEP community NOAH Land Surface Model (NOAH LSM) into AGRMET in late 1999. The soil hydrology physics are forced with analyses of shelter height temperature, relative humidity, and wind speed, short and longwave radition, and precipitation. As part of the efforts to unify land model in all NCEP global and regional models, NOAH LSM has been implemented into GFS in 2002. As AGRMET land states have spun up using same land physics that GFS executes, they provide ideal source of initial land states that are strictly self consistent with GFS land physics. Two sets of summer-time ensemble integration of atmospheric model will be performed, one using climatological soil wetness derived from the NCEP/DOE Reanalysis (R-2) and the other using AGRMET soil wetness analysis as initial conditions. The geographical variations of the predictability of soil wetness, precipitation, and near surface temperature will be examined from this dataset.

  14. Assimilation of Smos Observations to Generate a Prototype SMAP Level 4 Surface and Root-Zone Soil Moisture Product

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Crow, Wade T.; Koster, Randal D.; Kimball, John

    2012-01-01

    The Soil Moisture Active and Passive (SMAP; [1]) mission is being implemented by NASA for launch in October 2014. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high-resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. The Soil Moisture and Ocean Salinity (SMOS; [2]) mission was launched by ESA in November 2009 and has since been observing L-band (1.4 GHz) upwelling passive microwaves. In this paper we describe our use of SMOS brightness temperature observations to generate a prototype of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product [5].

  15. Soil Moisture Experiments 2004 and 2005 Results and Plans

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.

    2005-05-01

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

  16. Variability of soil moisture memory for wet and dry basins

    NASA Astrophysics Data System (ADS)

    Rahman, Mohammad Mahfuzur; Lu, Minjiao; Kyi, Khin Htay

    2015-04-01

    Soil moisture memory (SMM) is not only important for atmospheric weather/climate forecasting, but may also be useful in flood and drought prediction. Despite their importance, SMM studies are restricted in certain regions due to the scarcity of soil moisture data. To overcome this limitation, this study explains the variability of SMM in wet and dry basins, and shows an alternative way to predict the basin scale SMM using observed precipitation and potential evapotranspiration information only. This study presents the basin average SMM in the form of a timescale that indicates the duration of significant autocorrelations at 95% confidence intervals. The soil moisture autocorrelations were calculated using observed precipitation, potential evapotranspiration, streamflow and soil moisture data sets simulated using the XinAnJiang (XAJ) model, for 26 river basins across the USA. The XAJ model's capability to simulate seasonal cycles (temporal anomalies) of soil moisture was validated against cycles from the observed data set of the Spoon River basin of Illinois State, USA. Based on the validation experience, the XAJ model was thereafter used to simulate soil moisture data for the analysed basins. Basin scale SMM timescale ranges were computed from 11 to 133 days. The SMM timescale is highly influenced by precipitation variability and exhibits strong seasonality. Dry basins tend to show the highest memory during the winter months (December to February) and lowest in late spring (May). In contrast, wet basins have the lowest memory during winter and early spring (December to April) and highest in the late summer and early autumn (July to September). The SMM timescale displayed an exponential relationship with the basin aridity index, with an r2 value of 0.9. This relationship could be a cheap source of basin scale SMM prediction from widely available observed data sets (actual precipitation and potential evapotranspiration), and thus, could afford some knowledge of SMM

  17. Soil moisture trends in mountainous areas: a 50-yr analysis of modelled soil moisture over Sierra Nevada Mountains (Spain).

    NASA Astrophysics Data System (ADS)

    José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

    2016-04-01

    Soil moisture conditions the energy and water fluxes through the ground surface and constitutes a major hydrological state variable in the analysis of environmental processes. Detecting potential changes in soil moisture and analyzing their trend over a long period of study can help to understand its evolution in other similar areas and to estimate its future role. In mountainous areas, the snow distribution highly conditions soil water content and its implications on the local water cycle. Sierra Nevada, Southern Spain, is a linear mountain range, with altitude higher than 3000 m.a.s.l., where Mediterranean and alpine climates coexist. The snow dynamics dominates the hydrological regime, and the medium and long term trends observed in the snow persistence constitute one of the main potential drivers for soil moisture changes both on a seasonal and annual basis. This work presents a 50-yr study of the soil moisture trends in Sierra Nevada (SN); the distributed monthly mean soil moisture evolution during the recent past (1960-2010) is simulated and its relationship with meteorological variables (precipitation and temperature) analyzed in the five head river basins that the SN area comprises. For this, soil water content is simulated throughout the area by means of WiMMed, a distributed and physically based hydrological model developed for Mediterranean regions that includes snow modelling, which had been previously calibrated and validated in the study area. The analysis of soil moisture shows a globally decreasing annual rate, with a mean value of 0.0011 mmṡmm-1ṡyear-1 during the study period averaged over the whole study area, which locally ranges between 0.174 mmṡmm-1ṡyear-1 and 0.0014 mmṡmm-1ṡyear-1. As previous studies reported, the observed trend in precipitation is more influent than temperature on the snowfall regime change; therefore, as expected, the estimated trends of soil moisture are more related to this variable. Moreover, an increase of

