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Sample records for monitor soil moisture

  1. Soil Moisture Monitorization Using GNSS Reflected Signals

    CERN Document Server

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  4. Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring.

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    Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea

    2017-06-20

    This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil.

  5. Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring

    Directory of Open Access Journals (Sweden)

    Marco Leone

    2017-06-01

    Full Text Available This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil.

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

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    W. B. Anderson

    2012-04-01

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

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

    Directory of Open Access Journals (Sweden)

    W. B. Anderson

    2012-08-01

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

  8. Soil Moisture Monitoring using Surface Electrical Resistivity measurements

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

    2017-04-01

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

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

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

    2017-04-01

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

  10. NIR-red spectral space based new method for soil moisture monitoring

    Institute of Scientific and Technical Information of China (English)

    ZHAN ZhiMing; QIN QiMing; GHULAN Abduwasit; WANG DongDong

    2007-01-01

    Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is developed using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM+ data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0―20 cm soil depths, correlation coefficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions.

  11. NIR-red spectral space based new method for soil moisture monitoring

    Institute of Scientific and Technical Information of China (English)

    GHULAN; Abduwasit

    2007-01-01

    Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is de- veloped using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM+ data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0―20 cm soil depths, correlation coef- ficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions.

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

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    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

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

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    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. Soil Moisture Content Monitoring Based on ERS Wind Scatterometer Data

    Institute of Scientific and Technical Information of China (English)

    WANG Jian-ming; SHI Jian-cheng; SHAO Yun; LIU Wei

    2005-01-01

    The ERS-1/2 wind scatterometer (WSC) has a low resolution cell of about 50 km but provides a high repetition rate (<4 d) and can make measurements at multiple incidence angles. In order to estimate effective surface reflectivity (related to soil moisture content) over bare soil using WSC data, an original methodology based on the advance integral equation model (AIEM) is presented, which takes advantage of its multiple view angular characteristics. This method includes two steps. First, a simplified two-parameter surface scattering model is calibrated by AIEM simulated-database over a wide parameter space. Second, regression analyses are carried out using the simulated database to build the relation between those parameters of our model at different incident angles from two observations of Mid and Fore beams. From the model simulated database, our technique works quite well in estimating Γ0. The possibility of applying the model to retrieve soil moisture is investigated using a set of data collected from the Intensive Observation Period field campaign in 1998 of the Asian Monsoon Experiment Tibet (GAME-Tibet). The retrieved values obtained for the bare land surface are consistent with ground measurements collected in these areas and the correlation coefficient between retrieved soil moisture and the measured one reaches 0.65.

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

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    Liu, Qian; Zhao, Yingshi

    2015-08-01

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

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

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    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.

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

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

    2010-01-01

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

  18. Synergies of the European Microwave Remote Sensing Missions SMOS and ASCAT for Monitoring Soil Moisture

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    Scipal, K.; Wagner, W.

    2003-04-01

    The lack of global soil moisture observations is one of the most glaring and pressing deficiencies in current research activities of related fields, from climate monitoring and ecological applications to the quantification of biogeophysical fluxes. This has implications for important issues of the international political agenda like managing global water resources, securing food production and studying climate change. Currently it is held that only microwave remote sensing offers the potential to produce reliable global scale soil moisture information economically. Recognising the urgent need for a soil moisture mission several international initiatives are planning satellite missions dedicated to monitor the global hydrological cycle among them two European microwave satellites. ESA is planning to launch the Soil Moisture and Ocean Salinity Mission SMOS, in 2006. SMOS will measure soil moisture over land and ocean salinity over the oceans. The mission rests on a passive microwave sensor (radiometer) operated in L-band which is currently believed to hold the largest potential for soil moisture retrieval. One year before (2005) EUMETSAT will launch the Meteorological Operational satellite METOP which carries the active microwave system Advanced Scatterometer ASCAT on board. ASCAT has been designed to retrieve winds over the oceans but recent research has established its capability to retrieve soil moisture. Although currently it is hold that, using active microwave techniques, the effect of surface roughness dominates that of soil moisture (while the converse is true for radiometers), the ERS scatterometer was successfully used to derive global soil moisture information at a spatial resolution of 50 km with weekly to decadal temporal resolution. The quality of the soil moisture products have been assessed by independent experts in several pilot projects funded by the European Space Agency. There is evidence to believe that both missions will provide a flow of

  19. Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: comparison with data from a wireless soil moisture monitoring network

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    Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

    2016-04-01

    Electromagnetic induction (EMI) methods are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa) at various scales. Soil ECa is well known to be influenced by both the volumetric content and the electrical conductivity (EC) of soil water, as well as by soil temperature and by the volume of the solid particles and their EC. Among other applications, EMI has become widely used to determine soil water content or to study hydrological processes within the field of hydrogeophysics. Although the use of non-invasive EMI for imaging soil spatial properties is very attractive, the dependence of ECa on several properties and states challenges any interpretation with respect to individual soil properties or states such as θ. The major aim of this study was to further investigate the potential of repeated EMI measurements to map soil moisture at the hillslope scale, with particular focus on the temporal variability of the spatial patterns of ECa and soil moisture, respectively, and on the stability of the ECa-soil moisture relationship over time. To this end, we compared time series of EMI measurements with high-resolution soil moisture data for a non-intensively managed hillslope area in the Schäfertal catchment (Central Germany) for which the spatial distribution of soil properties and soil water dynamics were known in detail. Soil water and temperature dynamics were observed in 40 soil profiles at hourly resolution during 14 months using a wireless monitoring network. During this period of time, ECa was mapped on seven occasions using an EM38-DD device. For the investigated site, ECa showed small temporal variations (ranging between 0 and 24 mS/m) whereas the temporal range of soil moisture was very large (from very dry to soil saturation). Furthermore, temporal changes of the spatial pattern of ECa differed from temporal changes of the spatial pattern of soil moisture. The ECa-soil moisture

  20. The Use of Sentinel-1 for Monitoring of Soil Moisture within the Copernicus Global Land Service

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    Doubkova, M.; Wagner, W.; Naeimi, V.; Cao, S.; Bauer-Marschallinger, B.; Kidd, R.; Hasenauer, Stefan; Dostalova, A.; Paulik, Christopher

    2016-08-01

    Within the Copernicus Global Land Service (CGLS), a global Soil Water Index (SWI) product is available on an operational basis, derived from the Metop Advanced Scatterometer (ASCAT) with a spatial sampling of 0.1°. The SWI quantifies the moisture condition at various depths in the soil. To match the spatial resolution of the SWI data with the rest of the CGLS data products, the 1 km Sentinel-1 (S-1) surface soil moisture (SSM) product can be used. The S-1 SSM is retrieved by inverting a backscatter model trained using historic SAR observations. Here, the progress made in delivering the 1 km fused SWI as well as the 1 km S-1 SSM products at the Earth Observation Data Centre for Water Resources Monitoring (https://www.eodc.eu/) is reported. The first validation results of the 1 km fused SWI are satisfying demonstrating well the added fine- scale spatial soil moisture signal.

  1. An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network

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    George P. Petropoulos

    2017-06-01

    Full Text Available This paper describes a soil moisture dataset that has been collecting ground measurements of soil moisture, soil temperature and related parameters for west Wales, United Kingdom. Already acquired in situ data have been archived to the autonomous Wales Soil Moisture Network (WSMN since its foundation in July 2011. The sites from which measurements are being collected represent a range of conditions typical of the Welsh environment, with climate ranging from oceanic to temperate and a range of the most typical land use/cover types found in Wales. At present, WSMN consists of a total of nine monitoring sites across the area with a concentration of sites in three sub-areas around the region of Aberystwyth located in Mid-Wales. The dataset of composed of 0–5 (or 0–10 cm soil moisture, soil temperature, precipitation, and other ancillary data. WSMN data are provided openly to the public via the International Soil Moisture Network (ISMN platform. At present, WSMN is also rapidly expanding thanks to funding obtained recently which allows more monitoring sites to be added to the network to the wider community interested in using its data.

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

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    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.

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

    Science.gov (United States)

    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.

  4. Temporal stability of soil moisture spatial variability at two scales and its implication for optimal field monitoring

    Directory of Open Access Journals (Sweden)

    X. Zhou

    2007-05-01

    Full Text Available Soil moisture spatial distribution is a key component in characterizing and modeling water movement at multiple scales. The temporal stability of soil moisture spatial distribution at multiple depths was investigated at the 7.9-ha Shale Hills Catchment in central Pennsylvania with a year-round monitoring of 77 sites distributed across the catchment. For this catchment with heterogeneous soils and landforms, integration of soils information into the temporal stability assessment provided a more accurate location of representative monitoring sites for capturing mean soil moisture. The temporal stability pattern of soil moisture at the swale scale was similar to that at the catchment scale, suggesting that the swale could be used as a representative unit in the catchment study in terms of mean soil moisture dynamics. The temporal stability of soil moisture variability in this catchment varied over space and seasons. Temporally stable sites were found in the northwestern and southeastern parts of the catchment, while the areas near the stream and some swale areas had lower temporal stability. The spatial distribution of soil moisture was more stable over time during wet seasons, but less stable during transitional periods (i.e. drying or recharging periods. The temporal stability concept helps the optimal design of field monitoring sites and sampling strategies. On the other hand, the temporally unstable sites provide insights regarding the hydrological processes behind the spatial variability of soil moisture.

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

    Science.gov (United States)

    Cammalleri, Carmelo; Vogt, Jürgen

    2017-04-01

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

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

    Science.gov (United States)

    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

  7. Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

    Science.gov (United States)

    Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

    2011-01-01

    A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

  8. Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

    Science.gov (United States)

    Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

    2011-01-01

    A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

  9. Wireless sensor network deployment for monitoring soil moisture dynamics at the field scale

    Science.gov (United States)

    Majone, B.; Bellin, A.; Filippi, E.; Ioriatti, L.; Martinelli, M.; Massa, A.; Toller, G.

    2009-12-01

    We describe a recent deployment of soil moisture and temperature sensors in an apple tree orchard aimed at exploring the interaction between soil moisture dynamics and plant physiology. The field is divided into three parcels with different constant irrigation rates. The deployment includes dendrometers which monitor the variations of the trunk diameter. The idea is to monitor continuously and at small time steps soil moisture dynamics, soil temperature and a parameter reflecting plant stress at the parcel scale, in order to better investigate the interaction between plant physiology and soil moisture dynamics. Other sensors monitoring plant physiology can be easily accommodated within the Wireless Sensor Network (WSN). The experimental site is an apple orchard of 5000 m2 located at Cles, province of Trento, Italy, at the elevation of 640 m.a.s.l. In this site about 1200 apple trees are cultivated (cultivar Golden Delicious). The trees have been planted in 2004 in north-south rows 3.5 m apart. The deployment consists of 27 locations connected by a multi hop WSN, each one equipped with 5 soil moisture sensors (capacitance sensors EC-5, decagon Service) at the depths of 10, 20, 30, 50 and 80 cm, and a temperature sensor at the depth of 20 cm, for a total of 135 soil moisture and 27 temperature sensors. The proposed monitoring system is based on totally autonomous sensor nodes which allow both real time and historic data management. The data gathered are then organized in a database on a public web site. The node sensors are connected through an input/output interface to a WSN platform. The power supply consists of a solar panel able to provide 250 mA at 7 V and a 3V DC/DC converter based on a dual frequency high efficient switching regulator. The typical meteorological data are monitored with a weather station located at a distance of approximately 100 m from the experimental site. Great care has been posed to calibration of the capacitance sensors both in the

  10. Novel Measurement and Monitoring Approaches for Surface and Near-Surface Soil Moisture

    Science.gov (United States)

    Jones, S. B.; Sheng, W.; Zhou, R.; Sadeghi, M.; Tuller, M.

    2015-12-01

    The top inch of the earth's soil surface is a very dynamic and important layer where physical and biogeochemical processes take place under extreme diurnal and seasonal moisture and temperature variations. Some of these critical surfaces include biocrusts, desert pavements, agricultural lands, mine tailings, hydrophobic forest soils, all of which can significantly impact environmental conditions at large-scales. Natural hazards associated with surface conditions include dust storms, post-fire erosion and flooding in addition to crop failure. Less obvious, though continually occurring, are microbial-induced gas emissions that are also significantly impacted by surface conditions. With so much at stake, it is surprising that in today's technological world there are few if any sensors designed for monitoring the top few mm or cm of the soil surface. In particular, remotely sensed data is expected to provide near-real time surface conditions of our Earth, but we lack effective tools to measure and calibrate surface soil moisture. We are developing multiple methods for measurement and monitoring of surface and near-surface soil water content which include gravimetric as well as electromagnetic approaches. These novel measurement solutions and their prospects to improve soil surface water content determination will be presented.

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

    Directory of Open Access Journals (Sweden)

    Rosanno de Dios

    2009-06-01

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

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

    Science.gov (United States)

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

    2011-12-01

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

  13. Satellite remote sensing applications for surface soil moisture monitoring: A review

    Institute of Scientific and Technical Information of China (English)

    Lingli WANG; John J.QU

    2009-01-01

    Surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/ atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. Recent technological advances in satellite remote sensing have shown that soil moisture can be measured by a variety of remote sensing techniques,each with its own strengths and weaknesses. This paper presents a comprehensive review of the progress in remote sensing of soil moisture, with focus on technique approaches for soil moisture estimation from optical,thermal, passive microwave, and active microwave measurements. The physical principles and the status of current retrieval methods are summarized. Limitations existing in current soil moisture estimation algorithms and key issues that have to be addressed in the near future are also discussed.

  14. From ASCAT to Sentinel-1: Soil Moisture Monitoring using European C-Band Radars

    Science.gov (United States)

    Wagner, Wolfgang; Bauer-Marschallinger, Bernhard; Hochstöger, Simon

    2016-04-01

    The Advanced Scatterometer (ASCAT) is a C-Band radar instrument flown on board of the series of three METOP satellites. Albeit not operating in one of the more favorable longer wavelength ranges (S, L or P-band) as the dedicated Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, it is one of main microwave sensors used for monitoring of soil moisture on a global scale. Its attractiveness for soil moisture monitoring applications stems from its operational status, high radiometric accuracy and stability, short revisit time, multiple viewing directions and long heritage (Wagner et al. 2013). From an application perspective, its main limitation is its spatial resolution of about 25 km, which does not allow resolving soil moisture patterns driven by smaller-scale hydrometeorological processes (e.g. convective precipitation, runoff patterns, etc.) that are themselves related to highly variable land surface characteristics (soil characteristics, topography, vegetation cover, etc.). Fortunately, the technique of aperture synthesis allows to significantly improve the spatial resolution of spaceborne radar instruments up to the meter scale. Yet, past Synthetic Aperture Radar (SAR) missions had not yet been designed to achieve a short revisit time required for soil moisture monitoring. This has only changed recently with the development and launch of SMAP (Entekhabi et al. 2010) and Sentinel-1 (Hornacek et al. 2012). Unfortunately, the SMAP radar failed only after a few months of operations, which leaves Sentinel-1 as the only currently operational SAR mission capable of delivering high-resolution radar observations with a revisit time of about three days for Europe, about weekly for most crop growing regions worldwide, and about bi-weekly to monthly over the rest of the land surface area. Like ASCAT, Sentinel-1 acquires C-band backscatter data in VV polarization over land. Therefore, for the interpretation of both ASCAT and Sentinel-1

  15. A Cloud Computing-Enabled Spatio-Temporal Cyber-Physical Information Infrastructure for Efficient Soil Moisture Monitoring

    Directory of Open Access Journals (Sweden)

    Lianjie Zhou

    2016-06-01

    Full Text Available Comprehensive surface soil moisture (SM monitoring is a vital task in precision agriculture applications. SM monitoring includes remote sensing imagery monitoring and in situ sensor-based observational monitoring. Cloud computing can increase computational efficiency enormously. A geographical web service was developed to assist in agronomic decision making, and this tool can be scaled to any location and crop. By integrating cloud computing and the web service-enabled information infrastructure, this study uses the cloud computing-enabled spatio-temporal cyber-physical infrastructure (CESCI to provide an efficient solution for soil moisture monitoring in precision agriculture. On the server side of CESCI, diverse Open Geospatial Consortium web services work closely with each other. Hubei Province, located on the Jianghan Plain in central China, is selected as the remote sensing study area in the experiment. The Baoxie scientific experimental field in Wuhan City is selected as the in situ sensor study area. The results show that the proposed method enhances the efficiency of remote sensing imagery mapping and in situ soil moisture interpolation. In addition, the proposed method is compared to other existing precision agriculture infrastructures. In this comparison, the proposed infrastructure performs soil moisture mapping in Hubei Province in 1.4 min and near real-time in situ soil moisture interpolation in an efficient manner. Moreover, an enhanced performance monitoring method can help to reduce costs in precision agriculture monitoring, as well as increasing agricultural productivity and farmers’ net-income.

  16. [A Novel Method of Soil Moisture Content Monitoring by Land Surface Temperature and LAI].

    Science.gov (United States)

    Gao, Zhong-ling; Zheng, Xiao-po; Sun, Yue-jun; Wang, Jian-hua

    2015-11-01

    Land surface temperature (Ts) is influenced by soil background and vegetation growing conditions, and the combination of Ts and vegetation indices (Vis) can indicate the status of surface soil moisture content (SMC). In this study, Advanced Temperature Vegetation Dryness Index (ATVDI) used for monitoring SMC was proposed on the basis of the simulation results with agricultural climate model CUPID. Previous studies have concluded that Normalized Difference Vegetation Index (NDVI) easily reaches the saturation point, andLeaf Area Index (LAI) was then used instead of NDVI to estimate soil moisture content in the paper. With LAI-Ts scatter diagram established by the simulation results of CUPID model; how Ts varied with LAI and SMC was found. In the case of the identical soil background, the logarithmic relations between Ts and LAI were more accurate than the linear relations included in Temperature Vegetation Dryness Index (TVDI), based on which ATVDI was then developed. LAI-Ts scatter diagram with satellite imagery were necessary for determining the expression of the upper and lower logarithmic curves while ATVDI was used for monitoring SMC. Ts derived from satellite imagery were then transformed to the Ts-value which has the same SMC and the minimum LAI in study area with look-up table. The measured SMC from the field sites in Weihe Plain, Shanxi Province, China, and the products of LAI and Ts (MOD15A2 and MOD11A2, respectively) produced by the image derived from Moderate Resolution Imaging Spectrometer (MODIS) were collected to validate the new method proposed in this study. The validation results shown that ATVDI (R² = 0.62) was accurate enough to monitor SMC, and it achieved better result than TVDI. Moreover, ATVDI-derived result were Ts values with some physical meanings, which made it comparative in different periods. Therefore, ATVDI is a promising method for monitoring SMC in different time-spatial scales in agricultural fields.

  17. Soil moisture monitoring over a semiarid region using Envisat ASAR data

    Science.gov (United States)

    Amriche, Atef A. E.; Guerfi, Mokhtar

    2012-09-01

    Soil moisture (SM) is of fundamental importance to many agricultural, hydrological and climate studies. In this paper, a simple approach for mapping near-surface SM from Envisat ASAR data was developed. Four high-resolution images covering a semiarid region in Algeria were acquired with the same sensor configuration. We performed the pretreatment using the Basic Envisat SAR Toolbox of the European Space Agency. Then, we extracted the backscattering coefficient σ0 (dB) from the filtered and calibrated images. On the other hand, five training sites with different soil physical properties and vegetation cover were selected for monitoring SM. The field campaigns were conducted concurrent to satellite image acquisitions to measure soil water content in the top five centimeters using the gravimetric method. The study of linear regressions associated to the change detection approach allowed the expression of the backscattering coefficient as a function of volumetric soil moisture (σ0 = a*θ + b). The coefficients "a" and "b" of the equation slightly differ from one site to another and also from one season to the next. This difference is mainly due to the effects of surface roughness and vegetation biomass variations. Our study confirms a good agreement between the volumetric nearsurface SM and the radar backscattering coefficient for all the test fields. The comparison between measured and estimated SM proves the accuracy of the inversion models used here with a mean average error of less than 5%. At the end, high resolution maps of soil moisture distribution were obtained from the acquired radar images.

  18. The role of soil moisture in monitoring drought events over Europe

    Science.gov (United States)

    Cammalleri, Carmelo; Micale, Fabio; Vogt, Jürgen

    2015-04-01

    Drought is a complex phenomenon that manifests at different spatial and temporal scales. Within the European Drought Observatory (EDO, http://edo.jrc.ec.europa.eu) an integrated monitoring approach is embraced, attempting at combining various sources of drought information at European level in order to provide a set of drought monitoring tools that encompasses continental, national, regional and local scales. Each tool, ranging from precipitation-based to remotely sensed greenness indicators, aims at capturing different aspect of the heterogeneous nature of drought events. An accurate measure of the effects of drought on vegetated lands can be achieved by exploiting the capability of soil moisture to quantify plant water stress. This is commonly accomplished by either accounting for the level of the current soil moisture compared to the past history or by computing a water deficit index, based on the on the critical values of the soil water retention curve. Under the definition that a vegetated area can be considered affected by drought condition only when the soil moisture status in the root zone is simultaneously: i) unusually dry compared to the "normal" state and ii) causing severe water stress to the vegetation, it is an obvious consequence that a soil moisture-based drought indicator should capture both features. Here we describe a novel drought severity index. DSI, that accounts for the mutual occurrence of these two conditions by means of a weighted average of a water deficit factor and a dryness probability factor. The former quantifies the actual plant water stress level, whereas the latter verifies that the current water deficit condition is unusual for the specific site and period. The reliability of the estimates made by DSI is evaluated by analyzing the performance during some well-known drought events that occurred over Europe between 1995 and 2012. Overall, DSI seems to correctly distinguish the main drought events recognized in the dedicated

  19. Soil Moisture Monitoring Using GNSS-R Signals; First Experimental Results with the SAM Sensor

    Science.gov (United States)

    Egido, A.; Martin-Puig, C.; Felip, D.; Garcia, M.; Caparrini, M.; Farres, E.; Ruffini, G.

    2009-04-01

    Observing the Earth surface with Global Navigation Satellite Systems (GNSS) reflected signals has become a noteworthy remote sensing technique for the scientific community. The growing interest in GNSS as a remote sensing tool is due to its global availability and the carrier frequencies used. In fact, L-band, in which all current and next-future Global Navigation Satellite Systems emit, is a portion of the electromagnetic spectrum that highly interacts with the natural medium and for this reason, the possible applications exploiting these signals are numerous. In addition, the large number of GNSS signals in space, and their steadily increasing quantity and quality predicts a promising future for this remote sensing technique. Among a wide variety of applications, soil moisture (SM) monitoring represents an important niche for GNSS-R. SM is a prime parameter for the surface hydrologic cycle since it drives the evapotranspiration and the heat storage capability of the soil, as well as determines the possibility of surface runoff after rainfalls. Despite the recognised environmental and commercial relevance of SM, providing such parameter over global and large scales remains a significant challenge. Sensors based on GNSS-R offer a suitable and efficient solution to this issue. The basis for the retrieval of SM with GNSS-R systems lays in the variability of the ground dielectric properties associated to water content. The higher the concentration of water in the soil, the higher the dielectric constant and reflectivity, which affects signals that reflect from the Earth surface by increasing their peak power. Previous investigations, [1,2] demonstrated the capability of GPS bistatic scatterometers to sense small changes in surface reflectivity, becoming a precedent for this promising research line. GNSS-R present various advantages with respect to others methods currently used to retrieve soil moisture. Firstly, as already mentioned, GNSS signals lie in L band, which

  20. Soil moisture monitoring results at the radioactive waste management complex of the Idaho National Engineering Laboratory, FY-1993

    Energy Technology Data Exchange (ETDEWEB)

    McElroy, D.L.

    1993-11-01

    In FY-1993, two tasks were performed for the Radioactive Waste Management Complex (RWMC) Low Level Waste Performance Assessment to estimate net infiltration from rain and snow at the Subsurface Disposal Area (SDA) and provide soil moisture data for hydrologic model calibration. The first task was to calibrate the neutron probe to convert neutron count data to soil moisture contents. A calibration equation was developed and applied to four years of neutron probe monitoring data (November 1986 to November 1990) at W02 and W06 to provide soil moisture estimates for that period. The second task was to monitor the soils at two neutron probe access tubes (W02 and W06) located in the SDA of the RWMC with a neutron probe to estimate soil moisture contents. FY-1993 monitoring indicated net infiltration varied widely across the SDA. Less than 1.2 in. of water drained into the underlying basalts near W02 in 1993. In contrast, an estimated 10.9 in. of water moved through the surficial sediments and into the underlying basalts at neutron probe access tube W06. Net infiltration estimates from the November 1986 to November 1990 neutron probe monitoring data are critical to predictive contaminant transport modeling and should be calculated and compared to the FY-1993 net infiltration estimates. In addition, plans are underway to expand the current neutron probe monitoring system in the SDA to address the variability in net infiltration across the SDA.

  1. Monitoring Soil Moisture Deficit Effects on Vegetation Parameters Using Radiative Transfer Models Inversion and Hyperspectral Measurements Under Controlled Conditions

    Science.gov (United States)

    Bayat, Bagher; Van der Tol, Christiaan; Verhoef, Wouter

    2016-08-01

    Plant-available soil moisture is a key element which affects plant properties in their ecosystems. This study shows Poa pratensis -a species of grass- responses to soil moisture deficit during an artificial drought episode in a greenhouse experiment. We used radiative transfer model inversion to monitor the gradual manifestation of soil moisture deficit effects on vegetation in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 40 days. In a regular weekly schedule, canopy reflectance was measured. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters (mainly; LAI, Cab, Cw, Cdm and Cs). The relationships between these retrieved parameters with soil moisture content were established in two separated groups; stress and non-stressed. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil moisture content in the drought episode. These parameters co- varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level.

  2. Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System

    Directory of Open Access Journals (Sweden)

    Xueyan Zhang

    2017-02-01

    Full Text Available Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.

  3. Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System.

    Science.gov (United States)

    Zhang, Xueyan; Zhang, Jianwu; Li, Lin; Zhang, Yuzhu; Yang, Guocai

    2017-02-23

    Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.

  4. Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System

    Science.gov (United States)

    Zhang, Xueyan; Zhang, Jianwu; Li, Lin; Zhang, Yuzhu; Yang, Guocai

    2017-01-01

    Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer. PMID:28241488

  5. Spatial Soil Temperature and Moisture Monitoring Across the Transylvanian Plain, in Romania

    Science.gov (United States)

    Rusu, Teodor; Weindorf, David; Haggard, Beatrix; Moraru, Paula Ioana; Sopterean, Mara Lucia

    2011-01-01

    The Transylvanian Plain, Romania is an important region for agronomic productivity. However, limited soils data and adoption of best management practices hinder land productivity. Soil temperatures of the Transylvanian Plain were evaluated using a set of twenty datalogging stations positioned throughout the plain. Soil temperatures were monitored at the surface and at 10, 30, and 50 cm depths, and soil moisture was monitored at 10 cm. Preliminary results indicate that most soils of the Transylvanian Plain will have a mesic temperature regime. However, differences in seasonal warming and cooling trends across the plain were noted. These have important implications for planting recommendations. Growing degree days (GDDs) are preferred over maturity ratings, because they can account for temperature anomalies. The crop being considered for this study was corn. The base temperature (BT) was set at 10oC, and the upper threshold was 30oC. Two methods were used to calculate GDDs; 1) minimum and maximum daily temperatures, and 2) 24 h of averaged temperature data. Growing degree days were run from 110-199 day of year (DOY) to represent approximate planting date to tasseling. The DOY that 694 accumulated growing degree days (AGDDs) was reached at each site was then analyzed to identify differences across the TP. Three sites failed to reach 694 AGDDs by DOY 199, and were excluded from comparisons to other results. Averaged values were used to create spline interpolation maps with ArcMap 9.2 (ESRI, Redlands, CA, USA). The southeastern portion of the TP was found to tassel a month earlier assuming a planting date of 109 DOY. Four DeKalb® corn hybrids were then selected based on GDDs to tasseling, drydown, drought tolerance, and insect resistance. With a better understanding of the GDD trends across the TP, more effective planting and harvesting could be accomplished by Romanian farmers to maximize agronomic production.

  6. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    Science.gov (United States)

    Gu, Y.; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, J.F.; Verdin, J.P.

    2008-01-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

  7. Footprint Characteristics Revised for Field-Scale Soil Moisture Monitoring with Cosmic-Ray Neutrons

    CERN Document Server

    Köhli, M; Zreda, M; Schmidt, U; Dietrich, P; Zacharias, S

    2016-01-01

    Cosmic-ray neutron probes are widely used to monitor environmental water content near the surface. The method averages over tens of hectares and is unrivaled in serving representative data for agriculture and hydrological models at the hectometer scale. Recent experiments, however, indicate that the sensor response to environmental heterogeneity is not fully understood. Knowledge of the support volume is a prerequisite for the proper interpretation and validation of hydrogeophysical data. In a previous study, several physical simplifications have been introduced into a neutron transport model in order to derive the characteristics of the cosmic-ray probe's footprint. We utilize a refined source and energy spectrum for cosmic-ray neutrons and simulate their response to a variety of environmental conditions. Results indicate that the method is particularly sensitive to soil moisture in the first tens of meters around the probe, whereas the radial weights are changing dynamically with ambient water. The footprin...

  8. Rapid selection of a representative monitoring location of soil water content for irrigation scheduling using surface moisture-density gauge

    Science.gov (United States)

    Mubarak, Ibrahim; Janat, Mussadak; Makhlouf, Mohsen; Hamdan, Altayeb

    2016-10-01

    Establishing a representative monitoring location of soil water content is important for agricultural water management. One of the challenges is to develop a field protocol for determining such a location with minimum costs. In this paper, we use the concept of time stability in soil water content to examine whether using a short term monitoring period is sufficient to identify a representative site of soil water content and, therefore, irrigation scheduling. Surface moisture-density gauge was used as a means for measuring soil water content. Variations of soil water content in space and time were studied using geostatistical tools. Measuring soil water content was made at 30 locations as nodes of a 6×8 m grid, six times during the growing season. A representative location for average soil water content estimation was allocated at the beginning of a season, and thereafter it was validated. Results indicated that the spatial pattern of soil water content was strongly temporally stable, explained by the relationship between soil water content and fine soil texture. Two field surveys of soil water content, conducted before and after the 1st irrigation, could be sufficient to allocate a representative location of soil water content, and for adequate irrigation scheduling of the whole field. Surface moisture-density gauge was found to be efficient for characterising time stability of soil water content under irrigated field conditions.

