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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. 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

  3. 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

    2015-01-01

    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 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. PMID:26158774

  4. 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.

  5. 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.

  6. Agriculture intensifies soil moisture decline in Northern China

    DOE PAGESBeta

    Liu, Yaling; Pan, Zhihua; Zhuang, Qianlai; Miralles, Diego; Teuling, Adriann; Zhang, Tonglin; An, Pingli; Dong, Zhiqiang; Zhang, Jingting; He, Di; et al

    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

  7. 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

  8. 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...

  9. 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).

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  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. Using agricultural in situ soil moisture networks to validate satellite estimates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The validation of soil moisture remote sensing products is generally based upon in situ networks which are often in non-representative locations. Soil moisture sensors have until recently, been added to existing precipitation networks, which are not installed inside agricultural fields. An initial...

  13. 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...

  14. 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.

  15. Monitoring soil moisture dynamics via ground-penetrating radar survey of agriculture fields after irrigation

    NASA Astrophysics Data System (ADS)

    Muro, G.

    2015-12-01

    It is possible to examine the quality of ground-penetrating radar (GPR) as a measure of soil moisture content in the shallow vadose zone, where roots are most abundant and water conservation best management practices are critical in active agricultural fields. By analyzing temporal samplings of 100 Mhz reflection profiles and common-midpoint (CMP) soundings over a full growing season, the variability of vertical soil moisture distribution directly after irrigation events are characterized throughout the lifecycle of a production crop. Reflection profiles produce high-resolution travel time data and summed results of CMP sounding data provide sampling depth estimates for the weak, but coherent reflections amid strong point scatterers. The high ratio of clay in the soil limits the resolution of downward propagation of infiltrating moisture after irrigation; synthetic data analysis compared against soil moisture lysimeter logs throughout the profile allow identification of the discrete soil moisture content variation in the measured GPR data. The nature of short duration irrigation events, evapotranspiration, and drainage behavior in relation to root depths observed in the GPR temporal data allow further examination and comparison with the variable saturation model HYDRUS-1D. After retrieving soil hydraulic properties derived from laboratory measured soil samples and simplified assumptions about boundary conditions, the project aims to achieve good agreement between simulated and measured soil moisture profiles without the need for excessive model calibration for GPR-derived soil moisture estimates in an agricultural setting.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. Satellite surface soil moisture from SMOS and Aquarius: Assessment for applications in agricultural landscapes

    NASA Astrophysics Data System (ADS)

    Champagne, Catherine; Rowlandson, Tracy; Berg, Aaron; Burns, Travis; L'Heureux, Jessika; Tetlock, Erica; Adams, Justin R.; McNairn, Heather; Toth, Brenda; Itenfisu, Daniel

    2016-03-01

    Satellite surface soil moisture has become more widely available in the past five years, with several missions designed specifically for soil moisture measurement now available, including the Soil Moisture and Ocean Salinity (SMOS) mission and the Soil Moisture Active/Passive (SMAP) mission. With a wealth of data now available, the challenge is to understand the skill and limitations of the data so they can be used routinely to support monitoring applications and to better understand environmental change. This paper examined two satellite surface soil moisture data sets from the SMOS and Aquarius missions against in situ networks in largely agricultural regions of Canada. The data from both sensors was compared to ground measurements on both an absolute and relative basis. Overall, the root mean squared errors for SMOS were less than 0.10 m3 m-3 at most sites, and less where the in situ soil moisture was measured at multiple sites within the radiometer footprint (sites in Saskatchewan, Manitoba and Ontario). At many sites, SMOS overestimates soil moisture shortly after rainfall events compared to the in situ data; however this was not consistent for each site and each time period. SMOS was found to underestimate drying events compared to the in situ data, however this observation was not consistent from site to site. The Aquarius soil moisture data showed higher root mean squared errors in areas where there were more frequent wetting and drying cycles. Overall, both data sets, and SMOS in particular, showed a stable and consistent pattern of capturing surface soil moisture over time.

  3. 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.

  4. 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

  5. A Multi-Sensor Approach for Satellite Soil Moisture Monitoring for Agricultural Climate Risk Assessment

    NASA Astrophysics Data System (ADS)

    Champagne, C.; Cherneski, P.; Hadwen, T. A.; Davidson, A.

    2014-12-01

    Satellite missions specifically dedicated to soil moisture retrieval have become a reality in the past few years, with the launch of SMOS in 2009 and SMAP in 2014. While much of the work on applications around these missions has focussed on data assimilation systems for numerical weather prediction, there is also potential to use the data to support agricultural applications such as drought and flood assessment and yield forecasting. Previous work has examined the potential for using SMOS soil moisture for detecting spatial and temporal patterns of agroclimate risk, such as drought and excess wetness. This research builds upon that work through the examination of a data set with a longer reference period to determine if the dataset can be used as a baseline for detecting anomalies from normal conditions. Surface satellite soil moisture from a multi-sensor climate reference data set (1993 to 2010) and the SMOS surface soil moisture data (2010 - 2014) set were examined in hindsight to detect relevant trends for monitoring the climate conditions in agricultural regions of Canada. Soil moisture and soil moisture anomalies were examined against precipitation and temperature records over the relevant time periods, and compared against agroclimatic drought risk indicators, including the Palmer Drought Severity Index, the Standardized Precipitation Index and the MODIS Normalized Difference Vegetation Condition anomalies. High impact events, including the 2002 drought in the Canadian Prairies, excess wetness in the southern Manitoba in 2009 and 2011 were evaluated in detail. The potential for using these data sets in near real time to support agricultural decision making will be discussed.

  6. 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.

  7. 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 ...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  9. Spatial Scaling Assessment of Surface Soil Moisture Estimations Using Remotely Sensed Data for Precision Agriculture

    NASA Astrophysics Data System (ADS)

    Hassan Esfahani, L.; Torres-Rua, A. F.; Jensen, A.; McKee, M.

    2014-12-01

    Airborne and Landsat remote sensing are promising technologies for measuring the response of agricultural crops to variations in several agricultural inputs and environmental conditions. Of particular significance to precision agriculture is surface soil moisture, a key component of the soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface and affects vegetation health. Its estimation using the spectral reflectance of agricultural fields could be of value to agricultural management decisions. While top soil moisture can be estimated using radiometric information from aircraft or satellites and data mining techniques, comparison of results from two different aerial platforms might be complicated because of the differences in spatial scales (high resolution of approximately 0.15m versus coarser resolutions of 30m). This paper presents a combined modeling and scale-based approach to evaluate the impact of spatial scaling in the estimation of surface soil moisture content derived from remote sensing data. Data from Landsat 7 ETM+, Landsat 8 OLI and AggieAirTM aerial imagery are utilized. AggieAirTM is an airborne remote sensing platform developed by Utah State University that includes an autonomous Unmanned Aerial System (UAS) which captures radiometric information at visual, near-infrared, and thermal wavebands at spatial resolutions of 0.15 m or smaller for the optical cameras and about 0.6 m or smaller for the thermal infrared camera. Top soil moisture maps for AggieAir and Landsat are developed and statistically compared at different scales to determine the impact in terms of quantitative predictive capability and feasibility of applicability of results in improving in field management.

  10. Monitoring of soil moisture dynamics and spatial differences in an agricultural catchment

    NASA Astrophysics Data System (ADS)

    Oswald, Sascha; Baroni, Gabriele; Biro, Peter; Schrön, Martin

    2015-04-01

    A novel method to observe changes in soil moisture and other water pools at the land surface is non-invasive cosmic-ray neutron sensing. This approach by its physical principles is placed between in-soil measurements and remote sensing, and retrieves values for an intermediate spatial scale of several hectars, which can be used to quantify stored water at the land surface. It detects variations in the background of neutrons, induced initially from cosmic-rays hitting the atmosphere, and this can be related to interesting quantities at the land surface, such as soil moisture, but to some degree also snow water equivalent and changes in the biomass of vegetation. In a small catchment being used as a long-term landscape observatory of the TERENO initiative we retrieved cosmic-ray neutron measurements for several years, for up to four adjacent sites. The terrain was hilly with some slopes being partly used for agricultural fields, partly grassland. Here, after atmospheric corrections and a calibration procedure soil moisture dynamics could be observed for integral soil depths of several decimeters, clearly responding to precipitation events and offering a comparison to various local and non-local soil moisture measurements there. For winter periods with frost and snow, also the water mass stored in the snow cover can be retrieved. Furthermore, observed spatial differences can be related to vegetation, terrain and soil moisture state. Also, the relation to parameters representing crop biomass and growth will be discussed in respect to the retrieved cosmic-ray neutron signals, which have an influence on the interpretation as soil moisture.

  11. 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.

  12. 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.

  13. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

  15. 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.

  16. Downscaling Soil Moisture Product from SMOS for Monitoring Agricultural Droughts in South America

    NASA Astrophysics Data System (ADS)

    Nagarajan, K.; Fu, C.; Judge, J.; Fraisse, C.

    2012-12-01

    Availability of reliable near-surface soil moisture (SM) estimates at fine spatial resolutions of 1 km and at temporal resolutions of a few days is critical for accurate quantification of drought impacts on crop yields and recommending meaningful management and adaptation strategies. The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future NASA-Soil Moisture Active Passive (SMAP) missions provide unprecedented, global SM product every 2-3 days at spatial resolutions of ~50 km. In addition, the SMAP will provide a SM product at 10 km . Downscaling the above SM products to 1km is essential for any meaningful drought-related application in agricultural terrains. Optimal downscaling should retain information from higher-order moments and leverage information from auxiliary remote sensing products that are available at fine resolutions. In this study, a novel downscaling methodology based upon information theory was implemented to obtain distributed SM at 1 km every 3 days, using the SM product from SMOS. Observations of land surface temperature (LST), leaf area index (LAI) and land cover (LC) at 1 km from MODIS, and precipitation at 25 km from TRMM, were used as auxiliary information to facilitate the downscaling process. The use of information-theory in downscaling provides a hierarchical decomposition of image data that is optimal in terms of the transfer of information across scales and is therefore a better alternative to methods that use second-order statistics only. The downscaling methodology was implemented over the agricultural regions in the lower La Plata Basin (L-LPB) in South America. The L-LPB region is of great economic value in South America, where agricultural cover makes up about 25% of the continent's land area and is vulnerable to high losses in crop yields due to agricultural drought . Both remote sensing and in situ observations (precipitation, temperature, and soil moisture) obtained during the

  17. 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.

  18. Using Agricultural in Situ Soil Moisture Networks to Validate Satellite Estimates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The validation of soil moisture remote sensing products is generally based upon the in situ networks which are in non-representative locations. Soil moisture sensors have until recently, been added to existing precipitation networks which have different requirements for representativeness, such as ...

  19. 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

  20. Applications of soil moisture information

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  1. Spatiotemporal characterization of soil moisture fields in agricultural areas using cosmic-ray neutron probes and data fusion

    NASA Astrophysics Data System (ADS)

    Franz, Trenton; Wang, Tiejun

    2015-04-01

    Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE USA. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 12 by 12 km study domain also contained three stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong relationship between the mean and variance of soil moisture at several averaging scales. The relationships between the mean and higher order moments were not significant. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. In addition, we combined the data from the three stationary cosmic-ray neutron probes and mobile surveys using linear regression to derive a daily soil moisture product at 1, 3, and 12 km spatial resolutions for the entire growing season. The statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide daily center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

  2. Field-Scale Soil Moisture Observations in Irrigated Agriculture Fields Using the Cosmic-ray Neutron Rover

    NASA Astrophysics Data System (ADS)

    Franz, T. E.; Avery, W. A.; Finkenbiner, C. E.; Wang, T.; Brocca, L.

    2014-12-01

    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 the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 11 x11 km study domain also contained 3 stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong inverted parabolic relationship between the mean and variance of soil moisture. The relationship between the mean and higher order moments were not as strong. Geostatistical analysis indicated the range of the soil moisture semi-variogram was significantly shorter during periods of heavy irrigation as compared to non-irrigated periods. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. Statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

  3. 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

  4. A Simple Runoff Model Based on Topographic Wetness Indices and Soil Moisture for Central New York Agricultural Fields

    NASA Astrophysics Data System (ADS)

    Hofmeister, K.; Georgakakos, C.; Walter, M. T.

    2014-12-01

    Nonpoint source (NPS) pollution continues to be a leading cause of surface water degradation, especially in agricultural areas. In humid regions where variable source area (VSA) hydrology dominates, such as the Northeastern US, topographic wetness indices (TWI) are good approximations of relative soil moisture patterns. Mapping areas of the landscape likely to generate saturation-excess runoff and carry NPS pollution to surface waters could allow for more efficient, targeted best management practices in agricultural fields. Given the relationship between saturation excess runoff and soil water storage, we used volumetric water content (VWC) measured in five agricultural fields in central New York over two years (2012-2014) to develop runoff probability maps based on a soil topographic index (STI). The relationship between VWC and STI was strongest during the fall season after leaf fall at all sites except one. We calculated the probability of runoff occurring based on soil moisture and precipitation distributions during the sampling period. The threshold for runoff occurs when the depth of soil water and rainfall reach saturation of the soil, and appears to be at the average porosity of the soil at all sites. Counter to our initial hypothesis of a higher probability of saturation excess runoff during the spring when conditions are wetter, some sites showed higher frequencies of runoff during the fall season.

  5. 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.

  6. Importance of Verticle Coupling in Agricultural Models on Assimilation of Satellite-derived Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop yield in crop production models is simulated as a function of weather, ground conditions and management practices and it is driven by the amount of nutrients, heat and water availability in the root-zone. It has been demonstrated that assimilation of satellite-derived soil moisture data has the...

  7. Importance of Vertical Coupling in Agricultural Models on Assimilation of Satellite-derived Soil Moisture

    NASA Astrophysics Data System (ADS)

    Mladenova, I. E.; Crow, W. T.; Teng, W. L.; Doraiswamy, P.

    2010-12-01

    Crop yield in crop production models is simulated as a function of weather, ground conditions and management practices and it is driven by the amount of nutrients, heat and water availability in the root-zone. It has been demonstrated that assimilation of satellite-derived soil moisture data has the potential to improve the model root-zone soil water (RZSW) information. However, the satellite estimates represent the moisture conditions of the top 3 cm to 5 cm of the soil profile depending on system configuration and surface conditions (i.e. soil wetness, density of the canopy cover, etc). The propagation of this superficial information throughout the profile will depend on the model physics. In an Ensemble Kalman Filter (EnKF) data assimilation system, as the one examined here, the update of each soil layer is done through the Kalman Gain, K. K is a weighing factor that determines how much correction will be performed on the forecasts. Furthermore, K depends on the strength of the correlation between the surface and the root-zone soil moisture; the stronger this correlation is, the more observations will impact the analysis. This means that even if the satellite-derived product has higher sensitivity and accuracy as compared to the model estimates, the improvement of the RZSW will be negligible if the surface-root zone coupling is weak, where the later is determined by the model subsurface physics. This research examines: (1) the strength of the vertical coupling in the Environmental Policy Integrated Climate (EPIC) model over corn and soybeans covered fields in Iowa, US, (2) the potential to improve EPIC RZSW information through assimilation of satellite soil moisture data derived from the Advanced Microwave Scanning Radiometer (AMSR-E) and (3) the impact of the vertical coupling on the EnKF performance.