  18. Investigating the impact of limited irrigation practices on soil moisture variability and vineyard performance, Boise, Idaho

    NASA Astrophysics Data System (ADS)

    Duffin, J.; Wilkins, D. E.; Guenther, J.

    2012-12-01

    In semiarid regions, the changing climate may affect the timing and form of precipitation. This could result in increased water stress for agricultural production as available surface water for irrigation diminishes. To prepare for these changing conditions the possibility of limited-irrigation agriculture as an alternative to heavily-irrigated production is being investigated. This study specifically investigates the ability to grow productive wine grapes with different levels of limited irrigation in the Boise Front foothills at the West Foothills TIC Vineyard, located in a climate zone receiving less than 300 mm of annual precipitation over two growing seasons (2011-2012). The vineyard is divided into three test plots on a northwest facing-slope. Soil texture analyses show that soils are homogenous across all three plots. Traditional vineyard performance factors, such as planting densities, soil type, rootstock, and climate, are standardized and serve as constants in this study. Thus, the limiting factor for vine performance is the difference in irrigation on each plot. Water delivery through drip emitters varies in each of the three vineyard test plots from 2 gallons per week to 0.75 gallons per week. Soil moisture is monitored at depths of 0.25 meters and 0.50 meters in two pits in each of the test plots, collecting data in 2011 and 2012, and in a third pit added to each plot in 2012 at upper elevations. The paired upper elevation sensors record the natural soil moisture and the irrigated soil moisture in each irrigation scheme. Soil moisture for each plot, compared to the annual mortality and growth rates of the vines, will suggest a minimum irrigation level needed for limited irrigation farming and highlight other factors that may affect vine performance in this location.

  19. Measurement of soil moisture trends with airborne scatterometers. [Guymon, Oklahoma and Dalhart, Texas

    NASA Technical Reports Server (NTRS)

    Jones, C. L.; Mcfarland, M. J.; Rosethal, W. D.; Theis, S. W. (Principal Investigator)

    1982-01-01

    In an effort to investigate aircraft multisensor responses to soil moisture and vegetation in agricultural fields, an intensive ground sampling program was conducted in Guymon, Oklahoma and Dalhart, Texas in conjunction with aircraft data collected for visible/infrared and passive and active microwave systems. Field selections, sampling techniques, data processing, and the aircraft schedule are discussed for both sites. Field notes are included along with final (normalized and corrected) data sets.

  20. A radiative transfer model for microwave emissions from bare agricultural soils

    NASA Technical Reports Server (NTRS)

    Burke, W. J.; Paris, J. F.

    1975-01-01

    A radiative transfer model for microwave emissions from bare, stratified agricultural soils was developed to assist in the analysis of data gathered in the joint soil moisture experiment. The predictions of the model were compared with preliminary X band (2.8 cm) microwave and ground based observations. Measured brightness temperatures at vertical and horizontal polarizations can be used to estimate the moisture content of the top centimeter of soil with + or - 1 percent accuracy. It is also shown that the Stokes parameters can be used to distinguish between moisture and surface roughness effects.

  1. ESTAR - A synthetic aperture microwave radiometer for measuring soil moisture

    NASA Technical Reports Server (NTRS)

    Le Vine, D. M.; Griffis, A.; Swift, C. T.; Jackson, T. J.

    1992-01-01

    The measurement of soil moisture from space requires putting relatively large microwave antennas in orbit. Aperture synthesis, an interferometric technique for reducing the antenna aperture needed in space, offers the potential for a practical means of meeting these requirements. An aircraft prototype, electronically steered thinned array L-band radiometer (ESTAR), has been built to develop this concept and to demonstrate its suitability for the measurement of soil moisture. Recent flights over the Walnut Gulch Watershed in Arizona show good agreement with ground truth and with measurements with the Pushbroom Microwave Radiometer (PBMR).