  9. Preferential flows and soil moistures on a Benggang slope: Determined by the water and temperature co-monitoring

    Science.gov (United States)

    Tao, Yu; He, Yangbo; Duan, Xiaoqian; Zou, Ziqiang; Lin, Lirong; Chen, Jiazhou

    2017-10-01

    Soil preferential flow (PF) has important effects on rainfall infiltration, moisture distribution, and hydrological and ecological process; but it is very difficult to monitor and characterize on a slope. In this paper, soil water and soil temperature at 20, 40, 60, 80 cm depths in six positions were simultaneously monitored at high frequency to confirm the occurrence of PF at a typical Benggang slope underlain granite residual deposits, and to determine the interaction of soil moisture distribution and Benggang erosion. In the presence of PF, the soil temperature was first (half to one hour) governed by the rainwater temperature, then (more than one hour) governed by the upper soil temperature; in the absence of PF (only matrix flow, MF), the soil temperature was initially governed by the upper soil temperature, then by the rainwater temperature. The results confirmed the water replacement phenomenon in MF, thus it can be distinguished from PF by additional temperature monitoring. It indicates that high frequency moisture and temperature monitoring can determine the occurrence of PF and reveal the soil water movement. The distribution of soil water content and PF on the different positions of the slope showed that a higher frequency of PF resulted in a higher variation of average of water content. The frequency of PF at the lower position can be three times as that of the upper position, therefore, the variation coefficient of soil water content increased from 4.67% to 12.68% at the upper position to 8.18%-33.12% at the lower position, where the Benggang erosion (soil collapse) was more possible. The results suggest strong relationships between PF, soil water variation, and collapse activation near the Benggang wall.

  10. Drought monitoring over the Horn of Africa using remotely sensed evapotranspiration, soil moisture and vegetation parameters

    Science.gov (United States)

    Timmermans, J.; Gokmen, M.; Eden, U.; Abou Ali, M.; Vekerdy, Z.; Su, Z.

    2012-04-01

    The need to good drought monitoring and management for the Horn of Africa has never been greater. This ongoing drought is the largest in the past sixty years and is effecting the life of around 10 million people, according to the United Nations. The impact of drought is most apparent in food security and health. In addition secondary problems arise related to the drought such as large migration; more than 15000 Somalia have fled to neighboring countries to escape the problems caused by the drought. These problems will only grow in the future to larger areas due to increase in extreme weather patterns due to global climate change. Monitoring drought impact and managing the drought effects are therefore of critical importance. The impact of a drought is hard to characterize as drought depends on several parameters, like precipitation, land use, irrigation. Consequently the effects of the drought vary spatially and range from short-term to long-term. For this reason a drought event can be characterized into four categories: meteorological, agricultural, hydrological and socio-economical. In terms of food production the agricultural drought, or short term dryness near the surface layer, is most important. This drought is usually characterized by low soil moisture content in the root zone, decreased evapotranspiration, and changes in vegetation vigor. All of these parameters can be detected with good accuracy from space. The advantage of remote sensing in Drought monitoring is evident. Drought monitoring is usually performed using drought indices, like the Palmer Index (PDSI), Crop Moisture Index (CMI), Standard Precipitation Index (SPI). With the introduction of remote sensing several indices of these have shown great potential for large scale application. These indices however all incorporate precipitation as the main surface parameter neglecting the response of the surface to the dryness. More recently two agricultural drought indices, the EvapoTranspiration Deficit

  11. CPC Soil Moisture

    Data.gov (United States)

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

  12. Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from the SOMOMOUNT network

    Science.gov (United States)

    Pellet, Cécile; Hauck, Christian

    2017-06-01

    Besides its important role in the energy and water balance at the soil-atmosphere interface, soil moisture can be a particular important factor in mountain environments since it influences the amount of freezing and thawing in the subsurface and can affect the stability of slopes. In spite of its importance, the technical challenges and its strong spatial variability usually prevents soil moisture from being measured operationally at high and/or middle altitudes. This study describes the new Swiss soil moisture monitoring network SOMOMOUNT (soil moisture in mountainous terrain) launched in 2013. It consists of six entirely automated soil moisture stations distributed along an altitudinal gradient between the Jura Mountains and the Swiss Alps, ranging from 1205 to 3410 m a.s.l. in elevation. In addition to the standard instrumentation comprising frequency domain sensor and time domain reflectometry (TDR) sensors along vertical profiles, soil probes and meteorological data are available at each station. In this contribution we present a detailed description of the SOMOMOUNT instrumentation and calibration procedures. Additionally, the liquid soil moisture (LSM) data collected during the first 3 years of the project are discussed with regard to their soil type and climate dependency as well as their altitudinal distribution. The observed elevation dependency of LSM is found to be non-linear, with an increase of the mean annual values up to ˜ 2000 m a.s.l. followed by a decreasing trend towards higher elevations. This altitude threshold marks the change between precipitation-/evaporation-controlled and frost-affected LSM regimes. The former is characterized by high LSM throughout the year and minimum values in summer, whereas the latter typically exhibits long-lasting winter minimum LSM values and high variability during the summer.

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

    Science.gov (United States)

    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.

  14. Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

    Science.gov (United States)

    Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

    2014-12-01

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper

  15. An Assessment of the Capabilities of the ERS Satellites' Active Microwave Instruments for Monitoring Soil Moisture Change

    Directory of Open Access Journals (Sweden)

    K. Blyth

    1997-01-01

    Full Text Available The launch of the European Remote sensing Satellite (ERS-1 in July 1991 represented an important turning point in the development of Earth observation as it was the first of a series of satellites which would carry high resolution active microwave (radar sensors which could operate through the thickest cloudeover and provide continuity of data for at least a decade. This was of particular relevance to hydrological applications, such as soil moisture monitoring, which generally require frequent satellite observations to monitor changes in state. ERS-1 and its successor ERS-2 carry the active microwave instrument (AMI which operates in 3 modes (synthetic aperture radar, wind scatterometer and wave seatterometer together with the radar altimeter which may all be useful for the observation of soil moisture. This paper assesses the utility of these sensors through a comprehensive review of work in this field. Two approaches to soil moisture retrieval are identified: 1 inversion modelling, where the physical effects of vegetation and soil roughness on radar backscatter are quantified through the use of multi-frequency and/or multi-polarization sensors and 2 change detection where these effects are normalized through frequent satellite observation, the residual effects being attributed to short-term changes in soil moisture. Both approaches will be better supported by the future European Envisat-l satellite which will provide both multi-polarization SAR and low resolution products which should facilitate more frequent temporal observation.

  16. Seven Years of Advanced Synthetic Aperture Radar (ASAR Global Monitoring (GM of Surface Soil Moisture over Africa

    Directory of Open Access Journals (Sweden)

    Alena Dostálová

    2014-08-01

    Full Text Available A surface soil moisture (SSM product at a 1-km spatial resolution derived from the Envisat Advanced Synthetic Aperture Radar (ASAR Global Monitoring (GM mode data was evaluated over the entire African continent using coarse spatial resolution SSM acquisitions from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E and the Noah land surface model from the Global Land Data Assimilation System (GLDAS-NOAH. The evaluation was performed in terms of relative soil moisture values (%, as well as anomalies from the seasonal cycle. Considering the high radiometric noise of the ASAR GM data, the SSM product exhibits a good ability (Pearson correlation coefficient (R = ~0.6 for relative soil moisture values and root mean square difference (RMSD = 11% when averaged to 5-km resolution to monitor temporal soil moisture variability in regions with low to medium density vegetation and yearly rainfall >250 mm. The findings agree with previous evaluation studies performed over Australia and further strengthen the understanding of the quality of the ASAR GM SSM product and its potential for data assimilation. Problems identified in the ASAR GM algorithm over arid regions were explained by azimuthal effects. Diverse backscatter behavior over different soil types was identified. The insights gained about the quality of the data were used to establish a reliable masking of the existing ASAR GM SSM product and the identification of areas where further research is needed for the future Sentinel-1-derived SSM products.

  17. Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China

    Science.gov (United States)

    Chen, Hui; Wu, Wei; Liu, Hong-Bin

    2017-04-01

    Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index (M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M (M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.

  18. Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

    Directory of Open Access Journals (Sweden)

    R. Fieuzal

    2011-04-01

    Full Text Available The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (Envisat/ASAR and Formosat-2. Time series of images were collected over the Yaqui irrigated area (Mexico throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from Envisat/ASAR images takes advantage of the Formosat-2 instrument capabilities to monitor the seasonality of wheat canopies. This monitoring is performed using dense time series of images acquired by Formosat-2 to set up the SAFY vegetation model. Topsoil moisture estimates are not reliable at the timing of plant emergence and during plant senescence. Estimates are accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m3 m−3, 35% in relative value. This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha for a large range of biomass water content (from 5 and 65 t ha−1 independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6.

  19. Hoop column soil moisture spacecraft in low Earth orbit for global change monitoring

    Science.gov (United States)

    Ferebee, Melvin J., Jr.

    1991-01-01

    A subset of the total Global Change Technology Initiative instruments are required to be in low Earth, sunsynchronous orbits. There is one instrument, however, that requires its own specialized spacecraft; the Soil Moisture Microwave Radiometer (SMMR). The characteristic structure of the instrument is the 118 m hoop column support structure. The hoop is supported by an axially placed column. Tension cables support and shape an electromagnetically reflective mesh surface. The instrument is capable of detecting frequencies in the 1.4 GHz range (Soil Moisture and Sea Salinity). Three apertures are used to reduce the degree of paraboloid offset and improve the beam quality. The spacecraft configuration is determined by the instrument support requirements and the requirement that it can fit into the Titan IV cargo bay. The configuration is derived by cross referencing the instrument performance requirements with the performance of the spacecraft. The spacecraft design is similar with the Multi-mission Modular Spacecraft in terms of size and packaging. A description of the spacecraft's features will yield a summary of the technologies needed for the SMMR spacecraft.

  20. SOIL moisture data intercomparison

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2015-04-01

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

  2. Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

    Science.gov (United States)

    White, Kristopher D.; Case, Jonathan L.

    2014-01-01

    The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

  3. Entropy-Bayesian Inversion of Time-Lapse Tomographic GPR data for Monitoring Dielectric Permittivity and Soil Moisture Variations

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Z; Terry, N; Hubbard, S S; Csatho, B

    2013-02-12

    In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniqueness and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability distribution functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSim) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes

  4. Entropy-Bayesian Inversion of Time-Lapse Tomographic GPR data for Monitoring Dielectric Permittivity and Soil Moisture Variations

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Zhangshuan; Terry, Neil C.; Hubbard, Susan S.

    2013-02-22

    In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniqueness and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability density functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSIM) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes advantage of

  5. Monitoring Multitemporal Soil Moisture, Rainfall, and ET in Lake Manatee Watershed, South Florida under Global Changes

    Science.gov (United States)

    Chang, N.

    2009-12-01

    temporal distributions of key variables in the hydrological cycle, such as soil moisture, evapotranspiration (ET) and precipitation. The multi-sensor platform may include not only in-situ sensor network, ground-based radar, air-borne aircraft, but also even space-borne satellites. The use of a decadal-scale historical record from 1998 to 2008 to support such a trend analysis via NEXRAD (Rainfall), GOES (ET), and MODIS (soil moisture) satellite images may uniquely support middle-term and long-term water resources management in the near future. This study confirms that the potential of using remotely sensed time-series biophysical and ecohydrological states of landscape to characterize soil moisture condition, ET, and other states should be further investigated based on the pros and cons of each type of satellite imageries so as to maximize the beneficial use of remote sensing.

  6. Two year soil moisture and temperature monitoring from two vegetation communities on olivine-basalt soils from Coppermine Peninsula, Maritime Antarctica

    Science.gov (United States)

    Schaefer, Carlos; Thomazini, André; Michel, Roberto; Francelino, Márcio; Pereira, Antônio; Schünemann, Adriano; Mendonça, Eduardo Sá

    2017-04-01

    Current climate change is greatly affecting terrestrial ecosystems of Maritime Antarctica, especially due the variations in soil temperature and moisture content. The vegetation species distribution in Maritime Antarctica is highly heterogeneous on the landscape, being governed mainly by water regime and soil characteristics. Hence, the objective of this study was to evaluate soil temperature and moisture based on long-term in situ measurements from two well-developed vegetation communities in Coppermine Peninsula, Robert Island, Maritime Antarctica. The moss site (S1) is located in a marine terrace, highly influenced by ice/snow/permafrost melting (20 m a.s.l) not affected by permafrost. This site represents the most extensive moss carpet in Coppermine Peninsula, mainly constituted by Sanionia uncinata (Hedw.) Loeske, forming a dense carpet of 3-7 cm thickness. The moss/lichen site (S2) is located in an elevated area on basaltic ridge (29 m a.s.l.). The site has great influence of permafrost bellow the A horizon of the soil, at 50 cm depth. Vegetation species constitution is highly variable, with a significant occurrence of Polytrichastrum alpinum G.L. Smith. Musiccolas lichens populations of Psoroma cinnamomeum Malme, Ochrolechia frigida (Sw.). The monitoring systems consist of soil temperature probes (Campbell L107E thermocouple, accuracy of ± 0.2°C) and soil moisture probes (CS656 water content reflectometer, accuracy of ± 2.5%), placed in the active layer at 0-10 cm depths. Three probes were inserted at each site in triplicates, spaced at 2 m from each other. All probes were connected to a Campbell Scientific CR 1000 data logger, recording data at every 1 hour interval. We calculated the thawing days (TD), freezing days (FD); thawing degree days (TDD) and freezing degree days (FDD); all according to Guglielmin et al. (2008). This system recorded data of soil temperature and moisture from February 2014 to February 2016. A predominance of freezing conditions

  7. Passive microwave soil moisture research

    Science.gov (United States)

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

    1986-01-01

    During the four years of the AgRISTARS Program, significant progress was made in quantifying the capabilities of microwave sensors for the remote sensing of soil moisture. In this paper, a discussion is provided of the results of numerous field and aircraft experiments, analysis of spacecraft data, and modeling activities which examined the various noise factors such as roughness and vegetation that affect the interpretability of microwave emission measurements. While determining that a 21-cm wavelength radiometer was the best single sensor for soil moisture research, these studies demonstrated that a multisensor approach will provide more accurate soil moisture information for a wider range of naturally occurring conditions.

  8. Early Soil Moisture Field Experiments

    Science.gov (United States)

    Schmugge, T.

    2008-12-01

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

  9. Use of microwave remote sensing data to monitor spatio temporal characteristics of surface soil moisture at local and regional scales

    Directory of Open Access Journals (Sweden)

    A. Löw

    2005-01-01

    Full Text Available Hydrologic processes, such as runoff production or evapotranspiration, largely depend on the variation of soil moisture and its spatial pattern. The interaction of electromagnetic waves with the land surface can be dependant on the water content of the uppermost soil layer. Especially in the microwave domain of the electromagnetic spectrum, this is the case. New sensors as e.g. ENVISAT ASAR, allow for frequent, synoptically and homogeneous image acquisitions over larger areas. Parameter inversion models are therefore developed to derive bio- and geophysical parameters from the image products. The paper presents a soil moisture inversion model for ENVISAT ASAR data for local and regional scale applications. The model is validated against in situ soil moisture measurements. The various sources of uncertainties, being related to the inversion process are assessed and quantified.

  10. Remote monitoring of soil moisture using passive microwave-based technologies – theoretical basic and overview of selected algorithms for AMSR-E

    Science.gov (United States)

    Satellite-based passive microwave remote sensing has been shown to be a valuable tool in mapping and monitoring global soil moisture. The Advanced Microwave Scanning Radiometer on the Aqua platform (AMSR-E) has made significant contributions to this application. As the result of agency and individua...

  11. Impacts of rainfall features and antecedent soil moisture on occurrence of preferential flow: A study at hillslopes using high-frequency monitoring

    Science.gov (United States)

    Peng, Zhenyang; Tian, Fuqiang; Hu, Hongchang

    2016-04-01

    In order to evaluate influences of rainfall features and antecedent soil moisture on occurrence of preferential flow, a more than 2 years observation was conducted at 12 sites within a 7-km2 catchment, by applying the high-frequency monitoring approach. Totally 65 rainfall events were selected to compare among sites, and preferential flow was inferred when (i) responses of soil moisture did not follow a linear sequence with depth, and (ii) penetration velocity of wetting front in at least one horizon exceeded the threshold, which was set to be 5-10 times of the saturated hydraulic conductivity of soil matrix at different depths. Results showed that frequency of preferential flow was 40.7% in average, but varied from 17.9% to 74.3% among the sites. Correlations between the frequency and rainfall features, i.e. rainfall amount, duration, maximum and average intensity, were well fitted by logarithmic curves. Rainfall amount, which was most prominently correlated with frequency (R2=0.93), was regarded as the dominant driving factor of preferential flow, while average intensity was in second (R2=0.90). Antecedent soil moisture was also significantly correlated with the frequency. However, this should largely be attributed to the differences of soil moisture among sites, since varying range of soil moisture at a specific site was not wide enough to influence the frequency significantly. Further examination suggested that topography and surface cover (dead leaves and humus) were the controlling factors of both infiltration amount and occurrence of preferential flow, as water was more readily to infiltrate into soils and preferential flow was more readily to occur when slope gradient was small and surface cover was thick, while soil moisture was more likely to be a consequence of water storage capacity, rather than an inducer of preferential flow. This knowledge could be helpful in understanding the partitioning of surface runoff and infiltration, as well as runoff

  12. Capability of meteorological drought indices for detecting soil moisture droughts

    Directory of Open Access Journals (Sweden)

    Devanmini Halwatura

    2017-08-01

    New hydrological insights for the region: For three typical soil types and climate zones in Eastern Australia, and for two soil profiles, we have found a significant correlation between the indices and soil moisture droughts detected by Hydrus-1D. The failure rates and false alarm rates for detecting the simulated soil moisture droughts were generally below 50% for both indices and both soil profiles (the Reconnaissance Drought Index at Melbourne was the only exception. However, the complexity of Hydrus-1D and the uncertainty associated with the available, regionalised soil water retention curves encourage using the indices over Hydrus-1D in absence of appropriate soil moisture monitoring data.

  13. Nematode survival in relation to soil moisture

    NARCIS (Netherlands)

    Simons, W.R.

    1973-01-01

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

  14. Nematode survival in relation to soil moisture

    NARCIS (Netherlands)

    Simons, W.R.

    1973-01-01

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

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

    Science.gov (United States)

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

    2007-05-01

    This paper presents an evaluation of AMSR-E (Advanced Microwave Scanning Radiometer for EOS) soil moisture products, based on a comparison with three ground soil moisture networks. The selected ground sites are representative of various climatic, hydrologic and environmental conditions in temperate and semi-arid areas. They are located in the south-west of France, south-east of Australia and the Gourma region of the Sahel. These sites were respectively implemented in the framework of the projects SMOSREX (Surface Monitoring Of Soil Reservoir Experiment), SASMAS/GoREx (Scaling and Assimilation of Soil Moisture and Streamflow in the Goulburn River Experimental catchment) and AMMA (African Monsoon Multidisciplinary Analysis). In all cases, the arrangement of the soil moisture measuring sites was specifically designed to address the validation of remotely sensed soil moisture in the context of the preparation of the SMOS (Soil Moisture and Ocean Salinity) project. For the purpose of this study, 25km AMSR-E products were used, including brightness temperatures at 6.9 and 10.7 GHz, and derived soil moisture. The study is focused on the year 2005. It is based on ground soil moisture network measurements from 4 stations for SMOSREX extended to the SUDOUEST project of CESBIO, 12 stations for GoRex, and 4 stations for AMMA. Temporal and spatial features of soil moisture variability and stability is a critical issue to be addressed for remotely sensed soil moisture validation. While ground measurements provide information on soil moisture dynamics at local scale and high temporal resolution (hourly), satellite measurements are sparser in time (up to several days), but cover a larger region (25km x 25km for AMSR-E). First, a statistical analysis, including mean relative difference and Spearman rank, is conducted for the three soil moisture networks. This method is mainly based on the approach proposed by Cosh et al. (2004) for the purpose of the use of ground networks for

  16. Non-Nuclear Alternatives to Monitoring Moisture-Density Response in Soils

    Science.gov (United States)

    2013-03-01

    project. The principal investigator for this study was Dr. Ernest S. Berney IV, Airfields and Pavements Branch (APB), Engineering Systems and Materials...with the M+DI was the insertion of the probes into the soil. Insertion of four probes into a small area within a rigid guide plate resulted in the...American Society for Testing and Materials. _____ 2010. Standard test method for use of the dynamic cone penetrometer in shallow pavement applications

  17. Improving flood prediction by the assimilation of satellite soil moisture in poorly monitored catchments

    Science.gov (United States)

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particula...

  18. Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai; Leng, Guoyong; Li, Zhe

    2017-01-01

    Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought over SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.

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

    Directory of Open Access Journals (Sweden)

    Olotu Yahaya

    2016-10-01

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

  20. Moisture monitoring in waste disposal surface barriers.

    Science.gov (United States)

    Brandelik, Alex; Huebner, Christof

    2003-05-01

    Surface barriers for waste disposal sites should prevent waste water and gas emission into the environment. It is necessary to assess their proper operation by monitoring the water regime of the containment. A set of three new water content measuring devices has been developed that provide an economical solution for monitoring the moisture distribution and water dynamic. They will give an early warning service if the barrier system is at risk of being damaged. The cryo soil moisture sensor 'LUMBRICUS' is an in situ self-calibrating absolute water content measuring device. It measures moisture profiles at spot locations down to 2.5 m depth with an accuracy of better than 1.5% and a depth resolution of 0.03 m. The sensor inherently measures density changes and initial cracks of shrinking materials like clay minerals. The large area soil moisture sensor 'TAUPE' is a moisture sensitive electric cable network to be buried in the mineral barrier material of the cover. A report will be given with results and experiences on an exemplary installation at the Waste Disposal Facility Karlsruhe-West. 800 m2 of the barrier construction have been continuously monitored since December 1997. Volumetric water content differences of 1.5% have been detected and localised within 4 m. This device is already installed in two other waste disposal sites. A modified 'TAUPE' was constructed for the control of tunnels and river dams as well. Thin sheet moisture sensor 'FORMI' is specifically designed for moisture measurements in liners like bentonite, textile and plastic. Due to its flexibility it follows the curvature of the liner. The sensor measures independently from neighbouring materials and can be matched to a wide range of different thickness of the material. The sensors are patented in several countries.

  1. Evaluating ESA CCI soil moisture in East Africa

    Science.gov (United States)

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

    2016-06-01

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

  2. Measurement of soil moisture using gypsum blocks

    DEFF Research Database (Denmark)

    Friis Dela, B.

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

  3. Measurement of soil moisture using gypsum blocks

    DEFF Research Database (Denmark)

    Friis Dela, B.

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

  4. Comparative analysis of agricultural drought monitoring based on climate and soil moisture indicators in the Huang-Huai-Hai Plain of China

    Science.gov (United States)

    Wu, J.; Zhou, H.; An, X.

    2016-12-01

    Agricultural drought is one of very common agro-meteorological disasters, having a serious threat on crop growth and production. Effective drought monitoring will aid the drought response management to reduce drought loss. Currently there has been many drought indices used for agricultural drought monitoring. Climate-based Standardized Precipitation Evapotranspiration Index (SPEI) was widely used for agricultural drought monitoring in view of its merits of simple calculation, multi-scale and with consideration of evapotranspiration. Besides, soil moisture has been recognized as the most direct indicator for monitoring agricultural drought, which provides a huge potential for monitoring due to the increase of soil moisture accessibility. Given that algorithms of both indices are different and their monitoring results also may exist the discrepancies, it is necessary to analyze their performances of both indices in agricultural drought monitoring. In this study, we chose the climate-based SPEI and soil moisture-based index (SMI) to analyze. Firstly, drought events identified by SPEI and SMI were analyzed from the perspective of drought evolution. Then the performances of SPEI and SMI were assessed through the comparison with observed drought events. Finally, vegetation change since 2000 and impact of drought on vegetation growth in Huang-Huai-Hai (HHH) Plain were explored based on MODIS NDVI data. The results show that SPEI-based drought trend agrees with SMI-based analysis, demonstrating that drought has an alleviating trend in HHH Plain in recent years. The SPEI and SMI could identify most of drought events, whereas the SMI has better performance than SPEI when it comes to drought category. The NDVI in HHH Plain shows an upward trend since 2000 and drought occurred in 2000 causes a decline in vegetation vigor. Both the SPEI and SMI are significantly correlated with NDVI anomaly, and correlation between SMI and NDVI anomaly is slightly higher than that of SPEI.

  5. Satellite observed preferential states in soil moisture

    Science.gov (United States)

    Vilasa, Luis U.; De Jeu, Richard A. M.; Dolman, Han A. J.; Wang, Guojie

    2013-04-01

    This study presents observational evidence for the existence of preferential states in soil moisture content. Recently there has been much debate about the existence, location and explanations for preferential states in soil moisture. A number of studies have provided evidence either in support or against the hypothesis of a positive feedback mechanism between soil moisture and subsequent precipitation in certain regions. Researchers who support the hypothesis that preferential states in soil moisture holds information about land atmosphere feedback base their theory on the impact of soil moisture on the evaporation process. Evaporation recycles moisture to the atmosphere and soil moisture has a direct impact on the supply part of this process but also on the partitioning of the available energy for evaporation. According to this theory, the existence of soil moisture bimodality can be used as an indication of possible land-atmosphere feedbacks, to be compared with model simulations of soil moisture feedbacks. On the other hand, other researchers argue that seasonality in the meteorological conditions in combination with the non-linearity of soil moisture response alone can induce bimodality. In this study we estimate the soil moisture bimodality at a global scale as derived from the recently available 30+ year ESA Climate Change Initative satellite soil moisture dataset. An Expectation-Maximization iterative algorithm is used to find the best Gaussian Mixture Model, pursuing the highest likelihood for soil moisture bimodality. With this approach we mapped the regions where bi-modal probability distribution of soil moisture appears for each month for the period between 1979-2010. These bimodality areas are analyzed and compared to maps of model simulations of soil moisture feedbacks. The areas where more than one preferential state exists compare surprisingly well with the map of land-atmosphere coupling strength from model simulations. This approach might

  6. Modeling soil moisture memory in savanna ecosystems

    Science.gov (United States)

    Gou, S.; Miller, G. R.

    2011-12-01

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

  7. Soil moisture monitoring for climate research: evaluation of a low cost sensor in the framework of the Swiss soil Expperiment (SwissSMEX) campaign

    NARCIS (Netherlands)

    Mittelbach, H.; Casini, F.; Lehner, I.; Teuling, A.J.; Seneviratne, S.I.

    2011-01-01

    Soil moisture measurements are essential to understand land surface–atmosphere interactions. In this paper we evaluate the performance of the low-cost 10HS capacitance sensor (Decagon Devices, United States) using laboratory and field measurements. Measurements with 10HS sensors of volumetric water

  8. Estimating Soil Moisture from Satellite Microwave Observations

    Science.gov (United States)

    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

  9. A soil moisture climatology of Illinois

    Energy Technology Data Exchange (ETDEWEB)

    Hollinger, S.E.; Isard, S.A. (Illinois State Water Survey, Champaign, IL (United States) Univ. of Illinois, Urbana, IL (United States))

    1994-05-01

    Ten years of soil moisture measurements (biweekly from March through September and monthly during winter) within the top 1 m of soil at 17 grass-covered sites across Illinois are analyzed to provide a climatology of soil moisture for this important Midwest agricultural region. Soil moisture measurements were obtained with neutron probes that were calibrated for each site. Measurement errors are dependent upon the volumetric water content with errors less than 20 percent when soil moisture is above 0 percent of soil volume. Single point errors in moisture measurements from the top 1 m of soil range from 6 percent to 13 percent when volumetric soil moisture is 30 percent of soil volume. The average depletion in moisture between winter and summer over the 10-year period for the top 2 m of soil in Illinois was 72.3 mm. Three-quarters of this decrease occurred above 0.5 m and only 5 percent occurred between the 1.0-m and 2.0-m depths. The average moisture decrease between winter and summer during a wet year (1985) and a drought year (1988) in the top 2 m of soil was 64 percent and 204 percent of the average for the 10-year period, respectively. Seasonal means in soil moisture averaged for the state show the effects of different seasons and soil types on soil moisture. In the winter and spring a latitudinal gradient exists with the wetter soils in the southern part of the state. During summer and autumn there is a longitudinal gradient with the wetter soils in the eastern half of the state. The longitudinal gradient is closely associated with the depth of loess deposits.

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

    Science.gov (United States)

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

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

    Science.gov (United States)

    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

  12. Uneven moisture patterns in water repellent soils

    NARCIS (Netherlands)

    Dekker, L.W.; Ritsema, C.J.

    1996-01-01

    In the Netherlands, water-repellent soils are widespread and they often show irregular moisture patterns, which cause accelerated transport of water and solutes to the groundwater and surface water. Under grass cover, spatial variability in soil moisture content is high owing to fingered flow; in ar

  13. Capacitive Soil Moisture Sensor for Plant Watering

    Science.gov (United States)

    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.

  14. [Effects of supplemental irrigation by monitoring soil moisture on the'water-nitrogen utilization of wheat and soil NO3(-)-N leaching].

    Science.gov (United States)

    Shi, Yu; Yu, Zhen-wen; He, Jian-ning; Zhang, Yong-li

    2016-02-01

    Field experiments were conducted during 2012-2014 wheat growing seasons. With no irrigation in the whole stage (WO) treatment as control, three supplemental irrigation treatments were designed based on average relative soil moisture contents at 0-140-cm layer, at jointing and anthesis stages (65% for treatment W1 ; 70% for treatment W2; 75% for treatment W3; respectively), to examine effects of supplemental irrigation on nitrogen accumulation and translocation, grain yield, water use efficiency, and soil nitrate nitrogen leaching in wheat field., Soil water consumption amount, the percentage of soil water consumption and water irrigation to total water consumption in W2 were higher, and soil water consumption of W2 in 100-140 cm soil layer was also higher. The nitrogen accumulation before anthesis and after anthesis were presented as W2, W3>W1>W0, the nitrogen accumulation in vegetative organs at maturity as W3>W2>Wl>W0, and the nitrogen translocation from vegetative organs to grain and the nitrogen accumulation in grain at maturity as W2> W3>W1>W0. At maturity, soil NO3(-)-N content in 0-60 cm soil layer was presented. as W0>W1>W2>W3, that in 80-140 cm soil layer was significantly higher in W3 than in the other treatments, and no significant difference was found in 140-200 cm soil layer among all treatments. W treatment obtained the highest grain yield, water use efficiency, nitrogen uptake efficiency and partial productivity of applied nitrogen. As far as grain yield, water use efficiency, nitrogen uptake efficiency and soil NO3(1)-N leaching were concerned, the W2 regime was the optimal irrigation treatment in this experiment.

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

    African Journals Online (AJOL)

    Jane

    2011-10-17

    Oct 17, 2011 ... temperature under three soil moisture and two fertilizer levels in solar greenhouse .... temperature is governed by the one-dimensional heat conduction equation in the soil, and the soil temperature varied sinusoidally. We.