  8. 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

  9. Assimilation of Downscaled SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions in Brazil

    NASA Astrophysics Data System (ADS)

    Chakrabarti, S.; Bongiovanni, T. E.; Judge, J.; Principe, J. C.; Fraisse, C.

    2013-12-01

    Reliable soil moisture (SM) information in the root zone (RZSM) is critical for quantification of agricultural drought impacts on crop yields and for recommending management and adaptation strategies for crop management, commodity trading and food security.The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future National Aeronautics and Space Administration-Soil Moisture Active Passive (NASA-SMAP) missions provide SM at unprecedented spatial resolutions of 10-25 km, but these resolutions are still too coarse for agricultural applications in heterogeneous landscapes, making downscaling a necessity. This downscaled near-surface SM can be merged with crop growth models in a data assimilation framework to provide optimal estimates of RZSM and crop yield. The objectives of the study include: 1) to implement a novel downscalingalgorithm based on the Information theoretical learning principlesto downscale SMOS soil moisture at 25 km to 1km in the Brazilian La Plata Basin region and2) to assimilate the 1km-soil moisture in the crop model for a normal and a drought year to understand the impact on crop yield. In this study, a novel downscaling algorithm based on the Principle of Relevant Information (PRI) was applied to in-situ and remotely sensed precipitation, SM, land surface temperature and leaf area index in the Brazilian Lower La Plata region in South America. An Ensemble Kalman Filter (EnKF) based assimilation algorithm was used to assimilate the downscaled soil moisture to update both states and parameters. The downscaled soil moisture for two growing seasons in2010-2011 and 2011-2012 was assimilated into the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model over 161 km2 rain-fed region in the Brazilian LPB regionto improve the estimates of soybean yield. The first season experienced normal precipitation, while the second season was impacted by drought. Assimilation improved yield

  10. Radar scattering and soil moisture

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  11. 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.

  12. 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...

  13. 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.

  14. Remotely-Sensed Soil Moisture for Agricultural Decision Support: An Integration of National-Scale Hydroclimatic Classification and Ground-Based Sensors

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Agricultural managers employ soil moisture estimates to inform irrigation and drainage planning as well as the timing of entry for heavier equipment, but ground-based soil moisture sensors are often unavailable for the location in question. Data-driven models of soil moisture often require an array of inputs that are difficult to obtain beyond the scope of a research study and/or recalibration at each location for which predictions are needed. A hydroclimatic classification system was previously constructed from over 400 well-gauged catchments in the MOPEX database using four simple hydrologic and climatic indicators. These catchments are subsequently grouped in twenty-four clusters. A simple, lumped soil moisture model, receiving only public precipitation data as an input, is calibrated at the fifteen sites with ground-based soil moisture sensors, producing correlations 0.9 with respect to observed soil moisture values. The fifteen sites are also assessed in terms of textural and taxonomic properties. The model is then shown to be valid at other locations that are hydroclimatically and edaphically similar to the calibration site. By integrating this simple soil moisture algorithm with an existing system for hydroclimatic classification and publicly-available edaphic information (USDA's soil web, e.g.), a single set of calibrated parameters can facilitate remotely-sensed soil moisture estimates for agronomic decision-support at any site with similar edaphic and hydroclimatic properties.

  15. 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...

  16. 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.

  17. 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.

  18. Integrating NASA Satellite-Derived Precipitation and Soil Moisture Data Into the Digital-NGP Decision Support System for Agriculture

    NASA Astrophysics Data System (ADS)

    Teng, W.; Zhang, X.; Soriano, M.

    2007-12-01

    determined by weather and climate. Phenology of local crops will likely shift in response to global and regional climate changes, therefore it is important to track temporal variations of temperature and moisture for timely decision making. The objective of this study is to determine the extent to which NASA data and services can be usefully integrated into the Digital-NGP, i.e., can integration help to better answer the two key questions. The objective will be approached by availing the Digital-NGP of existing capabilities of Giovanni-AOVAS and AIS, as well as the capabilities of a new Giovanni-Soil Moisture instance.

  19. 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.

  20. Evaluating the performance of 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 ...

  1. 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 ...

  2. 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

  3. 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.

  4. Introducing a Soil Moisture Scaling Triangle

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2014-12-01

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

  5. 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.

  6. 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.

  7. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. 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.

  10. Remote sensing of soil moisture with microwave radiometers

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  11. Potential impacts of wintertime soil moisture anomalies from agricultural irrigation at low latitudes on regional and global climates

    NASA Astrophysics Data System (ADS)

    Wey, Hao-Wei; Lo, Min-Hui; Lee, Shih-Yu; Yu, Jin-Yi; Hsu, Huang-Hsiung

    2015-10-01

    Anthropogenic water management can change surface energy budgets and the water cycle. In this study, we focused on impacts of Asian low-latitude irrigation on regional and global climates during boreal wintertime. A state-of-the-art Earth system model is used to simulate the land-air interaction processes affected by irrigation and the consequent responses in atmospheric circulation. Perturbed experiments show that wet soil moisture anomalies at low latitudes can reduce the surface temperature on a continental scale through atmospheric feedback. The intensity of prevailing monsoon circulation becomes stronger because of larger land-sea thermal contrast. Furthermore, anomalous upper level convergence over South Asia and midlatitude climatic changes indicate tropical-extratropical teleconnections. The wintertime Aleutian low is deepened and an anomalous warm surface temperature is found in North America. Previous studies have noted this warming but left it unexplained, and we provide plausible mechanisms for these remote impacts coming from the irrigation over Asian low-latitude regions.

  12. Soil Moisture from Altimetry - SMALT

    NASA Astrophysics Data System (ADS)

    Berry, Philippa; Smith, Richard; Salloway, Mark; Lucas, Bruno Manuel; Dinardo, Salvatore; Benveniste, Jérôme

    2013-04-01

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. These models are created by cross-calibrating and reconciling multi-mission altimeter sigma0 measurements from ERS-1, ERS-2, EnviSat and Jason-2. This approach is made possible because altimeters are nadir-pointing, and most of the available radar altimeter datasets are from instruments operating in Ku band. These DREAMS are complicated to build and require multiple stages of processing and manual intervention. However, this approach obviates the requirement for detailed ground truth to populate theoretical models, facilitating derivation of surface soil moisture estimates over arid regions, where detailed survey data are generally not available. This paper presents results using the DREAMS over desert surfaces, and showcases the model outcomes over the Arabian and Tenere deserts. A global assessment is presented of areas where DREAMS are currently being generated, and an outline of the required processing to obtain soil surface moisture estimates is given. Results for altimeter derived soil moisture validation with ground truth are presented together with comparisons with other remotely sensed soil estimates. Soil moisture product from ERS-2 radar altimetry in arid regions is presented, and the temporal and spatial resolutions of these data are reported. The results generated by this ESA encouraged initiative will be made freely available to the global scientific community. First products are planned for release

  13. 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.

  14. 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.

  15. 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...

  16. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1994-01-01

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

  17. 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.

  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. Soil moisture variability within remote sensing pixels

    NASA Astrophysics Data System (ADS)

    Charpentier, Michael A.; Groffman, Peter M.

    1992-11-01

    The effects of topography and the level of soil moisture on the variability of soil moisture within remote sensing pixels were assessed during the First ISLSCP Field Experiment (FIFE) during 1987 and 1989. Soil moisture data from flat, sloped, and valley-shaped pixels were obtained over a wide range of moisture conditions. Relative elevation data were obtained for each study area to create digital elevation models with which to quantify topographic variability. Within-pixel soil moisture variability was shown to increase with increased topographic heterogeneity. The flat pixel had significantly lower standard deviations and fewer outlier points than the slope and valley pixels. Most pixel means had a positive skewness, indicating that most pixels will have areas of markedly higher than average soil moisture. Soil moisture variability (as indicated by the coefficient of variation) decreased as soil moisture levels increased. However, the absolute value of the standard deviation of soil moisture was independent of wetness. The data suggest that remote sensing will reflect soil moisture conditions less accurately on pixels with increased topographic variability and less precisely when the soil is dry. These differences in the inherent accuracy and precision of remote sensing soil moisture data should be considered when evaluating error sources in analyses of energy balance or biogeochemical processes that utilize soil moisture data produced by remote sensing.

  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. 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.

  4. 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.

  5. 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...

  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. SMALT - Soil Moisture from Altimetry

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  8. 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

  9. 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.

  10. 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.

  11. The Murrumbidgee soil moisture monitoring network data set

    NASA Astrophysics Data System (ADS)

    Smith, A. B.; Walker, J. P.; Western, A. W.; Young, R. I.; Ellett, K. M.; Pipunic, R. C.; Grayson, R. B.; Siriwardena, L.; Chiew, F. H. S.; Richter, H.

    2012-07-01

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

  12. [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. PMID:26964221

  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. 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.

  16. 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...

  17. 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...

  18. 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.

  19. 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.

  20. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  2. 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.

  3. 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 ...

  4. Large-scale surface soil moisture estimation using in situ networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Surface soil moisture estimation impacts a wide range of concerns, including agricultural management, climate, and weather modeling. New satellite technologies have been developed which allow for the estimation of surface soil moisture with moderate accuracy for the agricultural heartland of the U....

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Precipitation, Soil Moisture, and Climate Database, Little River Experimental Watershed, Georgia, United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The U.S. Department of Agriculture, Agricultural Research Service, Southeast Watershed Research Laboratory initiated a watershed research program at the Little River Experimental Watershed in 1967. Continuous rainfall measurement across the watershed began at that time. Soil moisture measurements ...

  7. 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.

  8. Evaluation of polarimetric SAR parameters for soil moisture retrieval

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  9. 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

  10. Soil moisture sensing with microwave techniques

    NASA Technical Reports Server (NTRS)

    Schmugge, T.

    1980-01-01

    Microwave approaches for the remote sensing of soil moisture are discussed, with the advantages described as follows: (1) the all-weather capability, (2) the greater penetration depth into the soil and through vegetation than with optical or infrared sensors, and (3) the large changes in the dielectric properties of soil produced by changes in water content. Both active and passive microwave approaches are discussed. The dependence of the relationship between microwave response and soil moisture on such things as soil texture, surface roughness, vegetative cover and nonuniform moisture and temperature profiles is analyzed from both the experimental and theoretical viewpoints. The dielectric properties of the soil are analyzed quantitatively, as these control the reflective and emissive properties of the soil surface, and a model for estimating a soil's dielectric properties from its texture and moisture content is also presented. Emissivity is calculated using the Fresnel equation of electromagnetic theory, and reflectivity is shown to be decreased by surface roughness, while the backscatter coefficient increases. It is demonstrated, that microwave radiometers are sensitive to soil moisture for a wide range of surface conditions, and that the longer wavelengths are best for soil moisture sensing.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  12. 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

  13. Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The additive 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 model-based soil moisture obtained before and after the assimilation of surface soil m...

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

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

  16. 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.

  17. 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...

  18. 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

  19. Soil Moisture Estimation under Vegetation Applying Polarimetric Decomposition Techniques

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  20. 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.

  1. Comparison of remote measurements of infrared surface temperatures and microwave soil moisture

    NASA Technical Reports Server (NTRS)

    Perry, Eileen M.; Carlson, Toby N.

    1987-01-01

    Scatterometric measurements of active microwave soil water content and radiometric measurements of thermal IR surface temperatures were made simultaneously fron an aircraft flying 400 m over an agricultural region of France after harvesting. The surface temperatures were used to deterine soil moisture availability estimates according to the Carlson (1986) model. Surface temperature or soil moisture availability and microwave soil moisture were correlated. The standard error in the IR temperature and soil moisture availability due to influences other than soil moisture is found to be + or - 2 C. The standard deviation of the temperature/moisture availability is greater than this standard error. It is shown that correlations between soil water content and moisture availability improve with increasing spatial or temporal variance in the measure surface temperatures.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  3. 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 ...

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

    NASA Astrophysics Data System (ADS)

    Kuhn, N. J.; Strunk, R.

    2012-04-01

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

  5. 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.

  6. 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.

  7. 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.

  8. Using SMOS obervations for science development of the SMAP level 4 surface and root zone soil moisture algorithm

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active and Passive (SMAP) mission is targeted for launch in October 2014. The 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 Oc...

  9. 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.

  10. 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...

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

    2014-05-01

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

  13. Geophysical mapping of variations in soil moisture

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    The geophysical investigation of soil characteristics is a matter of great actuality for agricultural, hydrogeological, geotechnical or archaeological purposes. The geophysical mapping of soil quality is subject of a recently started scientific project in Romania: "Soil investigation and monitoring techniques - modern tools for implementing the precision agriculture in Romania - CNCSIS 998/2009". One of the first studied soil parameter is moisture content, in irrigated or non-irrigated agricultural areas. The geophysical techniques employed in two areas located within the Romanian Plain, Prahova and Buzau counties, are the following: - electromagnetic (EM), using the EM38B (Geonics) conductivity meter for getting areal distribution of electric conductivity and magnetic susceptibility; - electric resistivity tomography (ERT), using the SuperSting (AGI) multi-electrode instrument for getting in-depth distribution of electric resistivity. The electric conductivity mapping was carried out on irrigated cultivated land in a vegetable farm in the Buzau county, the distribution of conductivity being closely related to the soil water content due to irrigation works. The soil profile is represented by a chernozem with the following structure: Am (0 - 40 cm), Bt (40-150 cm), Bt/C (150-170 cm), C (starting at 170 cm). The electromagnetic measurements showed large variations of this geophysical parameter within different cultivated sectors, ranging from 40 mS/m to 85 mS/m. The close association between conductivity and water content in this area is illustrated by such geophysical measurements on profiles situated at ca 50 m on non-irrigated land, displaying a mean value of 15 mS/m. This low conductivity is due to quite long time interval, of about three weeks, without precipitations. The ERT measurements using multi-electrode acquisition systems for 2D and 3D results, showed by means of electric resistivity variations, the penetration of water along the cultivated rows from the

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. Effect of soil moisture on chlorine deposition.

    PubMed

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

    2014-02-28

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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 Assessmen...

  4. 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 ...

  5. 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...

  6. Assimilation of Satellite-Based Soil Moisture into the USDA Global Crop Production Decision Support System

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The timely and accurate monitoring of climate conditions is essential for assessing agriculture efficiency and managing natural resources. Of particular importance is the estimation of near-surface soil moisture, which influences many aspects of local weather and global climate. Soil moisture is als...