  2. Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture

    NASA Astrophysics Data System (ADS)

    Rajib, Mohammad Adnan; Merwade, Venkatesh; Yu, Zhiqiang

    2016-05-01

    The objective of this study is to evaluate the relative potential of spatially distributed surface and root zone soil moisture estimates in calibration of Soil and Water Assessment Tool (SWAT) toward improving its hydrologic predictability with reduced equifinality. The Upper Wabash and Cedar Creek, two agriculture-dominated watersheds in Indiana, USA are considered as test beds to implement this multi-objective SWAT calibration. The proposed calibration approach is performed using remotely sensed Advanced Microwave Scanning Radiometer-Earth Observing System surface soil moisture (∼1 cm top soil) estimates (NASA's Aqua daily level-3 gridded land surface product-version 2) in sub-basin/HRU level together with observed streamflow data at the watershed's outlet. Although application of remote sensing data in calibration improves surface soil moisture simulation, other hydrologic components such as streamflow, evapotranspiration (ET) and deeper layer moisture content in SWAT remain less affected. An extension of this approach to apply root zone soil moisture estimates from limited field sensor data showed considerable improvement in the simulation of root zone moisture content and streamflow with corresponding observed data. Difference in relative sensitivity of parameters and reduced extent of uncertainty are also evident from the proposed method, especially for parameters related to the subsurface hydrologic processes. Regardless, precise representation of vertical soil moisture stratification at different layers is difficult with current SWAT ET depletion mechanism. While the results from this study show that root zone soil moisture can play a major role in SWAT calibration, more studies including various soil moisture data products are necessary to validate the proposed approach.

  3. Evaluation of soil moisture downscaling using a simple thermal-based proxy - the REMEDHUS network (Spain) example

    NASA Astrophysics Data System (ADS)

    Peng, J.; Niesel, J.; Loew, A.

    2015-12-01

    Soil moisture retrieved from satellite microwave remote sensing normally has spatial resolution on the order of tens of kilometers, which are too coarse for many regional hydrological applications such as agriculture monitoring and drought prediction. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of the simple vegetation temperature condition index (VTCI) downscaling scheme over a dense soil moisture observational network (REMEDHUS) in Spain. First, the optimized VTCI was determined through sensitivity analyses of VTCI to surface temperature, vegetation index, cloud, topography, and land cover heterogeneity, using data from Moderate Resolution Imaging Spectroradiometer~(MODIS) and MSG SEVIRI (METEOSAT Second Generation - Spinning Enhanced Visible and Infrared Imager). Then the downscaling scheme was applied to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture observations, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintaining the accuracy of CCI soil moisture. The accuracy level is comparable to other downscaling methods that were also validated against the REMEDHUS network. Furthermore, slightly better performance of MSG SEVIRI over MODIS was observed, which suggests the high potential of applying a geostationary satellite for downscaling soil moisture in the future. Overall, considering the simplicity, limited data requirements and comparable accuracy level to other complex methods, the VTCI downscaling method can facilitate relevant

  4. 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.

  5. Soil moisture and vegetation memories in a cold, arid climate

    NASA Astrophysics Data System (ADS)

    Shinoda, Masato; Nandintsetseg, Banzragch

    2011-10-01

    Continental climate is established as a result of a complex interplay between the atmosphere and various land-surface systems such as the biosphere, soil, hydrosphere, and cryosphere. These systems function as climate memory, allowing the maintenance of interannual atmospheric anomalies. In this paper, we present new observational evidence of an interseasonal moisture memory mechanism mediated by the land surface that is manifested in the coupled cold and arid climate of Mongolia. Interannual anomalies of soil moisture and vegetation due to rainfall during a given summer are maintained through the freezing winter months to the spring, acting as an initial condition for subsequent summer land-surface and rainfall conditions. Both the soil moisture and vegetation memories were prominent over the eastern part of the Mongolian steppe zone (103-112°E and 46-50°N). That is, the cold-season climate with low evapotranspiration and strong soil freezing acts to prolong the decay time scale of autumn soil moisture anomalies to 8.2 months that is among the longest in the world. The vegetation also has a memory of the similar time scale, likely because the large rootstock of the perennial plants dominant in the Mongolian steppe may remain alive, retain belowground biomass anomalies during the winter, and have an impact on the initial vegetation growth during the spring.

  6. Temporal Dynamics of Soil Moisture Variability: A Theoretical Framework

    NASA Astrophysics Data System (ADS)

    Albertson, J. D.; Montaldo, N.