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

    Science.gov (United States)

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

    2015-12-01

    Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at various scales by combining fixed and roving cosmic-ray neutron probes at four study sites across an East-West precipitation gradient overtopping the High Plains Aquifer (HPA). Each of the four study sites consisted of coarse scale mapping of the entire ~12 by 12 km domain and detailed mapping of 1 quarter section (0.8 by 0.8 km) agricultural field. By using a simplistic data merging technique we are able to produce a statistical daily soil moisture product at a variety of key spatial scales in support of irrigation water management technology: the individual sprinkler (~102 m2) for variable rate irrigation, the individual pie slice (~103 m2) for variable speed irrigation, and the quarter section (0.64 km2) for uniform rate irrigation. In addition, we are able to provide a daily soil moisture product over the 144 km2 study area at a variety of key remote sensing scales 1, 9, and 144 km2. These products can be used to support SMAP/SMOS through calibration, validation, and value addition by statistical downscaling. Future work could include larger scale monitoring in support of GRACE total water storage calculations in the HPA or other key groundwater resource locations by incorporating existing COSMOS sites or establishment of new networks.

  17. The Effects of Wildfire on Soil Moisture Dynamics

    Science.gov (United States)

    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

  18. Inference of Soil Hydrologic Parameters from Electronic Soil Moisture Records

    Science.gov (United States)

    Chandler, David G.; Seyfried, Mark S.; McNamara, James P.; Hwang, Kyotaek

    2017-04-01

    Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity and permanent wilting point have been determined by laboratory methods. This approach is challenged by issues of scale, boundary conditions and soil disturbance. We develop and compare four methods to determine values of field saturation, field capacity, plant extraction limit and initiation of plant water stress from long term in-situ monitoring records of TDR-measured volumetric water content (Q). The monitoring sites represent a range of soil textures, soil depths, effective precipitation and plant cover types in a semi-arid climate. The Q records exhibit attractors (high frequency values) that correspond to field capacity and the plant extraction limit at both annual and longer time scales, but the field saturation values vary by year depending on seasonal wetness in the semi-arid setting. The analysis for five sites in two watersheds is supported by comparison to values determined by a common pedotransfer function and measured soil characteristic curves. Frozen soil is identified as a complicating factor for the analysis and users are cautioned to filter data by temperature, especially for near surface soils.

  19. Soil Moisture Data Assimilation in Soil Water Flow Modeling

    Science.gov (United States)

    Pachepsky, Y. A.; Guber, A.; Jacques, D.; Pan, F.; van Genuchten, M.; Cady, R. E.; Nicholson, T. J.

    2010-12-01

    Soil water flow modeling has multiple applications. This modeling is based on simplifications stemming from both conceptual uncertainty and lack of detailed knowledge about parameters. Modern soil moisture sensors can provide detailed information about changes in soil water content in time and with depth. This information can be used for data assimilation in soil water flow modeling. The ensemble Kalman filter appears to be an appropriate method for that. Earlier we demonstrated ensemble simulations of soil water flow by using sets of pedotransfer functions (empirical relationships between soil hydraulic properties and soil basic properties, such as particle size distribution, bulk density, organic carbon content, etc.). The objective of this work was to apply the data assimilation with the ensemble Kalman filter to soil water flow modeling, using soil water content monitoring with TDR probes and an ensemble of soil water flow models parameterized with different pedotransfer functions. Experiments were carried out at the Bekkevoort site, Belgium. Sixty time domain reflectometry (TDR) probes with two rods) were installed along the trench in loamy soil at 12 locations with 50-cm horizontal spacing at five depths (15, 35, 55, 75, and 95 cm). Water content and weather parameters were monitored for one year with 15 min frequency. Soil water flow was simulated using the HYDRUS6 software. Mean daily means of water contents at the observation depths were the measurements used in data assimilation. Eighteen pedotransfer functions for water retention and one for hydraulic conductivity were applied to generate ensembles to evaluate the uncertainty in simulation results, whereas the replicated measurements at each of measurement depths were used to characterize the uncertainty in data. Data assimilation appeared to be very efficient. Even assimilating measurements at a single depth provided substantial improvement in simulations at other observation depths. Results on

  20. Response of grassland ecosystems to prolonged soil moisture deficit

    Science.gov (United States)

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

    2014-05-01

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

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

    Science.gov (United States)

    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

  2. Pattern similarity based soil moisture analysis for three seasons on a steep hillslope

    Science.gov (United States)

    Lee, Eunhyung; Kim, Sanghyun

    2017-08-01

    Soil moisture is an important factor for understanding hydrological and solute transport processes at the hillslope scale. The selection of representative points for soil moisture measurement has been explored to investigate temporal variation of average soil moisture with minimum costs and maximum stability. The optimal selection of soil moisture monitoring points has been reevaluated to address hillslope hydrological processes and the impacts of seasonal differences. An alternative method to select soil moisture measurement points was developed to adequately represent immediate soil moisture response patterns to sequential rainfall events. To address the seasonal features of rainfall events and their impacts on soil moisture redistribution along the hillslope, field soil moisture data were collected at 49 points for three seasons over periods of 25 days with bi-hourly monitoring intervals. For effective characterization of soil moisture variation, soil moisture datasets were classified using cluster analysis based on Euclidean similarity. Points delineated using the proposed method not only provide better stability of average soil moistures but also adequately represent the response patterns of soil moisture to rainfall events on the hillslope.

  3. On-irrigator pasture soil moisture sensor

    Science.gov (United States)

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

    2017-02-01

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

  4. Automated general temperature correction method for dielectric soil moisture sensors

    Science.gov (United States)

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

    2017-08-01

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

  5. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    Science.gov (United States)

    Zhu, Qing; Zhou, Zhiwen; Duncan, Emily W.; Lv, Ligang; Liao, Kaihua; Feng, Huihui

    2017-02-01

    Spatio-temporal variability of soil moisture (θ) is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time θ monitoring methods. This restricted the comprehensive and intensive examination of θ dynamics. In this study, we integrated the manual and real-time monitored data to depict the hillslope θ dynamics with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear (support vector machines-SVM) models were used to predict θ at 39 manual sites (collected 1-2 times per month) with θ collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each depth and manual site, an optimal prediction model was then determined at this depth of this site. Results showed that θ at the 39 manual sites can be reliably predicted (root mean square errors model. The subsurface flow dynamics was an important factor that determined whether the relationship was linear or non-linear. Depth to bedrock, elevation, topographic wetness index, profile curvature, and θ temporal stability influenced the selection of prediction model since they were related to the subsurface soil water distribution and movement. Using this approach, hillslope θ spatial distributions at un-sampled times and dates can be predicted. Missing information of hillslope θ dynamics can be acquired successfully.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2017-03-01

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

  8. Snow cover and soil moisture in mountains

    Science.gov (United States)

    Wever, N.; Lehning, M.

    2012-04-01

    Soil moisture is an important parameter of the climate system. It constrains evapotranspiration of plants and it functions as a storage of water, giving it an economic value, e.g. for agriculture. Furthermore, soil moisture is an important factor for predicting flood risk. In mountainous areas with a seasonal snow cover, the spatial distribution of snow depth is strongly influencing the spatial variation of soil moisture. To assess potential flooding situations during snow melt and rain on snow events in particular but for any heavy precipitation event in the mountains, it is important to understand the influence of the snow cover on soil status with respect to liquid and solid water. Only if this is known, the reaction of the soil i.e. amount of runoff, storage or melt, on additional water input can be assessed. For an operational assessment of the soil moisture state in the Swiss Alps at 140 measurement sites for snow and avalanche forecasting (IMIS network), the SNOWPACK model has been extended with a soil module, solving the Richards equation for the matrix flow. The modelling is validated with vertical profile measurements of soil moisture at meteorological stations in an Alpine catchment near Davos, Switzerland. It was found that the combination of a physical based snowpack model with a Richards equation solver seems to provide an adequate description of soil moisture fluctuations, especially in near surface layers. Soil moisture fluctuations, both measured and modelled, are strongly reduced when a snow cover is present. The measurements also revealed a strong increase in soil moisture, accompanied by a daily cycle in soil moisture during snow melt, extending down to 120cm depth. When soil properties from literature were assumed for the soil type in the vertical profile, the daily cycle in the model during snow melt was restricted mainly to the top layers, while observations show also a reaction in deeper layers. These observations are consistent with the

  9. Radar for Measuring Soil Moisture Under Vegetation

    Science.gov (United States)

    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. Soil moisture estimation with limited soil characterization for decision making

    Science.gov (United States)

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

    2009-04-01

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

  11. Predicting root zone soil moisture using surface data

    Science.gov (United States)

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

    2012-04-01

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

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

    Directory of Open Access Journals (Sweden)

    X.-P. Wang

    2011-02-01

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

  13. Microwave Measurements of Moisture Distributions in the Upper Soil Profile

    Science.gov (United States)

    Sadeghi, A. M.; Hancock, G. D.; Waite, W. P.; Scott, H. D.; Rand, J. A.

    1984-07-01

    Laboratory and field experiments were conducted to investigate the ability of microwave remote sensing systems to detect the moisture status of a silt loam soil exhibiting abrupt changes in moisture content near the surface. Laboratory soil profiles were prepared with a discontinuous moisture boundary in the subsurface. Reflectivity measurements of these profiles were made with a bistatic reflectometer operating over the frequency ranges of 1-2 and 4-8 GHz (wavelength ranges of 30-15 and 7.5-3.75 cm, respectively). These measurements exhibited a well-developed coherent interference pattern in good agreement with a simple two-layer reflectivity model. Field measurements of bare soil surfaces were conducted for initially saturated profiles and continued for extended periods of drying. During drying, coherent interference patterns similar to those observed in the laboratory were detected. These appear to be due to steep moisture gradients occurring between drying layers near the surface. The field results were modeled by a five-segment linear moisture profile with one or two steep segments and a multilayer reflectivity program. Agreement between model and field response over the frequency range was used to estimate the depth of drying layers within the soil. These depths were monitored over the second and third drying cycles. Formation of the drying layers under field conditions appears to be influenced by drying time, tillage, and evaporative demand. In any case, it appears that the coherent effects caused by nonuniform moisture profiles may substantially affect the reflectivity of even rough soil surfaces.

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

    KAUST Repository

    Singh, Gurjeet

    2016-05-05

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

  15. Effect of soil moisture on chlorine deposition.

    Science.gov (United States)

    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. Published by Elsevier B.V.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Jianghao Wang

    2015-09-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  19. Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

    Science.gov (United States)

    A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

    2015-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

  20. Soil moisture needs in earth sciences

    Science.gov (United States)

    Engman, Edwin T.

    1992-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

    results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

  2. Soil Moisture Remote Sensing with GNSS-R at the Valencia Anchor Station. The SOMOSTA (Soil Moisture Station) Experiment

    Science.gov (United States)

    Lopez-Baeza, Ernesto

    2016-07-01

    In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on soil moisture monitoring byGlobal Navigation Satellite System Reflected signals(GNSS-R) at the Valencia Anchor Station is introduced. L-band microwaves have very good advantages in soil moisture remote sensing, for being unaffected by clouds and the atmosphere, and for the ability to penetrate vegetation. During this experimental campaign, the ESA GNSS-R Oceanpal antenna was installed on the same tower as the ESA ELBARA-II passive microwave radiometer, both measuring instruments having similar field of view. This experiment is fruitfully framed within the ESA - China Programme of Collaboration on GNSS-R. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and two down-looking antennas for receiving LHCP (left-hand circular polarisation) and RHCP (right-hand circular polarisation) reflected signals from the soil surface. We could collect data from the three different antennas through the two channels of Oceanpal and, in addition, calibration could be performed to reduce the impact from the differing channels. Reflectivity was thus measured and soil moisture could be retrieved by the L- MEB (L-band Microwave Emission of the Biosphere) model considering the effect of vegetation optical thickness and soil roughness. By contrasting GNSS-R and ELBARA-II radiometer data, a negative correlation existed between reflectivity measured by GNSS-R and brightness temperature measured by the radiometer. The two parameters represent reflection and absorption of the soil. Soil moisture retrieved by both L-band remote sensing methods shows good agreement. In addition, correspondence with in-situ measurements and rainfall is also good.

  3. Quantitative Analysis of Moisture Effect on Black Soil Reflectance

    Institute of Scientific and Technical Information of China (English)

    LIU Huan-Jun; ZHANG Yuan-Zhi; ZHANG Xin-Le; ZHANG Bai; SONG Kai-Shan; WANG Zong-Ming; TANG Na

    2009-01-01

    Several studies have demonstrated that soil reflectance decreases with increasing soil moisture content,or increases when the soil moisture reaches a certain content;however,there are few analyses on the quantitative relationship between soil reflectance and its moisture,especially in the case of black soils in northeast China.A new moisture adjusting method was developed to obtain soil reflectance with a smaller moisture interval to describe the quantitative relationship between soil reflectance and moisture.For the soil samples with moisture contents ranging from air-dry to saturated,the changes in soil reflectance with soil moisture can be depicted using a cubic equation.Both moisture threshold (MT) and moisture inflexion (MI) of soil reflectance can also be determined by the equation.When the moisture range was smaller than MT,soil reflectance can be simulated with a linear model.However,for samples with different soil organic matter (OM),the parameters of the linear model varied regularly with the OM content.Based on their relationship,the soil moisture can be estimated from soil reflectance in the black soil region.

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

    Science.gov (United States)

    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

  5. Remote sensing applied to crop disease control, urban planning, and monitoring aquatic plants, oil spills, rangelands, and soil moisture

    Science.gov (United States)

    1975-01-01

    The application of remote sensing techniques to land management, urban planning, agriculture, oceanography, and environmental monitoring is discussed. The results of various projects are presented along with cost effective considerations.

  6. Soil moisture sensors based on metamaterials

    Directory of Open Access Journals (Sweden)

    Goran Kitić

    2012-12-01

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

  7. The NAFE'05/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation

    DEFF Research Database (Denmark)

    Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse D.

    2008-01-01

    -resolution data from SMOS; and 3) testing its assimilation into land surface models for root zone soil moisture retrieval. This paper describes the NAFE'05 and COSMOS airborne data sets together with the ground data collected in support of both aircraft campaigns. The airborne L-band acquisitions included 40 km x...... was to provide simulated Soil Moisture and Ocean Salinity (SMOS) observations using airborne L-band radiometers supported by soil moisture and other relevant ground data for the following: 1) the development of SMOS soil moisture retrieval algorithms; 2) developing approaches for downscaling the low....... The L-band data were accompanied by airborne thermal infrared and optical measurements. The ground data consisted of continuous soil moisture profile measurements at 18 monitoring sites throughout the 40 km x 40 km study area and extensive spatial near-surface soil moisture measurements concurrent...

  8. Soil moisture and temperature algorithms and validation

    Science.gov (United States)

    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...

  9. Estimating Subcanopy Soil Moisture with RADAR

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  11. Soil and Moisture Plan : 1971 - 1980 : Agassiz National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This Soil and Moisture Plan for Agassiz NWR provides an overview of the Refuge, a description of soil and moisture problems, and proposed solutions to these...

  12. Soil moisture mapping for aquarius

    Science.gov (United States)

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

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

    Science.gov (United States)

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

    2010-05-01

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

  14. Microwave Soil Moisture Retrieval Under Trees

    Science.gov (United States)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2013-04-01

    Technology) ASCAT data sets to identify two types of errors that are spectrally distinct. Based on a semi-empirical model of soil moisture dynamics, we consider possible digital filter designs to improve the accuracy of their soil moisture products by reducing systematic periodic errors and stochastic noise. We describe a methodology to design bandstop filters to remove artificial resonances, and a Wiener filter to remove stochastic white noise present in the satellite data. Utility of these filters is demonstrated by comparing de-noised data against in-situ observations from ground monitoring stations in the Murrumbidgee Catchment (Smith et al., 2012), southeast Australia. Albergel, C., de Rosnay, P., Gruhier, C., Muñoz Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y. H., & Wagner, W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226. Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters, 35, L24403. Smith, A. B., Walker, J. P., Western, A. W., Young, R. I., Ellett, K. M., Pipunic, R. C., Grayson, R. B., Siriwardena, L., Chiew, F. H. S., & Richter, H. (2012). The Murrumbidgee soil moisture network data set. Water Resources Research, 48, W07701. Su, C.-H., Ryu, D., Young, R., Western, A. W., & Wagner, W. (2012). Inter-comparison of microwave satellite soil moisture retrievals over Australia. Submitted to Remote Sensing of Environment.

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

    Directory of Open Access Journals (Sweden)

    M. Zribi

    2011-01-01

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

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

    Science.gov (United States)

    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

  18. Binned level-3 Sea Surface Salinity from the European Space Agency Soil Moisture Ocean Salinity (SMOS) in support of the National Centers for Environmental Information (NCEI) data quality monitoring system (DQMS) from 2010-06-01 to 2016-05-31 (NCEI Accession 0151732)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data quality monitoring system (DQMS) for the Soil Moisture Ocean Salinity (SMOS) satellites level-2 sea surface salinity (SSS) swath data was developed by the...

  19. Impacts of soil moisture content on visual soil evaluation

    Science.gov (United States)

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

    2017-04-01

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

  20. Trends and Scales of Observed Soil Moisture Variations in China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981 1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air (TDSA) are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth.Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers,cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation,whereas in the latter, the spatial scale is controlled by topography.

  1. Use of Soil Moisture Variability in Artificial Neural Network Retrieval of Soil Moisture

    Directory of Open Access Journals (Sweden)

    Bert Veenendaal

    2009-12-01

    Full Text Available Passive microwave remote sensing is one of the most promising techniques for soil moisture retrieval. However, the inversion of soil moisture from brightness temperature observations is not straightforward, as it is influenced by numerous factors such as surface roughness, vegetation cover, and soil texture. Moreover, the relationship between brightness temperature, soil moisture and the factors mentioned above is highly non-linear and ill-posed. Consequently, Artificial Neural Networks (ANNs have been used to retrieve soil moisture from microwave data, but with limited success when dealing with data different to that from the training period. In this study, an ANN is tested for its ability to predict soil moisture at 1 km resolution on different dates following training at the same site for a specific date. A novel approach that utilizes information on the variability of soil moisture, in terms of its mean and standard deviation for a (sub region of spatial dimension up to 40 km, is used to improve the current retrieval accuracy of the ANN method. A comparison between the ANN with and without the use of the variability information showed that this enhancement enables the ANN to achieve an average Root Mean Square Error (RMSE of around 5.1% v/v when using the variability information, as compared to around 7.5% v/v without it. The accuracy of the soil moisture retrieval was further improved by the division of the target site into smaller regions down to 4 km in size, with the spatial variability of soil moisture calculated from within the smaller region used in the ANN. With the combination of an ANN architecture of a single hidden layer of 20 neurons and the dual-polarized brightness temperatures as input, the proposed use of variability and sub-region methodology achieves an average retrieval accuracy of 3.7% v/v. Although this accuracy is not the lowest as comparing to the research in this field, the main contribution is the ability of ANN in

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

    Science.gov (United States)

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

    2013-12-01

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

  3. An inversion method for retrieving soil moisture information from satellite altimetry observations

    Science.gov (United States)

    Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

    2016-04-01

    Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i

  4. NASA Soil Moisture Active Passive (SMAP) Applications

    Science.gov (United States)

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

    2014-05-01

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

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

    Science.gov (United States)

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

    The Soil Moisture Active Passive (SMAP) mission, one of the first-tier missions recommended by the 2007 U.S. National Research Council Committee on Earth Science and Applications from Space, was confirmed in May 2012 by NASA to proceed into Implementation Phase (Phase C) with a planned launch in October 2014. SMAP will produce high-resolution and accurate global maps of soil moisture and its freeze/thaw state using data from a non-imaging synthetic aperture radar and a radiometer, both operating at L-band. Major challenges addressed by the observatory design include: (1) achieving global coverage every 2-3 days with a single observatory; (2) producing both high resolution and high accuracy soil moisture data, including through moderate vegetation; (3) using a mesh reflector antenna for L-band radiometry; (4) minimizing science data loss from terrestrial L-band radio frequency interference; (5) designing fault protection that also minimizes science data loss; (6) adapting planetary heritage avionics to meet SMAP's unique application and data volume needs; (7) ensuring observatory electromagnetic compatibility to avoid degrading science; (8) controlling a large spinning instrument with a small spacecraft; and (9) accommodating launch vehicle selection late in the observatory's development lifecycle.

  6. Traditional and microirrigation with stochastic soil moisture

    Science.gov (United States)

    Vico, Giulia; Porporato, Amilcare

    2010-03-01

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

  7. Spatial variability and its scale dependency of observed and modeled soil moisture under different climate conditions

    Directory of Open Access Journals (Sweden)

    B. Li

    2012-09-01

    Full Text Available Past studies on soil moisture spatial variability have been mainly conducted in catchment scales where soil moisture is often sampled over a short time period. Because of limited climate and weather conditions, the observed soil moisture often exhibited smaller dynamic ranges which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness of in situ soil moisture measurements (from a continuously monitored network across the US, modeled and satellite retrieved soil moisture obtained in a warm season (198 days were examined at large extent scales (>100 km over three different climate regions. The investigation on in situ measurements revealed that their spatial moments strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean across dry, intermediate, and wet climates. These climate specific features were vaguely or partially observable in modeled and satellite retrieved soil moisture estimates, which is attributed to the fact that these two data sets do not have climate specific and seasonal sensitive mean soil moisture values, in addition to lack of dynamic ranges. From the point measurements to satellite retrievals, soil moisture spatial variability decreased in each climate region. The three data sources all followed the power law in the scale dependency of spatial variability, with coarser resolution data showing stronger scale dependency than finer ones. The main findings from this study are: (1 the statistical distribution of soil moisture depends on spatial mean soil moisture values and thus need to be derived locally within any given area; (2 the boundedness of soil

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

    Science.gov (United States)

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

    2014-03-01

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

  9. Radon diffusion coefficients in soils of varying moisture content

    Science.gov (United States)

    Papachristodoulou, C.; Ioannides, K.; Pavlides, S.

    2009-04-01

    Radon is a naturally occurring radioactive gas that is generated in the Earth's crust and is free to migrate through soil and be released to the atmosphere. Due to its unique properties, soil gas radon has been established as a powerful tracer used for a variety of purposes, such as exploring uranium ores, locating geothermal resources and hydrocarbon deposits, mapping geological faults, predicting seismic activity or volcanic eruptions and testing atmospheric transport models. Much attention has also been given to the radiological health hazard posed by increased radon concentrations in the living and working environment. In order to exploit radon profiles for geophysical purposes and also to predict its entry indoors, it is necessary to study its transport through soils. Among other factors, the importance of soil moisture in such studies has been largely highlighted and it is widely accepted that any measurement of radon transport parameters should be accompanied by a measurement of the soil moisture content. In principle, validation of transport models in the field is encountered by a large number of uncontrollable and varying parameters; laboratory methods are therefore preferred, allowing for experiments to be conducted under well-specified and uniform conditions. In this work, a laboratory technique has been applied for studying the effect of soil moisture content on radon diffusion. A vertical diffusion chamber was employed, in which radon was produced from a 226Ra source, was allowed to diffuse through a soil column and was finally monitored using a silicon surface barrier detector. By solving the steady-state radon diffusion equation, diffusion coefficients (D) were determined for soil samples of varying moisture content (m), from null (m=0) to saturation (m=1). For dry soil, a D value of 4.1×10-7 m2s-1 was determined, which increased moderately by a factor of ~3 for soil with low moisture content, i.e. up to m ~0.2. At higher water fractions, a decrease

  10. Spatial and temporal variability of soil electrical conductivity related to soil moisture

    OpenAIRE

    José Paulo Molin; Gustavo Di Chiacchio Faulin

    2013-01-01

    Soil electrical conductivity (ECa) is a soil quality indicator associated to attributes interesting to site-specific soil management such as soil moisture and texture. Soil ECa provides information that helps guide soil management decisions, so we performed spatial evaluation of soil moisture in two experimental fields in two consecutive years and modeled its influence on soil ECa. Soil ECa, moisture and clay content were evaluated by statistical, geostatistical and regression analyses. Semiv...

  11. Modeling Transient Root-zone Soil Moisture Dichotomies in Landscapes with Intermixed Land Covers

    Science.gov (United States)

    Patrignani, A.; Ochsner, T. E.

    2015-12-01

    Although large-scale in situ soil moisture monitoring networks are becoming increasingly valuable research tools, deficiencies of many existing networks include the small spatial support of each station, the low spatial density of stations, and the almost exclusive deployment of stations in grassland vegetation. These grassland soil moisture observations may not adequately represent the real soil moisture patterns in landscapes with intermixed land cover types. The objectives of this study were i) to compare root-zone soil moisture dynamics of two dominant vegetation types across Oklahoma, grassland (observed) and winter wheat cropland (simulated); ii) to relate the soil moisture dynamics of grassland and cropland vegetation using an artificial neural network (ANN) as a transfer function; and iii) to use the resulting ANN to estimate the soil moisture spatial patterns for a landscape of intermixed grassland and wheat cropland. Root-zone soil moisture was represented by plant available water (PAW) in the top 0.8 m of the soil profile. PAW under grassland was calculated from 18 years of soil moisture observations at 78 stations of the Oklahoma Mesonet, whereas PAW under winter wheat was simulated for the same 78 locations using a soil water balance model. Then, we trained an ANN to reproduce the simulated PAW under winter wheat using only seven inputs: day of the year, latitude and longitude, measured PAW under grassland, and percent sand, silt, and clay. The resulting ANN was used, along with grassland soil moisture observations, to estimate the detailed soil moisture pattern for a 9x9 km2 Soil Moisture Active Passive (SMAP) grid cell. The seasonal dynamics of root-zone PAW for grassland and winter wheat were strongly asynchronous, so grassland soil moisture observations rarely reflect cropland soil moisture conditions in the region. The simple ANN approach facilitated efficient and accurate prediction of the simulated PAW under winter wheat, RMSE = 24 mm, using

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

    Science.gov (United States)

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

    2013-01-01

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

  13. Analysis of Joint Masonry Moisture Content Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, Kohta [Building Science Corporation, Westford, MA (United States)

    2015-10-01

    Adding insulation to the interior side of walls of masonry buildings in cold (and wet) climates may cause performance and durability problems. Some concerns, such as condensation and freeze-thaw, have known solutions, but wood members embedded in the masonry structure will be colder (and potentially wetter) after an interior insulation retrofit. Moisture content & relative humidity were monitored at joist ends in historic mass brick masonry walls retrofitted with interior insulation in a cold climate (Zone 5A); data were collected from 2012-2015. Eleven joist ends were monitored in all four orientations. One limitation of these results is that the renovation is still ongoing, with limited wintertime construction heating and no permanent occupancy to date. Measurements show that many joists ends remain at high moisture contents, especially at north- and east-facing orientations, with constant 100% RH conditions at the worst cases. These high moisture levels are not conducive for wood durability, but no evidence for actual structural damage has been observed. Insulated versus non-insulated joist pockets do not show large differences. South facing joists have safe (10-15%) moisture contents. Given the uncertainty pointed out by research, definitive guidance on the vulnerability of embedded wood members is difficult to formulate. In high-risk situations, or when a very conservative approach is warranted, the embedded wood member condition can be eliminated entirely, supporting the joist ends outside of the masonry pocket.

  14. EFFECTS OF SOIL CRUSTING ON SOIL MOISTURE, RUNOFF AND EROSION: FIELD OBSERVATIONS

    Institute of Scientific and Technical Information of China (English)

    Tongxin ZHU

    2002-01-01

    Soil crusting may have significant impacts on infiltration, runoff generation and erosion in agricultural lands or semi-arid and arid soils. The previous investigations on soil crusting were often conducted under simulated rainfall conditions. This study aims to evaluate the effects of soil crusting on soil moisture during inter-storm periods and soil and water losses during storm periods under natural rainfalls. The study site was located in the Loess Plateau of China. Four plots with a uniform slope and size were selected. Soil crusts were kept intact on the two plots throughout the monitoring periods of 1999 and 2000,but were broken after each rain storm event on the other two plots. Soil moisture was measured on all plots with an interval of one week at three depths and total event runoff and sediment discharges were measured in each storm. It was found that no marked difference in soil moisture and runoff exists between the crusted and uncrusted plots. This is because the rapid development of new crusts on the uncrusted plots during the storm events. However, the erosion rate on the uncrusted plots was significantly higher than that on the crusted plots, which was mainly caused by the disturbance of the surface soils on the uncrusted plots. This study questions the effectiveness of a common agricultural practice in the Loess Plateau, hoeing lands after rainfall, in reducing runoff and erosion.

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

    Science.gov (United States)

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

    2011-01-01

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

  16. Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China

    Directory of Open Access Journals (Sweden)

    S. Wang

    2012-08-01

    Full Text Available We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass (Andropogon, subshrub (Artemisia scoparia, shrub (Spiraea pubescens, plantation forest (Robinia pseudoacacia, and crop (Zea mays vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

  17. Stochastic modelling of soil moisture dynamics in a grassland of Qilian Mountain at point scale

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Stochastic modeling of soil moisture dynamics is crucial to the quantitative understanding of plant responses to water stresses, hydrological control of nutrient cycling processes, water competition among plants, and some other ecological dynamics, and thus has become a hotspot in ecohydrology at present. In this paper, we based on the continuously monitored data of soil moisture during 2002-2005 and daily precipitation date of 1992-2006, and tried to make a probabilistic analysis of soil moisture dynamics at point scale in a grassland of Qilian Mountain by integrating the stochastic model improved by Laio and the Monte Carlo method. The results show that the inter-annual variations for the soil moisture patterns at different depths are very significant, and that the coefficient of variance (CV) of surface soil moisture (20 cm) is almost continually kept at about 0.23 whether in the rich or poor rainy years. Interestingly, it has been found that the maximal CV of soil moisture has not always appeared at the surface layer. Comparison of the analytically derived soil moisture probability density function (PDF) with the statistical distribution of the observed soil moisture data suggests that the stochastic model can reasonably describe and predict the soil moisture dynamics of the grassland in Qilian Mountain at point scale. By extracting the statistical information of the historical precipitation data in 1994-2006, and inputting them into the stochastic model, we analytically derived the long-term soil moisture PDF without considering the inter-annual climate fluctuations, and then numerically derived the one when considering the inter-annual fluctuation effects in combination with a Monte-Carlo procedure. It was found that, though the peak position of the probability density distribution significantly moved towards drought when considering the disturbance forces, and its width was narrowed, accordingly its peak value was increased, no significant bimodality was

  18. Analysis of soil moisture variation by forest cover structure in lower western Himalayas, India

    Institute of Scientific and Technical Information of China (English)

    J.v.Tyagi; Nuzhat Qazi; S.P.Rai; M.P.Singh

    2013-01-01

    Soil moisture affects various hydrological processes,including evapotranspiration,infiltration,and runoff.Forested areas in the lower western Himalaya in India constitute the headwater catchments for many hill streams and have experienced degradation in forest cover due to grazing,deforestation and other human activities.This change in forest cover is likely to alter the soil moisture regime and,consequently,flow regimes in streams.The effect of change in forest cover on soil moisture regimes of this dry region has not been studied through long term field observations.We monitored soil matric potentials in two small watersheds in the lower western Himalaya of India.The watersheds consisted of homogeneous land covers of moderately dense oak forest and moderately degraded mixed oak forest.Observations were recorded at three sites at three depths in each watershed at fortnightly intervals for a period of three years.The soil moisture contents derived from soil potential measurements were analyzed to understand the spatial,temporal and profile variations under the two structures of forest cover.The analysis revealed large variations in soil moisture storage at different sites and depths and also during different seasons in each watershed.Mean soil moisture storage during monsoon,winter and summer seasons was higher under dense forest than under degraded forest.Highest soil moisture content occurred at shallow soil profiles,decreasing with depth in both watersheds.A high positive correlation was found between tree density and soil moisture content.Mean soil moisture content over the entire study period was higher under dense forest than under degraded forest.This indicated a potential for soil water storage under well managed oak forest.Because soil water storage is vital for sustenance of low flows,attention is needed on the management of oak forests in the Himalayan region.