  7. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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...

  12. Application of IEM model on soil moisture and surface roughness estimation

    NASA Technical Reports Server (NTRS)

    Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

    1995-01-01

    Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

  13. Global Soil Moisture Analysis at DWD

    NASA Astrophysics Data System (ADS)

    Lange, M.

    2012-04-01

    Small errors in the daily forecast of precipitation, evaporation and runoff accumulate to uncertainties of soil water content and lead to systematic biases of temperature and humidity profiles in the boundary layer if no corrections are applied. A new soil moisture assimilation scheme has been developed for the global GME model and runs operationally since March 2011. As many other variational schemes implemented at NWP centers (e.g. Canadian Met Service, DWD, ECMWF,, Meteo France) the scheme is based on minimisation of screen level forecast errors by adjusting the soil water content implicitly correcting the partitioning of available energy into latent and sensible heat. The original method proposed by Mahfouf (1991) and described in Hess, 2001 requires at least two additional model forecast runs to calculate the gradient of the cost function i.e. the sensitivity dT2m/dwb with T2m as 2m temperature and wb as the soil water content of the respective top and bottom soil layers. To overcome this computational costly approach in the new scheme the sensitivity of screen level temperature on soil moisture changes is parameterized with derivatives of analytical relations for transpiration from vegetation and bare soil evaporation as motivated by Jacobs and De Bruin (1992). The comparison of both methods shows high correlation of the temperature sensitivity that justifies the approximation. The method will be described in detail and verification results will be presented to demonstrate the impact of soil moisture analysis in GME. Hess, R. 2001: Assimilation of screen-level observations by variational soil moisture analysis. Meteorol. Atmos. Phys. 77, 145-154. Jacobs, C.M.M. and H.A.R. De Bruin, 1992: The Sensitivity of Regional Transpiration to Land-Surface Characteristics: Significance of Feedback. J. Clim. 5, 683-698. Mahfouf, J-F. 1991. Analysis of soil moisture from near-surface parameters: A feasibility study. J. Appl. Meteorol. 30: 1534-1547.

  14. Measuring soil moisture with imaging radars

    SciTech Connect

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

    1995-07-01

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

  15. 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

  16. 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...

  17. Soil moisture in sessile oak forest gaps

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  18. 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

  19. Inference of extractable soil moisture in the plant root zone at the Walnut River Watershed.

    SciTech Connect

    Song, J.

    1998-10-05

    Soil moisture content is a crucial variable in studies of hydrology, meteorology, and plant sciences. Soil moisture content influences the ability of land to hold additional water from precipitation and thus affects groundwater levels and runoff. Evapotranspiration rates are strongly influenced by soil moisture content near the surface; evapotranspiration regulates surface air temperature and is a major factor in modifying the water vapor content of the atmosphere. Adequate soil moisture is essential for plant growth; excesses and deficits of soil moisture must be considered in agricultural management practices. Soil moisture can be measured by a variety of in situ techniques, but such techniques often are inadequate for evaluation over large areas because of strong temporal and spatial variations. Here, a technique using standard surface meteorological observations together with remote sensing data from satellites is discussed.

  20. 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

  1. Alberta Soil Moisture Analyses using CaLDAS

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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...

  8. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  9. Microwave soil moisture retrieval under trees

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. Soil Moisture From Satellite Radar Altimetry (SMALT)

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. These DREAMS are complicated to build and require multiple stages of processing and manual intervention. However, this approach obviates the requirement for detailed ground truth to populate theoretical models, facilitating derivation of surface soil moisture estimates over arid regions, where detailed survey data are generally not available. DREAMS have been produced over a number of deserts worldwide and a selection are presented in this paper. An overview of the SMALT processing scheme, covering the progression of the data from altimeter sigma0 through to final soil moisture estimate, is included along with example SMALT products. In order to validate these products comparisons with other remote sensing techniques and in-situ data have been performed over a number of desert regions. SMALT products are made freely available to the scientific community through the website http://tethys.eaprs.cse.dmu.ac.uk/SMALT

  11. Soil Moisture Active Passive Validation Experiment 2008

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Estimating Subcanopy Soil Moisture with RADAR

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  13. 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 ...

  14. 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...

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  17. Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization

    PubMed Central

    Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie

    2015-01-01

    Robust models for predicting soil salinity that use visible and near-infrared (vis–NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis–NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future. PMID:26468645

  18. 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...

  19. 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

  20. 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

  1. MONITORING ROOT-ZONE SOIL MOISTURE THROUGH THE ASSIMILATION OF A THERMAL REMOTE SENSING-BASED SOIL MOISTURE PROXY INTO A WATER BALANCE MODEL

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Two types of Soil Vegetation Atmosphere Transfer (SVAT) modeling approaches can be applied to monitor root-zone soil moisture in agricultural landscapes. Water and Energy Balance (WEB) SVAT modeling is based on forcing a prognostic root-zone water balance model with observed rainfall and predicted ...

  2. Estimates of monthly mean soil moisture for 1979-1989

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  3. 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.

  4. 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.

  5. Soil Erosion and Agricultural Sustainability

    NASA Astrophysics Data System (ADS)

    Montgomery, D. R.

    2009-04-01

    Data drawn from a global compilation of studies support the long articulated contention that erosion rates from conventionally plowed agricultural fields greatly exceed rates of soil production, erosion under native vegetation, and long-term geological erosion. Whereas data compiled from around the world show that soil erosion under conventional agriculture exceeds both rates of soil production and geological erosion rates by up to several orders of magnitude, similar global distributions of soil production and geological erosion rates suggest an approximate balance. Net soil erosion rates in conventionally plowed fields on the order of 1 mm/yr can erode typical hillslope soil profiles over centuries to millennia, time-scales comparable to the longevity of major civilizations. Well-documented episodes of soil loss associated with agricultural activities date back to the introduction of erosive agricultural methods in regions around the world, and stratigraphic records of accelerated anthropogenic soil erosion have been recovered from lake, fluvial, and colluvial stratigraphy, as well as truncation of soil stratigraphy (such as truncated A horizons). A broad convergence in the results from studies based on various approaches employed to study ancient soil loss and rates of downstream sedimentation implies that widespread soil loss has accompanied human agricultural intensification in examples drawn from around the world. While a broad range of factors, including climate variability and society-specific social and economic contexts — such as wars or colonial relationships — all naturally influence the longevity of human societies, the ongoing loss of topsoil inferred from studies of soil erosion rates in conventional agricultural systems has obvious long-term implications for agricultural sustainability. Consequently, modern agriculture — and therefore global society — faces a fundamental question over the upcoming centuries. Can an agricultural system

  6. 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.

  7. Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Rank Stability Analysis of Surface and Profile Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. 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

  10. 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

  11. Developing an Operational System for Daily 800-m Resolution Soil Moisture Estimates across Oklahoma

    NASA Astrophysics Data System (ADS)

    Ochsner, T. E.; Patton, J. C.; Dong, J.; Patrignani, A.; Haffner, M.

    2015-12-01

    Researchers often need meso-scale, high resolution soil moisture estimates for research and decision support in the areas of hydrology, agriculture, and ecology. However, current soil moisture measurement techniques are commonly inadequate in terms of spatial resolution (satellites), spatial support or density (in situ networks), or temporal resolution (rovers). The development of operational systems for high resolution soil moisture estimation will create opportunities for improved drought monitoring, flood forecasting, agricultural management, and wildfire preparedness, as well as for calibration and validation of soil moisture satellites. We are working to develop such an estimation system by merging multiple information sources including: a statewide, mesoscale network (the Oklahoma Mesonet), a cosmic-ray neutron rover, high resolution land cover data, and a proven soil water balance model. This presentation will describe our vision and motivations, our methods, and our progress to date.

  12. 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

  13. 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.

  14. 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...

  15. 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 ...

  16. Penman-Monteith Evapotranspiration under Soil Moisture Limiting Conditions across California

    NASA Astrophysics Data System (ADS)

    Purdy, A. J.; Famiglietti, J. S.

    2014-12-01

    In arid and semi-arid regions soil moisture often limits the flux of water to meet the atmospheric evapotranspiration (ET) demand. Potentially drier conditions and more variable precipitation and snow in California create a need to better understand how this reservoir limits ET across the state. The upcoming Soil Moisture Active Passive (SMAP) mission's surface and root zone soil moisture data will provide additional information to force observation based ET models at spatial scales ranging from 3-36 km2. To support application of SMAP data to ET modeling we investigate the role of soil moisture within the Penman-Monteith representation at FLUXNET and agricultural sites across California. We present findings on actual ET under soil moisture limiting conditions that do not violate assumptions within this modeling framework.

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

    NASA Technical Reports Server (NTRS)

    Peterson, John B. (Inventor)

    1982-01-01

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

  18. 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.

  19. 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

  20. Microwave backscatter dependence on surface roughness, soil moisture, and soil texture. II - Vegetation-covered soil

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

    Results are presented for an experimental investigation to determine the relationship between radar backscatter coefficient (sigma) and soil moisture for vegetation-covered soil. These results extend a previous report which showed the experimental relationship between sigma and soil moisture for bare soil. It is shown that the highest correlation between sigma and soil moisture is 0.92 for the combined response of four crop types measured at 4.25 GHz, 10 deg incidence angle, and HH polarization. Radar look direction, relative to the crop row direction, is shown to have an insignificant effect on soil-moisture estimation if the radar frequency is higher than 4 GHz. The dependence on soil type can be minimized by expressing soil moisture in units of percent of field capacity. The possibility of using a single radar for measuring soil moisture for both bare and vegetated fields is demonstrated with a linear estimation algorithm having an experimental correlation coefficinet of 0.8.

  1. 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

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

    NASA Technical Reports Server (NTRS)

    Wang, J. R.

    1992-01-01

    Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.

  3. 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

  4. Soil moisture at watershed scale: Remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Fang, Bin; Lakshmi, Venkat

    2014-08-01

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

  5. 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.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    PubMed

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

    2010-01-01

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

  9. 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.

  10. 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.

  11. SMALT - Soil Moisture from Altimetry project

    NASA Astrophysics Data System (ADS)

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

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

  12. Impact of soil texture on soil moisture measurement accuracy by TDR in Sistan plain of Iran

    NASA Astrophysics Data System (ADS)

    sarani, noushin; Afrasiab, Peyman

    2014-05-01

    In the recent past, many researchers have developed various techniques for determining moisture content of soil. Among the various methods of estimating soil moisture, Time Domain Reflectometry (TDR) method is a relatively new method. TDR has been widely used in water system investigation in Agriculture, Geosciences, etc. The purpose of this study is determination of moisture measurement accuracy by TDR in various soil textures in Sistan plain. For this purpose, six textures and for each of them three Iteration were used. The studied textures were clay, loam, sandy loam, sandy clay loam, clay loam and sandy. The experiments were carried out at the laboratory of water engineering department of Zabol University in Iran. The provided textures were laid in the PVC cylinder with 50 cm height and 30 cm diameter. After 24 h of saturation, the soil water content of the samples was measured by oven-dry gravimetric and TDR methods. In each day the moisture measurement of each texture was carried out by these two methods until a moisture range was determined. For comparison between measured moisture values by TDR and gravimetric method, two statistical parameters include coefficient of determination (R2) and root mean square error (RMSE) were applied here. The results showed that by using SPSS, statistically significant at probably level of 1% indicated no difference between the measured value of moisture by TDR device and gravimetric method. For heavy textures consist of sandy clay loam, clay loam, and clay with increasing clay content when the moisture was low, TDR measured the moisture values less than the gravimetric method. Furthermore for light textures consist of sandy loam and sand, the TDR device measured the moisture values more than the gravimetric method. Also for clay loam and sandy clay at high moisture values, data measured by TDR was close to the gravimetric method. For all studied textures with increasing of clay content, the fitted lines slope and RMSE

  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. 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.

  15. 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.

  16. 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.

  17. Interaction between soil moisture memory and different climate variables

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2015-04-01

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

  18. 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.

  19. Emerging methods for noninvasive sensing of soil moisture dynamics from field to catchment scale

    NASA Astrophysics Data System (ADS)

    Bogena, H. R.; Huisman, J. A.; Vereecken, H.

    2015-12-01

    Soil moisture is an important state variable in the terrestrial system because it controls the exchange of water and energy between the land surface and the atmosphere. Soil moisture is highly variable in space and time with characteristic length scales ranging from a few centimeters up to several kilometers and characteristic time scales ranging from minutes up to years. Information on soil moisture dynamics is important for optimizing agricultural management, and to improve our understanding of biogeochemical processes, vadose zone processes, and atmospheric processes. Despite a wealth of available soil moisture measurement techniques, there still exists a gap in measurement capability of classical soil moisture monitoring technologies that makes large-scale soil moisture characterization with high temporal resolution highly challenging. In this presentation, we will review emerging soil moisture sensing techniques that are particularly well suited to overcome this space-time scale gap in measurement capability. In particular, we focus on recent advances in noninvasive techniques that allow continuous noninvasive and contactless measurements of soil moisture dynamics at the field to basin scale, e.g. cosmic-ray neutron probes (CRNP), GNSS reflectometry, ground-based microwave radiometry, gamma-ray monitoring, terrestrial gravimetry, and low-frequency electromagnetic surface waves (LFEMW). These methods have the following important advantages compared to other soil moisture sensing methods: (1) soil structure remains undisturbed by the measurements, (2) the measurement device can be operated continuously (e.g., also during tilling operations), and (3) the soil moisture measurements integrate large areas (i.e., larger than 100m2). We will present basic principles with a particular focus on measurement scale and accuracy, and will also provide example applications for selected methods.

  20. 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.

  1. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Spatial-temporal variability of soil moisture 15 has been remaining an challenge to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time soil moisture monitoring methods. This restricted the comprehensive and intensive examination of soil moisture dynamics. In this study, we aimed to integrate the manual and real-time monitored soil moisture to depict the hillslope dynamics of soil moisture with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear models (support vector machines-SVM) were used to predict soil moisture at 38 manual sites (collected 1-2 times per month) with soil moisture automatically collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each manual site, optimal soil moisture prediction model of this site was then determined. Results show that soil moisture at these 38 manual sites can be reliably predicted (root mean square errors<0.035 m3 m-3) using this approach. Absence or occurrence of subsurface flow can probably influence the choosing of SMLR or SVM in the prediction, respectively. Depth to bedrock, elevation, topographic wetness index, profile curvature, and relative difference of soil moisture and its standard deviation influenced the selection of prediction model since they related to the dynamics of soil water distribution and movement. By using this approach, hillslope soil moisture spatial distributions at un-sampled times and dates were predicted after a typical rainfall event. Missing information of hillslope soil moisture dynamics was then acquired successfully. This can be benefit for determining the hot spots and moments of soil water movement, as well as designing the proper soil moisture monitoring plan at the field scale.