    Much observational effort has been devoted of late to the issue of sub-grid variability of near surface soil moisture fields. This work has been motivated by the tendency for large scale atmospheric models to have coarse land surface grids (and hence soil moisture fields) and the prospect for the development of satellite platforms for re- motely sensing coarse grained soil moisture fields. The interest in sub-grid variability is intended to provide insights needed to complement the coarse scale models and observational systems. Interestingly, the empirical results have often appeared contra- dictory at first glance. Some studies have shown spatial variance to increase through the drying phase while other studies found the variance to decrease through time. Var- ious explanations have been proposed, typically centered on possible disparate scales of the studies or differing hydrometeorological conditions. In this presentation we de- rive from basic fluid mechanical tools a prognostic equation for the temporal evolution of the spatial variance of soil moisture. The resulting equation includes separate vari- ance production-destruction terms for infiltration, drainage, horizontal convergence- divergence, and evapotranspiration. In this talk we demonstrate how the individual terms contribute uniquely to the temporal changes of the spatial variance of soil mois- ture under contrasting physiographic and hydrometeorological conditions. We contend that the derived variance evolution equation provides a framework for reconciling em- pirical results that were previously considered to be contradictory.

  7. Assimilating AMSR-E data for soil moisture estimation

    NASA Astrophysics Data System (ADS)

    Li, X.; Koike, T.

    In the last decade we see a blooming of developing and applying of land data assimilation systems LDAS This technique by integrating both in situ and remote sensing data into the dynamics of land surface model is capable of producing the evolution of land surface state such as soil moisture soil temperature and snow water equivalent in physical and spatiotemporal consistence In this paper we introduce a few numerical experiments of assimilating the Advanced Microwave Scanning Radiometer AMSR-E brightness temperature data by using the LDAS we have developed The data assimilation method being used is the ensemble Kalman filter which is a Monte Carlo based sequential filter method The land model is the JMA Japan Meteorological Administration new SiB which originates from the Simple Biosphere SiB model but is reformulated with explicit snow and soil freeze thaw processes The observation operators are radiative transfer models of soil We used the semi-empirical Q h model in this study The system was tested using many observations collected during CEOP Coordinated Enhanced Observation Period a Global Energy and Water Experiment particularly at a semi-arid region site Mongolia and a cold region site Tibet-east The results showed that 1 The system can estimate land surface variables i e soil moisture soil temperature and snow much more reasonable than free-loop modeling 2 From the view point of remote sensing the soil moisture and temperature profiles can be retrieved successfully with the aid of additional information

  8. [Characteristics of soil moisture in artificial impermeable layers].

    PubMed

    Suo, Gai-Di; Xie, Yong-Sheng; Tian, Fei; Chuai, Jun-Feng; Jing, Min-Xiao

    2014-09-01

    For the problem of low water and fertilizer use efficiency caused by nitrate nitrogen lea- ching into deep soil layer and soil desiccation in dryland apple orchard, characteristics of soil moisture were investigated by means of hand tamping in order to find a new approach in improving the water and fertilizer use efficiency in the apple orchard. Two artificial impermeable layers of red clay and dark loessial soil were built in soil, with a thickness of 3 or 5 cm. Results showed that artificial impermeable layers with the two different thicknesses were effective in reducing or blocking water infiltration into soil and had higher seepage controlling efficiency. Seepage controlling efficiency for the red clay impermeable layer was better than that for the dark loessial soil impermeable layer. Among all the treatments, the red clay impermeable layer of 5 cm thickness had the highest bulk density, the lowest initial infiltration rate (0.033 mm · min(-1)) and stable infiltration rate (0.018 mm · min(-1)) among all treatments. After dry-wet alternation in summer and freezing-thawing cycle in winter, its physiochemical properties changed little. Increase in years did not affect stable infiltration rate of soil water. The red clay impermeable layer of 5 cm thickness could effectively increase soil moisture content in upper soil layer which was conducive to raise the water and nutrient use efficiency. The approach could be applied to the apple production of dryland orchard.