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

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

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

  20. Soil salinity and moisture measurement system for grapes field by wireless sensor network

    Directory of Open Access Journals (Sweden)

    M.K. Bhanarkar

    2016-12-01

    Full Text Available Soil moisture and salinity measurement are the essential factors for crop irrigation as well as to increase the yield. Grapes eminence depends on the water volume contents in soil and soil nutrients. Based on these conditions, we determined water demand for best quality of grapes by wireless sensor network (WSN. Using lot of chemical fertilizers increases soil salinity but reduces soil fertility, soil salinity defines electrical conductivity or salty soil. Precise agriculture systems are integrated with multiple sensors to monitor and control the incident. Integrated WSN is designed and developed to measure soil moisture and salinity. ATmega328 microcontroller, XBee and Soil sensors are integrated across the system. This system is more competent, it can be helpful to automatic irrigation system and soil salinity monitoring.

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Yuan Huang

    2015-08-01

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

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

    Science.gov (United States)

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

  4. Remote sensing of vegetation and soil moisture

    Science.gov (United States)

    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.

  5. Spatiotemporal soil and saprolite moisture dynamics across a semi-arid woody plant gradient

    Science.gov (United States)

    Niemeyer, Ryan J.; Heinse, Robert; Link, Timothy E.; Seyfried, Mark S.; Klos, P. Zion; Williams, Christopher J.; Nielson, Travis

    2017-01-01

    Woody plant cover has increased 10-fold over the last 140+ years in many parts of the semi-arid western USA. Woody plant cover can alter the timing and amount of plant available moisture in the soil and saprolite. To assess spatiotemporal subsurface moisture dynamics over two water years in a snow-dominated western juniper stand we compared moisture dynamics horizontally across a discontinuous canopy, and vertically in soil and saprolite. We monitored soil moisture at 15 and 60 cm and conducted periodic electromagnetic induction and electrical resistivity tomography surveys aimed at sensing moisture changes within the root zone and saprolite. Timing of soil moisture dry down at 15 cm was very similar between canopy patches and interspace. Conversely, dry down at 60 cm occurred 22 days earlier in the interspace than under canopy patches. After rainfall, interspaces with more shrubs showed greater increases in soil moisture than interspaces with few shrubs. For the few rainfall events that were large enough to increase soil moisture at 60 cm, increases in moisture occurred almost exclusively below the canopy. Soil water holding capacity from 0 to 150 cm was a primary driver of areas that were associated with the greatest change in distributed electrical conductivity - an indicator of changes in soil moisture - across the growing season. Vegetation was also correlated with a greater seasonal change in electrical conductivity at these depths. The seasonal change in resistivity suggested moisture extraction by juniper well into the saprolite, as deep as 12 m below the surface. This change in deep subsurface resistivity primarily occurred below medium and large juniper trees. This study suggests how tree roots are both increasing infiltration below their canopy while also extracting moisture at depths of upwards of 12 m. Information from this study can help improve our understanding of juniper resilience to drought and the hydrologic impacts of semi-arid land cover

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

    Science.gov (United States)

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

    1980-01-01

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

  7. Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

    Science.gov (United States)

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

    2016-04-01

    Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under

  8. Analysis of Joist Masonry Moisture Content Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, Kohta [Building Science Corporation, Westford, MA (United States)

    2015-10-08

    There are many existing buildings with load-bearing mass masonry walls, whose energy performance could be improved with the retrofit of insulation. However, adding insulation to the interior side of walls of such masonry buildings in cold (and wet) climates may cause performance and durability problems. Some concerns, such as condensation and freeze-thaw have known solutions. But wood members embedded in the masonry structure will be colder (and potentially wetter) after an interior insulation retrofit. Moisture content & relative humidity were monitored at joist ends in historic mass brick masonry walls retrofitted with interior insulation in a cold climate (Zone 5A); data were collected from 2012-2015. Eleven joist ends were monitored in all four orientations. One limitation of these results is that the renovation is still ongoing, with limited wintertime construction heating and no permanent occupancy to date. Measurements show that many joists ends remain at high moisture contents, especially at north- and east-facing orientations, with constant 100% RH conditions at the worst cases. These high moisture levels are not conducive for wood durability, but no evidence for actual structural damage has been observed. Insulated vs. non-insulated joist pockets do not show large differences. South facing joists have safe (10-15%) moisture contents. Given the uncertainty pointed out by research, definitive guidance on the vulnerability of embedded wood members is difficult to formulate. In high-risk situations, or when a very conservative approach is warranted, the embedded wood member condition can be eliminated entirely, supporting the joist ends outside of the masonry pocket.

  9. Developing a Soil Moisture Index for California Grasslands from Airborne Hyperspectral Imagery

    Science.gov (United States)

    Flamme, H. E.; Roberts, D. A.; Miller, D. L.

    2016-12-01

    Soil moisture is a key environmental factor controlling vegetation diversity and productivity, evaporation, transpiration, and rainfall runoff. Despite the contribution of soil moisture to ecological productivity, the hydrologic cycle, and erosion, it is currently not being monitored as accurately or as frequently as other environmental factors. Traditional soil moisture monitoring techniques rely on in situ measurements, which become costly when evaluating areas of unevenly distributed soil characteristics and varying topography. Alternatively, satellite remote sensing, such as passive microwave from SMAP, can provide soil moisture but only at very coarse spatial resolutions. Imagery from the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) has the potential to allow better spatial and temporal monitoring of soil moisture. This study established a relationship between plant available water and hyperspectral reflectance via linear regressions of data from 2013-2015 for two grassland field sites: 1) near Santa Barbara, California, at Coal Oil Point Reserve (COPR) and 2) Airstrip station (AIRS) at UC Santa Barbara's Sedgwick Reserve near Santa Ynez, California. Volumetric soil moisture measurements at 10 cm and 20 cm depths were provided by meteorological stations situated in COPR and AIRS while reflectance data were extracted from AVIRIS. We found strong correlations between plant available water and bands centered at wavelengths 704 nm and 831 nm, which we used to create Hyperspectral Soil Moisture Index (HSMI): 0.38((ρ831-ρ704)/(ρ831+ρ704))-0.02. HSMI demonstrated a coefficient of determination (R2) of 0.71 for linear regressions of reflectance versus plant available water with a lag time of 28 days. We applied HSMI to the AIRS and COPR grasslands for 2011 AVIRIS scenes. Plant available water values predicted by HSMI were 0.039 higher at AIRS and 0.048 higher at COPR than the field measurements at the sites. Differences in grass species, soil

  10. 基于光谱特征空间的农田植被区土壤湿度遥感监测%Soil moisture monitoring of vegetative area in farmland by remote sensing based on spectral feature space

    Institute of Scientific and Technical Information of China (English)

    吴春雷; 秦其明; 李梅; 张宁

    2014-01-01

    土壤湿度遥感动态监测在农业生产中具有重要作用。近年来,多种基于光谱特征空间的土壤水分监测指数被陆续提出,并得到广泛关注和应用,但当前多数监测指数未考虑混合像元的影响。该文针对垂直干旱指数(perpendicular drought index,PDI)在农田植被覆盖区监测精度降低问题,分析了植被覆盖下的PDI误差分布规律,引入垂直植被指数(perpendicular vegetation index,PVI)作为植被覆盖表征量,在PVI-PDI二维空间对PDI模型进行调整,提出了适于植被覆盖的植被调整垂直干旱指数(vegetation adjusted perpendicular drought index, VAPDI),并利用内蒙古明安镇研究区实测土壤湿度数据,对PDI与VAPDI进行了比较和验证。结果表明,在裸土、麦茬、土豆、豇豆4种植被覆盖类型中,PDI与土壤实测含水率的决定系数分别为0.630、0.504、0.571、0.543, VAPDI 与土壤实测含水率的决定系数分别为0.599、0.523、0.602、0.585。VAPDI 在植被区的误差略小于 PDI,一定程度上克服了植被覆盖对监测精度的影响。通过PDI和VAPDI空间分布图的比较也说明,VAPDI对土壤湿度的差别有更好的区分能力,在中尺度土壤表层水分遥感反演方面具有一定的优势。该研究可为农田土壤湿度遥感监测方法选择及监测误差分析提供参考依据。%Dynamic monitoring of soil moisture by remote sensing can play a significant role in agricultural production, weather research, and ecological environment evaluation. In recent years, continuous attention has been focused on the thought that soil moisture information can be extracted from multi-dimensional spectral feature space. A variety of soil moisture monitoring indices have been put forward in succession based on the spectral feature space, and some of them have gotten widespread attention and application such as PDI (perpendicular drought index), an simple

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  13. Soil moisture patterns in a northern coniferous forest

    Science.gov (United States)

    Thomas F. McLintock

    1959-01-01

    The trend of soil moisture during the growing season, the alternate wetting from rainfall and drying during clear weather, determines the amount of moisture available for tree growth and also fixes, in part, the environment for root growth. In much of the northern coniferous region both moisture content and root environment are in turn affected by the hummock-and-...

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

    Science.gov (United States)

    Kanniah, Kasturi; Siang, Kang Chuen

    2016-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  16. effect of soil moisture on trace elements concentrations using ...

    African Journals Online (AJOL)

    H. Sahraoui and M. Hachicha

    2017-01-01

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

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

    Science.gov (United States)

    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. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    Science.gov (United States)

    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).

  19. Remote Monitoring of Near-Surface Soil Moisture Dynamics In Unstable Slopes Using a Low-Power Autonomous Resistivity Imaging System

    Science.gov (United States)

    Chambers, J. E.; Meldrum, P.; Gunn, D.; Wilkinson, P. B.; Uhlemann, S.; Swift, R. T.; Kuras, O.; Inauen, C.; Hutchinson, D.; Butler, S.

    2016-12-01

    ERT monitoring has been demonstrated in numerous studies as an effective means of imaging near surface processes for applications as diverse as permafrost studies and contaminated land assessment. A limiting factor in applying time-lapse ERT for long-term studies in remote locations has been the availability of cost-effective ERT measurement systems designed specifically for monitoring applications. Typically, monitoring is undertaken using repeated manual data collection, or by building conventional survey instruments into a monitoring setup. The latter often requires high power and is therefore difficult to operate remotely without access to mains electricity. We describe the development of a low-power resistivity imaging system designed specifically for remote monitoring, taking advantage of, e.g., solar power and data telemetry. Here, we present the results of two field deployments. The system has been installed on an active railway cutting to provide insights into the effect of vegetation on the moisture dynamics in unstable infrastructure slopes and to gather subsurface information for pro-active remediation measures. The system, comprising 255 electrodes, acquires 4596 reciprocal measurement pairs twice daily during standard operation. In case of severe weather events, the measurement schedule is reactively changed, to gather high temporal resolution data to image rainfall infiltration processes. The system has also been installed along a leaking and marginally stable canal embankment; a less favourable location for remote monitoring, with limited solar power and poor mobile reception. Nevertheless, the acquired data indicated the effectiveness of remedial actions on the canal. The ERT results showed that one leak was caused by the canal and fixed during remediation, while two other "leaks" were shown to be effects of groundwater dynamics. The availability of cost-effective, low-power ERT monitoring instrumentation, combined with an automated workflow of

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

    Science.gov (United States)

    Pan, Feifei; Nieswiadomy, Michael

    2016-11-01

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

  1. Assimilating soil moisture into an Earth System Model

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan

    2017-04-01

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

  2. The global distribution and dynamics of surface soil moisture

    Science.gov (United States)

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

    2017-01-01

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

  3. Enhancing agricultural forecasting using SMOS surface soil moisture retrievals

    Science.gov (United States)

    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...

  4. On bimodality in warm season soil moisture observations

    NARCIS (Netherlands)

    Teuling, A.J.; Uijlenhoet, R.; Troch, P.A.A.

    2005-01-01

    It has recently been suggested that the bimodality in warm season soil moisture observations in Illinois is evidence of a soil moisture-precipitation feedback. Other studies however provide little evidence for a strong feedback in this region. Here we show that seasonality in the meteorological cond

  5. Climate variability effects on spatial soil moisture dynamics

    NARCIS (Netherlands)

    Teuling, A.J.; Hupet, F.; Uijlenhoet, R.; Troch, P.A.

    2007-01-01

    We investigate the role of interannual climate variability on spatial soil moisture variability dynamics for a field site in Louvain-la-Neuve, Belgium. Observations were made during 3 years under intermediate (1999), wet (2000), and extremely dry conditions (2003). Soil moisture variability dynamics

  6. Spatial and temporal variability of soil electrical conductivity related to soil moisture

    Directory of Open Access Journals (Sweden)

    José Paulo Molin

    2013-02-01

    Full Text Available Soil electrical conductivity (ECa is a soil quality indicator associated to attributes interesting to site-specific soil management such as soil moisture and texture. Soil ECa provides information that helps guide soil management decisions, so we performed spatial evaluation of soil moisture in two experimental fields in two consecutive years and modeled its influence on soil ECa. Soil ECa, moisture and clay content were evaluated by statistical, geostatistical and regression analyses. Semivariogram models, adjusted for soil moisture, had strong spatial dependence, but the relationship between soil moisture and soil ECa was obtained only in one of the experimental fields, where soil moisture and clay content range was higher. In this same field, coefficients of determinations between soil moisture and clay content were above 0.70. In the second field, the low soil moisture and clay content range explain the absence of a relationship between soil ECa and soil moisture. Data repetition over the years, suggested that ECa is a qualitative indicator in areas with high spatial variability in soil texture.

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

    Science.gov (United States)

    Goodchild, Martin; Kühn, Karl; Jenkins, Dick

    2014-05-01

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

  8. Estimating soil moisture distribution using polarimetric airborne SAR

    Science.gov (United States)

    Tadono, Takeo; Qong, Muhtar; Wakabayashi, Hiroyuki; Shimada, Masanobu; Shi, Jiancheng

    2000-12-01

    The goal of this study is to develop an algorithm for estimating the surface soil moisture and surface roughness using polarimetric Synthetic Aperture Radar (SAR) data. In this study, an algorithm was applied to polarimetric airborne SAR data to estimate distributions of surface soil moisture and roughness. To validate the estimated soil moisture, we simultaneously conducted an experiment in October 1999 in Tsukuba Science City, Ibaragi Prefecture of Japan. Surface soil moisture was obtained by the Time- Domain Reflectometry (TDR) method, and the horizontal profiles of the land surface height were measured by a comb- style instrument for calculating the surface roughness parameters in test sites. Because the problem is site- specific and depends upon the measurement accuracy of both the ground truth data, the SAR system including speckle noise, and the effects of vegetation and artificial constructions, such as buildings, houses, roads, and roadside trees, the comparison results did not agree well with measured and inferred soil moisture.

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

    Science.gov (United States)

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

  10. COSMOS: The COsmic-ray Soil Moisture Observing System

    Directory of Open Access Journals (Sweden)

    M. Zreda

    2012-04-01

    Full Text Available Area-average soil moisture at the sub-kilometer scale is needed but until the advent of the cosmic-ray method (Zreda et al., 2008, it was difficult to measure. This new method is now being implemented routinely in the COsmic-ray Soil Moisture Observing System (or COSMOS. The stationary cosmic-ray soil moisture probe (sometimes called "neutronavka" measures the neutrons that are generated by cosmic rays within air and soil, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. COSMOS has already deployed 53 of the eventual 500 neutronavkas distributed mainly in the USA, each generating a time series of average soil moisture over its hectometer horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in COSMOS, and give example time series of soil moisture obtained from COSMOS probes.

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

    Directory of Open Access Journals (Sweden)

    M. Zreda

    2012-11-01

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

  12. Spectrum properties analysis of different soil moisture content

    Science.gov (United States)

    Fang, Shenghui; Hu, Bo; Lin, Fan

    2009-10-01

    Soil moisture content is one of the most important factors in soil business. The basic of detecting soil moisture content using remote sensing technology is to analyze the relationship between soil moisture content and emissivity. In this paper, based on the analysis of spectrum collection and processing by a portable spectrometer, a set of measure schemes were first established which can accurately measure the reflectivity and emissivity of soil spectrum with different moisture content in near-infrared and thermal infrared bands. Then we selected different bare soil areas as the areas for survey, and studied the relationship of different moisture content and the spectrum curve in the soil both of the same kind and of different kind (like the soil whose structure has been modified caused by the change of organic matter contents or soil particle size). Finally, we emphasized on the quantitative relationship between soil reflectivity & emissivity and soil moisture content using the test data, and establish a model depicting the quantitative relationship above in near-infrared and thermal infrared bands.

  13. Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

    2014-07-01

    Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

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

    Directory of Open Access Journals (Sweden)

    Cécile ePellet

    2016-01-01

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

  15. The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications

    Directory of Open Access Journals (Sweden)

    Wolfgang Wagner

    2013-02-01

    Full Text Available Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm, its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in

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

    Science.gov (United States)

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

    2017-09-01

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

  17. Estimation of soil moisture in paddy field using Artificial Neural Networks

    CERN Document Server

    Arif, Chusnul; Setiawan, Budi Indra; Doi, Ryoichi

    2013-01-01

    In paddy field, monitoring soil moisture is required for irrigation scheduling and water resource allocation, management and planning. The current study proposes an Artificial Neural Networks (ANN) model to estimate soil moisture in paddy field with limited meteorological data. Dynamic of ANN model was adopted to estimate soil moisture with the inputs of reference evapotranspiration (ETo) and precipitation. ETo was firstly estimated using the maximum, average and minimum values of air temperature as the inputs of model. The models were performed under different weather conditions between the two paddy cultivation periods. Training process of model was carried out using the observation data in the first period, while validation process was conducted based on the observation data in the second period. Dynamic of ANN model estimated soil moisture with R2 values of 0.80 and 0.73 for training and validation processes, respectively, indicated that tight linear correlations between observed and estimated values of s...

  18. GNSSProbe, penetrating GNSS signals for measuring soil moisture

    Science.gov (United States)

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

    2016-04-01

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

  19. Soil moisture and potential measurements in NW Italy

    Science.gov (United States)

    Ferraris, Stefano; Canone, Davide; Previati, Maurizio

    2015-04-01

    The vertical variability of soil moisture in the rootzone is a key factor and it is not taken into account in many hydrological models. Therefore it is here proposed a novel approach that is based on the inversion of a semianalytical solution of the equation governing the infiltration and the exfiltration processes. The inversion allows keeping the information contained in the vertical spatial variability. It has been monitored with TDR measurements down to 2 meters depth. Also, the hysteresis and dynamical effects are then taken into account, with water potential measurements, in order to correctly predict the water retention both in infiltration and in drainage/exfiltration transients. References M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). Soil water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009

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

    OpenAIRE

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

    2013-01-01

    Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The “open field” soil gas vapor concentration profile is observed to be sensitive to the soil moisture di...

  1. Soil moisture initialization effects in the Indian monsoon system

    OpenAIRE

    Asharaf, S.; A. Dobler; Ahrens, B.

    2011-01-01

    Towards the goal to understand the role of land-surface processes over the Indian sub-continent, a series of soil-moisture sensitivity simulations have been performed using a non-hydrostatic regional climate model COSMO-CLM. The experiments were driven by the lateral boundary conditions provided by the ERA-Interim (ECMWF) reanalysis. The simulation results show that the pre-monsoonal soil moisture has a significant influence on the monsoonal precipitation. Both, positive and negative soil-moi...

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

    Science.gov (United States)

    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

  3. Performance of AMSR_E soil moisture data assimilation in CLM4.5 model for monitoring hydrologic fluxes at global scale

    Science.gov (United States)

    Liu, Di; Mishra, Ashok K.

    2017-04-01

    In this study, we evaluated the performance of community land surface model (CLM4.5) to simulate the hydrologic fluxes, such as, soil moisture (SM), evapotranspiration (ET) and runoff with (without) remote sensing data assimilation. The Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR_E) daily SM (both ascending and descending) are incorporated into the CLM4.5 model using data assimilation (DA) technique. The GLDAS data is used to validate the AMSR_E SM data and evaluate the performance of CLM4.5 simulations. The AMSR_E SM data are rescaled to meet the resolution of CLM4.5 model. By assimilating the AMSR_E SM data into the CLM4.5 model can improve the SM simulations, especially over the climate transition zones in Africa, East Australia, South South America, Southeast Asia, and East North America in summer season. The Local Ensemble Kalman Filter (LEnKF) technique improves the performance of CLM4.5 model compared to the directly substituted method. The improvement in ET and surface runoff simulations from CLM4.5 model assimilated with AMSR_E SM data shares similar spatial patterns with SM.

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

    Science.gov (United States)

    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.

  5. Exploiting optical E.O. data for soil moisture retrieval

    Science.gov (United States)

    Richter, Katja; D'Urso, Guido; Palladino, Mario; Vuolo, Francesco

    2008-10-01

    In the context of agricultural applications, the knowledge of soil moisture availability is an essential aspect for irrigation management. The microwave waveband region (SAR) has been primarily used to estimate soil moisture from Earth Observation (E.O.) data. However, the optical domain (0.4 - 2.5 μm) may as well offer the possibility to get information about soil moisture since an overall decrease of soil reflectance corresponds to increasing surface soil water content. Data from two different experiments (ESA SPARC and AgriSAR) have been exploited aiming at estimating soil moisture from optical E.O. data by using the radiative transfer model PROSAILH. A soil scale factor (α) was introduced into the model and estimated using a LUT inversion technique. Relatively high negative relationships between the α-factor and the measured soil water content (up to R2 = 0.73) could be found for several crop types with low vegetation cover. The results of this study indicate the potential to retrieve surface soil moisture information from optical E.O. data for similar soil types. The method gives the advantage of retrieving simultaneously soil and canopy characteristics from the same E.O. data sources by using a physical method of parameter estimation.

  6. The influence of soil moisture deficits on Australian heatwaves

    Science.gov (United States)

    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.

  7. Elimination of the soil moisture effect on the spectra for reflectance prediction of soil salinity using external parameter orthogonalization method

    Science.gov (United States)

    Peng, Xiang; Xu, Chi; Zeng, Wenzhi; Wu, JingWei; Huang, JieSheng

    2016-01-01

    Soil salinization is a common desertification process, especially in arid lands. Hyperspectral remote sensing of salinized soil is favored for its advantages of being efficient and inexpensive. However, soil moisture often jointly has a great influence on the soil reflectance spectra under field conditions. It is a challenge to establish a model to eliminate the effect of soil moisture and quantitatively estimate the salinity contents of slightly and moderately salt-affected soil. A controlled laboratory experiment was conducted by way of continuously monitoring changes of soil moisture and salt content, which was mainly focused on the slightly and moderately salt-affected soil. We investigated the external parameter orthogonalization (EPO) method to remove the effect of soil moisture (4 to 36% in weight base) by preprocessing soil spectral reflectance and establishing the partial least squares regression after EPO preprocessing model (EPO-PLS) to predict soil salt content. Through comparing PLS with EPO-PLS model, R2 and ratio of prediction to deviation rose from 0.604 and 1.063, respectively, to 0.874 and 2.865 for validation data. Root mean square error and bias were, respectively, reduced from 1.163 and 0.141 g/100 g to 0.718 and 0.044 g/100 g. The performance of the model after EPO algorithm preprocessing was improved significantly.

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

    Science.gov (United States)

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

    2009-12-01

    Soil Moisture is an important variable in hydrological cycle. It plays a vital role in agronomy, meteorology, and hydrology. In spite of being an important variable, soil moisture measuring stations are sparse. This is due to high cost involved in the installation of dense network of measuring stations required to map a comprehensive spatio-temporal behavior of soil moisture. Hence, there is a need to develop an alternate method to measure soil moisture. This research relates soil moisture (SM) to backscatter (σ°) obtained from Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) and Normalized Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer. SM data is obtained from Soil Climate Analysis Network (SCAN). σ° measurements are normalized at an incidence angle of 10° at which it has the highest sensitivity to SM. An empirical model that relates SM to normalized σ° and NDVI is developed. NDVI takes into account the different vegetation densities. The relationship between model variables is approximated to be linear. The model is applied to data from 1998 to 2008 where 75% of the data is used for calibration and the remaining 25% for validation. Figure 1 shows the comparison of observed and modeled soil moisture for a site with low vegetation. Even though the model underestimates the soil moisture content, it captures the signal well and produces peaks similar to the observed soil moisture. The model performs well with a correlation of 0.71 and root mean square error of 4.0%. The accuracy of the model depends on vegetation density. Table 1 summarizes the model performance for different vegetation densities. The model performance decreases with the increase in vegetation as the leaves in the vegetation canopy attenuate the incident microwaves which reduces the penetration depth and subsequently the sensitivity to soil moisture. This research provides a new insight into the microwave remote sensing of soil

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

    Science.gov (United States)

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

    2015-12-01

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

  10. Predicting Soil Moisture in the Field from Amplitude Temperature

    Science.gov (United States)

    Al-Kayssi, A. W.

    2009-04-01

    Measurements of amplitude temperature and soil moisture content of sandy loam and silty clay loam soils were conducted in Al-Mada'in Research Station south of Baghdad during the period from the 1st of February to the 30th of April, 2004. Exponential regression relations were developed between amplitude temperature and volumetric moisture content for soil depths of 0.5, 3.0, 7.5 and 15cm below surface, which was highly significant (R2>0.96). A good linear regression between measured and predicted soil moisture contents was deduced for each depth (r>0.97). Soil moisture content was successfully predicted from the regression line when amplitude temperature was known.

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

    Science.gov (United States)

    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

  12. Soil moisture sensor calibration for organic soil surface layers

    Directory of Open Access Journals (Sweden)

    S. Bircher

    2015-12-01

    Full Text Available 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 Sodankyl

  13. Soil moisture sensor calibration for organic soil surface layers

    Science.gov (United States)

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

    2016-04-01

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

  14. Impacts of Soil Moisture Content and Vegetation on Shear Strength of Unsaturated Soil

    Institute of Scientific and Technical Information of China (English)

    YANG Yong-hong; ZHANG Jian-guo; ZHANG Jian-hui; LIU Shu-zhen; WANG Cheng-hua; XIAO Qing-hua

    2005-01-01

    It is analyzed that the impacts of vegetation type and soil moisture content on shear strength of unsaturated soil through direct shearing tests for various vegetation types, different soil moisture contents and different-depth unsaturated soil. The results show that the cohesion of unsaturated soil changes greatly, and the friction angle changes a little with soil moisture content. It is also shown that vegetation can improve shear strength of unsaturated soil, which therefore provides a basis that vegetation can reinforce soil and protect slopes.

  15. Analog modeling of transient moisture flow in unsaturated soil

    NARCIS (Netherlands)

    Wind, G.P.

    1979-01-01

    Hydraulic and electronic analog models are developed for the simulation of moisture flow and accumulation in unsaturated soil. The analog models are compared with numerical models and checked with field observations. Application of soil physical knowledge on a soil technological problem by means of

  16. A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

    Science.gov (United States)

    Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

  17. Estimation of soil moisture in paddy field using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Chusnul Arif

    2012-04-01

    Full Text Available In paddy field, monitoring soil moisture is required for irrigation scheduling and water resource allocation, management and planning. The current study proposes an Artificial Neural Networks (ANN model to estimate soil moisture in paddy field with limited meteorological data. Dynamic of ANN model was adopted to estimate soil moisture with the inputs of reference evapotranspiration (ETo and precipitation. ETo was firstly estimated using the maximum, average and minimum values of air temperature as the inputs of model. The models were performed under different weather conditions between the two paddy cultivation periods. Training process of model was carried out using the observation data in the first period, while validation process was conducted based on the observation data in the second period. Dynamic of ANN model estimated soil moisture with R2 values of 0.80 and 0.73 for training and validation processes, respectively, indicated that tight linear correlations between observed and estimated values of soil moisture were observed. Thus, the ANN model reliably estimates soil moisture with limited meteorological data.

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

    Science.gov (United States)

    Fontes, Adan Fimbres

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

  19. Precipitation and soil impacts on partitioning of subsurface moisture in Avena barbata: Observations from a greenhouse experiment

    Energy Technology Data Exchange (ETDEWEB)

    Salve, R.; Torn, M.S.

    2011-03-01

    The primary objective of this study was to assess the impact of two grassland soils and precipitation regimes on soil-moisture dynamics. We set up an experiment in a greenhouse, and monitored soil moisture dynamics in mesocosms planted with Avena barbata, an annual species found in California grasslands. By repeating the precipitation input at regular intervals, we were able to observe plant manipulation of soil moisture during well-defined periods during the growing season. We found that the amount of water partitioned to evapotranspiration, seepage, and soil storage varied among different growth stages. Further, both soil type and precipitation regimes had a significant impact on redistributing soil moisture. Whereas in the low-precipitation treatments most water was released to the atmosphere as evapotranspiration, major losses from the high-precipitation treatment occurred as gravity drainage. Observations from this study emphasize the importance of understanding intra-seasonal relationships between vegetation, soil, and water.

  20. Downscaling soil moisture using multisource data in China

    Science.gov (United States)

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

    2016-10-01

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

  1. Using GPS Interferometric Reflectometry to estimate soil moisture and vegetation water content fluctuations

    Science.gov (United States)

    Chew, C. C.; Small, E. E.; Larson, K. M.; Braun, J. J.; Shreve, C. M.