  4. Surface soil moisture estimation at the watershed scale using in situ networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Surface soil moisture estimation impacts a wide range of concerns, including agricultural management, climate, and weather modeling. New satellite technologies have been developed with allow for this estimation on a high temporal basis with moderate accuracy for the agricultural heartland of the U....

  5. 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.

  6. Soil moisture estimation from radar altimetry

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

    The climate of West African Sahel is controlled by a complex system of interactions between the atmosphere, biosphere and hydrosphere, known as the West African monsoon. The rainfall dynamics at various spatial and temporal scales, which have a strong impact on human activities, are mainly governed by surface conditions - vegetation cover and soil moisture. This important parameter of the hydrological cycle is poorly described at regional, continental or global scale. Space-borne sensors exhibit a strong potential for the study of continental surfaces. Radar altimetry, initially developed to make accurate measurements of ocean topography, is commonly used for the survey of ice sheets and river stages. Several studies showed that changes in snow cover, soil water content and vegetation properties are responsible for variations of the backscatter response. Over the Sahel region, maxima of the backscatter coefficients are correlated to rain events. We present the results of an analysis of the backscatter coefficients from Topex/Poseidon and ENVISAT/RA-2 over the Gourma site (Mali) and compare them with in- situ and satellite measurements of precipitation, soil moisture and vegetation.

  7. 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.

  8. 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

  9. 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...

  10. 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...

  11. Short-term soil moisture response to low-tech erosion control structures in a semi arid rangeland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Although rock check dams have been used for centuries to control erosion and support subsistence agriculture on western US rangelands, there is a lack of data for quantifying their impact on soil moisture distribution. The purpose of this study was to measure and document soil moisture in associatio...

  12. Retrieval of Surface and Subsurface Moisture of Bare Soil Using Simulated Annealing

    NASA Astrophysics Data System (ADS)

    Tabatabaeenejad, A.; Moghaddam, M.

    2009-12-01

    Soil moisture is of fundamental importance to many hydrological and biological processes. Soil moisture information is vital to understanding the cycling of water, energy, and carbon in the Earth system. Knowledge of soil moisture is critical to agencies concerned with weather and climate, runoff potential and flood control, soil erosion, reservoir management, water quality, agricultural productivity, drought monitoring, and human health. The need to monitor the soil moisture on a global scale has motivated missions such as Soil Moisture Active and Passive (SMAP) [1]. Rough surface scattering models and remote sensing retrieval algorithms are essential in study of the soil moisture, because soil can be represented as a rough surface structure. Effects of soil moisture on the backscattered field have been studied since the 1960s, but soil moisture estimation remains a challenging problem and there is still a need for more accurate and more efficient inversion algorithms. It has been shown that the simulated annealing method is a powerful tool for inversion of the model parameters of rough surface structures [2]. The sensitivity of this method to measurement noise has also been investigated assuming a two-layer structure characterized by the layers dielectric constants, layer thickness, and statistical properties of the rough interfaces [2]. However, since the moisture profile varies with depth, it is sometimes necessary to model the rough surface as a layered structure with a rough interface on top and a stratified structure below where each layer is assumed to have a constant volumetric moisture content. In this work, we discretize the soil structure into several layers of constant moisture content to examine the effect of subsurface profile on the backscattering coefficient. We will show that while the moisture profile could vary in deeper layers, these layers do not affect the scattered electromagnetic field significantly. Therefore, we can use just a few layers

  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. Mesoscale Monitoring of Soil Moisture Across a Statewide Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. 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.

  19. Inter-Annual Variability of Soil Moisture Stress Function in the Wheat Field

    NASA Astrophysics Data System (ADS)

    Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.

    2014-12-01

    Root-zone soil moisture content is a key variable that controls the exchange of water and energy fluxes between land and atmosphere. In the soil-vegetation-atmosphere transfer (SVAT) schemes, the influence of root-zone soil moisture on evapotranspiration (ET) is parameterized by the soil moisture stress function (SSF). Dependence of actual ET: potential ET (fPET) or evaporative fraction to the root-zone soil moisture via SSF can also be used inversely to estimate root-zone soil moisture when fPET is estimated by remotely sensed land surface states. In this work we present fPET versus available soil water (ASW) in the root zone observed in the experimental farm sites in Victoria, Australia in 2012-2013. In the wheat field site, fPET vs ASW exhibited distinct features for different soil depth, net radiation, and crop growth stages. Interestingly, SSF in the wheat field presented contrasting shapes for two cropping years of 2012 and 2013. We argue that different temporal patterns of rainfall (and resulting soil moisture) during the growing seasons in 2012 and 2013 are responsible for the distinctive SSFs. SSF of the wheat field was simulated by the Agricultural Production Systems sIMulator (APSIM). The APSIM was able to reproduce the observed fPET vs. ASW. We discuss implications of our findings for existing modeling and (inverse) remote sensing approaches relying on SSF and alternative growth-stage-dependent SSFs.

  20. Soil Moisture Comparison between SMOS and MUSAG for a Brazilian Semi-Arid region

    NASA Astrophysics Data System (ADS)

    Ferreira, Antonio Geraldo; Lopez-Baeza, Ernesto; De Andrade, M. Fernando C. M.

    In this paper a comparison between soil moisture information generated by MUSAG a Model of Soil Moisture for Agricultural Activities and SMOS a polar orbit satellite which forms part of ESA's Living Planet Programme will be made. MUSAG was calibrated for Ceará State, in the northeastern part of Brazil Region, a semi-arid region. The model makes a soil water balance taking meteorological and soil parameters in different climatic stations operated by FUNCEME (Ceara State Foundation for Meteorology and Water Resources. The MUSAG’s input data are daily precipitation (from the 184 raingauges distributed along of Ceará), evaporation and soil type, and the model’s output are soil moisture maps where moisture is presented as the percentage of soil moisture on the soil water maximum storage capacity. SMOS generates soil moisture information by data retrieval by using MIRAS (Microwave Imaging Radiometer) a sensor on board SMOS. The comparison will consider data selected from mainly Ceara’s rainy season (frebuary to may) for the years 2011 and 2012 and 2013.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  3. A global validation of the ASCAT Soil Water Index (SWI) with in situ data from the International Soil Moisture Network.

    NASA Astrophysics Data System (ADS)

    Paulik, C.; Naeimi, V.; Dorigo, W.; Wagner, W.; Kidd, R.

    2012-04-01

    Soil Moisture is an Essential Climate Variable and a key parameter in hydrology, meteorology and agriculture. Surface Soil Moisture (SSM) can be estimated from measurements taken by ASCAT onboard Metop-A and have been successfully validated by several studies (C. Albergel et.al. 2009 and 2012, M.Parrens et.al. 2012). Profile soil moisture, while equally important, can not be measured directly by remote sensing. The near real-time Soil Water Index (SWI) product, developed within the framework of the GMES project geoland2 aims to close this gap. It is produced from ASCAT SSM estimates using a two-layer water balance model which describes the relationship between surface and profile soil moisture as a function of time. It provides daily global data about moisture conditions for 8 characteristic time lengths representing different depths. The objective of this work was to assess the quality of the SWI data for different measurement depths. SWI data from January 1st 2007 until the end of 2010 was compared to in situ soil moisture data from 420 stations belonging to 22 observation networks which are available through the International Soil Moisture Network. These stations delivered 1331 station/depth combinations which were compared to the SWI values. After excluding observations made during frozen conditions the average significant correlation coefficients were 0.564 (min -0.684, max 0.955) while being greater than 0.3 for 88% of all station/depth combinations.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  5. 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).

  6. 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.

  7. 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).

  8. L-band Soil Moisture Mapping using Small UnManned Aerial Systems

    NASA Astrophysics Data System (ADS)

    Dai, E.

    2015-12-01

    Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.

  9. 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.

  10. Predicting root zone soil moisture with satellite near-surface moisture data in semiarid environments

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    One of the most critical variables in semiarid environment is the soil water content that represents a controlling factor for both ecological and hydrological processes. Soil moisture monitoring over large scales may be extremely useful, but it is limited by the fact that most of the available tools provides only surface measurements not representative of the effective amount of water stored in the subsurface. Therefore, a methodology able to infer root-zone soil moisture starting from surface measurements is highly desirable. Recently a new simplified formulation has been introduced to provide a formal description of the mathematical relationship between surface measurements and root-zone soil moisture (Manfreda et al., HESS 2014). This is a physically based approach derived from the soil water balance equation, where different soil water loss functions have been explored in order to take into account for the non-linear processes governing soil water fluxes. The study highlighted that the soil loss function is the key for such relationship that is therefore strongly influenced by soil type and physiological plant types. The new formulation has been tested on soil moisture based on measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases. The method sheds lights on the physical controls for soil moisture dynamics and on the possibility to use such a simplified method for the description of root-zone soil moisture. Furthermore, the method has been also couple with an Enasamble Kalman Filter (EnKF) in order to optimize its performances for the large scale monitoring based the new satellite near-surface moisture data (SMAP). The optimized SMAR-EnKF model does well in both wet and dry climates and across many different soil types (51 SCAN locations) providing a strategy for real-time soil moisture monitoring.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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).

  17. 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.

  18. Impact of Surface Soil Moisture of Pesticide Volatilization Fluxes

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Validation of Distributed Soil Moisture: Airborne Polarimetric SAR vs. Ground-based Sensor Networks

    NASA Astrophysics Data System (ADS)

    Jagdhuber, T.; Kohling, M.; Hajnsek, I.; Montzka, C.; Papathanassiou, K. P.

    2012-04-01

    The knowledge of spatially distributed soil moisture is highly desirable for an enhanced hydrological modeling in terms of flood prevention and for yield optimization in combination with precision farming. Especially in mid-latitudes, the growing agricultural vegetation results in an increasing soil coverage along the crop cycle. For a remote sensing approach, this vegetation influence has to be separated from the soil contribution within the resolution cell to extract the actual soil moisture. Therefore a hybrid decomposition was developed for estimation of soil moisture under vegetation cover using fully polarimetric SAR data. The novel polarimetric decomposition combines a model-based decomposition, separating the volume component from the ground components, with an eigen-based decomposition of the two ground components into a surface and a dihedral scattering contribution. Hence, this hybrid decomposition, which is based on [1,2], establishes an innovative way to retrieve soil moisture under vegetation. The developed inversion algorithm for soil moisture under vegetation cover is applied on fully polarimetric data of the TERENO campaign, conducted in May and June 2011 for the Rur catchment within the Eifel/Lower Rhine Valley Observatory. The fully polarimetric SAR data were acquired in high spatial resolution (range: 1.92m, azimuth: 0.6m) by DLR's novel F-SAR sensor at L-band. The inverted soil moisture product from the airborne SAR data is validated with corresponding distributed ground measurements for a quality assessment of the developed algorithm. The in situ measurements were obtained on the one hand by mobile FDR probes from agricultural fields near the towns of Merzenhausen and Selhausen incorporating different crop types and on the other hand by distributed wireless sensor networks (SoilNet clusters) from a grassland test site (near the town of Rollesbroich) and from a forest stand (within the Wüstebach sub-catchment). Each SoilNet cluster

  20. 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.

  1. Plumbum contamination detecting model for agricultural soil using hyperspectral data

    NASA Astrophysics Data System (ADS)

    Liu, Xiangnan; Huang, Fang; Wang, Ping

    2008-10-01

    The issue of environmental pollution due to toxic heavy metals in agricultural land has caused worldwide growing concern in recent years. Being one of toxic heavy metals, the accumulation of Plumbum (Pb) may have negative effects on natural and agricultural vegetation growth, yield and quality. It can also constitute short-term and long-term health risks by entering the food chain. In this study, we analyze the relationships between physical and chemical characteristics, biological parameters of soil-vegetation system and hyperspectral spectrum responses systematically. The relation between hyperspectral data and the biological parameters of Pb polluted wheat canopy such as leaf pigments, leaf moisture, cell structure and leaf area index (LAI) are discussed. We detect the changes in the wheat biological parameters and spectral response associated with Pb concentration in soil. To reveal the impact mechanisms of Pb concentration on agricultural soil, six models including chlorophyll-leaf moisture model, chlorophyll-cell structure model, chlorophyll-LAI model, leaf moisture-cell structure model, leaf moisture-LAI model, cell structure- LAI model are explored. We find that changes in Pb concentration present various features in different models. Pb contamination in agricultural soil can be identified and assessed effectively while integrating the characteristics of those developed models.

  2. 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

  3. Land surface model evaluation using a new soil moisture dataset from Kamennaya Steppe, Russia

    NASA Astrophysics Data System (ADS)

    Atkins, T.; Robock, A.; Speranskaya, N.

    2004-12-01

    The land surface affects the atmosphere through the transfer of energy and moisture and serves as the lower boundary in numerical weather prediction and climate models. To obtain good forecasts, these models must therefore accurately portray the land surface. Actual in situ measurements are vital for testing and developing these models. It is with this in mind that we have obtained a dataset of soil moisture, soil temperature and meteorological measurements from Kamennaya Steppe, Russia. The meteorological dataset spans the time period 1965-1991, while the soil moisture dataset runs from 1956-1991. The soil moisture dataset contains gravimetric volumetric total soil moisture measurements for 10 layers taken from forest, agricultural and grassland soils. The meteorological dataset contains 3-hourly measurements of precipitation, temperature, wind speed, pressure and relative humidity. We obtained longwave and shortwave radiation data from standard formulae. The data will be made available to the public via the Rutgers University Center for Environmental Prediction Global Soil Moisture Data Bank. Soil temperature is important in determining the timing, duration and intensity of runoff and snowmelt, particularly at the beginning and end of the winter when the ground is only partially frozen. Soil temperature can in turn be affected by the vertical distribution of roots. The soil temperature data are for 1969-1991. The data are daily averaged for every 20 cm to 1.2 meters in depth. These data are used to investigate the natural sensitivity of soil temperature to vegetation type and root distribution. We also use the temperature data, as well as water balance and snowfall data to test the sensitivity of the Noah land surface model (LSM) soil temperature to vertical root distribution, and what effect that has on the hydrology of the site. In addition to soil temperature data, we also have soil moisture data for several vegetation types. We compare the soil moisture time

  4. 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

  5. Soil Moisture Performance Prediction for the NPOESS Microwave Imager/Sounder (MIS)

    NASA Astrophysics Data System (ADS)

    Li, L.; McWilliams, G.