  9. 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

  10. Soil Moisture Remote Sensing using GPS-Interferometric Reflectometry

    NASA Astrophysics Data System (ADS)

    Chew, Clara

    Ground-reflected Global Positioning System (GPS) signals can be used opportunistically to infer changes in land-surface characteristics surrounding a GPS monument. GPS satellites transmit at L-band, and at microwave frequencies the permittivity of the ground surface changes primarily due to its moisture content. Temporal changes in ground-reflected GPS signals are thus indicative of temporal changes in the moisture content surrounding a GPS antenna. The interference pattern of the direct and reflected GPS signal for a single satellite track is recorded in signal-to-noise ratio (SNR) data. Alternating constructive and destructive interference as the satellite passes over the antenna results in a noisy oscillating wave at low satellite elevation angles, from which the phase, amplitude, and frequency (or reflector height) can be calculated. Here, an electrodynamic model that simulates SNR data is validated against field observations. The model is then used to show that temporal changes in these SNR metrics may be used to estimate changes in surface soil moisture in the top 5 cm of the soil column. Results show that changes in SNR phase are best correlated with changes in soil moisture, with an approximately linear slope. Surface roughness decreases the sensitivity of SNR phase to soil moisture, though the effect is not significant for small roughness values (<5 cm). Modeling experiments show that all three SNR metrics are affected by changes in the permittivity and height of a vegetation canopy. SNR amplitude is the best indicator of changes in vegetation. An increase in either canopy permittivity or height will cause a corresponding decrease in SNR phase. Seasonal changes in vegetation must be removed if soil moisture is to be estimated using phase data. An algorithm is presented that uses modeled relationships between canopy parameters and SNR metrics to remove seasonal vegetation effects from the phase time series, from which soil moisture time series may be

  11. Soil biota and agriculture production in conventional and organic farming

    NASA Astrophysics Data System (ADS)

    Schrama, Maarten; de Haan, Joj; Carvalho, Sabrina; Kroonen, Mark; Verstegen, Harry; Van der Putten, Wim

    2015-04-01

    Sustainable food production for a growing world population requires a healthy soil that can buffer environmental extremes and minimize its losses. There are currently two views on how to achieve this: by intensifying conventional agriculture or by developing organically based agriculture. It has been established that yields of conventional agriculture can be 20% higher than of organic agriculture. However, high yields of intensified conventional agriculture trade off with loss of soil biodiversity, leaching of nutrients, and other unwanted ecosystem dis-services. One of the key explanations for the loss of nutrients and GHG from intensive agriculture is that it results in high dynamics of nutrient losses, and policy has aimed at reducing temporal variation. However, little is known about how different agricultural practices affect spatial variation, and it is unknown how soil fauna acts this. In this study we compare the spatial and temporal variation of physical, chemical and biological parameters in a long term (13-year) field experiment with two conventional farming systems (low and medium organic matter input) and one organic farming system (high organic matter input) and we evaluate the impact on ecosystem services that these farming systems provide. Soil chemical (N availability, N mineralization, pH) and soil biological parameters (nematode abundance, bacterial and fungal biomass) show considerably higher spatial variation under conventional farming than under organic farming. Higher variation in soil chemical and biological parameters coincides with the presence of 'leaky' spots (high nitrate leaching) in conventional farming systems, which shift unpredictably over the course of one season. Although variation in soil physical factors (soil organic matter, soil aggregation, soil moisture) was similar between treatments, but averages were higher under organic farming, indicating more buffered conditions for nutrient cycling. All these changes coincide with

  12. Moisture effect in prompt gamma measurements from soil samples.

    PubMed

    Naqvi, A A; Khiari, F Z; Liadi, F A; Khateeb-Ur-Rehman; Raashid, M A; Isab, A H

    2016-09-01

    The variation in intensity of 1.78MeV silicon, 6.13MeV oxygen, and 2.22MeV hydrogen prompt gamma rays from soil samples due to the addition of 5.1, 7.4, 9.7, 11.9 and 14.0wt% water was studied for 14MeV incident neutron beams utilizing a LaBr3:Ce gamma ray detector. The intensities of 1.78MeV and 6.13MeV gamma rays from silicon and oxygen, respectively, decreased with increasing sample moisture. The intensity of 2.22MeV hydrogen gamma rays increases with moisture. The decrease in intensity of silicon and oxygen gamma rays with moisture concentration indicates a loss of 14MeV neutron flux, while the increase in intensity of 2.22MeV gamma rays with moisture indicates an increase in thermal neutron flux due to increasing concentration of moisture. The experimental intensities of silicon, oxygen and hydrogen prompt gamma rays, measured as a function of moisture concentration in the soil samples, are in good agreement with the theoretical results obtained through Monte Carlo calculations.