    2010-12-01

    High-precision GPS receivers can be used to estimate fluctuations in near surface soil moisture, snow and vegetation water content. This approach, referred to as GPS-Interferometric Reflectometry (GPS-IR), relates precise changes in the geometry of reflected GPS signals to observe soil moisture and snow while simultaneously using signal attenuation and diffuse scattering to infer changes in vegetative state. Previous remote sensing research has shown that microwave signals (e.g., L-band) are optimal for measuring hydrologic variables, such as soil moisture, and because GPS satellites transmit similar signals, they can be useful for sensing water in the environment. In addition, standard GPS antenna configurations that are used in NSF's Plate Boundary Observatory network yield sensing footprints of ~1000 m2. Given this sensitivity, hundreds of GPS receivers that exist in the U.S. could be used to provide near-real time estimates of soil moisture and vegetation water content for satellite validation, drought monitoring and related studies. A significant obstacle to using L-band (or similar) signals for remote sensing is differentiating the effects of soil moisture and vegetation on the retrieval of hydrologic variables. This same challenge exists when using GPS-IR data. We have established nine research sites with identical GPS and hydrologic infrastructure to study this problem. These sites span a wide range of soil, vegetation, and climate types. In addition to daily GPS and hourly soil moisture data, we have collected weekly vegetation water content samples at all sites. Our data demonstrate that soil moisture fluctuations can be estimated from GPS-IR records when vegetation water content is low (moisture and vegetation signals and quantifying errors in our retrieval algorithm.

  2. Evaluation of satellite soil moisture products over Norway using ground-based observations

    Science.gov (United States)

    Griesfeller, A.; Lahoz, W. A.; Jeu, R. A. M. de; Dorigo, W.; Haugen, L. E.; Svendby, T. M.; Wagner, W.

    2016-03-01

    In this study we evaluate satellite soil moisture products from the advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over Norway using ground-based observations from the Norwegian water resources and energy directorate. The ASCAT data are produced using the change detection approach of Wagner et al. (1999), and the AMSR-E data are produced using the VUA-NASA algorithm (Owe et al., 2001, 2008). Although satellite and ground-based soil moisture data for Norway have been available for several years, hitherto, such an evaluation has not been performed. This is partly because satellite measurements of soil moisture over Norway are complicated owing to the presence of snow, ice, water bodies, orography, rocks, and a very high coastline-to-area ratio. This work extends the European areas over which satellite soil moisture is validated to the Nordic regions. Owing to the challenging conditions for soil moisture measurements over Norway, the work described in this paper provides a stringent test of the capabilities of satellite sensors to measure soil moisture remotely. We show that the satellite and in situ data agree well, with averaged correlation (R) values of 0.72 and 0.68 for ASCAT descending and ascending data vs in situ data, and 0.64 and 0.52 for AMSR-E descending and ascending data vs in situ data for the summer/autumn season (1 June-15 October), over a period of 3 years (2009-2011). This level of agreement indicates that, generally, the ASCAT and AMSR-E soil moisture products over Norway have high quality, and would be useful for various applications, including land surface monitoring, weather forecasting, hydrological modelling, and climate studies. The increasing emphasis on coupled approaches to study the earth system, including the interactions between the land surface and the atmosphere, will benefit from the availability of validated and improved soil moisture satellite datasets, including those

  3. Quasi-quantitative relationship between soil moisture and polarization characteristics

    Institute of Scientific and Technical Information of China (English)

    ZHANG Qiao; SUN Xiaobing; LI Ya'nan; QIAO Yanli

    2010-01-01

    Besides amplitude, frequency and phase, the polarization is another basic property of the electromagnetic wave. In the remote sensing field, the polarization is mainly applied in active detection systems of radar and iidar. This paper presents the quantitative relationship between soil moisture and polarization signatures in a certain type of soil in a farm. And this relationship is expected to be introduced on agriculture and hydrology ultimately. The experiments were performed both in the laboratory and the field. Soil samples with different moisture contents were measured at three wavebands on visible spectrum,and at several viewing angles in the plane of incidence. The polarization signature was indicated by the multi-band and multi-angle degree of linear polarization (DOLP) in this paper. The soil moisture were divided into five levels according to the properties of DOLP curves, namely, the quasi-quantitative relationship between soil moisture and its polarization signature were established. The percentages of soil moisture of the five levels are:≤10%, 10%-20%, 20%-40%, 40%-56% and >56%,respectively. Although this division for soil moisture is on a rather large scale, it will meet the precision of application agricultural and hydrologic remote sensing.

  4. Evaluating Soil Moisture Status Using an e-Nose

    Directory of Open Access Journals (Sweden)

    Andrzej Bieganowski

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2016-03-15

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

  6. [Variation characteristics of soil moisture in apple orchards of Luochuan County, Shaanxi Province of Northwest China].

    Science.gov (United States)

    Wang, Yan-Ping; Han, Ming-Yu; Zhang, Lin-Sen; Dang, Yong-Jian; Qu, Jun-Tao

    2012-03-01

    To have an overall understanding on the soil moisture characteristics in the apple orchards of Luochuan County can not only provide theoretical basis for selecting apple orchard sites, choosing the best root-stock combination, and improving the soil water management, but also has reference importance in increasing the productive efficiency of our apple orchards. In this study, a fixed-point continuous monitoring was conducted on the overall soil moisture environment and the variation characteristics of soil moisture in the County apple orchards differed in age class, stand type, and tree type (standard or dwarfed). For the apple orchards in the County, the rhizosphere (0-200 cm) soils of most apple trees were water-deficient, and the deficit in 0-60 cm soil layer was less than that in 60-200 cm layer. During growth season, the water storage in 0-60 cm soil layer had the same variation trend as the rainfall pattern. The relative soil moisture content in most orchards was less than 60% , and seasonal drought was quite severe. The coefficient of variation of soil moisture content decreased with soil depth. With the increasing age of the orchards, soil water storage decreased. At the same planting density, the orchards with dwarfed trees had more water storage in 0-5 m soil layer than the orchards with standard trees. However, when the orchards were planted with dwarfed trees at a higher density, the soil water storage in the orchards with dwarfed trees was lesser than that in the standard orchards. The mature orchards on highland had the highest soil moisture content, followed by the mature orchards on flat land, and on terraced land. Tree density had great effects on the soil moisture content. When the tree density was the same, planting dwarfed trees could decrease the water consumption, and increase the soil moisture content significantly. To decrease the planting density through the removal of trees would be an effective way to maintain the soil water balance of

  7. SMAP Level 4 Surface and Root Zone Soil Moisture

    Science.gov (United States)

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

    2017-01-01

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

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

    Data.gov (United States)

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

  9. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

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

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...... height from coand cross-polarized ratio, have been examined, but the results are less satisfactory. As soil moisture response to backscattering coefficient σo is mainly coupled to surface roughness effect for bare fields, a bilinear model coupling volumetric soil moisture mv and surface rms height σ...

  10. Soil Moisture for Western Russia and The Ukraine

    Data.gov (United States)

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

  11. Climate variability effects on spatial soil moisture dynamics

    OpenAIRE

    A. J. Teuling; Hupet, F.; R. Uijlenhoet; P. A. Troch

    2007-01-01

    We investigate the role of interannual climate variability on spatial soil moisture variability dynamics for a field site in Louvain-la-Neuve, Belgium. Observations were made during 3 years under intermediate (1999), wet (2000), and extremely dry conditions (2003). Soil moisture variability dynamics are simulated with a comprehensive model for the period 1989-2003. The results show that climate variability induces non-uniqueness and two distinct hysteresis modes in the yearly relation between...

  12. Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

    Science.gov (United States)

    Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

    2017-04-01

    From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    O. Shamir

    2016-06-01

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

  15. Determining soil moisture by assimilating soil temperature measurements using the Ensemble Kalman Filter

    Science.gov (United States)

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

    2015-12-01

    This study investigates the potential to estimate the vertical profile of soil moisture by assimilating temperature observations at a limited number of depths into a coupled heat and moisture transport model (Hydrus-1D). The method is developed with a view to assimilating temperature data from distributed temperature sensing (DTS) to estimate soil moisture at high resolution over large areas. The correlation between temperature and soil moisture in the shallow soil (top ∼ 50 cm) ensures that soil moisture can be estimated using just soil temperature observations. Synthetic tests across a range of soil textures show that with data assimilation both modeled temperature and the moisture profile are improved considerably compared to the ensemble open loop model simulations. In addition, employing data assimilation provides a means to quantitatively account for different sources of uncertainty. This is particularly relevant in the context of DTS given the influence of spatial variability in soil texture and its impact on estimation error. The data assimilation approach could also be used to determine, the number of temperature observations required and the depths at which they should be made. Results suggest that temperature observed at two depths is typically sufficient to estimate soil moisture using this approach. The root mean square error (RMSE) in soil moisture was reduced by up to 75% in the top 20 cm. Furthermore, this approach solves many of the challenges identified in the application of an inversion approach to estimate soil moisture from DTS.

  16. THE CLAY CONTENT EFFECT ON THE FORMATION OF SHALLOW MOLE DRAINAGE AND THE RATE OF LOWERING SOIL MOISTURE CONTENT

    Directory of Open Access Journals (Sweden)

    Siti Suharyatun

    2014-10-01

    loam soil did not infl uence the rate of lowering soil moisture content. Contrary, the mole drainage installed in clay soil has effected to increase the rate of lowering soil moisture content. Keywords: Mole drainage, soil moisture content, clay content

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

    Science.gov (United States)

    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 ( sampling events during 80 days. In both case we

  18. Gully Impact on Soil Moisture in the Gully Bank

    Institute of Scientific and Technical Information of China (English)

    ZHENG Ji-Yong; WANG Li-Mei; SHAO Ming-An; WANG Quan-Jiu; LI Shi-Qing

    2006-01-01

    In order to preliminarily look at rules for soil moisture changes in the bank of the gully and to provide some recommendations for vegetative restoration in gully bank regions in the Loess Plateau, changes of soil moisture with depth and distance to the gully edge and their dynamic changes with time were observed to study the soil water characteristics in the bank of the gully. The results showed that soil water content increased with increasing distance from the gully edge, whereas for the same time period, the closer the distance to the gully wall, the greater the water loss; and that the influential distance of side evaporation decreased as depth increased.

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

    Science.gov (United States)

    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

  20. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    Science.gov (United States)

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

    2015-07-21

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

  1. Stemflow of desert shrub and its significance in soil moisture replenishment

    Directory of Open Access Journals (Sweden)

    X.-P. Wang

    2010-08-01

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

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

    Science.gov (United States)

    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...

  3. A Comprehensive Laboratory Study to Improve Ground Truth Calibration of Remotely Sensed Near-Surface Soil Moisture

    Science.gov (United States)

    Babaeian, E.; Tuller, M.; Sadeghi, M.; Sheng, W.; Jones, S. B.

    2016-12-01

    Optical satellite and airborne remote sensing (RS) have been widely applied for characterization of large-scale surface soil moisture distributions. However, despite the excellent spatial resolution of RS data, the electromagnetic radiation within the optical bands (400-2500 nm) penetrates the soil profile only to a depth of a few millimeters; hence obtained moisture estimates are limited to the soil surface region. Furthermore, moisture sensor networks employed for ground truth calibration of RS observations commonly exhibit very limited spatial resolution, which consequently leads to significant discrepancies between RS and ground truth observations. To better understand the relationship between surface and near-surface soil moisture, we employed a benchtop hyperspectral line-scan imaging system to generate high resolution surface reflectance maps during evaporation from soil columns filled with source soils covering a wide textural range and instrumented with a novel time domain reflectometry (TDR) sensor array that allows monitoring of near surface moisture at 0.5-cm resolution. A recently developed physical model for surface soil moisture predictions from shortwave infrared reflectance was applied to estimate surface soil moisture from surface reflectance and to explore the relationship between surface and near-surface moisture distributions during soil drying. Preliminary results are very promising and their applicability for ground truth calibration of RS observations will be discussed.

  4. Study of soil moisture sensor for landslide early warning system: Experiment in laboratory scale

    Science.gov (United States)

    Yuliza, E.; Habil, H.; Munir, M. M.; Irsyam, M.; Abdullah, M.; Khairurrijal

    2016-08-01

    The high rate of rainfall is the main trigger factor in many cases of landslides. However, each type of soils has unique characteristics and behavior concerning the rainfall infiltration. Therefore, early warning system of landslide will be more accurate by monitoring the changes of ground water condition. In this study, the monitoring of ground water changes was designed by using soil moisture sensor and simple microcontroller for data processing. The performance of soil moisture sensor was calibrated using the gravimetric method. To determine the soil characteristic and behavior with respect to water content that induce landslides, an experiment involving small-scale landslide model was conducted. From these experiments, the electric resistance of the soil increased as soil water content increases. The increase of soil water content led to the rise of the pore pressure and soil weight which could cause soil vulnerability to the movement. In addition, the various soil types were used to determine the responses of soils that induce the slope failure. Experimental results showed that each type of soils has different volumetric water content, soil matrix suction and shear strength of the slope. This condition influenced the slope stability that trigger of landslide.

  5. Evaluation of soil moisture by bistatic microwave remote sensing

    Science.gov (United States)

    Singh, K. P.; Sharma, S. K.

    1992-07-01

    Bistatic outdoor measurements of soil moisture at X-band of microwave frequencies are reported in this paper. The moisture content in the soil greatly affects the dielectric constant and the loss tangent of the composite material and hence the response to microwave signals are also affected. In turn, it has been observed to reflect, in our measurements, on the following derived cognisable parameters, namely, scattering cross-section, and brightness temperature. These parameters are seen to depend, besides moisture content on incidence angle, polarization and surface roughness too. The importance of these outdoor measurements are shown in microwave remote sensing. Limitations of our measurements are also outlined.

  6. Evaluation of uncertainty in field soil moisture estimations by cosmic-ray neutron sensing

    Science.gov (United States)

    Scheiffele, Lena Maria; Baroni, Gabriele; Schrön, Martin; Ingwersen, Joachim; Oswald, Sascha E.

    2017-04-01

    Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter

  7. Employing satellite retrieved soil moisture for parameter estimation of the hydrologic model mHM

    Science.gov (United States)

    Zink, Matthias; Mai, Juliane; Rakovec, Oldrich; Schrön, Martin; Kumar, Rohini; Schäfer, David; Samaniego, Luis

    2016-04-01

    Hydrological models are usually calibrated against observed streamflow at the catchment outlet and thus they are conditioned by an integral catchment signal. Rakovec et al. 2016 (JHM) recently demonstrated that constraining model parameters against river discharge is a necessary, but not a sufficient condition. Such a procedure ensures the fulfillment of the catchment's water balance but can lead to high predictive uncertainties of model internal states, like soil moisture, or a lack in spatial representativeness of the model. However, some hydrologic applications, as e.g. soil drought monitoring and prediction, rely on this information. Within this study we propose a framework in which the mesoscale Hydrologic Model (mHM) is calibrated with soil moisture retrievals from various sources. The aim is to condition the model on soil moisture (SM), while preserving good performance in streamflow estimation. We identify the most appropriate objective functions by conducting synthetic experiments. The best objective function is determined based on: 1) deviation between synthetic and simulated soil moisture, 2) nonparametric comparison of SM fields (e.g. copulas), and 3) by euclidian distance of model parameters, which is zero if the parameters of the synthetic data are recovered. Those objective functions performing best are used to calibrate mHM against different satellite soil moisture products, e.g. ESA-CCI, H-SAF, and in situ observations. This procedure is tested in three distinct European basins (upper Sava, Neckar, and upper Guadalquivir basin) ranging from snow domination to semi arid climatic conditions. Results obtained with the synthetic experiment indicate that objective functions focusing on the temporal dynamics of SM are preferable to objective functions aiming at spatial patterns or catchment averages. Since the deviation of soil moisture fields (1) and their copulas (2) don't lead to conclusive results, the decision of the best performing objective

  8. Indirect Measurement of Evapotranspiration from Soil Moisture Depletion

    Science.gov (United States)

    Li, M.; Chen, Y.

    2007-12-01

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

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

    Science.gov (United States)

    Dijkstra, F. A.; Cheng, W.

    2005-12-01

    While it is well known that soil moisture directly affects microbial activity and soil C decomposition, it is unclear if the presence of plants alters these effects through rhizosphere processes. We studied soil moisture effects on soil C decomposition with and without sunflower and soybean. Plants were grown in two different soil types with soil moisture contents of 45 and 85% of field capacity in a greenhouse experiment. We continuously labeled plants with depleted 13C, which allowed us to separate plant-derived CO2-C from original soil-derived CO2-C in soil respiration measurements. We observed an overall increase in soil-derived CO2-C efflux in the presence of plants (priming effect) in both soils with on average a greater priming effect in the high soil moisture treatment (60% increase in soil-derived CO2-C compared to control) than in the low soil moisture treatment (37% increase). Greater plant biomass in the high soil moisture treatment contributed to greater priming effects, but priming effects remained significantly higher after correcting for plant biomass. Possibly, root exudation of labile C may have increased more than plant biomass and may have become more effective in stimulating microbial decomposition in the higher soil moisture treatment. Our results indicate that changing soil moisture conditions can significantly alter rhizosphere effects on soil C decomposition.

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

    Science.gov (United States)

    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.

  11. Can soil moisture be mapped onto the terrain?

    Directory of Open Access Journals (Sweden)

    E. M. Blyth

    2004-01-01

    Full Text Available Soil moisture heterogeneity has an effect on the rainfall–runoff characteristics of a landscape. The aggregate effect on the mean water balance over an area can be quantified successfully using models such as the PDM (Moore, 1986 and TOPMODEL (Beven and Kirkby, 1979. These rainfall–runoff models have been embedded in the large-scale land surface schemes used in meteorological models. However, there is also a requirement (e.g. model validation to identify the spatial structure of the fine-scale soil moisture heterogeneity that makes up these aggregate models. In some types of landscape, this will be dictated by topography, in others by soil characteristics, or by a combination of both. A method to distribute area-average soil moisture according to the likely effect of local topography is presented and tested. The heterogeneity of the soil moisture is described by the Xinanxiang distribution (Zhao et al., 1980, commonly used to describe the natural spatial heterogeneity of the landscape. This distribution is then mapped onto the terrain using a topographic index to locate the wettest and driest areas. Soil moisture data from the Wye catchment in Wales and from the Pang catchment in Berkshire, England, are used to test the method. It is found that soil moisture data from the Wye catchment follow the topographic index reasonably well, whereas data from the quick-draining, chalky Pang catchment do not. The conclusion that topographic index is a useful indicator only in some landscapes applies equally to using this mapping method and those models that use topographic index directly. Keywords: soil moisture, heterogeneity, topographic index, data

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

    Science.gov (United States)

    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.

  13. Inverse modeling of soil characteristics from surface soil moisture observations: potential and limitations

    Directory of Open Access Journals (Sweden)

    A. Loew

    2008-01-01

    Full Text Available Land surface models (LSM are widely used as scientific and operational tools to simulate mass and energy fluxes within the soil vegetation atmosphere continuum for numerous applications in meteorology, hydrology or for geobiochemistry studies. A reliable parameterization of these models is important to improve the simulation skills. Soil moisture is a key variable, linking the water and energy fluxes at the land surface. An appropriate parameterisation of soil hydraulic properties is crucial to obtain reliable simulation of soil water content from a LSM scheme. Parameter inversion techniques have been developed for that purpose to infer model parameters from soil moisture measurements at the local scale. On the other hand, remote sensing methods provide a unique opportunity to estimate surface soil moisture content at different spatial scales and with different temporal frequencies and accuracies. The present paper investigates the potential to use surface soil moisture information to infer soil hydraulic characteristics using uncertain observations. Different approaches to retrieve soil characteristics from surface soil moisture observations is evaluated and the impact on the accuracy of the model predictions is quantified. The results indicate that there is in general potential to improve land surface model parameterisations by assimilating surface soil moisture observations. However, a high accuracy in surface soil moisture estimates is required to obtain reliable estimates of soil characteristics.

  14. Revealing plot scale heterogeneity in soil moisture dynamics under contrasting vegetation assemblages using 3D electrical resistivity tomography (ERT) surveys

    Science.gov (United States)

    Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

    2016-04-01

    Soil moisture is a fundamental component of the water cycle that influences many hydrological processes, such as flooding, solute transport, biogeochemical processes, and land-atmosphere interactions. The relationship between vegetation and soil moisture is complex and reciprocal. Soil moisture may affect vegetation distribution due to its function as the primary source of water, in turn the structure of vegetation canopies regulate water partitioning into interception, throughfall and steam flow. Such spatial differences in inputs, together with complex patterns of water uptake from distributed root networks can create marked heterogeneity in soil moisture dynamics at small scales. Traditional methods of monitoring soil moisture have revolved around limited point measurements, but improved geophysical techniques have facilitated a trend towards more spatially distributed measurements to help understand this heterogeneity. Here, we present a study using 3D ERT surveys in a 3.2km upland catchment in the Scottish Highlands where increasing afforestation (for climate change adaptation, biofuels and conservation) has the potential to increase interception losses and reduce soil moisture storage. The study combined 3D surveys, traditional point measurements and laboratory analysis of soil cores to assess the plot scale soil moisture dynamics in podzolic soils under forest stands of 15m high Scots pine (Pinus sylvestris) and adjacent non-forest plots dominated by heather (Calluna vulgaris) shrubs (water content in the soils below. These results are important as the point to potential water stresses with planned increased afforestation which may be compounded by climate change projections of decreasing precipitation during the growing season.

  15. Precipitation estimation using L-band and C-band soil moisture retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-09-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to ˜100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  16. Soil Moisture Remote Sensing using GPS-Interferometric Reflectometry

    Science.gov (United States)

    Chew, Clara

    Ground-reflected Global Positioning System (GPS) signals can be used opportunistically to infer changes in land-surface characteristics surrounding a GPS monument. GPS satellites transmit at L-band, and at microwave frequencies the permittivity of the ground surface changes primarily due to its moisture content. Temporal changes in ground-reflected GPS signals are thus indicative of temporal changes in the moisture content surrounding a GPS antenna. The interference pattern of the direct and reflected GPS signal for a single satellite track is recorded in signal-to-noise ratio (SNR) data. Alternating constructive and destructive interference as the satellite passes over the antenna results in a noisy oscillating wave at low satellite elevation angles, from which the phase, amplitude, and frequency (or reflector height) can be calculated. Here, an electrodynamic model that simulates SNR data is validated against field observations. The model is then used to show that temporal changes in these SNR metrics may be used to estimate changes in surface soil moisture in the top 5 cm of the soil column. Results show that changes in SNR phase are best correlated with changes in soil moisture, with an approximately linear slope. Surface roughness decreases the sensitivity of SNR phase to soil moisture, though the effect is not significant for small roughness values (moisture is to be estimated using phase data. An algorithm is presented that uses modeled relationships between canopy parameters and SNR metrics to remove seasonal vegetation effects from the phase time series, from which soil moisture time series may be estimated. Results indicate that this algorithm can successfully estimate surface soil moisture with an RMSE of 0.05 cm3 cm-3 or lower for many of the antennas that comprise the Plate Boundary Observatory (PBO) network.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2013-10-01

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

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

    Science.gov (United States)

    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

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

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in 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/hm2 per year, ranging from (6.1±3.2) Mg CO2-C/hm2 per 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.

  2. Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data

    Science.gov (United States)

    Zawadzki, Jaroslaw; Kędzior, Mateusz

    2016-03-01

    Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band, radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission, which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavorable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries - Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118,861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe. This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012. This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of a large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, Centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual

  3. Soil moisture dynamics in an eastern Amazonian tropical forest

    Science.gov (United States)

    Bruno, Rogério D.; da Rocha, Humberto R.; de Freitas, Helber C.; Goulden, Michael L.; Miller, Scott D.

    2006-08-01

    We used frequency-domain reflectometry to make continuous, high-resolution measurements for 22 months of the soil moisture to a depth of 10 m in an Amazonian rain forest. We then used these data to determine how soil moisture varies on diel, seasonal and multi-year timescales, and to better understand the quantitative and mechanistic relationships between soil moisture and forest evapotranspiration. The mean annual precipitation at the site was over 1900 mm. The field capacity was approximately 0.53 m3 m-3 and was nearly uniform with soil depth. Soil moisture decreased at all levels during the dry season, with the minimum of 0.38 m3 m-3 at 3 m beneath the surface. The moisture in the upper 1 m showed a strong diel cycle with daytime depletion due to evapotranspiration. The moisture beneath 1 m declined during both day and night due to the combined effects of evapotranspiration, drainage and a nighttime upward movement of water. The depth of active water withdrawal changed markedly over the year. The upper 2 m of soil supplied 56% of the water used for evapotranspiration in the wet season and 28% of the water used in the dry season. The zone of active water withdrawal extended to a depth of at least 10 m. The day-to-day rates of moisture withdrawal from the upper 10 m of soil during rain-free periods agreed well with simultaneous measurements of whole-forest evapotranspiration made by the eddy covariance technique. The forest at the site was well adapted to the normal cycle of wet and dry seasons, and the dry season had only a small effect on the rates of land-atmosphere water vapour exchange.

  4. Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests

    Science.gov (United States)

    Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi

    2016-04-01

    Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    NARCIS (Netherlands)

    Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

    2012-01-01

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

  7. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

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

    Science.gov (United States)

    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.

  10. Using Plant Temperature to Evaluate the Response of Stomatal Conductance to Soil Moisture Deficit

    Directory of Open Access Journals (Sweden)

    Ming-Han Yu

    2015-10-01

    Full Text Available Plant temperature is an indicator of stomatal conductance, which reflects soil moisture stresses. We explored the relationship between plant temperature and soil moisture to optimize irrigation schedules in a water-stress experiment using Firmiana platanifolia (L. f. Marsili in an incubator. Canopy temperature, leaf temperature, and stomatal conductance were measured using thermal imaging and a porometer. The results indicated that (1 stomatal conductance decreased with declines in soil moisture, and reflected average canopy temperature; (2 the variation of the leaf temperature distribution was a reliable indicator of soil moisture stress, and the temperature distribution in severely water-stressed leaves exhibited greater spatial variation than that in the presence of sufficient irrigation; (3 thermal indices (Ig and crop water stress index (CWSI were theoretically proportional to stomatal conductance (gs, Ig was certified to have linearity relationship with gs and CWSI have a logarithmic relationship with gs, and both of the two indices can be used to estimate soil moisture; and (4 thermal imaging data can reflect water status irrespective of long-term water scarcity or lack of sudden rainfall. This study applied thermal imaging methods to monitor plants and develop adaptable irrigation scheduling, which are important for the formulation of effective and economical agriculture and forestry policy.

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

    Science.gov (United States)

    Mace, R.

    2016-12-01

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

  12. Development of a Coordinated National Soil Moisture Network: A Pilot Study

    Science.gov (United States)

    Quiring, S. M.; Lucido, J. M.; Winslow, L.; Ford, T.; Bijoy Baruah, P.; Verdin, J. P.; Pulwarty, R. S.; Strobel, M.

    2015-12-01

    Soil moisture is critical for accurate drought assessment and forecasting, identifying flood potential, climate modeling, estimation of crop yields and water budgeting. However, soil moisture data are collected by many agencies and organizations in the United States using a variety of instruments and methods for varying applications. These data are often distributed and represented in disparate formats, posing significant challenges for reuse. Recognizing this need, the President's Climate Action Plan called for the creation of a coordinated national soil moisture network. In response, a team led by the National Integrated Drought Information System has completed a proof-of-concept pilot project. The pilot comprises both in-situ and assimilated soil moisture datasets. It focuses on providing real-time soil moisture data via standard web services to feed map-based visualization tools in order to meet the following use cases: operational drought monitoring, experimental land surface modeling, and operational hydrological modeling. The result of this pilot is a reference architecture that will inform the implementation of the national network.

  13. Small-scale soil moisture determination with GPR

    Science.gov (United States)

    Igel, Jan; Preetz, Holger

    2010-05-01

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

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

    OpenAIRE

    F. E. Moyano; N. Vasilyeva; L. Bouckaert; Cook, F; J. Craine; J. Curiel Yuste; Don, A.; Epron, D.; Formanek, P; A. Franzluebbers; Ilstedt, U; T. Kätterer; Orchard, V.; Reichstein, M.; Rey, A.

    2012-01-01

    Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the rep...

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

    OpenAIRE

    F. E. Moyano; N. Vasilyeva; L. Bouckaert; Cook, F; J. Craine; J. Curiel Yuste; Don, A.; Epron, D.; Formanek, P; A. Franzluebbers; Ilstedt, U; T. Kätterer; Orchard, V.; Reichstein, M.; Rey, A.

    2011-01-01

    Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4 % in global soil carbon stock predictions by 2100. The necessity of improving t...

  16. Does Soil Moisture Influence Climate Variability and Predictability over Australia?.

    Science.gov (United States)

    Timbal, B.; Power, S.; Colman, R.; Viviand, J.; Lirola, S.

    2002-05-01

    Interannual variations of Australian climate are strongly linked to the El Niño-Southern Oscillation (ENSO) phenomenon. However, the impact of other mechanisms on prediction, such as atmosphere-land surface interactions, has been less frequently investigated. Here, the impact of soil moisture variability on interannual climate variability and predictability is examined using the Bureau of Meteorology Research Centre atmospheric general circulation model. Two sets of experiments are run, each with five different initial conditions. In the first set of experiments, soil moisture is free to vary in response to atmospheric forcing in each experiment according to a set of simple prognostic equations. A potential predictability index is computed as the ratio of the model's internal variability to its external forced variability. This estimates the level of predictability obtained assuming perfect knowledge of future ocean surface temperatures. A second set of five experiments with prescribed soil moisture is performed. A comparison between these two sets of experiments reveals that fluctuations of soil moisture increase the persistence, the variance, and the potential predictability of surface temperature and rainfall. The interrelationship between these two variables is also strongly dependent upon the soil water content. Results are particularly marked over Australia in this model. A novel feature of this study is the focus on the effectiveness of ENSO-based statistical seasonal forecasting over Australia. Forecasting skill is shown to be crucially dependent upon soil moisture variability over the continent. In fact, surface temperature forecasts in this manner are not possible without soil moisture variability. This result suggests that a better representation of land-surface interaction has the potential to increase the skill of seasonal prediction schemes.