    2009-12-01

    Soil moisture is a key environmental variable in the global water, energy and carbon cycles and in environmental assessment and prediction. It greatly affects a broad range of scientific and operational applications in hydrology, climate studies and agriculture. Soil moisture is also a desired input parameter to Numerical Weather Prediction (NWP) models since it controls the land-atmosphere interaction, such as dust emission and heating/moistening of the lower atmosphere. It is also a critical battlespace environment variable affecting military operations. The soil moisture content is critically related to trafficability as well as being a vital determinant of thermal and electromagnetic signatures that are vital to the operational ground mission in C4ISR (command, control, communications, computers, intelligence, surveillance, and reconnaissance). The National Polar-orbiting Operational Environmental Satellite System’s (NPOESS) Microwave Imager/Sounder (MIS) instrument is in development, with soil moisture sensing depth as one of the two Key Performance Parameters (KPPs). The other one is ocean surface wind speed precision. Based on the current design, the MIS sensor shares many channel configurations similar to the WindSat instrument, which provides an opportunity to predict MIS soil moisture performance using WindSat data. The WindSat land surface algorithm is a physically-based algorithm used to retrieve simultaneously the soil moisture, land surface temperature and vegetation water content for a range of surface types except for snow, frozen, rainy and flood surfaces. The algorithm has been rigorously validated against global in-situ data and has demonstrated great science potential in study of soil moisture response to precipitation, ITCZ (Intertropical Convergence Zone) propagation, drought detection, and heat wave evolution. The evaluation results suggest that the WindSat data products meet IORD II threshold soil moisture requirements. To approximate MIS

  6. Soil moisture retrieval from combined use of microwave (RADARSAT-2) and optical remote sensing (MODIS)

    NASA Astrophysics Data System (ADS)

    Gan, T. Y.; Nasreen, J.

    2012-04-01

    The potential of using the newly available, quad-polarized, RADARSAT-2 synthetic Aperture Radar (SAR) data in near surface soil moisture retrieval was examined. Seven Radarsat-2 images have been acquired over the Paddle River Basin (PRB), Alberta, Canada and soil samples, from 9 sites (agricultural, herbaceous and pasture land sites and 25 soil samples from a plot about 200m x 200m per site), have been collected within the basin on those 7 days when the RADARSAT-2 satellite flew over the study site to obtain actual soil moisture information. Soil moisture was retrieved from the RADARSAT-2 SAR data using the popular theoretical Integral Equation model (IEM), linear and nonlinear regressions. Normalized Difference Vegetation Index (NDVI) and Land Surface temperature (LST) from the optical sensor of the Moderate resolution Imaging Spectroradiometer (MODIS) satellite have also been used as predictors in the regression algorithms. The combined use of radar backscatters, LST and NDVI as the predictors produced the best soil moisture retrieval results than using radar backscatters as the only predictor. This is probably because radar and optical data together could provide more information than radar backscatters alone the surface characteristics and the effects of vegetation on soil moisture. With reference to field measurements, soil moisture retrieved from HH polarized RADARSAT-2 SAR data by the best regression and the IEM models over the 9 sites achieved correlation coefficients of 0.89 and 0.91, respectively. Our results are slightly inferior to that of Biftu and Gan (1999) who also retrieved soil moisture for PRB using single (HH) polarized RADARSAT-1 SAR data probably because we conducted our study in the early growing season and so subjected to more pronounced effect of vegetation on soil moisture retrieval than that of Biftu and Gan (1999) who conducted their study during the post harvest season.

  7. Prefractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

    NASA Astrophysics Data System (ADS)

    Cumbrera, R.; Tarquis, A. M.; Gascó, G.; Millán, H.

    2012-04-01

    Image 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 x 0.60 m width x 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 three days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a KodakTM digital camera. The mean image size was 1600 x 945 pixels with one physical pixel ≈ 373 μm of the photographed soil pit. Each soil image was analyzed using two prefractal 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 (Γ1) and Shannon entropy at the unit scale (S1). All prefractal 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 prefractal parameters can be incorporated within site-specific agriculture toolbox. While fractal exponents condense 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. Key words: Image analysis, fractal scaling, apparent soil moisture, Vertisols Acknowledgements This work has been

  8. [Modeling Soil Spectral Reflectance with Different Mass Moisture Content].

    PubMed

    Sun, Yue-jun; Zheng, Xiao-po; Qin, Qi-ming; Meng, Qing-ye; Gao, Zhong-ling; Ren, Hua-zhong; Wu, Ling; Wang, Jun; Wang, Jian-hua

    2015-08-01

    The spatio-temporal distribution and variation of soil moisture content have a significant impact on soil temperature, heat balance between land and atmosphere and atmospheric circulation. Hence, it is of great significance to monitor the soil moisture content dynamically at a large scale and to acquire its continuous change during a certain period of time. The object of this paper is to explore the relationship between the mass moisture content of soil and soil spectrum. This was accomplished by building a spectral simulation model of soil with different mass moisture content using hyperspectral remote sensing data. The spectra of soil samples of 8 sampling sites in Beijing were obtained using ASD Field Spectrometer. Their mass moisture contents were measured using oven drying method. Spectra of two soil samples under different mass moisture content were used to construct soil spectral simulation model, and the model was validated using spectra of the other six soil samples. The results show that the accuracy of the model is higher when the mass water content of soil is below field capacity. At last, we used the spectra of three sampling points on campus of Peking University to test the model, and the minimum value of root mean square error between simulated and measured spectral reflectance was 0.0058. Therefore the model is expected to perform well in simulating the spectrum reflectance of different types of soil when mass water content below field capacity. PMID:26672301

  9. Summer soil moisture spatiotemporal variability in southeastern Arizona

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Soil Moisture Algorithm Validation with Ground Based Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Validation satellite-based soil moisture algorithms and products is particularly challenging due to the disparity of scales of the two observation methods, conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value over a large ar...

  14. 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 ...

  15. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Field observations of soil moisture variability across scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Diurnal variation of diazinon volatilization: Soil moisture effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Global Evaluation of Remotely-Sensed Soil Moisture Retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  2. VALIDATION OF SATELLITE-BASED SOIL MOISTURE ALGORITHMS

    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 ...

  3. WindSat Soil Moisture Algorithm and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. 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...

  5. 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.

  6. SMOS Soil Moisture Product Validation In Croplands

    NASA Astrophysics Data System (ADS)

    Niclos, R.; Rivas, R.; Garcia-Santos, V.; Dona, C.; Valor, E.; Holzman, M.; Bayala, M.; Carmona, F.; Ocampo, D.; Thibeault, M.; Soldano, A.

    2013-12-01

    A validation campaign was carried out to evaluate the SMOS-MIRAS Soil Moisture (SM) SML2UDP product (v5.51) in the Pampean Region of Argentina. The study area was selected because it is a vast area of flatlands containing quite homogeneous rainfed croplands considered SMOS nominal land uses. Transects of ground SM measurements were collected by ThetaProbe ML2x probes within four ISEA-grid SMOS nodes, where permanent SM stations are located. The first validation results showed a negative bias between concurrent SMOS data and ground SM measurements, which means a slight SMOS-MIRAS underestimation, and a standard deviation of ± 0.06 m3m-3. Additionally, a correlation was obtained between the ground SM values and the SM station data within a node. Therefore, the station data adjusted to obtain node representative values could be used to continue the validation of SMOS-retrieved data in the future.

  7. Evaluating near-surface soil moisture using Heat Capacity Mapping Mission data

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

    Four dates of Heat Capacity Mapping Mission (HCMM) data were analyzed in order to evaluate HCMM thermal data use in estimating near-surface soil moisture in a complex agricultural landscape. Because of large spatial and temporal ground cover variations, HCMM radiometric temperatures alone did not correlate with soil water content. The radiometric temperatures consisted of radiance contributions from different canopies and their respective soil backgrounds. However, when surface soil temperatures were empirically estimated from HCMM temperatures and percent cover of each pixel, a highly significant correlation was obtained between the estimated soil temperatures and near-surface soil water content.

  8. 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.

  9. Soil moisture: applications and needs in vadose zone hydrology

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Huisman, S.; Bogena, H.; Vanderborght, J.; Vrugt, J.; Hopmans, J. W.

    2007-12-01

    In this presentation, we address the state of the art in using soil moisture measurements to derive soil hydraulic properties, to quantify water and energy fluxes in the vadose zone, to retrieve spatial and temporal dynamics of soil moisture profiles, and to develop monitoring networks. We will discuss these issues at two different scales important in vadose zone hydrology: the field and the catchment scale. Analyzing the value of soil moisture measurements is motivated by our increasing ability to measure soil moisture due to the availability of novel non- invasive measurement techniques at the field and catchment scale, of remote sensing platforms and improved retrieval algorithms as well as of novel soil moisture network sensor technologies in providing high quality soil moisture data with high spatial and temporal resolution. We advocate that optimal use of soil moisture measurements will require further development of down- and upscaling algorithms to bridge the disparity in scales between hydrological measurements and mathematical models, to improve data assimilation techniques for retrieving the vertical and horizontal distribution of soil moisture including its temporal dynamics but also hydrological parameters driving the flow of water and to explore the potential in combining hydrogeophysical techniques with remote sensing measurement of soil moisture. With respect to the issue of upscaling we feel that stochastic upscaling theories developed in vadose zone research have not really been optimally used at scales larger than the field scale. This will be illustrated by applying stochastic theories in interpreting observed soil moisture fields. Applications of these theories might help in bridging the gap between model and measurement scale at larger scales.

  10. 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.

  11. Modeling Soil Moisture Fields Using the Distributed Hydrologic Model MOBIDIC

    NASA Astrophysics Data System (ADS)

    Castillo, A. E.; Entekhabi, D.; Castelli, F.

    2011-12-01

    The Modello Bilancio Idrologico DIstributo e Continuo (MOBIDIC) is a fully-distributed physically-based basin hydrologic model [Castelli et al., 2009]. MOBIDIC represents watersheds using a system or reservoirs that interact through both mass and energy fluxes. The model uses a single-layered soil on a grid. For each grid element, soil moisture is conceptually partitioned into gravitational (free) and capillary-bound water. For computational parsimony, linear parameterization is used for infiltration rather than solving it using the nonlinear Richard's Equation. Previous applications of MOBIDIC assessed model performance based on streamflow which is a flux. In this study, the MOBIDIC simulated soil moisture, a state variable, is compared against observed values as well as values simulated by the legacy Simultaneous Heat and Water (SHAW) model [Flerchinger, 2000] which was chosen as the benchmark. Results of initial simulations with the original version of MOBIDIC prompted several model modifications such as changing the parameterization of evapotranspiration and adding capillary rise to make the model more robust in simulating the dynamics of soil moisture. In order to test the performance of the modified MOBIDIC, both short-term (a few weeks) and extended (multi-year) simulations were performed for 3 well-studied sites in the US: two sites are mountainous with deep groundwater table and semiarid climate, while the third site is fluvial with shallow groundwater table and temperate climate. For the multi-year simulations, both MOBIDIC and SHAW performed well in modeling the daily observed soil moisture. The simulations also illustrated the benefits of adding the capillary rise module and the other modifications introduced. Moreover, it was successfully demonstrated that MOBIDIC, with some conceptual approaches and some simplified parameterizations, can perform as good, if not better, than the more sophisticated SHAW model. References Castelli, F., G. Menduni, and B

  12. 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

  13. Microwave and gamma radiation observations of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  14. 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

  15. A sensor for the measurement of the moisture of undisturbed soil samples.

    PubMed

    Kitić, Goran; Crnojević-Bengin, Vesna

    2013-01-01

    This paper presents a very accurate sensor for the measurement of the moisture of undisturbed soil samples. The sensor relies on accurate estimation of the permittivity which is performed independently of the soil type, and a subsequent calibration. The sensor is designed as an upgrade of the conventional soil sampling equipment used in agriculture--the Kopecky cylinder. The detailed description of the device is given, and the method for determining soil moisture is explained in detail. Soil moisture of unknown test samples was measured with an absolute error below 0.0057 g/g, which is only 2.24% of the full scale output, illustrating the high accuracy of the sensor. PMID:23385404

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    Speranskaya, N. A.

    2009-04-01

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

  19. 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.

  20. Development of a Drought Severity Assessment Framework using Remotely Sensed Soil Moisture Products under Climate Change Scenario

    NASA Astrophysics Data System (ADS)

    Mohanty, B. P.; Shin, Y.

    2012-12-01

    Evaluating drought severity based on future climate scenarios plays an important role for water resources management. In this study we assessed drought severity based on soil moisture for individual soil-crop combinations. Based on the historical data, pixel-scale hydraulic parameters at finer-scales were estimated from remotely sensed (RS) soil moisture using a newly developed algorithm EMOGA (Ensemble Multiple Operators Genetic Algorithm) coupled with Soil-Water-Atmosphere-Plant (SWAP) hydrological model. These estimated hydraulic parameters along with meteorological variables obtained from general circulation models (GCMs) were used to predict soil moisture using the SWAP model. Further, drought severity was calculated using a soil moisture deficit index (SMDI) based on the projected soil moisture obtained from the SWAP model. The proposed model was evaluated based on synthetic and field data under different hydro-climates (Lubbock, Texas; Little Washita watershed, Oklahoma; Walnut Creek watershed, Iowa). Finer-scale root zone soil moisture predictions were considerably influenced by various combinations of environmental factors (soils, crops, groundwater table, etc.) along with GCM scenarios. However, these local environmental factors had relatively limited impacts (compared to precipitation dynamics) on reducing drought severity in the study region. The absolute SMDI values do indicate the occurrence of agricultural drought during 2010-2020. Thus, our proposed approach can be used to assess drought severity at finer-scales using a RS soil moisture product for efficient agricultural/water resources management.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. How far SAR has fulfilled its expectation for soil moisture retrieval

    NASA Astrophysics Data System (ADS)

    Srivastava, Hari Shanker; Patel, Parul; Navalgund, Ranganath R.

    2006-12-01

    Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity to dielectric properties of the target. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other parameters like surface roughness, crop cover and soil texture. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited for resolving these effects and incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisition, the gap period between the two acquisitions should be minimum. However, for RADARSAT-1 the gap is typically of the order of 3 days. To overcome this difficulty, simultaneously acquired ENVISAT-1 ASAR HH/VV and VV/VH data was studied for operational soil moisture estimation. Cross-polarised SAR data has been exploited for its sensitivity to vegetation for crop-covered fields where as co-pol ratio has been used to incorporate surface roughness for the case of bare soil. Although there has not been any multi-frequency SAR system onboard a satellite platform, efforts have also been made to understand soil moisture sensitivity and penetration capability at different frequencies using SIR-C/X-SAR and multi-parametric Airborne SAR data. This paper describes multi-incidence angle, multi-polarised and multi-frequency SAR approaches for soil moisture retrieval over large agricultural area.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. 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...

  6. 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.

  7. 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.