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  14. About soil cover heterogeneity of agricultural research stations' experimental fields

    NASA Astrophysics Data System (ADS)

    Rannik, Kaire; Kõlli, Raimo; Kukk, Liia

    2013-04-01

    Depending on local pedo-ecological conditions (topography, (geo) diversity of soil parent material, meteorological conditions) the patterns of soil cover and plant cover determined by soils are very diverse. Formed in the course of soil-plant mutual relationship, the natural ecosystems are always influenced to certain extent by the other local soil forming conditions or they are site specific. The agricultural land use or the formation of agro-ecosystems depends foremost on the suitability of soils for the cultivation of feed and food crops. As a rule, the most fertile or the best soils of the area, which do not present any or present as little as possible constraints for agricultural land use, are selected for this purpose. Compared with conventional field soils, the requirements for the experimental fields' soil cover quality are much higher. Experimental area soils and soil cover composition should correspond to local pedo-ecological conditions and, in addition to that, represent the soil types dominating in the region, whereas the fields should be as homogeneous as possible. The soil cover heterogeneity of seven arable land blocks of three research stations (Jõgeva, Kuusiku and Olustvere) was studied 1) by examining the large scale (1:10 000) digital soil map (available via the internet), and 2) by field researches using the transect method. The stages of soils litho-genetic and moisture heterogeneities were estimated by using the Estonian normal soils matrix, however, the heterogeneity of top- and subsoil texture by using the soil texture matrix. The quality and variability of experimental fields' soils humus status, was studied more thoroughly from the aspect of humus concentration (g kg-1), humus cover thickness (cm) and humus stocks (Mg ha-1). The soil cover of Jõgeva experimental area, which presents an accumulative drumlin landscape (formed during the last glacial period), consist from loamy Luvisols and associated to this Cambisols. In Kuusiku area

  15. 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.

  16. Spatio-temporal distribution and emergence of beetles in arable fields in relation to soil moisture.

    PubMed

    Holland, J M; Thomas, C F G; Birkett, T; Southway, S

    2007-02-01

    Predatory beetles contribute to the control of crop pests and are an important food resource for farmland birds. Many of these beetle species overwinter as larvae within agricultural soils, however, their spatio-temporal emergence patterns are poorly understood, even though such knowledge can assist with their management for biocontrol. Soil moisture is considered to be a key factor influencing oviposition site selection and larval survival. The time, density and spatial pattern of Carabidae and Staphylidae emergence was therefore measured across two fields and compared to soil moisture levels in the previous winter and adult distribution in the previous July. The mean density of Carabidae and Staphylidae that emerged between April and harvest within each field was 157 and 86 m-2, indicating that soils are an important over-wintering habitat for beneficial invertebrates and should be managed sympathetically if numbers are to be increased. Of the species that were sufficiently numerous to allow their spatial pattern to be analysed, all showed a heterogeneous emergence pattern, although patches with high emergence were stable over the sampling period. The distribution of eight species was influenced by soil moisture levels in the previous winter and eight species, although not the same, were spatially associated with the distribution of adults in the previous summer suggesting that the females selected oviposition areas with the appropriate soil wetness.

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

  18. Validation of the Soil Moisture Active Passive mission using USDA-ARS experimental watersheds

    NASA Astrophysics Data System (ADS)

    Cosh, M. H.; Jackson, T. J.; Bindlish, R.; Colliander, A.; Kim, S.; Das, N. N.; Yueh, S. H.; Bosch, D. D.; Goodrich, D. C.; Prueger, J. H.; Starks, P. J.; Livingston, S.; Seyfried, M. S.; Coopersmith, E. J.

    2015-12-01

    The calibration and validation program of the Soil Moisture Active Passive mission (SMAP) relies upon an international cooperative of in situ networks to provide ground truth references across a variety of landscapes. The USDA Agricultural Research Service operates several experimental watersheds which contribute to the validation of SMAP soil moisture products. These watersheds consist of a network of in situ sensors that measure soil moisture at a variety of depths including the 5 cm depth, which is critical for satellite validation. Comparisons of the in situ network estimates to the satellite products are ongoing, but initial results have shown strong correlation between satellite estimates and in situ soil moisture measurements once scaling functions were applied. The scaling methodologies for the in situ networks are being reviewed and evaluated. Results from the Little Washita, Fort Cobb, St. Joseph's and Little River Experimental Watersheds show good agreement between the satellite products and in situ measurements. Walnut Gulch results show high accuracy, although with the caveat that these domains are semi-arid with a substantially lower dynamic range. The South Fork Watershed is examined more closely for its detailed scaling function development as well as an apparent bias between satellite and in situ values.