  17. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    Science.gov (United States)

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

    2014-05-01

    Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at pMataix-Solera, J., Doerr, S.H. & Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent

  18. Wireless device for monitoring the temperature - moisture regime in situ

    Science.gov (United States)

    Hudec, Ján; Štofanik, Vladimír; Vretenár, Viliam; Kubičár, Ľudovít

    2014-05-01

    This contribution presents the wireless device for monitoring the temperature - moisture regime in situ. For the monitoring so called moisture sensor is used. Principle of moisture sensor is based on measuring the thermal conductivity. Moisture sensor has cylindrical shape with about 20 mm diameter and 20 mm length. It is made of porous material identical to the monitored object. The thermal conductivity is measured by hot-ball method. Hot-ball method is patented invention of the Institute of Physic SAS. It utilizes a small ball, diameter up to 2 mm, in which sensing elements are incorporated. The ball produces heat spreading into surrounding material, in our case into body of the moisture sensor. Temperature of the ball is measured simultaneously. Then change of the temperature, in steady state, is inversely proportional to the thermal conductivity. Such moisture sensor is inserted into monitored wall. Thermophysical properties of porous material are function of moisture. Moisture sensors are calibrated for dry and water saturated state. Whole the system is primarily intended to do long-term monitoring. Design of a new electronic device was needed for this innovative method. It covers all needed operations for measurement. For example energizing hot-ball sensor, measuring its response, storing the measured data and wireless data transmission. The unit is able to set parameters of measurement via wireless access as well. This contribution also includes the description of construction and another features of the wireless measurement system dedicated for this task. Possibilities and functionality of the system is demonstrated by actual monitoring of the tower of St. Martin's Cathedral in Bratislava. Correlations with surrounding meteorological conditions are presented. Some of them can be also measured by our system, right in the monitoring place.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  1. Temporal stability of soil moisture in various semi-arid steppe ecosystems and its application in remote sensing

    Science.gov (United States)

    Schneider, K.; Huisman, J. A.; Breuer, L.; Zhao, Y.; Frede, H.-G.

    2008-09-01

    SummaryMonitoring soil moisture is often necessary in hydrological studies on various scales. One of the challenges is to determine the mean soil moisture of large areas with minimum labour and costs. The aim of this study is to test temporal persistence of sample locations to decrease the number of samples required to make reliable estimates of mean moisture content in the top soil. Soil moisture data on four experimental sites were collected during the vegetation period in 2004-2006. The experimental sites are located in a steppe environment in northern China, and are characterised by different grazing management which causes differences in vegetation cover. A total of 100 sampling points per site were ranked with respect to their difference to field mean soil moisture using the time-stability concept. We tested whether: (a) representative sample locations exist that predict field mean soil moisture to an acceptable degree, and (b) these locations are time-stable beyond a single vegetation period. Time-stable locations with a low deviation from mean field soil moisture and low standard deviation were identified for each site. Although the time-stability characteristics of some points varied between years, the selected points were appropriate to predict mean soil moisture of the sites for multiple years. On the field scale, time-stability and the persistence of patterns were analysed by the use of a Spearman rank correlation. The analysis showed that persistence depended on grazing management and the related plant cover. It is concluded that the time-stability concept provides useful information for the validation of hydrological or remote sensing models, or for the upscaling of soil moisture information to larger scales. A preliminary comparison of soil moisture measurements derived from ground-truth and remote sensing data showed that the data matched well in some cases, but that the considerable difference in spatial extent promotes differences in other cases.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  4. BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

    Science.gov (United States)

    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).

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

    Science.gov (United States)

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

    1983-01-01

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

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

    Science.gov (United States)

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

    1992-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-01

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

  8. Influence of spatial and temporal variability of subsurface soil moisture and temperature on vapour intrusion

    Science.gov (United States)

    Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu

    2014-05-01

    A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface soil moisture and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in moisture and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface soil properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be affected by spatial and temporal variability of subsurface soil moisture and temperature. The monthly monitoring of soil-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. Soil-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the soil-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of soil-gas monitoring wells for human risk assessment is a site specific decision. Subsurface soil-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface soil properties such as temperature and moisture that fluctuate with the seasons of the year.

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

    Science.gov (United States)

    Shinoda, Masato; Nandintsetseg, Banzragch

    2011-10-01

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

  10. Preliminary analysis of distributed in situ soil moisture measurements

    Directory of Open Access Journals (Sweden)

    L. Brocca

    2005-01-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

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

    Science.gov (United States)

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

    2013-02-01

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

  13. Effects of pruning intensity on jujube transpiration and soil moisture of plantation in the Loess Plateau

    Science.gov (United States)

    Nie, Zhenyi; Wang, Xing; Wang, Youke; Ma, Jianpeng; Wei, Xinguang; Chen, Dianyu

    2017-01-01

    In order to ease soil desiccation and prevent ecological deterioration in the Loess Plateau, where jujube (Zizyphus jujube MIll) is widely cultivated as a drought tolerant plant, four pruning intensities (PI), from PI-1 (light) to PI-4 (heavy) were set up based on total length of secondary branches to study the effects of pruning on transpiration and soil moisture in jujube plantations. Furthermore, growth indexes were regularly monitored to estimate jujubes biomass. Sap flow, meteorological and soil moisture conditions were monitored using thermal dissipation probes (TDP), weather station (RR-9100) and the combination of time domain transmission (TDT) technology and neutron moisture gauges (CNC503B), respectively. The results showed that daily actual transpiration of jujube was positively correlated with leaf biomass. Compared with PI-1, jujube transpiration during growth period under PI-2, PI-3, and PI-4 dropped by 11.1%, 29.2%, and 47.9%, respectively. On the contrary, annual water storage under PI-2, PI-3, and PI-4 increased by 6.29 mm, 25.78 mm and 34.74 mm while water use efficiency increased by 5.1%, 15.7% and 24.2%, respectively. Overall, increase in pruning intensity could significantly reduce water consumption of jujube and improve soil moisture in jujube plantations.

  14. Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

    Science.gov (United States)

    Engman, Edwin T.

    1997-01-01

    Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

  15. Evaluation of Soil Moisture Retrieval from the ERS and Metop Scatterometers in the Lower Mekong Basin

    Directory of Open Access Journals (Sweden)

    Heiko Apel

    2013-03-01

    Full Text Available The natural environment and livelihoods in the Lower Mekong Basin (LMB are significantly affected by the annual hydrological cycle. Monitoring of soil moisture as a key variable in the hydrological cycle is of great interest in a number of Hydrological and agricultural applications. In this study we evaluated the quality and spatiotemporal variability of the soil moisture product retrieved from C-band scatterometers data across the LMB sub-catchments. The soil moisture retrieval algorithm showed reasonable performance in most areas of the LMB with the exception of a few sub-catchments in the eastern parts of Laos, where the land cover is characterized by dense vegetation. The best performance of the retrieval algorithm was obtained in agricultural regions. Comparison of the available in situ evaporation data in the LMB and the Basin Water Index (BWI, an indicator of the basin soil moisture condition, showed significant negative correlations up to R = −0.85. The inter-annual variation of the calculated BWI was also found corresponding to the reported extreme hydro-meteorological events in the Mekong region. The retrieved soil moisture data show high correlation (up to R = 0.92 with monthly anomalies of precipitation in non-irrigated regions. In general, the seasonal variability of soil moisture in the LMB was well captured by the retrieval method. The results of analysis also showed significant correlation between El Niño events and the monthly BWI anomaly measurements particularly for the month May with the maximum correlation of R = 0.88.

  16. Monitoring of Double Stud Wall Moisture Conditions in the Northeast

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, K. [Building Science Corporation, Westford, MA (United States)

    2015-03-01

    Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing.; Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.

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

    Science.gov (United States)

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

    2015-04-01

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

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

    Directory of Open Access Journals (Sweden)

    A. Sekertekin

    2016-10-01

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

  19. Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

    Science.gov (United States)

    2011-01-01

    Baumgardner, M. F., Silva, L. F., Biehl, L. L., and E. R. Stoner, 1985, "The Reflec- tance Properties of Soils," Advances in Agronomy , 38:1-44...retrieval algorithms for the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) on the Aqua satellite. AMSR-E is a passive... Advanced Microwave Scanning Radiometer Soil Moisture Products," IEEE Transactions on Geoscience and Remote Sensing, 48(12):4256- 4272. Jackson, T. J

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

    Science.gov (United States)

    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

  1. Satellite microwave estimates of soil moisture and applications for desertification studies

    Science.gov (United States)

    Owe, Manfred; Van de Griend, Adriaan A.; de Jeu, Richard A.; de Vries, Jorrit; Seyhan, E.

    1998-12-01

    Based on a series of studies conducted in Botswana and preliminary results from an ongoing study in Spain, developments in microwave remote sensing by satellite which can be used to monitor near real-time surface moisture and also study long term soil moisture climatology are described. A progression of methodologies beginning with single polarization studies and leading to both dual polarization and multiple frequency techniques are described. Continuing analysis of a nine year data set of satellite-derived surface moisture in Spain is ongoing. Preliminary results from this study appear to provide some evidence of long term decertification in certain parts of this region. The methodologies developed during these investigations can be applied to other regions, and have the potential for providing modelers with extended data sets of independently derived surface moisture for simulation and validation studies, and climate change studies at the global scale.

  2. Monitoring Moisture Damage Propagation in GFRP Composites Using Carbon Nanoparticles

    Directory of Open Access Journals (Sweden)

    Ahmed Al-Sabagh

    2017-03-01

    Full Text Available Glass fiber reinforced polymer (GFRP composites are widely used in infrastructure applications including water structures due to their relatively high durability, high strength to weight ratio, and non-corrosiveness. Here we demonstrate the potential use of carbon nanoparticles dispersed during GFRP composite fabrication to reduce water absorption of GFRP and to enable monitoring of moisture damage propagation in GFRP composites. GFRP coupons incorporating 2.0 wt % carbon nanofibers (CNFs and 2.0 wt % multi-wall carbon nanotubes (MWCNTs were fabricated in order to study the effect of moisture damage on mechanical properties of GFRP. Water absorption tests were carried out by immersing the GFRP coupons in a seawater bath at two temperatures for a time period of three months. Effects of water immersion on the mechanical properties and glass transition temperature of GFRP were investigated. Furthermore, moisture damage in GFRP was monitored by measuring the electrical conductivity of the GFRP coupons. It was shown that carbon nanoparticles can provide a means of self-sensing that enables the monitoring of moisture damage in GFRP. Despite the success of the proposed technique, it might not be able to efficiently describe moisture damage propagation in GFRP beyond a specific threshold because of the relatively high electrical conductivity of seawater. Microstructural investigations using Fourier Transform Infrared (FTIR explained the significance of seawater immersion time and temperature on the different levels of moisture damage in GFRP.

  3. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.

    2010-08-01

    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  4. Influence of soil moisture content on surface albedo and soil thermal parameters at a tropical station

    Science.gov (United States)

    Sugathan, Neena; Biju, V.; Renuka, G.

    2014-06-01

    Half hourly data of soil moisture content, soil temperature, solar irradiance, and reflectance are measured during April 2010 to March 2011 at a tropical station, viz., Astronomical Observatory, Thiruvananthapuram, Kerala, India (76°59'E longitude and 8°29'N latitude). The monthly, seasonal and seasonal mean diurnal variation of soil moisture content is analyzed in detail and is correlated with the rainfall measured at the same site during the period of study. The large variability in the soil moisture content is attributed to the rainfall during all the seasons and also to the evaporation/movement of water to deeper layers. The relationship of surface albedo on soil moisture content on different time scales are studied and the influence of solar elevation angle and cloud cover are also investigated. Surface albedo is found to fall exponentially with increase in soil moisture content. Soil thermal diffusivity and soil thermal conductivity are also estimated from the subsoil temperature profile. Log normal dependence of thermal diffusivity and power law dependence of thermal conductivity on soil moisture content are confirmed.

  5. Influence of soil moisture content on surface albedo and soil thermal parameters at a tropical station

    Indian Academy of Sciences (India)

    Neena Sugathan; V Biju; G Renuka

    2014-07-01

    Half hourly data of soil moisture content, soil temperature, solar irradiance, and reflectance are measured during April 2010 to March 2011 at a tropical station, viz., Astronomical Observatory, Thiruvananthapuram, Kerala, India (76° 59’E longitude and 8°29’N latitude). The monthly, seasonal and seasonal mean diurnal variation of soil moisture content is analyzed in detail and is correlated with the rainfall measured at the same site during the period of study. The large variability in the soil moisture content is attributed to the rainfall during all the seasons and also to the evaporation/movement of water to deeper layers. The relationship of surface albedo on soil moisture content on different time scales are studied and the influence of solar elevation angle and cloud cover are also investigated. Surface albedo is found to fall exponentially with increase in soil moisture content. Soil thermal diffusivity and soil thermal conductivity are also estimated from the subsoil temperature profile. Log normal dependence of thermal diffusivity and power law dependence of thermal conductivity on soil moisture content are confirmed.

  6. GCOM-W soil moisture and temperature algorithms and validation

    Science.gov (United States)

    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...

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

    Science.gov (United States)

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

    2016-01-01

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

  8. An adaptive ensemble Kalman filter for soil moisture data assimilation

    Science.gov (United States)

    In a 19-year twin experiment for the Red-Arkansas river basin we assimilate synthetic surface soil moisture retrievals into the NASA Catchment land surface model. We demonstrate how poorly specified model and observation error parameters affect the quality of the assimilation products. In particul...

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

    Science.gov (United States)

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

    2016-03-01

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

  10. Examining moisture and temperature sensitivity of soil organic matter decomposition in a temperate coniferous forest soil

    Directory of Open Access Journals (Sweden)

    C. E. Gabriel

    2011-02-01

    Full Text Available Temperature and moisture are primary environmental drivers of soil organic matter (SOM decomposition, and the development of a better understanding fo their roles in this process through depth in soils is needed. The objective of this research is to independently assess the roles of temperature and moisture in driving heterotrophic soil respiration for shallow and deep soils in a temperate red spruce forest. Minimally disturbed soil cores from shallow (0–25 cm and deep (25–50 cm layers were extracted from a 20 yr old red spruce stand and were then transferred to a climate chamber where they were incubated for 3 months under constant and diurnal temperature regimes. Soils were subjected to different watering treatments representing a full range of water contents. Temperature, moisture, and CO2 surface flux were assessed daily for all soils and continuously on a subset of the microcosms. The results from this study indicate that shallow soils dominate the contribution to surface flux (90% and respond more predictably to moisture than deep soils. An optimum moisture range of 0.15 to 0.60 water-filled pore space was observed for microbial SOM decomposition in shallow cores across which a relatively invariant temperature sensitivity was observed. For soil moisture conditions experienced by most field sites in this region, flux-temperature relationships alone can be used to reasonably estimate heterotrophic respiration, as in this range moisture does not alter flux, with the exception of rewetting events along the lower part of this optimal range. Outside this range, however, soil moisture determines SOM decomposition rates.

  11. [Effects of nitrogen fertilization, soil moisture and soil temperature on soil respiration during summer fallow season].

    Science.gov (United States)

    Zhang, Fang; Guo, Sheng-Li; Zou, Jun-Liang; Li, Ze; Zhang, Yan-Jun

    2011-11-01

    On the loess plateau, summer fallow season is a hot rainy time with intensive soil microbe activities. To evaluate the response of soil respiration to soil moisture, temperature, and N fertilization during this period is helpful for a deep understanding about the temporal and spatial variability of soil respiration and its impact factors, then a field experiment was conducted in the Changwu State Key Agro-Ecological Experimental Station, Shaanxi, China. The experiment included five N application rates: unfertilized 0 (N0), 45 (N45), 90 (N90), 135(N135), and 180 (N180) kg x hm(-2). The results showed that at the fallow stage, soil respiration rate significantly enhanced from 1.24 to 1.91 micromol x (m2 x s)(-1) and the average of soil respiration during this period [6.20 g x (m2 x d)(-1)] was close to the growing season [6.95 g x (m2 x d)(-1)]. The bivariate model of soil respiration with soil water and soil temperature was better than the single-variable model, but not so well as the three-factor model when explaining the actual changes of soil respiration. Nitrogen fertilization alone accounted for 8% of the variation soil respiration. Unlike the single-variable model, the results could provide crucial information for further research of multiple factors on soil respiration and its simulation.

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

    Directory of Open Access Journals (Sweden)

    Shai Sela

    2014-08-01

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

  13. Estimating soil hydraulic properties from soil moisture time series by inversion of a dual-permeability model

    Science.gov (United States)

    Dalla Valle, Nicolas; Wutzler, Thomas; Meyer, Stefanie; Potthast, Karin; Michalzik, Beate

    2017-04-01

    Dual-permeability type models are widely used to simulate water fluxes and solute transport in structured soils. These models contain two spatially overlapping flow domains with different parameterizations or even entirely different conceptual descriptions of flow processes. They are usually able to capture preferential flow phenomena, but a large set of parameters is needed, which are very laborious to obtain or cannot be measured at all. Therefore, model inversions are often used to derive the necessary parameters. Although these require sufficient input data themselves, they can use measurements of state variables instead, which are often easier to obtain and can be monitored by automated measurement systems. In this work we show a method to estimate soil hydraulic parameters from high frequency soil moisture time series data gathered at two different measurement depths by inversion of a simple one dimensional dual-permeability model. The model uses an advection equation based on the kinematic wave theory to describe the flow in the fracture domain and a Richards equation for the flow in the matrix domain. The soil moisture time series data were measured in mesocosms during sprinkling experiments. The inversion consists of three consecutive steps: First, the parameters of the water retention function were assessed using vertical soil moisture profiles in hydraulic equilibrium. This was done using two different exponential retention functions and the Campbell function. Second, the soil sorptivity and diffusivity functions were estimated from Boltzmann-transformed soil moisture data, which allowed the calculation of the hydraulic conductivity function. Third, the parameters governing flow in the fracture domain were determined using the whole soil moisture time series. The resulting retention functions were within the range of values predicted by pedotransfer functions apart from very dry conditions, where all retention functions predicted lower matrix potentials

  14. Ottawa National Wildlife Refuge : Soil and Moisture Conservation Plan : 1972 Calendar Year

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This is the Ottawa National Wildlife Refuge Soil and Moisture Conservation Plan. The Soil and Moisture Conservation Plan outlines the relationship between refuge...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

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

    2015-05-01

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

  18. Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate

    OpenAIRE

    Milad Jajarmizadeh; Sobri bin Harun; Shamsuddin Shahid; Shatirah Akib; Mohsen Salarpour

    2014-01-01

    The soil and water assessment tool (SWAT) is a physically based model that is used extensively to simulate hydrologic processes in a wide range of climates around the world. SWAT uses spatial hydrometeorological data to simulate runoff through the computation of a retention curve number. The objective of the present study was to compare the performance of two approaches used for the calculation of curve numbers in SWAT, that is, the Revised Soil Moisture Index (SMI), which is based on previou...

  19. Experimental Measurement of Diffusive Extinction Depth and Soil Moisture Gradients in Southwestern Saudi Arabian Dune Sand

    KAUST Repository

    Mughal, Iqra

    2013-05-01

    In arid lands, a major contribution to water loss is by soil water evaporation. Desert sand dunes in arid regions are devoid of runoff and have high rates of infiltration. Rainwater is commonly stored within them because of the low permeability soils in the underlying desert pavement. In such cases, moisture is confined in the sand dune below a depth, termed as the “extinction depth”, where it is protected from evaporation during long dry periods. Moreover, desert sand dunes have sparse vegetation, which results in low transpiration losses from the stored water. The water accumulated below the extinction depth of the sand dunes can be utilized for various purposes such as in irrigation to support desert agriculture. In this study, field experiments were conducted in Western Saudi Arabia to monitor the soil moisture gradients and determine the diffusive extinction depth of dune sand. The dune sand was saturated with water and was exposed to natural conditions (evaporation and precipitation). The decline of the water level in the sand column was continuously recorded using transducers and sensors installed at different depths monitored the temporal variation of temperature and moisture content within the sand. The hydrological simulator HYDRUS-1D was used to construct the vertical profiles of soil water content and temperature and the results obtained from HYDRUS-1D were compared to the gradients monitored by the sensors.

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

    Science.gov (United States)

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

    2017-04-01

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

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  2. Transient Soil Moisture Characteristics Below Different Land Cover Types: Implications for Quantifying Groundwater Recharge

    Science.gov (United States)

    Jayawickreme, D. H.; van Dam, R. L.; Hyndman, D. W.

    2006-12-01

    Statistical analysis of temporal water budgets in Michigan watersheds shows a significant link between land covers and streamflow characteristics. The observed differences in water budgets between the investigated watersheds are largely attributed to spatial heterogeneity and temporal variability of vegetation characteristics. Our findings suggest that management of regional groundwater resources should consider the effects of spatial and temporal vegetation changes. However, due to inadequate information, vegetation dynamics are not considered in most hydrologic models. By instrumenting suitable field sites in Michigan with different land cover types to monitor spatial and temporal variations in subsurface soil moisture , we investigate the interdependence of land cover, climate, soil moisture, and groundwater recharge in regional watersheds. Our approach involves resistivity and ground penetrating radar surveys, in-situ continuous moisture/temperature monitoring at field sites, and computer modeling of evapotranspiration and groundwater recharge. The results of this research are expected to improve our understanding of the impact of vegetation on soil moisture and groundwater recharge from site to regional scales and demonstrate the importance of incorporating land cover types and vegetation dynamics in regional groundwater resource assessment models.

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

    Science.gov (United States)

    Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

  4. Calibration and validation of the COSMOS rover for surface soil moisture

    Science.gov (United States)

    The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...

  5. Upscaling of soil moisture measurements in NW Italy

    Science.gov (United States)

    Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Brunod, Christian; Ratto, Sara; Cauduro, Marco

    2015-04-01

    There is large mismatch in spatial scale between the climate and meteorological model grid, and the scale of soil and vegetation measurements. Remote sensing data can help to fit the model scale, but they cannot provide rootzone data. In this work some soil moisture datasets are analysed for the sake of providing larger scale estimation of soil moisture and water and energy fluxes. The first dataset refers to a plain site near Torino, where measurements are taken since 1997 (Baudena et al., 2012), and a mountain site close to the town. The second one is a dataset in the mountains of Valle d'Aosta (Brocca et al., 2013), where 4 years of data are available. The use of digital elevation models and vegetation maps is shown in this work. Some soil processes (e.g. Whalley et al., 2012) are usually disregarded, but in this work their possible impact is considered. References L. Brocca, A. Tarpanelli, T. Moramarco, F. Melone, S.M. Ratto, M. Cauduro, S. Ferraris, N. Berni, F. Ponziani, W. Wagner, T. Melzer (2013). Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations VADOSE ZONE JOURNAL, vol. 8-2, p. 1-10, doi:10.2136/vzj2012.0102 M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). Soil water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009 W.R. Whalley, G.P. Matthews, S. Ferraris (2012). The effect of compaction and shear deformation of saturated soil on hydraulic conductivity. SOIL & TILLAGE RESEARCH, vol. 125, p. 23-29, ISSN: 0167-1987

  6. Soil Moisture Estimation in South-Eastern New Mexico Using High Resolution Synthetic Aperture Radar (SAR Data

    Directory of Open Access Journals (Sweden)

    A.K.M. Azad Hossain

    2016-01-01

    Full Text Available Soil moisture monitoring and characterization of the spatial and temporal variability of this hydrologic parameter at scales from small catchments to large river basins continues to receive much attention, reflecting its critical role in subsurface-land surface-atmospheric interactions and its importance to drought analysis, irrigation planning, crop yield forecasting, flood protection, and forest fire prevention. Synthetic Aperture Radar (SAR data acquired at different spatial resolutions have been successfully used to estimate soil moisture in different semi-arid areas of the world for many years. This research investigated the potential of linear multiple regressions and Artificial Neural Networks (ANN based models that incorporate different geophysical variables with Radarsat 1 SAR fine imagery and concurrently measured soil moisture measurements to estimate surface soil moisture in Nash Draw, NM. An artificial neural network based model with vegetation density, soil type, and elevation data as input in addition to radar backscatter values was found suitable to estimate surface soil moisture in this area with reasonable accuracy. This model was applied to a time series of SAR data acquired in 2006 to produce soil moisture data covering a normal wet season in the study site.

  7. L band microwave remote sensing and land data assimilation improve the representation of prestorm soil moisture conditions for hydrologic forecasting

    Science.gov (United States)

    Crow, W. T.; Chen, F.; Reichle, R. H.; Liu, Q.

    2017-06-01

    Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total streamflow divided by total rainfall accumulation in depth units) and prestorm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting streamflow response to future rainfall events.type="synopsis">type="main">Plain Language SummaryForecasting streamflow conditions is important for minimizing loss of life and property during flooding and adequately planning for low streamflow conditions accompanying drought. One way to improve these forecasts is measuring the amount of water in the soil—since soil moisture conditions determine what fraction of rainfall will run off horizontally into stream channels (versus vertically infiltrate into the soil column). Within the past 5 years, there have been important advances in our ability to monitor soil moisture over large scales using both satellite-based sensors and the application of new land data assimilation techniques. This paper illustrates that these advances have significantly improved our capacity to forecast how much streamflow will be generated by future precipitation events. These results may eventually be used by operational forecasters to improve flash flood forecasting and agricultural water use management.

  8. Using Distributed-Hydrology-Soil-Vegetation Model to Study Road Effects on Stream flow and Soil Moisture

    Science.gov (United States)

    Cuo, L.; Giambelluca, T. W.; Ziegler, A. D.; Nullet, M. A.

    2003-12-01

    The distributed-hydrology-soil-vegetation model (DHSVM) was applied in Pang Khum Experimental Watershed (PKEW), located near 19.05\\deg N, 98.65\\deg E in the mountainous region of northern Thailand, headwaters of the Chao Phraya River system. PKEW has a highly seasonal rainfall regime, with 90% of the annual 1200-1400 mm rainfall occurring during the southwest summer monsoon. The elevation of PKEW ranges from approximately 1100 to 1500 m. Total road area including road banks is about 1.2% of the basin area. About 57% of the road area occurs on slopes steeper than 10%. All roads are unpaved. Land cover in PKEW is affected by swidden agriculture. Six land cover and nine soil classes are identified in the basin. We have been working in the area since 1997 as part of the Thailand Roads Project (TRP). Within the basin, we are monitoring microclimate at two sites, soil moisture at four sites, and rainfall at five sites. Streamflow is measured at the outlet. Based on digital elevation data, DHSVM explicitly accounts for the spatial distribution of the stream and road networks, soil depth, soil and vegetation types. The model run period, including warm up, calibration and validation, is from August 1997 to January 2001. Field measurements provide forcing data, calibration data, and guidance in parameter selection. Model calibration and validation were done by aggregating simulated hourly soil moisture and stream flow into daily values and comparing them with aggregated daily measurements. For the calibration period, RMSEs of soil moisture and streamflow were lower than the observed variability as represented by the standard deviation, median absolute deviation, and (for stream flow) interquartile range. Model performance drops in validation period, but RMSEs remain near or lower than observed variability. We ran DHSVM with and without roads to examine their effects. Significant effects of roads were found despite the very low proportion of the watershed covered by roads

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heter...... predictions of the response of soil carbon to future climate scenarios will require the integration of soil-dependent moisture-respiration functions coupled with realistic representations of soil water dynamics.......Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model...... the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data...

  12. Growing season soil moisture following restoration treatments of varying intensity in semi-arid ponderosa pine forests

    Science.gov (United States)

    O'Donnell, F. C.; Springer, A. E.; Sankey, T.; Masek Lopez, S.

    2014-12-01

    Forest restoration projects are being planned for large areas of overgrown semi-arid ponderosa pine forests of the Southwestern US. Restoration involves the thinning of smaller trees and prescribed or managed fire to reduce tree density, restore a more natural fire regime, and decrease the risk of catastrophic wildfire. The stated goals of these projects generally reduced plant water stress and improvements in hydrologic function. However, little is known about how to design restoration treatments to best meet these goals. As part of a larger project on snow cover, soil moisture, and groundwater recharge, we measured soil moisture, an indicator of plant water status, in four pairs of control and restored sites near Flagstaff, Arizona. The restoration strategies used at the sites range in both amount of open space created and degree of clustering of the remaining trees. We measured soil moisture using 30 cm vertical time domain reflectometry probes installed on 100 m transects at 5 m intervals so it would be possible to analyze the spatial pattern of soil moisture. Soil moisture was higher and more spatially variable in the restored sites than the control sites with differences in spatial pattern among the restoration types. Soil moisture monitoring will continue until the first snow fall, at which point measurements of snow depth and snow water equivalent will be made at the same locations.

  13. 利用地表温度与LAI的新型土壤湿度监测方法%A Novel Method of Soil Moisture Content Monitoring by Land Surface Temperature and LAI

    Institute of Scientific and Technical Information of China (English)

    高中灵; 郑小坡; 孙越君; 王建华

    2015-01-01

    地表温度( Ts )是土壤湿度和植被生长状态等因素的综合反映,利用植被指数和 Ts 能够监测土壤湿度的时空分布特征。利用农田气候模型CUPID的 Ts 模拟结果,发展了利用温度与叶面积指数(LAI)的新型土壤水分反演方法(advanced temperature vegetation dryness index ,ATVDI)。前人研究表明归一化植被指数(NDVI)容易达到饱和状态,因此利用LAI代替NDVI开展土壤水分反演。利用CUPID模型模拟结果构建LAI‐Ts 散点图,分析 Ts 随LAI与土壤湿度的变化特征,利用对数关系式改进了温度植被干旱指数(TVDI)中相同土壤湿度时 Ts 与植被指数之间的线性关系,建立了ATVDI方法。在实际应用中,首先利用LAI与Ts 的散点图确定对数曲线的上边界与下边界,然后采用查找表的方法将每个像元对应的 Ts 变换为研究区最小叶面积指数对应的 Ts 。以陕西省关中作为研究区,利用 MODIS 的 LAI和 Ts 产品(MOD11A2和MOD15A2)以及野外观测土壤湿度数据对ATVDI模型进行验证,结果表明该方法具有较高的监测精度,R2达到0.62。此外,A T VDI的计算结果具有一定的物理意义,使得不同时期的监测结果具有一致性,因而可更好地满足不同空间尺度土壤湿度的动态监测。%Land surface temperature (Ts ) is influenced by soil background and vegetation growing conditions ,and the combina‐tion of Ts and vegetation indices (Vis) can indicate the status of surface soil moisture content (SMC) .In this study ,Advanced Temperature Vegetation Dryness Index (ATVDI) used for monitoring SMC was proposed on the basis of the simulation results with agricultural climate model CUPID .Previous studies have concluded that Normalized Difference Vegetation Index (NDVI) easily reaches the saturation point ,andLeaf Area Index (LAI) was then used instead of NDVI to estimate soil moisture content in the paper .With LAI

  14. Timber harvest effect on soil moisture in the southern Sierra Nevada: Is there a measurable impact?

    Science.gov (United States)

    Meadows, M. W.; Bales, R. C.; Conklin, M. H.; Goulden, M.; Hartsough, P. C.; Hopmans, J. W.; Hunsaker, C. T.; Lucas, R. G.; Malazian, A. I.