  8. Planning for a Canadian Contribution to a Soil Moisture Mission

    NASA Astrophysics Data System (ADS)

    Bélair, Stéphane; Melo, Stella

    2009-12-01

    First Workshop on Canadian SMAP Applications and Cal-Val; Montreal, Quebec, Canada, 6-7 October 2009; The Soil Moisture Active and Passive (SMAP) mission will combine low-frequency microwave radiometer and high-resolution radar instruments to measure surface soil moisture and freeze-thaw state. This NASA mission, managed by the Jet Propulsion Laboratory, has the potential to enable a diverse range of applications including drought and flood guidance, agricultural productivity estimation and risk mitigation, weather forecasting, climate predictions, human health risk assessment and mitigation, and defense systems. Recognizing the potential relevance of SMAP's measurements for Canada, Environment Canada (EC) and the Canadian Space Agency (CSA) are joining efforts to develop Canadian participation in this mission. As part of this effort, the First Workshop on Canadian SMAP Applications and Cal-Val was held in Canada. The main objective of this workshop was to develop a consolidated plan for Canadian participation in the SMAP mission that would address the needs of different Canadian government departments and academia.

  9. 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.

  10. Mapping patterns of soil properties and soil moisture using electromagnetic induction to investigate the impact of land use changes on soil processes

    NASA Astrophysics Data System (ADS)

    Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

    2016-04-01

    As highlighted by many authors, classical or geophysical techniques for measuring soil moisture such as destructive soil sampling, neutron probes or Time Domain Reflectometry (TDR) have some major drawbacks. Among other things, they provide point scale information, are often intrusive and time-consuming. ElectroMagnetic Induction (EMI) instruments are often cited as a promising alternative hydrogeophysical methods providing more efficiently soil moisture measurements ranging from hillslope to catchment scale. The overall objective of our research project is to investigate whether a combination of geophysical techniques at various scales can be used to study the impact of land use change on temporal and spatial variations of soil moisture and soil properties. In our work, apparent electrical conductivity (ECa) patterns are obtained with an EM multiconfiguration system. Depth profiles of ECa were subsequently inferred through a calibration-inversion procedure based on TDR data. The obtained spatial patterns of these profiles were linked to soil profile and soil water content distributions. Two catchments with contrasting land use (agriculture vs. natural forest) were selected in a subtropical region in the south of Brazil. On selected slopes within the catchments, combined EMI and TDR measurements were carried out simultaneously, under different atmospheric and soil moisture conditions. Ground-truth data for soil properties were obtained through soil sampling and auger profiles. The comparison of these data provided information about the potential of the EMI technique to deliver qualitative and quantitative information about the variability of soil moisture and soil properties.

  11. Calibrating a FDR sensor for soil moisture monitoring in a wetland in Central Kenya

    NASA Astrophysics Data System (ADS)

    Böhme, Beate; Becker, Mathias; Diekkrüger, Bernd

    The recent transformation of wetlands into farmland in East Africa is accelerating due to growing food-demand, land shortages, and an increasing unpredictability of climatic conditions for crop production in uplands. However, the conversion of pristine wetlands into sites of production may alter hydrological attributes with negative effects on production potential. Particularly the amount and the dynamics of plant available soil moisture in the rooting zone of crops determine to a large extent the agricultural production potential of wetlands. Various methods exist to assess soil moisture dynamics with Frequency Domain Reflectometry (FDR) being among the most prominent. However, the suitability of FDR sensors for assessing plant available soil moisture has to date not been confirmed for wetland soils in the region. We monitored the seasonal and spatial dynamics of water availability for crop growth in an inland valley wetland of the Kenyan highlands using a FDR sensor which was site-specifically calibrated. Access tubes were installed within different wetland use types and hydrological situations along valley transects and soil properties affecting soil moisture (organic C, texture, and bulk density) were investigated. There was little variation in soil attributes between physical positions in the valley, and also between topsoil and subsoil attributes with the exception of organic C contents. With a root mean squared error of 0.073 m3/m3, the developed calibration function of the FDR sensor allows for reasonably accurate soil moisture prediction for both within-site comparisons and the monitoring of temporal soil moisture variations. Applying the calibration equation to a time series of profile probe readings over a period of one year illustrated not only the temporal variation of soil moisture, but also effects of land use.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. Validation of the ASCAT Soil Water Index using in situ data from the International Soil Moisture Network

    NASA Astrophysics Data System (ADS)

    Paulik, Christoph; Dorigo, Wouter; Wagner, Wolgang; Kidd, Richard

    2014-08-01

    Soil moisture is an essential climate variable and a key parameter in hydrology, meteorology and agriculture. Surface Soil Moisture (SSM) can be estimated from measurements taken by ASCAT onboard Metop-A and have been successfully validated by several studies. Profile soil moisture, while equally important, cannot be directly measured by remote sensing but must be modeled. The Soil Water Index (SWI) product developed for near real time applications within the framework of the GMES project geoland2 aims to provide such a modeled profile estimate using satellite data as input. It is produced from ASCAT SSM estimates using a two-layer water balance model which describes the relationship between surface and profile soil moisture as a function of time. It provides daily global data about moisture conditions for eight characteristic time lengths representing different depths. The objective of this work was to assess the overall quality of the SWI data. Furthermore we tested the assumptions of the used water balance model and checked if ancillary information about topography, water fraction and noise information are useful for identifying observations of questionable quality. SWI data from January 1st 2007 until the end of 2011 was compared to in situ soil moisture data from 664 stations belonging to 23 observation networks which are available through the International Soil Moisture Network (ISMN). These stations delivered 2081 time series at different depths which were compared to the SWI values. The average of the significant Pearson correlation coefficients was 0.54 while being greater than 0.5 for 64.4% of all time series. It was found that the characteristic time length showing the highest correlation increases with in situ observation depth, thus confirming the SWI model assumptions. Relationships of the correlation coefficients with topographic complexity, water fraction, in situ observation depth, and soil moisture noise were found.

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

    NASA Astrophysics Data System (ADS)

    Cisty, Milan; Suchar, Martin; Bajtek, Zbynek

    2010-05-01

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

  18. 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

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  11. A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

    NASA Astrophysics Data System (ADS)

    Tuttle, S. E.; Salvucci, G.

    2012-12-01

    Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil

  12. 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.

  13. The influence of soil moisture deficits on Australian heatwaves

    NASA Astrophysics Data System (ADS)

    Herold, N.; Kala, J.; Alexander, L. V.

    2016-06-01

    Several regions of Australia are projected to experience an increase in the frequency, intensity and duration of heatwaves (HWs) under future climate change. The large-scale dynamics of HWs are well understood, however, the influence of soil moisture deficits—due for example to drought—remains largely unexplored in the region. Using the standardised precipitation evapotranspiration index, we show that the statistical responses of HW intensity and frequency to soil moisture deficits at the peak of the summer season are asymmetric and occur mostly in the lower and upper tails of the probability distribution, respectively. For aspects of HWs related to intensity, substantially greater increases are experienced at the 10th percentile when antecedent soil moisture is low (mild HWs get hotter). Conversely, HW aspects related to longevity increase much more strongly at the 90th percentile in response to low antecedent soil moisture (long HWs get longer). A corollary to this is that in the eastern and northern parts of the country where HW-soil moisture coupling is evident, high antecedent soil moisture effectively ensures few HW days and low HW temperatures, while low antecedent soil moisture ensures high HW temperatures but not necessarily more HW days.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Response of grassland ecosystems to prolonged soil moisture deficit

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture is commonly used for predictions of plant response and productivity. Climate change is predicted to cause an increase in the frequency and duration of droughts over the next century, which will result in prolonged periods of below-normal soil moisture. This, in turn, is expected to impact regional plant production, erosion and air quality. In fact, the number of consecutive months of soil moisture content below the drought-period mean has recently been linked to regional tree and shrub mortality in the southwest United States. This study investigated the effects of extended periods of below average soil moisture on the response of grassland ANPP to precipitation. Grassland ecosystems were selected for this study because of their ecological sensitivity to precipitation patterns. It has been postulated that the quick ecological response of grasslands to droughts can provide insight to large scale functional responses of regions to predicted climate change. The study sites included 21 grassland biomes throughout arid-to-humid climates in the United States with continuous surface soil moisture records for 2-13 years during the drought period from 2000-2013. Annual net primary production (ANPP) was estimated from the 13-year record of NASA MODIS Enhanced Vegetation Index extracted for each site. Prolonged soil moisture deficit was defined as a period of at least 10 consecutive months during which soil moisture was below the drought-period mean. ANPP was monitored before, during and after prolonged soil moisture deficit to quantify shifts in the functional response of grasslands to precipitation, and in some cases, new species assemblages that included invasive species. Preliminary results indicated that when altered climatic conditions on grasslands led to an increase in the duration of soil water deficit, then the precipitation-to-ANPP relation became non-linear. Non-linearity was associated with extreme grassland dieback and changes in the historic

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and

  20. 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

  1. A synergisitic Neural Network Soil Moisture Retrieval Algorithm for SMAP

    NASA Astrophysics Data System (ADS)

    Kolassa, J.; Reichle, R. H.; Gentine, P.; Prigent, C.; Aires, F.; Fang, B.

    2015-12-01

    A Neural Network (NN)-based algorithm is developed to retrieve surface soil moisture from Soil Moisture Active/Passive (SMAP) microwave observations. This statistical approach serves as an alternative to the official Radiative Transfer (RT) based SMAP retrieval algorithm, since it avoids an explicit formulation of the RT processes as well as the use of often uncertain or unavailable a priori knowledge for additional surface parameters. The NN algorithm is calibrated on observations from the SMAP radiometer and radar as well as surface soil moisture fields from the MERRA-2 reanalysis. To highlight different physical aspects of the satellite signals and to maximize the soil moisture information, different preprocessing techniques of the SMAP data are investigated. These include an analysis of radiometer polarization and diurnal indices to isolate the surface temperature contribution, as well as the radar co- and cross-polarized channels to account for vegetation effects. A major difference with respect to the official retrieval is the increased importance given to the information provided by the SMAP radar or other active sensors, utilizing not only the relative spatial structures, but also the absolute soil moisture information provided. The NN methodology combines multiple sensor observations in a data fusion approach and is thus able to fully exploit the complementarity of the information provided by the different instruments. The algorithm is used to compute global estimates of surface soil moisture and evaluated against retrieved soil moisture from SMOS as well as in situ observations from the International Soil Moisture Network (ISMN). The calibration on MERRA-2 data means that the NN retrieval algorithm functions as the model operator in a data assimilation framework yielding soil moisture estimates that are very compatible with the model. This could facilitate the assimilation of SMAP observations into land surface and numerical weather prediction models.

  2. 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.

  3. Soil moisture storage and hillslope stability

    NASA Astrophysics Data System (ADS)

    Talebi, A.; Uijlenhoet, R.; Troch, P. A.

    2007-09-01

    Recently, we presented a steady-state analytical hillslope stability model to study rain-induced shallow landslides. This model is based on kinematic wave dynamics of saturated subsurface storage and the infinite slope stability assumption. Here we apply the model to investigate the effect of neglecting the unsaturated storage on the assessment of slope stability in the steady-state hydrology. For that purpose we extend the hydrological model to compute the soil pore pressure distribution over the entire flow domain. We also apply this model for hillslopes with non-constant soil depth to compare the stability of different hillslopes and to find the critical slip surface in hillslopes with different geometric characteristics. In order to do this, we incorporate more complex approaches to compute slope stability (Janbu's non-circular method and Bishop's simplified method) in the steady-state analytical hillslope stability model. We compare the safety factor (FS) derived from the infinite slope stability method and the more complex approach for two cases: with and without the soil moisture profile in the unsaturated zone. We apply this extended hillslope stability model to nine characteristic hillslope types with three different profile curvatures (concave, straight, convex) and three different plan shapes (convergent, parallel, divergent). Overall, we find that unsaturated zone storage does not play a critical role in determining the factor of safety for shallow and deep landslides. As a result, the effect of the unsaturated zone storage on slope stability can be neglected in the steady-state hydrology and one can assume the same bulk specific weight below and above the water table. We find that steep slopes with concave profile and convergent plan shape have the least stability. We also demonstrate that in hillslopes with non-constant soil depth (possible deep landslides), the ones with convex profiles and convergent plan shapes have slip surfaces with the minimum

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

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2014-05-01

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

  5. Mapping of soil moisture at the field scale using full-waveform inversion of proximal ground penetrating radar data

    NASA Astrophysics Data System (ADS)

    Minet, Julien; Lambot, Sébastien; Vanclooster, Marnik

    2010-05-01

    Characterizing the spatial and temporal variability of soil moisture using geophysical methods is an important issue in many hydrological researches and applications. In order to bridge the scale gap between large-scale remote sensing of soil moisture and small-scale invasive methods, we developed a proximal ground penetrating radar (GPR) technique based on vector network analyzer technology and an off-ground antenna. Soil dielectrical properties are retrieved by resorting to full-waveform inversion of the GPR signal and soil moisture is derived from the dielectric permittivity using petrophysical relationships. The method is particularly suited for high-resolution mapping of soil moisture at the field scale and was widely applied for that purpose. In addition, the full-waveform inversion of the GPR signal on a large frequency bandwidth allows for the characterization of soil moisture at different depths, as it inherently maximizes the extraction of information. Hence, inversions of GPR data from field acquisition with different soil models permit to reconstruct two-layered or continuously-variable profiles, at locations where soil moisture profiles conditions are encountered. We conducted field campaigns in agricultural fields in the loess belt area in Belgium using the GPR system mounted on a 4-wheel motorcycle, allowing for real-time acquisition of the GPR signals. Inversions of the GPR signals for the retrieval of surface, two-layered and continuous profiles of soil moisture were subsequently performed. Surface soil moisture maps were in good agreement with field observations and surface volumetric sampling measurements. At the field scale, patterns were mainly explained by the topography, i.e., soil moisture values were positively correlated with the topographic wetness index. Furthermore, the total variance of soil moisture within the fields appeared to be related to the mean soil moisture itself. Finally, two-layered and continuous profile inversions showed

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

    NASA Astrophysics Data System (ADS)

    Ryu, D.; Akuraju, V.

    2013-12-01

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

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Soil moisture change linking contrasting atmosphere-landscape scales and hydro-climatic changes

    NASA Astrophysics Data System (ADS)

    Destouni, Georgia; Verrot, Lucile

    2014-05-01

    Soil moisture plays a central role for land-climate interactions in the climate system. Soil moisture is also a key landscape component for hydrological and biogeochemical cycling, waterborne solute/pollutant transport, and vegetation, ecosystem and agricultural conditions. The soil moisture definition as a ratio of water volume to bulk soil volume (water content) and/or of water volume to pore volume (degree of saturation) applies across different spatial scales - from centimetres to kilometres - depending on the question of interest and the measurement method used to answer it. This paper presents a quantification framework that links large-scale hydro-climatic conditions at the surface with typically locally accounted for soil and groundwater conditions in the subsurface. The framework enables evaluation and screening of variability and change in long-term soil moisture statistics. Such statistics are here assessed for observed hydro-climatic records extending over the whole 20th century and for different soils in a major Swedish hydrological drainage basin. Frequencies of particularly dry and wet soil moisture events are investigated for different climatic periods within this century. Results show large increase in the frequency of dry events from the beginning to the end of the century, even though precipitation has increased over this time. The increase in dry event frequency implies increased risk for hydrological drought, agricultural drought and groundwater drought under decreasing meteorological drought risk. The risk increase for other types of drought than the meteorological is here caused by increased evapotranspiration along with increased temporal variability in runoff driven by historic agricultural expansion and intensification, rather than by atmospheric climate change. Synthesized hydro-climatic data across different scales and parts of the world shows similar emerging patterns of landscape-driven rather than atmosphere-driven hydro

  12. 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

  13. 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

  14. 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

  15. 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.