  19. Computer simulation of a space SAR using a range-sequential processor for soil moisture mapping

    NASA Technical Reports Server (NTRS)

    Fujita, M.; Ulaby, F. (Principal Investigator)

    1982-01-01

    The ability of a spaceborne synthetic aperture radar (SAR) to detect soil moisture was evaluated by means of a computer simulation technique. The computer simulation package includes coherent processing of the SAR data using a range-sequential processor, which can be set up through hardware implementations, thereby reducing the amount of telemetry involved. With such a processing approach, it is possible to monitor the earth's surface on a continuous basis, since data storage requirements can be easily met through the use of currently available technology. The Development of the simulation package is described, followed by an examination of the application of the technique to actual environments. The results indicate that in estimating soil moisture content with a four-look processor, the difference between the assumed and estimated values of soil moisture is within + or - 20% of field capacity for 62% of the pixels for agricultural terrain and for 53% of the pixels for hilly terrain. The estimation accuracy for soil moisture may be improved by reducing the effect of fading through non-coherent averaging.

  20. 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...

  1. 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 ...

  2. SMAP Validation and Accuracy Assessment of Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Introduction: The Soil Moisture Active Passive (SMAP) mission was launched in January, 2015 and will begin its calibration and validation (Cal/Val) phase in May, 2015. This will begin with a focus on instrument measurements, brightness temperature and backscatter, and evolve to the geophysical produ...

  3. An adaptive ensemble Kalman filter for soil moisture data assimilation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In a 19-year twin experiment for the Red-Arkansas river basin we assimilate synthetic surface soil moisture retrievals into the NASA Catchment land surface model. We demonstrate how poorly specified model and observation error parameters affect the quality of the assimilation products. In particul...

  4. 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.

  5. GCOM-W soil moisture and temperature algorithms and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. 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...

  7. The Soil Moisture Active Passive (SMAP) applications activity

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP mea...

  8. Uncertainties of soil moisture in historical simulations and future projections

    NASA Astrophysics Data System (ADS)

    Cheng, Shanjun; Huang, Jianping; Ji, Fei; Lin, Lei

    2017-02-01

    Uncertainties of soil moisture in historical simulations (1920-2005) and future projections (2006-2080) were investigated by using the outputs from the Coupled Model Intercomparison Project Phase 5 and Community Earth System Model. The results showed that soil moisture climatology varies greatly among models despite the good agreement between the ensemble mean of simulated soil moisture and the Global Land Data Assimilation System data. The uncertainties of initial conditions and model structure showed similar spatial patterns and magnitudes, with high uncertainties in dry regions and low uncertainties in wet regions. In addition, the long-term variability of model structure uncertainty rapidly decreased before 1980 and increased thereafter, but the uncertainty in initial conditions showed an upward trend over the entire time span. The model structure and initial conditions can cause uncertainties at all time scales. Despite these large uncertainties, almost all of the simulations showed significant decreasing linear trends in soil moisture for the 21st century, especially in the Mediterranean region, northeast and southwest South America, southern Africa, and southwestern USA.

  9. 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, ...

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  11. Why different passive microwave algorithms give different soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several algorithms have been used to retrieve surface soil moisture from brightness temperature observations provided by low frequency microwave satellite sensors such as the Advanced Microwave Scanning Radiometer on NASA EOS satellite Aqua (AMSR-E). Most of these algorithms have originated from the...

  12. Toward Global Soil Moisture Estimation By Satellite Precipitation Radars

    NASA Astrophysics Data System (ADS)

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

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

  13. Influence of soil moisture on C incorporation and preservation in soil

    NASA Astrophysics Data System (ADS)

    Majumder, B.; Gocke, M.; Kuzyakov, Y.; Wiesenberg, G.