    2013-12-01

    We monitored soil-moisture storage, evapotranspiration and streamflow in a Sierra Nevada mixed-conifer forest for three post-snowmelt spring/summer seasons during water years 2010-2013. We measured volumetric water content using a COsmic-ray Soil Moisture Observing Systems (COSMOS) to estimate shallow soil-moisture storage and an eddy-covariance flux tower to measure evapotranspiration, covering an area of about 20 ha. Soil-moisture sensors were also strategically placed at depths of 10, 30, 60 and 90 cm at 30 locations in and around the COSMOS and tower footprints. Timber harvest occurred during the summer of 2012, involving uneven-age thinning limited to trees less than 76.2 cm diameter at breast height (DBH). Timber harvest intensity varied by tree size class: approximately 39% of the trees 0 to 25.5 cm DBH, 21% of the trees 25.5 to 50.8 cm DBH, and 4% of trees 50.8-76.2 cm DBH. Merchantable timber removed from the site was about 81-100 cubic m per ha. Annual evapotranspiration was similar for all four years, averaging about 80 cm each year, despite large variability in annual precipitation amounts. Annual evapotranspiration was about 10% lower following harvest. However, 2012 and 2013 were both dry years. Water year 2011 was one of the wettest years on record - approximately 200 cm of precipitation - while 2012 was one of the driest with 70 cm of precipitation. Each year soil desiccation immediately followed snow-cover depletion, dropping from field capacity by about 20% volumetric water content over a 3-month period. The rate of soil-water loss was about the same for all years. In 2012 and 2013 the dates of snow disappearance were 2-3 months earlier than in 2011. About half of the annual total evapotranspiration for 2010-2012 occurred during the 3-month period following snowmelt. Each year, total summer precipitation was only 4-6 cm. Thus soil-water storage derived from snowmelt and rainfall provides much of the moisture for evapotranspiration in the mixed

  15. Soil Moisture Sensing via Swept Frequency Based Microwave Sensors

    Directory of Open Access Journals (Sweden)

    Greg A. Holt

    2012-01-01

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

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

    Science.gov (United States)

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

    2012-04-01

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

  17. Relationship between oriental migratory locust plague and soil moisture extracted from MODIS data

    Science.gov (United States)

    Liu, Zhenbo; Shi, Xuezheng; Warner, Eric; Ge, Yunjian; Yu, Dongsheng; Ni, Shaoxiang; Wang, Hongjie

    2008-02-01

    Locust plagues have been the source of some of the most severe natural disasters in human history. Soil moisture content is among the most important of the numerous factors influencing plague onset and severity. This paper describes a study initiated in three pilot locust plague monitoring regions, i.e., Huangzao, Yangguanzhuang, and Tengnan in Huanghua county, Hebei province, China, to examine the impact of soil moisture status on oriental migratory locust [ Locusta migratoria manilensis (L.) Meyen] plague breakout as related to the life cycle, oviposition in autumn, survival in winter, and incubation in summer. Thirty-nine temperature vegetation dryness index (TVDI) data sets, which represent soil moisture content, were extracted from MODIS remote sensing images for two representative time periods: a severe locust plague breakout year (2001-2002) and a slight plague year (2003-2004). TVDI values demonstrated distinctive soil moisture status differences between the 2 years concerned. Soil moisture conditions in the severe plague year were shown to be lower than those in slight plague year. In all three pilot regions, average TVDI value in the severe plague year was 0.07 higher than that in slight plague year, and monthly TVDI values in locust oviposition period (September and October) and incubation period (March, April and May) were higher than their corresponding monthly figures in slight plague year. No remarkable TVDI differences were found in other months during the locust life cycle between the 2 years. TVDI values for September and October (2001), March, April and May (2002) were 0.11, 0.08, 0.16, 0.11 and 0.16 higher than their corresponding monthly figures in 2003-2004 period, respectively.

  18. Monitoring and evaluating soil quality

    NARCIS (Netherlands)

    Bloem, J.; Schouten, A.J.; Sørensen, S.J.; Rutgers, M.; Werf, van der A.K.; Breure, A.M.

    2006-01-01

    This book provides a selection of microbiological methods that are already applied in regional or national soil quality monitoring programs. It is split into two parts: part one gives an overview of approaches to monitoring, evaluating and managing soil quality. Part two provides a selection of meth

  19. Indicators for Monitoring Soil Biodiversity

    DEFF Research Database (Denmark)

    Bispo, A.; Cluzeau, D.; Creamer, R.

    2009-01-01

    is made for a set of suitable indicators for monitoring the decline in soil biodiversity (Bispo et al. 2007). These indicators were selected both from a literature review and an inventory of national monitoring programmes. Decline in soil biodiversity was defined as the reduction of forms of life living...... indicators are actually measured.   For monitoring application it was considered in ENVASSO that only three key indicators per soil stress were practical. For indicating biodiversity decline it was difficult to arrive at a small set of indicators due to the complexity of soil biota and functions. Therefore...

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

    Science.gov (United States)

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

    2017-01-01

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

  1. Multivariate hydrological data assimilation of soil moisture and groundwater head

    Science.gov (United States)

    Zhang, Donghua; Madsen, Henrik; Ridler, Marc E.; Kidmose, Jacob; Jensen, Karsten H.; Refsgaard, Jens C.

    2016-10-01

    Observed groundwater head and soil moisture profiles are assimilated into an integrated hydrological model. The study uses the ensemble transform Kalman filter (ETKF) data assimilation method with the MIKE SHE hydrological model code. The method was firstly tested on synthetic data in a catchment of less complexity (the Karup catchment in Denmark), and later implemented using data from real observations in a larger and more complex catchment (the Ahlergaarde catchment in Denmark). In the Karup model, several experiments were designed with respect to different observation types, ensemble sizes and localization schemes, to investigate the assimilation performance. The results showed the necessity of using localization, especially when assimilating both groundwater head and soil moisture. The proposed scheme with both distance localization and variable localization was shown to be more robust and provide better results. Using the same assimilation scheme in the Ahlergaarde model, groundwater head and soil moisture were successfully assimilated into the model. The hydrological model with assimilation showed an overall improved performance compared to the model without assimilation.

  2. Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

    Science.gov (United States)

    Koster, R. D.; Walker, G. K.

    2015-01-01

    The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

  3. Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate

    Directory of Open Access Journals (Sweden)

    Milad Jajarmizadeh

    2014-01-01

    Full Text Available The soil and water assessment tool (SWAT is a physically based model that is used extensively to simulate hydrologic processes in a wide range of climates around the world. SWAT uses spatial hydrometeorological data to simulate runoff through the computation of a retention curve number. The objective of the present study was to compare the performance of two approaches used for the calculation of curve numbers in SWAT, that is, the Revised Soil Moisture Index (SMI, which is based on previous meteorological conditions, and the Soil Moisture Condition II (SMCII, which is based on soil features for the prediction of flow. The results showed that the sensitive parameters for the SMI method are land-use and land-cover features. However, for the SMCII method, the soil and the channel are the sensitive parameters. The performances of the SMI and SMCII methods were analyzed using various indices. We concluded that the fair performance of the SMI method in an arid region may be due to the inherent characteristics of the method since it relies mostly on previous meteorological conditions and does not account for the soil features of the catchment.

  4. Monitoring of frozen soil hydrology in macro-scale in the Qinghai-Xizang Plateau

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Monitoring of frozen soil hydrology in macro-scale was performed by Chinese and Japanese scientists from 1997 to 1998. Quality measured data were obtained. Measured data on soil moisture and temperature are preliminarily analyzed. Based on profiles of soil temperature and moisture in individual measured sites, intra-annual freezing and melting process of soil is discussed. Maximum frozen and thawed depths and frozen days in various depths are estimated. The work emphasized the spatial distribution on soil temperature and moisture in macro-scale and the effect of topography on conditions of soil water and heat.

  5. Multilayer soil model for improvement of soil moisture estimation using the small perturbation method

    Science.gov (United States)

    Song, Kaijun; Zhou, Xiaobing; Fan, Yong

    2009-12-01

    A multilayer soil model is presented for improved estimation of soil moisture content using the first-order small perturbation method (SPM) applied to measurements of radar backscattering coefficient. The total reflection coefficient of the natural bare soil including volume scattering contribution is obtained using the multilayer model. The surface reflection terms in SPM model are replaced by the total reflection coefficient from the multilayer soil surface in estimating soil moisture. The difference between the modified SPM model and the original SPM surface model is that the modified SPM model includes both the surface scattering and the volumetric scattering of the natural bare soil. Both the modified SPM model and the original SPM model are tested in soil moisture retrievals using experimental microwave backscattering coefficient data in the literature. Results show that the mean square errors between the measured data and the values estimated by the modified SPM model from all samples are 5.2%, while errors from the original SPM model are 8.4%. This indicates that the capability of estimating soil moisture by the SPM model is improved when the surface reflection terms are replaced by the total reflection coefficients of multilayer soil model over bare or very sparsely vegetation covered fields.

  6. Regional soil moisture simulation for Shaanxi Province using SWAT model validation and trend analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The soil moisture in Shaanxi Province,a region with complex topography,is simulated using the distributed hydrological model Soil Water Assessment Tool(SWAT).Comparison and contrast of modeled and observed soil moisture show that the SWAT model can reasonably simulate the long-term trend in soil moisture and the spatiotemporal variability of soil moisture in the region.Comparisons to NCEP/NCAR and ERA40 reanalysis of soil moisture show that the trend of variability in soil moisture simulated by SWAT is more consistent with the observed.SWAT model results suggested that high soil moisture in surface soil layers appears in the southern Shaanxi with high vegetation cover,and the Qinling mountainous region with frequent orographic precipitation.In deeper soil layers,high soil moisture appears in the river basins and plains.The regional soil moisture showed a generally decreasing trend on all soil layers from 1951 to 2004,with a stronger and significant decreasing trend in deeper soil layers,especially in the northern parts of the province.

  7. Evaluation of soil moisture and Palmer Drought Severity Index in Brazil

    Science.gov (United States)

    Rossato, Luciana; Antônio Marengo, José; Bassi Marinho Pires, Luciana

    2016-04-01

    Soil moisture is one of the main factors for the study of drought, climate and vegetation. In the case of drought, this is a regional phenomenon and affects food security more than any other natural disaster. Therefore, monitoring of different types of drought has been based on indexes that standardize on temporal and spatial scales. Currently, the monitoring of different types of drought is based on indexes that attempt to encapsulate on temporal and regional levels allowing thereby the comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, the Palmer Drought Severity Index was estimated for the entire Brazilian territory, using meteorological (precipitation and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil) data. The data field capacity and permanent wilting point were obtained from the physical properties of the soil, while the water storage in the soil was calculated considering the water balance model. Analyses were made for the years 2000 through 2014, which includes periods with and without occurrence of drought, respectively. The results showed that the PDSI had higher negative indices for the years 2003 and 2012 in Brazil's Northeast region, and this region was strongly affected by drought during those years. These indices can serve as a basis for assessing future drought projections, considering different scenarios. The results also show that soil moisture constitutes one of the limiting factors for obtaining high agricultural productivity, in order to reduce the effects caused by drought. Therefore, these indices can serve as a basis for assessing future drought projections, considering different scenarios. It would be desirable to assist decision makers in action plans with more effective strategies, allowing farmers to live with drought without losing their livelihood.

  8. Estimating soil moisture from satellite microwave observations: Past and ongoing projects, and relevance to GCIP

    Science.gov (United States)

    Owe, M.; Van de Griend, A. A.; de Jeu, R.; de Vries, J. J.; Seyhan, E.; Engman, E. T.

    1999-08-01

    On the basis of a series of studies conducted in Botswana and preliminary results from an ongoing study in Spain, developments in microwave remote sensing by satellite, which can be used to monitor near-real-time surface moisture and also study long-term soil moisture climatology, are described. A progression of methodologies beginning with single-polarization studies and leading to both dual polarization and multiple frequency techniques are described. Continuing analysis of a 9 year data set of satellite-derived surface moisture in Spain is ongoing. Preliminary results from this study appear to provide some evidence of long-term desertification in certain parts of this region. The methodologies developed during these investigations can be applied easily to other regions such as the GCIP area and could provide useful databases for simulation and validation studies. Additionally, they have strong potential for global applications such as climate change studies.

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

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

    2016-01-15

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

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

    Science.gov (United States)

    Van de Vyvere, Laura; Desenfans, Olivier

    2016-04-01

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

  12. Microwave remote sensing of soil moisture with vegetation effect

    Science.gov (United States)

    Tsegaye, Teferi D.; Inguva, Ramarao; Lang, Roger H.; O'Neill, Peggy E.; Fahsi, Ahmed; Coleman, Tommy L.; Tadesse, Wubishet; Rajbhandari, Narayan B.; Aburemie, Sunnie A.; de Matthaeis, Paolo

    1999-12-01

    The objectives of this study were: to examine the sensitivity of radar backscatter, to estimate soil moisture under a corn plot and to evaluate the effectiveness and sensitivity of a Radiative Transfer Model (RTM), adapted from the earlier work of Njoku and Kong, (1977) in predicting brightness temperature from a grass plot. Microwave radar measurements were collected from plots of different vegetation cover types, vegetation density, and moisture conditions during the Huntsville 1998 field experiment. A large amount of ground data on brightness temperatures, soil moisture, and vegetation characteristics (e.g., biomass, and water content) were collected. The experiments were conducted at Alabama A&M University's, Winfred Thomas Agricultural Research Station, located near Hazel Green, Alabama. Six plots, one 50 X 60 m smooth bare plot, one 50 X 60 m grass plot, and four 30 X 50 m corn plots at full, 2/3, 1/2, and 1/3 densities were used. Radar backscatter data were obtained from a ground based truck mounted radar operating at L, C, and X bands (1.6, 4.75, and 10 GHz) with four linear polarization HH, HV, VV, and VH and two incidence angles (15 and 45 degrees). Soil moisture values were determined using Water Content Reflectometry (WCR). Three types of soil temperature sensors (Infrared Thermometer, Thermistor, and a 4-sensor averaging thermocouple probes) were used. A discrete backscatter approach model and RTM were evaluated. Comparisons between model prediction and experimental observation for HH polarization indicated good agreement for a corn full plot. The direct-reflected scattering coefficient is found to be the most dominant term for both polarization and the backscatter is also highly sensitive to soil moisture. The trends in time variation of brightness temperature are in agreement with the experimental results and the numerical results are within a few percent of the experimental results. The vegetation corrections as estimated by the Jackson and Schmugge

  13. Noninvasive Monitoring of Soil Static Characteristics and Dynamic States

    DEFF Research Database (Denmark)

    Cassiani, Giorgio; Ursino, Nadia; Deiana, Rita

    2012-01-01

    emission, texture analysis, and laboratory calibration of an electrical constitutive relationship on soil samples complete the dataset. We observe that the growth of vegetation, with the associated below-ground allocation of biomass, has a significant impact on the soil moisture dynamics. It is well known......In this paper we present the results of seasonal monitoring and irrigation tests performed on an experimental farm in a semiarid region of Southern Sardinia. The goal of the study is to understand the soil–vegetation interactions and how they can affect the soil water balance, particularly in view...... of possible climatic changes. We used long-term electromagnetic induction (EMI) time lapse monitoring and short-term irrigation experiments monitored using electrical resistivity tomography (ERT) and EMI, supported by time domain reflectometry (TDR) soil moisture measurements. Mapping of natural ?-ray...

  14. Soil Moisture Estimation Using MODIS Images (Case Study: Mashhad Plain Area

    Directory of Open Access Journals (Sweden)

    M. Fashaee

    2016-09-01

    area is selected in the Mashhad plain in Khorasan Razavi province of I.R. Iran. Study area is about 1,200 square kilometers and is located around the Golmakan center of agricultural research. In this study, water deficit index (WDI was zoning by MODIS images in subset of Mashhad plain during water year of 2011-2012. Then, based on the close relationship between WDI and soil moisture parameter, a linear relationship between these two parameters were fitted. Soil moisture is measured by the TDR and every 7 days at 5 depths of 5, 10, 20, 30 and 50 cm from the surface. Remote Sensing (RS technology used as a tool for providing some of the data that is required. The moderate resolution imaging spectroradiometer (MODIS instrument is popular for monitoring soil moisture because of its high spectral (36 bands resolution, moderate spatial (250–1000 m resolution and various products for land surface properties. MODIS products used in the present study include: MOD09A1 land surface albedo data, MOD11A1 land surface temperature data, and MOD13A1 vegetation data. Using ArcMap 9.2 and ERDAS IMAGINE 2010 softwares, WDI was calculated pixel by pixel for 18 days (non-cloudy days and simultaneous with measurement of soil moisture at the station. Results and Discussion: The results showed that the northeastern region is predominantly rainfed and irrigated farmlands are under water stress. Conversely, the southwestern part of the area is mountainous with less water stress. Based on NDVI, there is also less crop cover in the southwestern part of the region during the year. The results showed that about 44% of the index values are in the range of 0.2-0.3. Then about 22% of the index values are in the range of 0.3-0.4. Thus it can be concluded that over 66% of the index values are in the range of 0.2-0.4. According to the maximum index value (WDI=0.59 on the 201th day of year and the minimum values (WDI=0.0004 on the 129th day of year during the time period of study, it seems that water

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

    Science.gov (United States)

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

    2010-01-01

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

  16. Time series modeling of soil moisture dynamics on a steep mountainous hillside

    Science.gov (United States)

    Kim, Sanghyun

    2016-05-01

    The response of soil moisture to rainfall events along hillslope transects is an important hydrologic process and a critical component of interactions between soil vegetation and the atmosphere. In this context, the research described in this article addresses the spatial distribution of soil moisture as a function of topography. In order to characterize the temporal variation in soil moisture on a steep mountainous hillside, a transfer function, including a model for noise, was introduced. Soil moisture time series with similar rainfall amounts, but different wetness gradients were measured in the spring and fall. Water flux near the soil moisture sensors was modeled and mathematical expressions were developed to provide a basis for input-output modeling of rainfall and soil moisture using hydrological processes such as infiltration, exfiltration and downslope lateral flow. The characteristics of soil moisture response can be expressed in terms of model structure. A seasonal comparison of models reveals differences in soil moisture response to rainfall, possibly associated with eco-hydrological process and evapotranspiration. Modeling results along the hillslope indicate that the spatial structure of the soil moisture response patterns mainly appears in deeper layers. Similarities between topographic attributes and stochastic model structures are spatially organized. The impact of temporal and spatial discretization scales on parameter expression is addressed in the context of modeling results that link rainfall events and soil moisture.

  17. Configuration of the relationship of soil moistures for vertical soil profiles on a steep hillslope using a vector time series model

    Science.gov (United States)

    Kim, Sanghyun; Sun, Hanna; Jung, Sungwon

    2011-03-01

    SummaryVariation in soil moisture content throughout soil profiles during several sequential rainfalls represents the internal hydrological response on a hillslope scale. A multiplex TDR system has been operating on a mountainous hillslope to obtain the time series of soil moisture along two transects in the study area. The soil moisture modeling conducted in this study highlights our understanding of the inter-relationships between soil moistures at identical spatial locations, but at different depths. A sequential procedure was used for the time series modeling to delineate an appropriate model for application to all monitoring points. The feedback relationship of soil wetness between two different depths was expressed with the proposed vector autoregressive model. Based on the successful modeling of 31 coupled soil water histories, the vertical distributions of the stochastic model throughout the study area were obtained. The distribution of the delineated models implied a spatial distribution of the hydrological processes, such as vertical infiltration for the upper soil layers and some of the lower soil layers (38 out of 62 models), lateral redistribution and subsurface flow over bedrock mostly for the lower soil layers (24 out of 62 models) on the steep hillslope. With the use of the resultant models, applications were proposed to improve the data acquisition system, i.e. gap filling for missing data and limited prediction for an ungauged location.

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

    Science.gov (United States)

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

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil

  19. Visualization of soil-moisture change in response to precipitation within two rain gardens in Ohio

    Science.gov (United States)

    Dumouchelle, Denise H.; Darner, Robert A.

    2014-01-01

    Stormwater runoff in urban areas is increasingly being managed by means of a variety of treaments that reduce or delay runoff and promote more natural infiltration. One such treatment is a rain garden, which is built to detain runoff and allow for water infiltration and uptake by plants.Water flow into or out of a rain garden can be readily monitored with a variety of tools; however, observing the movement of water within the rain garden is less straightforward. Soil-moisture probes in combination with an automated interpolation procedure were used to document the infiltration of water into two rain gardens in Ohio. Animations show changes in soil moisture in the rain gardens during two precipitation events. At both sites, the animations demonstrate underutilization of the rain gardens.

  20. Carbon Turnover in Alaskan Tundra Soils: Effects of Organic Matter Quality, Temperature, Moisture and Fertilizer

    National Research Council Canada - National Science Library

    Gaius R. Shaver; A. E. Giblin; K. J. Nadelhoffer; K. K. Thieler; M. R. Downs; J. A. Laundre; E. B. Rastetter

    2006-01-01

    .... This study describes how soil C loss is related to temperature, moisture and chemical composition of organic matter in Alaskan tundra soils, including soils that were fertilized annually for 8 years prior to the study...

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

    Science.gov (United States)

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

    2014-11-01

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

  2. Soil wettability, moisture status and CO2 flux in a long term drought and warming simulation experiment

    Science.gov (United States)

    Urbanek, Emilia; Bösken, Janina; Titema, Albert; Nunez Pastrana, David; Emmett, Bridget

    2014-05-01

    Current climatic predictions include altered rainfall patterns and increased temperatures which in consequence can enhance the development of soil water repellency (SWR; i.e. hydrophobicity). Soils may become more severely water-repellent or SWR may spread into the environments where it has not been observed before. As the soil moisture dynamics, including restricted infiltration and uneven distribution of water is severely altered in water-repellent soils, so might be the decomposition of organic matter and overall exchange of gases like CO2 between the soil and the atmosphere. Long-term climatic simulation study has been conducted for over a decade at upland heathland sites in Oldebroek (Netherlands) and in Clocaenog (UK) [1]. At each site nine 20 m2-large plots were selected and each three were subjected to: a drought effect created by a rainfall exclusion using an automatic self retracting waterproof curtains; a warming effect using a self retracting curtains reflecting infrared radiation overnight, and control plots. The soil at the sites was a peaty podzol and sandy podzol both highly prone to soil water repellency development. The sites were constantly monitored since the start of the experiment and the range of meteorological and environmental measurements included for example: soil moisture, temperature, vegetation and root zone changes, soil CO2 flux. The observations of soil moisture content have shown that the soil moisture did not recover to the original values in the drought system even after the rainfall exclusion has been stopped for winter time, suggesting the development of soil water repellency [2]. The severe changes in moisture dynamics have also significantly affected the soil CO2 flux. The aim of the study was to investigate whether the long-term drought and warming treatments have any effect on the severity and persistence of SWR and how far the moisture changes and the SWR altered the CO2 flux from these soils. The measurements of the SWR

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

    Science.gov (United States)

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

    2016-06-01

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

  4. Impact of Some Agronomic Practices on Paddy Field Soil Health Under Varied Ecological Conditions:I.Influence of Soil Moisture

    Institute of Scientific and Technical Information of China (English)

    A.SUBHANI; LIAOMIN; 等

    2001-01-01

    The effects of individual and combined additions of urea(100μg N g-1soil) and insecticide (triazophos at field rate,FR) under different moisture levles of air-dried soil(AD),50% of water-holding capacity(WHC),100%,WHC and flooded soil(FS) on some selected soil properties in a paddy field soil were examined in a laboratory incubation study.The results indicated that after 21-day incubation at 25℃ ,the different moisture levels led to significant changes in the parameters studied,Flooding of soil with distilled waer significantly increased the electron transport system(ETS)/dehydrogenase activity and phenol content of the soil compared to the other moisture levels,while protein and phospholipis behaved differently at varied moisture levels with or without the addition of urea and /or triazophos.Increased ETS activity was observed with N addition at higher moisture levels thile insecticide incorporation decreased it at all moisture levels as compared to the control(moisture only).The phenol contents slightly decreasd and increased with N and insecticide applications ,respectively,The soil protein contents were found to be unaffected among all the soil treatents at all moisture levels.The soil protein contents were found to be unaffected among all the soil treatments at all moisture levels.However,among different moisture levels,reduced quantities of proteins were estimated at 50% WHC ,suggesting more N-mineralization.Lower quantities of soil biomass phospholipids,among all treatments,were recored at higher moisture levels(100% WHC and FS) than at the loer levels,An overall slight enhancement in phospholipid contents with N and small reduction with insecticide addition,respectively,was noticed against the untreated soil.The toxictiy of fertilizer and insecticide decreased as the soil moisture contents increased,suggesting rapid degradation of agrochemicals.

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

    Directory of Open Access Journals (Sweden)

    J. A. Yeakley

    1998-01-01

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

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

    Directory of Open Access Journals (Sweden)

    C. A. Rivera Villarreyes

    2011-07-01

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

  7. Temporal Dynamics of Soil Moisture Variability at the Landscape Scale: Implications for Land Surface Models.

    Science.gov (United States)

    Montaldo, N.; Albertson, J. D.

    2001-12-01

    Meteorological and hydrological forecasting models share soil moisture as a critical boundary condition. Partitioning of received energy at the land surface depends directly on this variable, as does the partitioning of rainfall into its possible routes over and through the soil. In Land Surface Models (LSMs) the temporal dynamic of soil moisture spatial variability is a fundamental issue in large-scale flux predictions. From remote sensing observations soil moisture values are averaged in the horizontal over rather large regions (pixels). The averaging areas will be getting even larger as we move from aircraft mounted sensors to satellite mounting. These data are to be used ultimately to estimate spatial averages of other processes that depend on soil moisture, such as, runoff generation, drainage, evaporation, sensible heat fluxes, crop yield, microbial activity, etc. Consequently, the LSMs have to predict spatial averaged flux over large region from average values of the soil moisture. But soil moisture variances affect flux predictions, which depend nonlinearly on soil moisture, because many of the other processes possess distinct threshold aspects to their nonlinear dependence on soil moisture. Through application of well-developed Reynolds averaging rules from fluid mechanics to the equation of Richards and Darcy-Buckingham, we write a conservation equation for the horizontal variance of soil moisture. And, through closure arguments, we are able to describe the individual terms that produce and destroy spatial variance through time in terms of the mean soil moisture state and other observable system properties such as vegetation and soil properties variability. Finally, we calculate land surface fluxes from second order Taylor expansion, using our soil moisture variance closure model, and the other observable system properties. In this work, we demonstrate significant improvements in land surface large-scale flux predictions using the proposed soil moisture

  8. Temporal Dynamics of Soil Moisture Variability: Implications For Land Surface Models

    Science.gov (United States)

    Montaldo, N.; Albertson, J. D.

    Meteorological and hydrological forecasting models share soil moisture as a critical boundary condition. Partitioning of received energy at the land surface depends di- rectly on this variable, as does the partitioning of rainfall into its possible routes over and through the soil. In Land Surface Models (LSMs) the temporal dynamic of soil moisture spatial variability is a fundamental issue in large-scale flux predictions. From remote sensing observations soil moisture values are averaged in the horizontal over rather large regions (pixels). The averaging areas will be getting even larger as we move from aircraft mounted sensors to satellite mounting. These data are to be used ultimately to estimate spatial averages of other processes that depend on soil moisture, such as, runoff generation, drainage, evaporation, sensible heat fluxes, crop yield, mi- crobial activity, etc. Consequently, the LSMs have to predict spatial averaged flux over large region from average values of the soil moisture. But soil moisture variances af- fect flux predictions, which depend nonlinearly on soil moisture, because many of the other processes possess distinct threshold aspects to their nonlinear dependence on soil moisture. Through application of well-developed Reynolds averaging rules from fluid mechanics to the equation of Richards and Darcy-Buckingham, we write a con- servation equation for the horizontal variance of soil moisture. And, through closure arguments, we are able to describe the individual terms that produce and destroy spa- tial variance through time in terms of the mean soil moisture state and other observable system properties such as vegetation and soil properties variability. Finally, we calcu- late land surface fluxes from second order Taylor expansion, using our soil moisture variance closure model, and the other observable system properties. In this work, we demonstrate significant improvements in land surface large-scale flux predictions us- ing the proposed

  9. Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

    Science.gov (United States)

    Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei

    2016-12-01

    Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the Earth's 'third pole'. Large-scale spatially consistent and temporally continuous soil moisture datasets are of great importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is a relatively new passive microwave product, with the satellite being launched on November 5, 2010. This study validates and reconstructs FY-3B/MWRI soil moisture across the TP. First, the validation is performed using in situ measurements within two in situ soil moisture measurement networks (1° × 1° and 0.25° × 0.25°), and also compared with the Essential Climate Variable (ECV) soil moisture product from multiple active and passive satellite soil moisture products using new merging procedures. Results show that the ascending FY-3B/MWRI product outperforms the descending product. The ascending FY-3B/MWRI product has almost the same correlation as the ECV product with the in situ measurements. The ascending FY-3B/MWRI product has better performance than the ECV product in the frozen season and under the lower NDVI condition. When the NDVI is higher in the unfrozen season, uncertainty in the ascending FY-3B/MWRI product increases with increasing NDVI, but it could still capture the variability in soil moisture. Second, the FY-3B/MWRI soil moisture product is subsequently reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and NDVI, LST, and albedo, but also the relationship between the soil moisture and four-dimensional variations using the

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

    Science.gov (United States)

    Gupta, Manika; Bolten, John; Lakshmi, Venkat

    2016-04-01

    -evapotranspiration (ET) and MODIS land surface temperature (LST) products. The soil moisture estimates for the root zone are also validated with the in-situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005) by evaluating the root mean square error (RMSE) and Mean Bias error (MBE).

  11. Effects of soil moisture content on upland nitrogen loss

    Science.gov (United States)

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

    2017-03-01

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

  12. Effects of soil moisture content and tractor wheeling intensity on traffic-induced soil compaction

    Directory of Open Access Journals (Sweden)

    Iman AHMADI

    2015-12-01

    Full Text Available Soil compaction causes deleterious effects on physical and mechanical proprieties of agricultural soils. In order to investigate the effect of soil moisture content and tractor wheeling intensity on traffic-induced soil compaction, this study was carried out on a field with clay loam soil. Soil dry bulk density and hydraulic conductivity as well as emergence percentage of corn seedlings and dry mass of the sampled mature plants were considered the dependent variables of the experiment. Independent variables consisted of soil moisture content with five levels (12, 15, 17, 19, and 21%, traffic intensity with three levels (four, two, and zero passes of tractor wheel (tractor model: John Deere 3350 from the entire area of the plot, and soil sampling depth with three levels (0-10, 10-20, and 20-30 cm. According to the results of this study, gradual increase in soil water content generally resulted in an increase in soil bulk density; moreover, increasing the tractor wheeling intensity from 0 to 4 passes increased bulk density by 13%. Furthermore, the driest soil water content had the highest and the wettest soil water content had the lowest emergence percentage of corn seedlings among the treatments; moreover, traffic intensity treatment inversely affected the emergence percentage of corn seedlings and the dry mass of mature plants. To sum up, these results indicate that, for improving water permeability and reducing dry bulk density of the examined clay loam soil, as well as better emergence of corn seedlings and ultimately increasing crop yield, it is recommended to avoid wheeling when soil moisture content is high, reduce the number of machinery wheel passes from the farm as low as possible, and restrict the wheel passes to fixed strips along the field, whenever possible.