  16. Field Observations of Soil Moisture Variability across Scales

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  17. Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

    NASA Technical Reports Server (NTRS)

    Lin, D. S.; Wood, E. F.; Famiglietti, J. S.; Mancini, M.

    1994-01-01

    Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

  18. 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.

  19. Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    This study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large-scale, high-resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into Hydrus-1D to estimate soil moisture as well as soil thermal and hydraulic properties. However, this approach was limited to bare soil and assumed that the cable depths were perfectly known. In order for Passive DTS to be more broadly applicable as a soil hydrology research and remote sensing soil moisture product validation tool, it must be applicable in vegetated areas. To address this first limitation, the forward model (Hydrus-1D) was improved through the inclusion of a canopy energy balance scheme. Synthetic tests were used to demonstrate that without the canopy energy balance scheme, the PBS estimated soil moisture could be even worse than the open loop case (no assimilation). When the improved Hydrus-1D model was used as the forward model in the PBS, vegetation impacts on the soil heat and water transfer were well accounted for. This led to accurate and robust estimates of soil moisture and soil properties. The second limitation is that, cable depths can be highly uncertain in DTS installations. As Passive DTS uses the downward propagation of heat to extract moisture-related variations in thermal properties, accurate estimates of cable depths are essential. Here synthetic tests were used to demonstrate that observation depths can be jointly estimated with other model states and parameters. The state and parameter results were only slightly poorer than those obtained when the cable depths were perfectly known. Finally, in situ temperature data from four soil profiles with different, but known, soil textures were used to test the proposed approach. Results show good agreement between the observed and estimated soil moisture, hydraulic properties, thermal properties, and

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. 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...

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Determining soil moisture from geosynchronous satellite infrared data - A feasibility study

    NASA Technical Reports Server (NTRS)

    Wetzel, P. J.; Atlas, D.; Woodward, R. H.

    1984-01-01

    Numerical modelling results are reported from a pilot study investigating the feasibility of developing a technique for daily soil moisture measurement throughout the world, based on GOES infrared data. A detailed one-dimensional boundary layer-surface-soil model was used in order to determine which physical parameters observable from GOES are most sensitive to soil moisture, and which are most effected by seasonal changes, atmospheric effects and vegetation cover. The results of the sensitivity test show that the mid-morning differential of surface temperature with respect to absorbed solar radiation is optimally sensitive to soil moisture. A case study comparing model results with GOES infrared data confirms the sensitivity of this parameter to soil moisture and also confirms the applicability of the model to predicting area-averaged surface temperature changes. Model measurements of soil moisture are expected to be most accurate for dry or marginal agricultural areas where drought is common. Sources of error, including the advection of clouds, are examined and methods of minimizing error are discussed.

  5. 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.

  6. 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

  7. 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.

  8. Evaluating Soil Moisture Status Using an e-Nose.

    PubMed

    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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  10. 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.

  11. Iterative method of finding hydraulic conductivity characteristics of soil moisture

    NASA Astrophysics Data System (ADS)

    Rysbaiuly, Bolatbek; Adamov, Abilmazhin

    2016-08-01

    The work considers an initial boundary value problem for a nonlinear equation of hydraulic conductivity. A method of finding a nonlinear diffusion coefficient is developed and hydraulic conductivity of soil moisture is found. Numerical calculations are conducted.

  12. 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.

  13. 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

  14. 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.

  15. Improved soil moisture balance methodology for recharge estimation

    NASA Astrophysics Data System (ADS)

    Rushton, K. R.; Eilers, V. H. M.; Carter, R. C.

    2006-03-01

    Estimation of recharge in a variety of climatic conditions is possible using a daily soil moisture balance based on a single soil store. Both transpiration from crops and evaporation from bare soil are included in the conceptual and computational models. The actual evapotranspiration is less than the potential value when the soil is under stress; the stress factor is estimated in terms of the readily and total available water, parameters which depend on soil properties and the effective depth of the roots. Runoff is estimated as a function of the daily rainfall intensity and the current soil moisture deficit. A new concept, near surface soil storage, is introduced to account for continuing evapotranspiration on days following heavy rainfall even though a large soil moisture deficit exists. Algorithms for the computational model are provided. The data required for the soil moisture balance calculations are widely available or they can be deduced from published data. This methodology for recharge estimation using a soil moisture balance is applied to two contrasting case studies. The first case study refers to a rainfed crop in semi-arid northeast Nigeria; recharge occurs during the period of main crop growth. For the second case study in England, a location is selected where the long-term average rainfall and potential evapotranspiration are of similar magnitudes. For each case study, detailed information is presented about the selection of soil, crop and other parameters. The plausibility of the model outputs is examined using a variety of independent information and data. Uncertainties and variations in parameter values are explored using sensitivity analyses. These two case studies indicate that the improved single-store soil moisture balance model is a reliable approach for potential recharge estimation in a wide variety of situations.

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

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Holmes, Thomas

    2015-04-01

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

  17. Volatilization of EPTC as affected by soil moisture

    NASA Astrophysics Data System (ADS)

    Fu, Liqun

    Volatilization is an important process that controls the dissipation of pesticides after field application. Soil moisture plays an important role in controlling the volatilization of pesticides. However, the extent of this role is unclear. This study was conducted to determine how soil moisture affects the sorption capacity and vapor loss of EPTC (S-ethyl dipropyl carbamothioate) from two soils, Weswood clay loam (fine- silty, mixed, thermic fluventic ustochrepts) and Padina loamy sand (loamy, siliceous, thermic grossarenic paleustalfs). Soil samples with different moisture contents were exposed to saturated EPTC vapor for 1, 2, 5, or 12 days and sorbed concentrations were measured. Sorption capacity of Weswood after 12 days exposure was about 12 times higher with air-dry soil than at the wilting point (-1500 kPa). For Padina, after 12 days exposure, the sorption capacity was about 18 times higher at air- dry than at -1500 kPa. The maximum sorption extrapolated from the partitioning coefficients determined with an equilibrium batch system and Henry's law were similar to the sorption capacities when moisture content was close to the wilting point for both soils. Desorption of EPTC vapor from soils with different moistures was determined by a purge and trap method. EPTC vapor losses strongly depended on the soil moisture and/or the humidity of the air. If the air was dry, volatilization of EPTC was much larger when the soil was wet. If humidity of the air was high, the effect of soil moisture on volatilization was not as great. No significant correlation at a confidence level of 95% was found between water and EPTC vapor losses for either soil when water saturated air was used as a purge gas. When purged with dry air, losses of water and EPTC vapor were strongly correlated at a confidence level of 99%. This study indicates that decreasing soil moisture significantly increases EPTC sorption and decreases volatilization. Simulation of volatilization with a one

  18. Physical controls of soil moisture variability at multiple scales

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Mohanty, B.

    2013-12-01

    Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. Soil moisture, and, by association, soil hydraulic parameters have been known to be a function of location, and the support scale at which they are measured. Recent increase in remote sensing platforms necessitates increased calibration/validation efforts of their soil moisture products with ground-based measurements. Such cal/val operations require some form of up- or down-scaling process. Understanding the factors that drive soil hydrological processes at different scales, and their variability, is very critical to minimize errors due to this step in the cal/val procedure. Existing literature provides a description of the different sources of soil moisture variability across a range of resolutions from point to continental scales, classified under four categories: soil texture and structure, topography, vegetation, and meteorological forcings. While it is accepted that a dynamic relationship exists between these physical controls and the soil hydraulic properties across spatial scales, the nature of the relationship is not very well understood. In order to formulate better scaling algorithms, it is first necessary to determine the form and amount of influence exerted by the controlling factors on the variability of the soil moisture or hydraulic parameters at each scale of interest. One method to understand the effect of the physical controls is to analyze the covariance or coherence of the physical controls with the soil hydraulic properties across multiple scales and different hydro-climates. Such a study, using wavelet analysis, is presented here. A variety of datasets from multiple platforms across the globe were employed in this study. The AMSR-E soil moisture product was used as the remotely sensed, coarse resolution dataset. Fine resolution

  19. 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.

  20. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    PubMed

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

    2015-07-21

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  2. Improving runoff prediction through the assimilation of the ASCAT soil moisture product

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

    The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale) with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates has to be carefully checked. The validation of these estimates with in-situ measurements is not straightforward due the well-known problems related to the spatial mismatch and the measurement accuracy. The analysis of the effects deriving from assimilating remotely sensed soil moisture data into hydrological or meteorological models could represent a more valuable method to test their reliability. In particular, the assimilation of satellite-derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue. In this study, the soil wetness index (SWI) product derived from the Advanced SCATterometer (ASCAT) sensor onboard of the Metop satellite was tested. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc) to assess its relationship with modeled data. Then, by using a simple data assimilation technique, the linearly rescaled SWI that matches the range of variability of modelled data (denoted as SWI*) was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place. The most significant flood events, which occurred in the period 2000-2009 on five subcatchments of the Upper Tiber River in central Italy, ranging in extension between 100 and 650 km2, were used as case studies

  3. Improving runoff prediction through the assimilation of the ASCAT soil moisture product

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

    The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale) with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates has to be carefully checked. The validation of these estimates with in-situ measurements is not straightforward due the well-known problems related to the spatial mismatch and the measurement accuracy. The analysis of the effects deriving from assimilating remotely sensed soil moisture data into hydrological or meteorological models could represent a more valuable method to test their reliability. In particular, the assimilation of satellite-derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue. In this study, the soil wetness index (SWI) product derived from the Advanced SCATterometer (ASCAT) sensor onboard of the Metop satellite was tested. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc) to assess its relationship with modeled data. Then, by using a simple data assimilation technique, the linearly rescaled SWI that matches the range of variability of modelled data (denoted as SWI*) was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place. The most significant flood events, which occurred in the period 2000-2009 on five subcatchments of the Upper Tiber River in Central Italy, ranging in extension between 100 and 650 km2, were used as case studies

  4. 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

  5. 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.

  6. 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

  7. Soil Moisture Characterization for Biogenic Emissions Modeling in Texas

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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. 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

  13. Assessment of soil moisture dynamics on an irrigated maize field using cosmic ray neutron sensing

    NASA Astrophysics Data System (ADS)

    Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E.

    2015-04-01

    In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate soil moisture at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is affected by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting soil moisture. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three soil sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different soil sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and soil organic carbon, thus representing an equivalent water content of the soil, the differences decreased. Soil moisture estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the soil moisture determined with point scale measurements but they are less affected by the heterogeneous moisture conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a

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

    SciTech Connect

    Robock, A.; Vinnikov, K.Ya.; Schlosser, C.A.; Xue, Y.; Speranskaya, N.A.

    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 are compared to observations of soil moisture, literally {open_quotes}ground truth,{close_quotes} 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. 34 refs., 19 figs., 3 tabs.

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

    PubMed

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

    2013-01-01

    The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass. PMID:23579833

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

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

  18. [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. PMID:21847933

  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. 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.

  1. Aircraft scatterometer observations of soil moisture on rangeland watersheds

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  3. 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 ...

  4. 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

  5. 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.

  6. 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.

  7. Advances in downscaling soil moisture for use in drought and flood assessments: Implications for data from the Soil Moisture Active and Passive (SMAP) Mission

    NASA Astrophysics Data System (ADS)

    Lakshmi, V.; Fang, B.; Narayan, U.

    2015-12-01

    Hydrological hazards, namely droughts and floods are dependent on the deficit and excess of soil moisture. With the launch of the Soil Moisture Active and Passive Mission (SMAP) in January 2015 we will have twice a day global observations of soil moisture. However the spatial resolution of soil moisture retrieved from the SMAP radiometer is 10s of km and the SMAP radar will provide backscatter observations 100m-1km. High spatial resolution of soil moisture helps to monitor floods and droughts in a spatially distributed fashion. The current focus is finding the best way to obtain high spatial resolution soil moisture using the radar and radiometer observations. In this presentation we will deal with downscaling by couple of methods - (a) Use of the thermal inertia relation between soil moisture and surface temperature modulated by vegetation (b) Relationship between soil moisture and evaporation (c) Change detection using high spatial resolution active radar data.

  8. 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

  9. Evaluation of SMOS L2 soil moisture data over the Eastern Poland using ground measurements

    NASA Astrophysics Data System (ADS)

    Usowicz, Jerzy; Łukowski, Mateusz; Słomiński, Jan; Stankiewicz, Krystyna; Usowicz, Bogusław; Lipiec, Jerzy; Marczewski, Wojciech

    2013-04-01

    Validation of SMOS products is vital for their further use in the study of climate and hydrology. Several authors [1,2] have recently evaluated SMOS soil moisture data with an aid of in-situ observations of soil moisture. Collow and Robock have reported a dry bias as compared to in situ observations. Since their results are not much conclusive, they call for further studies using more data. Bircher and co-authors have also noted significant discrepancies between Danish network and SMOS soil moisture. SWEX_POLAND soil moisture network consists of 9 stations located in Eastern Poland. These stations are located on the areas representing variety types of land use: meadows, cultivated fields, wetlands and forests. We have expanded our analysis, as presented in the EGU 2012, using data from all network stations. Similarly as before, we have used three methods in our comparison studies: the Bland-Altman method, concordance correlation coefficient and total deviation index. Using these methods we have confirmed a fair/moderate agreement of SMOS L2 SM data and network observations. Like the other authors we have also noted the significant biases in SMOS soil moisture. However, the general trends in dynamics of soil moisture revealed by SMOS, the SWEX_POLAND network and referred to GLDAS, are in a considerable relevancy. We have shown that the SMOS satellite measurements are reliable, so can be used to detect areas of dry and moist soil. In Poland the trends indicating the growth of agricultural droughts are depicted by SMOS L2 very well, even better than national drought services for the agriculture. It is worth to note that the year 2011 was more variable and drier than the 2010 for Poland. Moreover, SMOS data prove the well-known property of central Poland to be drier than the rest of the country. It is expected that further mitigation of RFI contamination in Poland will be available due to the cooperation of ESA SMOS to the national spectrum control services (UKE

  10. Bulk Density and Soil Moisture Sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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 – ...