    2012-04-01

    Sequestration of atmospheric C into soil is only mediated by plant. Plant leaf can use atmospheric C by photosynthesis, thereafter this C is translocated into soil through plant root exudates and root fragments. With changing climatic conditions like decreasing rainfall especially during growing seasons of plants, water availability is thought to raise as limiting factor for plant growth and thus sequestration of C. However, little is known about the pathway of translocation of C from atmosphere to soil at different moisture regimes. To quantify atmospheric C incorporation in plant and its preservation into soil via the rhizosphere, a laboratory experiment on Juncus effusus, which is adapted to very moist conditions, was conducted. The plants were kept at levels of 70 and 100% soil moisture (relative to field capacity, which was adjusted daily to a difference of 30% between high and low moisture levels) for several months. C uptake by plants and translocation towards soil was traced 3, 7, 14 and 21 days after 14CO2 pulse labeling in bulk carbon and lipid fractions of plants and soils. J. effusus produced higher leaf and root biomass at 100% moisture as compared to 70% soil moisture. Consequently, rhizosphere-dry mass increased with increasing root biomass. Considering whole pot (plant & soil together), 14C proportion of shoots decreased and that of roots increased successively from 3 to 21 days after labelling due to translocation of C from shoots to roots. 14C content of rhizosphere was observed to be highest at day 14 after labeling at 100% soil moisture, implied an exceptional increase of root exudates, whereas root exudation was less in 70% soil moisture. As a result of C translocation from roots to soil, 14C content of soil increased until day 7 after labeling. Thereafter, soil 14C content decreased more sharply with time at 100% soil moisture than at 70% moisture. Moreover, to gain quantitative knowledge of 14C preservation, a comparatively recalcitrant C

  14. [Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

    PubMed

    Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

    2015-08-01

    Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

  15. Effects of soil moisture on the diurnal pattern of pesticide emission: Comparison of simulations with field measurements

    NASA Astrophysics Data System (ADS)

    Reichman, Rivka; Yates, Scott R.; Skaggs, Todd H.; Rolston, Dennis E.

    2013-02-01

    Pesticide volatilization from agricultural soils is one of the main pathways in which pesticides are dispersed in the environment and affects ecosystems including human welfare. Thus, it is necessary to have accurate knowledge of the various physical and chemical mechanisms that affect volatilization rates from field soils. A verification of the influence of soil moisture modeling on the simulated volatilization rate, soil temperature and soil-water content is presented. Model simulations are compared with data collected in a field study that measured the effect of soil moisture on diazinon volatilization. These data included diurnal changes in volatilization rate, soil-water content, and soil temperature measured at two depths. The simulations were performed using a comprehensive non-isothermal model, two water retention functions, and two soil surface resistance functions, resulting in four tested models. Results show that the degree of similarity between volatilization curves simulated using the four models depended on the initial water content. Under fairly wet conditions, the simulated curves mainly differ in the magnitude of their deviation from the measured values. However, under intermediate and low moisture conditions, the simulated curves also differed in their pattern (shape). The model prediction accuracy depended on soil moisture. Under normal practices, where initial soil moisture is about field capacity or higher, a combination of Brooks and Corey water retention and the van de Grind and Owe soil surface resistance functions led to the most accurate predictions. However, under extremely dry conditions, when soil-water content in the top 1 cm is below the volumetric threshold value, the use of a full-range water retention function increased prediction accuracy. The different models did not affect the soil temperature predictions, and had a minor effect on the predicted soil-water content of Yolo silty clay soil.

  16. Using NASA UAVSAR Datasets to Link Soil Moisture to Crop Conditions

    NASA Astrophysics Data System (ADS)

    Davitt, A. W. D.; McDonald, K. C.; Azarderakhsh, M.; Winter, J.

    2015-12-01

    California and The Central Valley are experiencing one of that region's worst, persistent droughts, which represents the continuation of a prolonged drought that started in the early 2000's. Due to the continued drought, many agricultural regions in The Central Valley have been experiencing water shortages, negatively impacting agricultural production and the socio-economics of the region. Due to these impacts, there has been an increased incentive to find new ways to conserve water for use in irrigation. Recent advances in remote sensing techniques provide the ability for end users to better understand field conditions so they may make more informed decisions on irrigation timing and amounts. However, a good understanding of soil moisture and its role in crop health and yield is lacking to support informed water management decisions. Though known to be important, a robust understanding of the role of the spatio-temporal patterns in soil moisture linked to crop health is lacking. Remote sensing platforms such as NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provide the capacity to obtain within-field measurements to estimate within-field and field-to-field variability in soil moisture. UAVSAR radar images acquired from 2010 to 2014 for Yolo County, California are being examined to determine the suitability of high resolution (field scale) multi-temporal L-band radar backscatter imagery for soil moisture assessment and crop conditions through the growing season. By using such data and linking to in-situ meteorology measurements, modeling (MIMICS), and other remote sensing derived datasets (Sentinel, Landsat, MODIS, and TOPS-SIMS), an integrated monitoring system can potentially support the assessment of agricultural field conditions. This allows growers to optimize the use of limited water supplies through informed water management practices, potentially improving crop conditions and yield in a water stressed region.

  17. 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