  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. A High-Temporal and Spatial Resolution Soil Moisture and Soil Temperature Network In Iowa Using Wireless Links

    NASA Astrophysics Data System (ADS)

    Niemeier, J. J.; Kruger, A.; Krajewki, W. F.; Eichinger, W. E.; Hornbuckle, B. K.; Cunha, L.

    2007-12-01

    Over the past year we have created an in-situ soil moisture and soil temperature network in a 200 acre agricultural plot at Ames, Iowa. This work is part of a collaborative effort between researchers at The University of Iowa, and Iowa State University. The purpose of the network is to provide high temporal and spatial resolution soil moisture and soil temperature data to validate remotely-sensed observations of the terrestrial water cycle. This is part of a larger effort by the authors and collaborators to improve the quantitative value of remotely-sensed observations of the water cycle. In addition to the soil moisture and soil temperature measurements, detailed precipitation data, and atmospheric data such as air temperature, humidity, pressure, wind direction and velocity, and solar radiation data are collected. The current soil moisture network consists of 10 Iowa and Iowa State stations, each equipped with seven pairs of soil moisture and soil temperature sensors. In the future, the network will be expanded to 15 stations. At each of the 10 station the sensors pairs are deployed at depths of 1.5, 4.5, 15, 30, and 60 cm to provide a vertical profile of soil moisture and soil temperature. Prior to installation we calibrated the soil temperature sensors to within 0.1 degree Celsius. The time-domain reflectometry soil moisture measurements are adjusted for local soil conditions. At each of the 10 stations, data are collected every 10 minutes. The data are transmitted wirelessly with low power radio links to a central location. The system started collecting data at the beginning of July, 2007. One of the challenges we faced is how to provide reliable solar power to the wireless nodes, since the current crop, corn, grows up to 3 m tall, and casts dense shadows. The corn also significantly attenuates the radios signals, and the radios fell far short of their advertized ranges. Consequently, we had to use high-gain antennas, and robust retransmit communication modes

  14. Future Soil Moisture Satellite Missions and Research Needs

    NASA Astrophysics Data System (ADS)

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

    2001-12-01

    During the coming decade, launches of a number of satellite microwave sensors will provide new and unique opportunities for acquiring global information on the amount and distribution of surface soil moisture and its frozen/thawed state. This new information will provide potentially significant enhancements to the predictive capabilities of numerical weather and climate models as well as improved capabilities for monitoring and predicting floods, droughts, and other natural hazards. The development focus has been on L-band (1.4 GHz) passive microwave sensors (radiometers) as the basis for new satellite mission concepts since these instruments are uniquely suited to acquiring soil moisture information over a wide range of vegetation and heterogeneous terrain, and under nearly all weather conditions. Active microwave sensors (radars) can provide higher spatial resolution measurements and, in combination with passive sensors, enhanced information on surface moisture and its freeze/thaw condition. The soil moisture and surface freeze/thaw state together control the `surface resistance' to water and energy exchanges at the surface. Among the new soil moisture mission concepts under consideration for launch in ~2005 or later are the Soil Moisture and Ocean Salinity (SMOS) and Hydrosphere States (HYDROS) missions, and higher-resolution follow-on missions. These missions use different but complementary technological approaches to surface soil moisture sensing. In the nearer term, launches of the Advanced Scanning Microwave Radiometers (AMSRs) on the NASA EOS-Aqua and National Space Development Agency of Japan ADEOS-II satellites in 2002, and similar instruments to be launched in subsequent years as part of Department of Defense and National Polar-orbiting Operational Environmental Satellite System (NPOESS) programs, will provide new C-band (~6.9 GHz) data that will be useful for soil moisture monitoring under more limited vegetation and environmental conditions. There are

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Yan, B.; Dickinson, R. E.

    2012-12-01

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

  17. 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

    2016-01-01

    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

  18. 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.

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  1. Using data assimilation techniques to calibrate soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  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. ?? 2006 Institute of Botany, Chinese Academy of

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  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. 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

  7. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The contributions of precipitation and soil moisture observations to soil moisture skill in a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derive...

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Estimation of soil moisture using radar and optical images over Grassland areas

    NASA Astrophysics Data System (ADS)

    EL HAJJ, Mohammad; Baghdadi, Nicolas; Zribi, Mehrez; Bellaud, Gilles; Cheviron, Bruno; Courault, Dominique; Hagolle, Olivier; Charron, François

    2015-04-01

    The purpose of this study was to develop an inversion approach to estimate soil moisture over Grassland areas by coupling SAR and optical data. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT 4/5, LANDSAT 7/8) images were acquired over an agriculture region in southeastern France. In most cases, the optical and radar images were not separated by more than four days. Ground-truth measurements of volumetric soil moisture and vegetation descriptors were performed simultaneously with image acquisitions. In this study, the semi-empirical water-cloud model (WCM) was used to model the total backscattering coefficient in HH and HV polarizations as a function of soil moisture and vegetation descriptor. WCM was fitted against in situ measurements to estimates WCM parameters according to each vegetation descriptor and each radar polarization (HH and HV). The parameterized water cloud model was then used to generate one synthetic dataset using wide range of soil moisture and NDVI values. Next, a noise was applied to both simulated radar responses and NDVI. An inversion technique based on Multi-Layer Perceptron (MLP) neural networks (NN) were used to invert the radar signal in order to estimate the soil moisture. Three inversion configurations were defined using in addition to one vegetation descriptor: (1) HH polarization, (2) HV polarization, and (3) both HH and HV polarizations. The neural networks were trained and validated on the noisy synthetic dataset. Next, the inversion approach was then conducted on real dataset comprised observed SAR data, soil moisture and NDVI. The best soil moisture estimates were obtained with the use of HH (in addition to one vegetation descriptor). For NDVI (Normalized Difference vegetation index) lower than about 0.8 the RMSE (Root Mean Square Error) between measured and estimated soil moisture is about 0.05 cm3/cm3. However, for NDVI greater than about 0.8 the RMSE on estimated soil moisture is about 0.08 cm3/cm3.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  15. Soil moisture and electrical conductivity prediction and their implication for landmine detection technologies

    NASA Astrophysics Data System (ADS)

    Katsube, T. John; Keating, Pierre K.; McNairn, Heather; Das, Yogadhish; DiLabio, Ron; Singhroy, Vern; Connell-Madore, Shauna; Best, Mel E.; Hunter, James; Klassen, Rod; Dyke, Larry

    2004-09-01

    Physical properties, such as soil moisture, magnetic susceptibility and electrical conductivity (EC) are sources of signal interference for many landmine detectors. Soil EC mechanisms and their relationship to moisture are being studied to increase the soil EC prediction accuracy by radar remote sensing, airborne and ground electromagnetic (EM) methods. This is required for effective detection operations in problematic regions of the world. Results indicate that responses of free water and bound water to drying rates and EC are very different, to the extent that moist clay-poor soil may have lower EC compared to dryer clay-rich soil at certain moisture contents. These suggest that soil EC prediction should start with analyses of radar remote sensing data acquired on separate days, followed by high frequency airborne EM surveys, and validation by ground EM surveys and laboratory soil sample analyses. Due to the various expertise required, a team of relevant experts (e.g., geology, geophysics, remote sensing, petrophysics, agriculture, soil physics, electrical engineering and demining) should be organized to provide information on detector viability for demining in problematic areas in the world. It is also proposed to develop wide frequency band EM systems to provide much of the required information in one measurement.

  16. Satellite microwave observations of soil moisture variations. [by the microwave radiometer on the Nimbus 5 satellite

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Rango, A.; Neff, R.

    1975-01-01

    The electrically scanning microwave radiometer (ESMR) on the Nimbus 5 satellite was used to observe microwave emissions from vegetated and soil surfaces over an Illinois-Indiana study area, the Mississippi Valley, and the Great Salt Lake Desert in Utah. Analysis of microwave brightness temperatures (T sub B) and antecedent rainfall over these areas provided a way to monitor variations of near-surface soil moisture. Because vegetation absorbs microwave emission from the soil at the 1.55 cm wavelength of ESMR, relative soil moisture measurements can only be obtained over bare or sparsely vegetated soil. In general T sub B increased during rainfree periods as evaporation of water and drying of the surface soil occurs, and drops in T sub B are experienced after significant rainfall events wet the soil. Microwave observations from space are limited to coarse resolutions (10-25 km), but it may be possible in regions with sparse vegetation cover to estimate soil moisture conditions on a watershed or agricultural district basis, particularly since daily observations can be obtained.

  17. Soil Organic Matter in Agricultural Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In agricultural systems, soil organic matter (SOM) has been recognized as an important source of nutrients and maintains favorable soil structure. Organic matter is considered a major binding agent that stabilizes soil aggregates. Soil aggregates especially, water stable aggregates, are important i...

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Soil Moisture Active/Passive (SMAP) Mission is one of the first satellites being developed by NASA in response to the National Research Council's Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow better estimates of water and energy transfers between Earth's surface and atmosphere, which are primary driving factors for weather and climate. Soil moisture measurements are also of great importance in assessing flooding potential and as input to flood prediction models. Conversely, observations of widespread low soil moisture levels can provide early warning of drought conditions, reduced water supply and crop loss. SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP freeze/thaw timing observations will also reduce a major uncertainty in quantifying the global carbon balance and will help resolve the problem of the missing carbon sink. The SMAP mission concept would utilize L-band radar and radiometry. These instruments will share a rotating 6-meter mesh antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. Soil moisture products at 3, 10 and 40 km resolutions will be derived. These will both complement and extend the records of the ESA SMOS mission and offer an order of magnitude improvement in spatial resolution. SMAP is currently in Phase A and scheduled for a 2013 launch. The science teams will be focusing on algorithm development and validation over the next few years. These efforts will be described.

  19. 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

  20. 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

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

    NASA Astrophysics Data System (ADS)

    Schimel, J.

    2013-12-01

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

  2. 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.

  3. 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.

  4. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  7. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and

  9. 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

  10. Global High Resolution Mapping and Assimilation of Soil Moisture Observations from the SMAP Radar and Radiometer

    NASA Astrophysics Data System (ADS)

    Reichle, Rolf; Crow, Wade; Entekhabi, Dara; Kimball, John; Koster, Randal; Noku, Eni; O'Neill, Peggy

    2010-05-01

    The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2015. 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, SMAP high-resolution soil moisture mapping has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we provide a brief overview of the SMAP science objectives, instruments, and data products, with a special focus on the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a wide swath (1000 km) using conical scanning at a constant incidence angle (40°). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar, however, is very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows blending the advantages of each instrument, enabling SMAP to provide global retrievals of surface soil moisture with a horizontal resolution of about 10 km and a refresh rate of 2 to 3 days. Additionally, a radar-based soil-vegetation freeze/thaw product in boreal latitudes will be provided at 3 km resolution with 1-2 day revisit. SMAP directly observes surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (~top 1 m of the soil column), which is not directly measured

  11. Geostatistical and Fractal Characteristics of Soil Moisture Patterns from Plot to Catchment Scale Datasets

    NASA Astrophysics Data System (ADS)

    Korres, Wolfgang; Reichenau, Tim G.; Fiener, Peter; Koyama, Christian N.; Bogena, Heye R.; Cornelissen, Thomas; Baatz, Roland; Herbst, Michael; Diekkrüger, Bernd; Vereecken, Harry; Schneider, Karl

    2016-04-01

    Soil moisture and its spatio-temporal pattern is a key variable in hydrology, meteorology and agriculture. The aim of the current study is to analyze spatio-temporal soil moisture patterns of 9 datasets from the Rur catchment (Western Germany) with a total area of 2364 km², consisting of a low mountain range (forest and grassland) and a loess plain dominated by arable land. Data was acquired across a variety of land use types, on different spatial scales (plot to mesoscale catchment) and with different methods (field measurements, remote sensing, and modelling). All datasets were analyzed using the same methodology. In a geostatistical analysis sill and range of the theoretical variogram were inferred. Based on this analysis, three groups of datasets with similar characteristics in the autocorrelation structure were identified: (i) modelled and measured datasets from a forest sub-catchment (influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the total catchment (influenced by the land-use structure of the cropped area), and (iii) modelled datasets from the cropped part of the Rur catchment (influenced by large scale variability of soil properties). A fractal analysis revealed that soil moisture patterns of all datasets show a multi-fractal behavior (varying fractal dimensions, patterns are only self-similar over certain ranges of scales), with at least one scale break and generally high fractal dimensions (high spatial variability). Corresponding scale breaks were found in various datasets and the factors explaining these scale breaks are consistent with the findings of the geostatistical analysis. The joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at maximum porosity and wilting point in the soils, can have a large influence on the soil moisture patterns and their autocorrelation structure.

  12. The Soil Moisture Active and Passive (SMAP) Mission: Improving Science Application Tools and Research

    NASA Astrophysics Data System (ADS)

    Escobar, V. M.; Brown, M. E.; Moran, S. M.

    2011-12-01

    NASA depends on the science community to identify and prioritize leading-edge scientific questions and the observations required to answer them. The Soil Moisture Active and Passive (SMAP) Mission has been identified as a priority for NASA's Science Mission Directorate through the most recent decadal survey. Following launch in 2014, SMAP will deliver global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial hydrologic and carbon cycle applications. The SMAP observatory consists of two multipolarization L-band sensors, a radar and radiometer that share a deployable mesh reflector antenna. The combined observations from the two sensors will allow accurate estimation of soil moisture at spatial scales. The wide-swath (1000 km) measurements will allow global mapping of soil moisture and freeze/thaw state with a 2-3 day revisit frequency and 1-2 day revisit in boreal latitudes. The synergy of active and passive observations enables measurements of soil moisture and freeze/thaw state with unprecedented resolution, sensitivity, area coverage and revisit frequency. SMAP data are valuable for both scientific research and practical applications. SMAP has the potential to drive a diverse range of novel research in drought and flood guidance, agricultural productivity estimation, weather forecasting, climate prediction, human health risk analysis and defense systems. The accuracy, resolution, and global coverage of SMAP soil moisture and freeze/thaw measurements will provide new information for many science and applications disciplines. A SMAP Applications Team will explore ways to measure interaction and integration of SMAP data with the Emergency Management User community of Maryland in order to produce quantitative metrics related to long-term projects, milestone completion, and movement of SMAP products into routine operations for emergency response.

  13. 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.

  14. 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.

  15. 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

  16. Radar estimates of soil moisture over the Konza Prairie

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  17. 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).

  18. Soil temperature error propagation in passive microwave retrieval of soil moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the near future two dedicated soil moisture satellites will be launched (SMOS and SMAP), both carrying an L-band radiometer. It is well known that microwave soil moisture retrieval algorithms must account for the physical temperature of the emitting surface. Solutions to this include: difference ...

  19. 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].

  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. 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

  2. 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

  3. Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band

    NASA Astrophysics Data System (ADS)

    Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.

    2013-12-01

    In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three d