  13. Modeling the Effects of Soil Moisture at a GPS-Interferometric Reflectometry Station

    Science.gov (United States)

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

    2011-12-01

    GPS-Interferometric Reflectometry (GPS-IR) uses ground-reflected GPS signals to estimate near-surface soil moisture. Data are recorded by high-precision, geodetic-quality GPS antennas/receivers, for example those that comprise NSF's EarthScope Plate Boundary Observatory. The ground reflections used in GPS-IR are representative of a ~1000 m2 area around an antenna. As the dielectric constant of the surface fluctuates, the phase, amplitude, and frequency of signal-to-noise ratio (SNR) data recorded by the GPS unit change. Based on field observations, it has been shown that these characteristics of the SNR data are sensitive to shallow soil moisture. A single-scattering, electrodynamic model was used to simulate SNR output over a range of soil moisture conditions. All simulations were for a 2.4 m tall antenna surrounded by a surface free of roughness or vegetation. The model was run using three different types of soil moisture profiles: constant with depth, monotonic variations with depth, and observed profiles interpolated from field data. For all profiles, amplitude, phase shift, and frequency changes were calculated from simulated SNR data. The three GPS metrics are well correlated with soil moisture content modeled at the soil surface because a majority of the incident microwave energy is reflected at the air-soil interface. When surface soil is dry relative to the underlying soil, GPS metrics are also strongly correlated with soil moisture averaged over the top 5 cm of the soil column. The relationship between GPS metrics and soil moisture averaged over 5 cm is not as strong when surface soil is relatively wet (>35% volumetric soil moisture). Interpolated profiles from field data resulted in a very strong correlation between SNR metrics and soil moisture averaged over the top 5 cm of soil, suggesting that soil moisture estimated from SNR data is useful for various hydrologic applications.

  14. APPLICATION ON FY -3A SATELLITE DATA TO MONITOR SOIL MOISTURE IN TIlE SOURCE OF THE THREE RIVERS IN QINGHAI PROVINCE%FY-3a卫星数据在青海省三江源区土壤水分监测中的应用

    Institute of Scientific and Technical Information of China (English)

    张娟

    2012-01-01

    MERSI boarded on the new generation polar olution channel that improves inversional capability on orbit meteorological satellite FY - 3 a has 250 meters res- ground objects in China. This study based on 250 meters resolution satellite data and vegetation water supply index built soil moisture monitoring model in the source of the three rivers in Qinghai province. The relationship of vegetation water supply and soil moisture was verified by using surface conventional observation soil moisture data. The results showed: Soil moisture on remote sens- ing retrieval and observation data coincided rather well, when vegetation index is 0.3 - 0.5.%中国新一代极轨气象卫星FY-3a,搭载的中分辨率光谱成像仪(MER$I)具有5个250m分辨率通道,进一步加强了对地表地物的反演能力。本研究利用FY-3a250m分辨率卫星资料,采用植被供水指数法,建立了青海省三江源区土壤水分监测模型,利用气象部门地面常规监测点土壤水分资料,验证了植被供水指数与土壤水分之间的关系,从验证结果看:当植被指数为0.3~0.5时,遥感反演出的土壤水分值与实测值较为接近。

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

    Science.gov (United States)

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

    2014-08-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

    Science.gov (United States)

    Orth, René; Seneviratne, Sonia I.

    2014-12-01

    Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We

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

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

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

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

    Science.gov (United States)

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

  1. Seedling establishment and physiological responses to temporal and spatial soil moisture changes

    Science.gov (United States)

    Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

    2016-01-01

    In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

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

    Science.gov (United States)

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

  3. Temporal and spatial variability of soil hydraulic properties with implications on soil moisture simulations and irrigation scheduling

    Science.gov (United States)

    Feki, Mouna; Ravazzani, Giovanni; Mancini, Marco

    2017-04-01

    The increase in consumption of water resources, combined with climate change impacts, calls for new sources of water supply and/or different managements of available resources in agriculture. One way to increase the quality and quantity of agricultural production is using modern technology to make farms more "intelligent", the so-called "precision agriculture" also known as 'smart farming'. To this aim hydrological models play crucial role for their ability to simulate water movement from soil surface to groundwater and to predict onset of stress condition. However, optimal use of mathematical models requires intensive, time consuming and expensive collection of soil related parameters. Typically, soils to be characterized, exhibit large variations in space and time as well during the cropping cycle, due to biological processes and agricultural management practices: tillage, irrigation, fertilization and harvest. Soil properties are subjected to diverse physical and chemical changes that lead to a non-stability in terms of water and chemical movements within the soil and to the groundwater as well. The aim of this study is to assess the variability of soil hydraulic properties over a cropping cycle. The study site is a surface irrigated Maize field located in Secugnago (45◦13'31.70" N, 9 ◦36'26.82 E), in Northern Italy-Lombardy region. The field belongs to the Consortium Muzza Bassa Lodigiana, within which meteorological data together with soil moisture were monitored during the cropping season of 2015. To investigate soil properties variations, both measurements in the field and laboratory tests on both undisturbed and disturbed collected samples were performed. Soil samples were taken from different locations within the study area and at different depths (surface, 20cm and 40cm) at the beginning and in the middle of the cropping cycle and after the harvest. During three measuring campaigns, for each soil samples several parameters were monitored (Organic

  4. The Seasonal Difference in Soil Moisture Patterns Considering the Meteorological Variables Throughout the Korean Peninsula

    Directory of Open Access Journals (Sweden)

    Eunsang Cho

    2016-01-01

    Full Text Available This study focuses on the seasonal differences in soil moisture patterns considering the impact of meteorological variables (air/ground temperature, precipitation, and the amount of insolation on soil moisture variability over the Korean peninsula between January 2012 and February 2013. We found that soil moisture spatial distributions changed differently with the mean soil moisture content according to the season using statistical metrics (skewness and kurtosis (summer: 1 June to 31 August, winter: 1 November to 31 January. Daily variations in meteorological variables had different relationships with the changes in soil moisture for two seasons. Air and soil temperature changes clearly had negative relationships with the soil moisture change during the summer period while they had positive relationships during the winter period. Temporal stability testing showed that the representative soil moisture sites on a regional scale could be changed with seasonal periods, especially in the Asian monsoon region. In conclusion, these results provide evidence that there are clear differences in soil moisture patterns according to seasonal characteristics. This study might be useful for further researches relating to climate-meteorological effects on soil moisture patterns on a regional scale.

  5. Non-Parametric Evolutionary Algorithm for Estimating Root Zone Soil Moisture

    Science.gov (United States)

    Mohanty, B.; Shin, Y.; Ines, A. M.

    2013-12-01

    Prediction of root zone soil moisture is critical for water resources management. In this study, we explored a non-parametric evolutionary algorithm for estimating root zone soil moisture from a time series of spatially-distributed rainfall across multiple weather locations under two different hydro-climatic regions. A new genetic algorithm-based hidden Markov model (HMMGA) was developed to estimate long-term root zone soil moisture dynamics at different soil depths. Also, we analyzed rainfall occurrence probabilities and dry/wet spell lengths reproduced by this approach. The HMMGA was used to estimate the optimal state sequences (weather states) based on the precipitation history. Historical root zone soil moisture statistics were then determined based on the weather state conditions. To test the new approach, we selected two different soil moisture fields, Oklahoma (130 km x 130 km) and Illinois (300 km x 500 km), during 1995 to 2009 and 1994 to 2010, respectively. We found that the newly developed framework performed well in predicting root zone soil moisture dynamics at both the spatial scales. Also, the reproduced rainfall occurrence probabilities and dry/wet spell lengths matched well with the observations at the spatio-temporal scales. Since the proposed algorithm requires only precipitation and historical soil moisture data from existing, established weather stations, it can serve an attractive alternative for predicting root zone soil moisture in the future using climate change scenarios and root zone soil moisture history.

  6. Scaling Soil Moisture from Meter to Kilometer Scale Using P-Band Radar

    Science.gov (United States)

    Cuenca, Richard; Hagimoto, Yutaka; Moghaddam, Mahta

    2015-04-01

    Correct evaluation of regional scale soil moisture content remains one of the challenging limitations for reasonable prediction of regional scale carbon fluxes. The airborne P-band radar of the NASA AirMOSS project retrieves relatively high spatial resolution dielectric constant signals over an experimental domain of 100 by 25-km sensitive to a depth of on the order of 75-cm. The continuous (15-min time resolution over multiple years) ground-based monitoring transects over nine experimental sites in North America are on the spatial scale of 100-m horizontal and 1-m vertical in seven depth layers. The efficient data management scheme of the ground-based data and the experimental protocol of the airborne P-band radar flights are described. Correlation of the distinct seasonal soil moisture signals of the grassland, deciduous, evergreen and tropical forest monitoring sites with the P-band radar dielectric retrieval are demonstrated. Derivation of robust soil water hydraulic properties based on the extensive database developed at the monitoring sites is described.

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

    Science.gov (United States)

    Coates, Victoria; Pattison, Ian; Sander, Graham

    2016-04-01

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

  8. The role of tree species and soil moisture in soil organic matter stabilization and destabilization

    Science.gov (United States)

    Hatten, J. A.; Dewey, J.; Roberts, S.; McNeal, K.; Shaman, A.

    2014-12-01

    Inputs of labile organic substrates to soils are commonly associated with elevated soil organic carbon mineralization rates; this process is known as the priming effect. Plant presence and soil conditions (i.e. water regime, nutrient status) are known to be interacting factors governing priming. In this study, we examine the role of differing species, loblolly pine (Pinus taeda L.) and nuttall oak (Quercus texana B.), and moisture regimes (low and high) upon the soil priming effect in a fine textured soil. We explore whether there is depletion of original soil carbon and concurrent replacement through addition of fresh organic matter from the planted tree species. By employing a series of planted and plant-free pots in a greenhouse mesocosm study, we were able to characterize the composition of soil organic matter and its carbon with the use of CuO oxidation products (e.g. lignin, cutin/suberin biomarkers). Carbon was elevated on the low moisture samples relative to all other treatments, and the C:N ratio suggests that newly produced plant carbon replaced original soil carbon. The soil lignin content of the planted treatments was lower than the plant-free treatments suggesting that lignin present in the original soil may have been preferentially degraded by priming and not replaced. We will discuss the utility of CuO oxidation products to explore soil organic carbon dynamics and the implications of understanding the role of species and soil moisture in predicting the response of soil carbon to land use and climate change.

  9. A Wireless Sensor Network For Soil Monitoring

    Science.gov (United States)

    Szlavecz, K.; Cogan, J.; Musaloiu-Elefteri, R.; Small, S.; Terzis, A.; Szalay, A.

    2005-12-01

    The most spatially complex stratum of a terrestrial ecosystem is its soil. Among the major challenges of studying the soil ecosystem are the diversity and the cryptic nature of biota, and the enormous heterogeneity of the soil substrate. Often this patchiness drives spatial distribution of soil organisms, yet our knowledge on the spatio-temporal patterns of soil conditions is limited. To monitor the environmental conditions at biologically meaningful spatial scales we have developed and deployed a wireless sensor network of thirty nodes. Each node is based on a MICAz mote connected to a custom-built sensor suite that includes a Watermark soil moisture sensor, an Irrometer soil temperature sensor, and sensors capable of recording ambient temperature and light intensity. To assess CO2 production at the ground level a subset of the nodes is equipped with Telaire 6004 CO2 sensor. We developed the software running on the motes from scratch, using the TinyOS development environment. Each mote collects measurements every minute, and stores them persistently in a non-volatile memory. The decision to store data locally at each node enables us to reliably retrieve the data in the face of network losses and premature node failures due to power depletion. Collected measurements are retrieved over the wireless network through a PC-class computer acting as a gateway between the sensor network and the Internet. Considering that motes are battery powered, the largest obstacle hindering long-term sensor network deployments is power consumption. To address this problem, our software powers down sensors between sampling cycles and turns off the radio (the most energy prohibitive mote component) when not in use. By doing so we were able to increase node lifetime by a factor of ten. We collected field data over several weeks. The data was ingested into a SQL Server database, which provides data access through a .NET web services interface. The database provides functions for spatial

  10. Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.

    Science.gov (United States)

    Jarvi, Mickey P; Burton, Andrew J

    2013-09-01

    The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (respiration in a sugar maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.

  11. Developing a dual assimilation approach for thermal infrared and passive microwave soil moisture retrievals

    Science.gov (United States)

    Hain, Christopher Ryan

    Soil moisture plays a vital role in the partitioning of sensible and latent heat fluxes in the surface energy budget and the lack of a dense spatial and temporal network of ground-based observations provides a challenge to the initialization of the true soil moisture state in numerical weather prediction simulations. The retrieval of soil moisture using observations from both satellite-based thermal-infrared (TIR) and passive microwave (PM) sensors has been developed (Anderson et al., 2007; Hain et al., 2009; Jackson, 1993; Njoku et al., 2003). The ability of the TIR and microwave observations to diagnose soil moisture conditions within different layers of the soil profile provides an opportunity to use each in a synergistic data assimilation approach towards the goal of diagnosing the true soil moisture state from surface to root-zone. TIR and PM retrievals of soil moisture are compared to soil moisture estimates provided by a retrospective Land Information System (LIS) simulation using the NOAH LSM during the time period of 2003--2008. The TIR-based soil moisture product is provided by a retrieval of soil moisture associated with surface flux estimates from the Atmosphere-Land-Exchange-Inversion (ALEXI) model (Anderson et al., 1997; Mecikalski et al., 1999; Hain et al., 2009). The PM soil moisture retrieval is provided by the Vrijie Universiteit Amsterdam (VUA)-NASA surface soil moisture product. The VUA retrieval is based on the findings of Owe et al. (2001; 2008) using the Land Surface Parameter model (LPRM), which uses one dual polarized channel (6.925 or 10.65 GHz) for a dual-retrieval of surface soil moisture and vegetation water content. In addition, retrievals of ALEXI (TIR) and AMSR-E (PM) soil moisture are assimilated within the Land Information System using the NOAH LSM. A series of data assimilation experiments is completed with the following configuration: (a) no assimilation, (b) only ALEXI soil moisture, (c) only AMSR-E soil moisture, and (d) ALEXI

  12. Canopy and leaf gas exchange of Haloxylon ammodendron under different soil moisture regimes

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In order to reveal the drought resistance and adaptation of the C4 desert plant Haloxylon ammodendron under artificially controlled soil moisture regimes,representative plants were selected to measure canopy photosynthesis using canopy photosynthetic measurement system.The results showed that appropriate soil moisture significantly enhances the canopy and leaf photosynthetic capacity,and extremely high soil moisture is not conducive to the photosynthesis of H.ammodendron.

  13. Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

    OpenAIRE

    Xun Chai; Tingting Zhang; Yun Shao; Huaze Gong; Long Liu; Kaixin Xie

    2015-01-01

    Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar) images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We ...

  14. Evaluation of soil pH and moisture content on in-situ ozonation of pyrene in soils.

    Science.gov (United States)

    Luster-Teasley, S; Ubaka-Blackmoore, N; Masten, S J

    2009-08-15

    In this study, pyrene spiked soil (300 ppm) was ozonated at pH levels of 2, 6, and 8 and three moisture contents. It was found that soil pH and moisture content impacted the effectiveness of PAH oxidation in unsaturated soils. In air-dried soils, as pH increased, removal increased, such that pyrene removal efficiencies at pH 6 and pH 8 reached 95-97% at a dose of 2.22 mg O(3)/mg pyrene. Ozonation at 16.2+/-0.45 mg O(3)/ppm pyrene in soil resulted in 81-98% removal of pyrene at all pH levels tested. Saturated soils were tested at dry, 5% or 10% moisture conditions. The removal of pyrene was slower in moisturized soils, with the efficiency decreasing as the moisture content increased. Increasing the pH of the soil having a moisture content of 5% resulted in improved pyrene removals. On the contrary, in the soil having a moisture content of 10%, as the pH increased, pyrene removal decreased. Contaminated PAH soils were stored for 6 months to compare the efficiency of PAH removal in freshly contaminated soil and aged soils. PAH adsorption to soil was found to increase with longer exposure times; thus requiring much higher doses of ozone to effectively oxidize pyrene.

  15. DO3SE modelling of soil moisture to determine ozone flux to European forest trees

    Directory of Open Access Journals (Sweden)

    M. Schaub

    2011-12-01

    Full Text Available The DO3SE (Deposition of O3 for Stomatal Exchange model is an established tool for estimating ozone (O3 deposition, stomatal flux and impacts to a variety of vegetation types across Europe. It has been embedded within the EMEP (European Monitoring and Evaluation Programme photochemical model to provide a policy tool capable of relating the risk of vegetation damage to O3 precursor emission scenarios for use in policy formulation. A key limitation of regional flux-based risk assessments so far has been the approximation that soil water deficits are not limiting O3 flux due to the unavailability of evaluated methods for modelling soil water deficits and their influence on stomatal conductance (gsto, and ultimately O3 flux. This paper describes the development and evaluation of a method to estimate soil moisture status and its influence on gsto for a variety of forest tree species. The soil moisture module uses the Penman-Monteith energy balance method to drive water cycling through the soil-plant-atmosphere system and empirical data describing gsto relationships with pre-dawn leaf water status to estimate the biological control of transpiration. We trial four different methods to estimate this biological control of the transpiration stream, which vary from simple methods that relate soil water content or potential directly to gsto to more complex methods that incorporate hydraulic resistance and plant capacitance that control water flow through the plant system. These methods are evaluated against field data describing a variety of soil water variables, gsto and transpiration data for Norway spruce (Picea abies, Scots pine (Pinus sylvestris, birch (Betula pendula, aspen (Populus tremuloides, beech (Fagus sylvatica and holm oak (Quercus ilex collected from ten sites across Europe and North America. Modelled estimates of these variables show consistency with observed data when applying the simple empirical methods, with the timing and magnitude of

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

    Science.gov (United States)

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

    2017-04-01

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

  17. Numerical Simulation of Moisture Movement in Unsaturated Expansive Soil Slope Suffering Permeation

    Institute of Scientific and Technical Information of China (English)

    Chen Shanxiong; Yu Song; Liu Zhiguo; Xu Haibin

    2005-01-01

    This study develops a way of analyzing moisture movement in unsaturated expansive soil slope. The basic equations and the integrated finite difference method for moisture movement in unsaturated soils are briefly described, and the calculation code MFUS2 has been developed. The moisture movements in unsaturated expansive soil slopes suffering precipitation were simulated numerically. The simulation results show that expansion or contraction must be taken into account in an analysis model. A simplified equivalent model for calculating rainwater infiltration into expansive soil slopes has been developed. The simplified equivalent model divides the soil slope into two layers according to the extent of weathering of the soil mass at depth. Layer Ⅰ is intensively weathered and moisture can be fully evaporated or rapidly absorbed. The moisture movement parameters take into account the greater soil permeability caused by fissures. Layer Ⅱ is unweathered and the soil is basically undisturbed. The moisture movement parameters of homogeneous soils are applicable. The moisture movements in unsaturated expansive soil slopes suffering precipitation were simulated numerically using the simplified equivalent model. The simulation results show that the moisture movement in the expansive soil slope under rainfall permeation mainly takes place in the extensively weathered layer Ⅰ, which closely simulates the real situation.

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

    Directory of Open Access Journals (Sweden)

    C. A. Rivera Villarreyes

    2011-12-01

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

  19. Using NASA UAVSAR Datasets to Link Soil Moisture to Crop Conditions

    Science.gov (United States)

    Davitt, A. W. D.; McDonald, K. C.; Azarderakhsh, M.; Winter, J.

    2015-12-01

    California and The Central Valley are experiencing one of that region's worst, persistent droughts, which represents the continuation of a prolonged drought that started in the early 2000's. Due to the continued drought, many agricultural regions in The Central Valley have been experiencing water shortages, negatively impacting agricultural production and the socio-economics of the region. Due to these impacts, there has been an increased incentive to find new ways to conserve water for use in irrigation. Recent advances in remote sensing techniques provide the ability for end users to better understand field conditions so they may make more informed decisions on irrigation timing and amounts. However, a good understanding of soil moisture and its role in crop health and yield is lacking to support informed water management decisions. Though known to be important, a robust understanding of the role of the spatio-temporal patterns in soil moisture linked to crop health is lacking. Remote sensing platforms such as NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provide the capacity to obtain within-field measurements to estimate within-field and field-to-field variability in soil moisture. UAVSAR radar images acquired from 2010 to 2014 for Yolo County, California are being examined to determine the suitability of high resolution (field scale) multi-temporal L-band radar backscatter imagery for soil moisture assessment and crop conditions through the growing season. By using such data and linking to in-situ meteorology measurements, modeling (MIMICS), and other remote sensing derived datasets (Sentinel, Landsat, MODIS, and TOPS-SIMS), an integrated monitoring system can potentially support the assessment of agricultural field conditions. This allows growers to optimize the use of limited water supplies through informed water management practices, potentially improving crop conditions and yield in a water stressed region.

  20. Soil Moisture Active Passive (SMAP) Data and Services at the NASA NSIDC DAAC

    Science.gov (United States)

    Leon, Amanda; Jodha Singh Khalsa, Siri; Leslie, Shannon

    2016-04-01

    The NASA Soil Moisture Active Passive (SMAP) mission, launched on 31 January 2015, provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. The SMAP instrument includes both a radiometer and a synthetic aperture radar (SAR) operating at the L-band (1.20-1.41 GHz) and provides global coverage at the equator every 3 days. The SMAP mission will play a critical role in understanding the Earth's water and energy cycles, improving weather and climate forecasting, and developing disaster prediction and monitoring services. The NASA Distributed Active Archive Centers (DAACs) at the National Snow and Ice Data Center (NSIDC) and the Alaska Satellite Facility (ASF) are jointly distributing and supporting SMAP data products. The DAACs draw upon their unique expertise - NSIDC with cryospheric and remotely-sensed soil moisture data and ASF with SAR data - as well as their shared technologies to provide synergistic data access and support for SMAP products. NSIDC DAAC provides distribution and support of the SMAP Level-1 radiometer products, the Level-2 through Level-4 soil moisture products, the Level-3 freeze/thaw product, and the Level-4 carbon net ecosystem exchange product. By leveraging NASA Earth Science Data and Information System (ESDIS) data systems, NSIDC DAAC provide data discovery, access, and visualization services for SMAP that are common across all NASA Earth science data archived at the DAACs. NSIDC DAAC also provides custom services aimed at meeting the unique needs of their SMAP user communities. This presentation strives to educate and expand the SMAP user community as well as engage with current and potential users for areas of opportunity in the support and services that NSIDC DAAC provides.

  1. Effect of soil moisture on the sorption of trichloroethene vapor to vadose-zone soil at picatinny arsenal, New Jersey

    Science.gov (United States)

    Smith, J.A.; Chiou, C.T.; Kammer, J.A.; Kile, D.E.

    1990-01-01

    This report presents data on the sorption of trichloroethene (TCE) vapor to vadose-zone soil above a contaminated water-table aquifer at Picatinny Arsenal in Morris County, NJ. To assess the impact of moisture on TCE sorption, batch experiments on the sorption of TCE vapor by the field soil were carried out as a function of relative humidity. The TCE sorption decreases as soil moisture content increases from zero to saturation soil moisture content (the soil moisture content in equilibrium with 100% relative humidity). The moisture content of soil samples collected from the vadose zone was found to be greater than the saturation soil-moisture content, suggesting that adsorption of TCE by the mineral fraction of the vadose-zone soil should be minimal relative to the partition uptake by soil organic matter. Analyses of soil and soil-gas samples collected from the field indicate that the ratio of the concentration of TCE on the vadose-zone soil to its concentration in the soil gas is 1-3 orders of magnitude greater than the ratio predicted by using an assumption of equilibrium conditions. This apparent disequilibrium presumably results from the slow desorption of TCE from the organic matter of the vadose-zone soil relative to the dissipation of TCE vapor from the soil gas.

  2. Performance evaluation of WRF-Noah Land surface model estimated soil moisture for hydrological application: Synergistic evaluation using SMOS retrieved soil moisture

    Science.gov (United States)

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

    2015-10-01

    This study explores the performance of soil moisture data from the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim reanalysis datasets using the Weather Research and Forecasting (WRF) mesoscale numerical weather model coupled with the Noah Land surface model for hydrological applications. For evaluating the performance of WRF for soil moisture estimation, three domains are taken into account. The domain with best performance is used for estimating the soil moisture deficit (SMD). Further, several approaches are presented in this study to evaluate the efficiency of WRF simulated soil moisture for SMD estimation and compared against Soil Moisture and Ocean Salinity (SMOS) downscaled and non-downscaled soil moisture. In this study, the first approach is based on the empirical relationship between WRF soil moisture and the SMD on a continuous time series basis, while the second approach is focused on the vegetation cover impact on SMD retrieval, depicted in terms of growing and non-growing seasons. The linear growing and non-growing seasonal model in combination performs well with the NSE = 0.79, RMSE = 0.011 m; Bias = 0.24 m, in comparison to linear model (NSE = 0.70, RMSE = 0.013 m; Bias = 0.01 m). The performance obtained using WRF soil moisture is comparable to SMOS level 2 product but lower than the downscaled SMOS datasets. The results indicate that methodologies could be useful for modelers working in the field of soil moisture information system and SMD estimation at a catchment scale. The study could be useful for ungauged basins that pose a challenge to hydrological modeling due to unavailability of datasets for proper model calibration and validation.

  3. On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar.

    Science.gov (United States)

    Verhoest, Niko E C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M Susan; Mattia, Francesco

    2008-07-15

    Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale.

  4. Monitoring hillslope moisture dynamics with surface ERT for enhancing spatial significance of hydrometric point measurements

    Science.gov (United States)

    Hübner, R.; Heller, K.; Günther, T.; Kleber, A.

    2015-01-01

    Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.

  5. Differentiating between spatial and temporal effects by applying modern data analyzing techniques to measured soil moisture data

    Science.gov (United States)

    Hohenbrink, Tobias L.; Lischeid, Gunnar; Schindler, Uwe

    2013-04-01

    Large data sets containing time series of soil hydrological variables exist due to extensive monitoring work in the last decades. The interplay of different processes and influencing factors cause spatial and temporal patterns which contribute to the total variance. That implies that monitoring data sets contain information about the most relevant processes. That information can be extracted using modern data analysis techniques. Our objectives were (i) to decompose the total variance of an example data set of measured soil moisture time series in independent components and (ii) relate them to specific influencing factors. Soil moisture had been measured at 12 plots in an Albeluvisol located in Müncheberg, northeastern Germany, between May 1st, 2008 and July 1st, 2011. Each plot was equipped with FDR probes in 7 depths between 30 cm and 300 cm. Six plots were cultivated with winter rye and silage maize (Crop Rotation System I) and the other six with silage maize, winter rye/millet, triticale/lucerne and lucerne (Crop Rotation System II). We applied a principal component analysis to the soil moisture data set. The first component described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. Together they explained 80 % of the data set's total variance. An analysis of the first two components confirmed that measured plots showed similar signal damping extend in each depth. The fourth component revealed the impact of the two different crop rotation systems which explained about 4 % of the total variance and 13 % of the spatial variance of soil moisture data. That is only a minor fraction compared to small scale soil texture heterogeneity effects. Principal component analysis has proven to be a useful tool to extract less apparent signals.

  6. Spatial and temporal variability of soil moisture in a restored reach of an Alpine river

    Science.gov (United States)

    Luster, Jörg

    2010-05-01

    replicates for each FPZ and depth. At all monitoring locations the occurrence of water saturation in a given soil layer could be related to river discharge and additional soil moisture peaks in topsoil to rain events. However, absolute soil moisture levels during unsatured conditions exhibited strong spatial variability in all FPZ, probably mainly due to variability in soil texture and plant cover. In addition, in the grass zone the major summer floodings changed conditions at least temporarily. On one hand, the soil's field capacity apparently increased stepwise with each flooding, which may be explained either by fresh input of fine sediments or by retarded wetting of hydrophobic microsites rich in soil organic matter. On the other hand, the dominant canary reed grass was irreversibly flattened by each flood and replaced by a new generation of small seedlings. Processes and events as those described before complicate predictions of soil moisture in highly dynamic and biologically active systems like colonized gravel bars. In addition, it has consequences for the rate of sensitive biogeochemical processes such as denitrification which is strongly affected by soil moisture.

  7. [Soil moisture content and fine root biomass of rubber tree (Hevea brasiliensis) plantations at different ages].

    Science.gov (United States)

    Lin, Xi-Hao; Chen, Qiu-Bo; Hua, Yuan-Gang; Yang, Li-Fu; Wang, Zhen-Hui

    2011-02-01

    By using soil core sampling method, this paper studied the soil moisture regime of rubber plantations and the fine root biomass of Hevea brasiliensis in immature period (5 a), early yielding period (9 a), and peak yielding period (16 a). With the increasing age of rubber trees, the soil moisture content of rubber plantations increased but the fine root biomass decreased. The soil moisture content at the depth of 0-60 cm in test rubber plantations increased with soil depth, and presented a double-peak pattern over the period of one year. The fine root biomass of rubber trees at different ages had the maximum value in the top 10 cm soil layers and decreased with soil depth, its seasonal variation also showed a double-peak pattern, but the peak values appeared at different time. Soil moisture content and soil depth were the main factors affecting the fine root biomass of H. brasiliensis.

  8. A synergistic approach for soil moisture estimation using modified Dubois model with dual-polarized SAR and optical satellite data

    Science.gov (United States)

    Thanabalan, P.; Vidhya, R.

    2016-05-01

    This paper discusses about an estimation of soil moisture in agricultural region using SAR data with the use of HH and HV polarization. In this study the semi empirical approach derived by Dubois et al (1) was modified to work using (σdegHH) and σ°VV) so that soil moisture can be obtained for the larger area extent. The optical remote sensing is helps to monitor changes in vegetation biomass and canopy cover surface reflectance by using NDVI and LAI from which the site suitability from different land use/land cover are identified. The second use involves retrieve the backscattering coefficient valuesσ°) derived from SAR for soil moisture studies. In SAR techniques, the relative surface roughness can be directly estimate using surface roughness derivation empirical algorithms. The mid incidence angle is used to overcome the incidence angle effect and it worked successfully to this study. The modified Dubois Model (MDM) in combination with The Topp's et al (2) model is used to retrieve soil moisture. These two models have equations (HH, VV) and two independent variables i.e. root mean square height (s) and dielectric constant (epsilon). The linear regression analysis is performed and the surface roughness derived from SAR is well correlated with ground surface roughness having the value of (r2 = 0.69). By using the dielectric constant (epsilon) the modified Dubois model in combination with Topp's model are performed and the soil moisture is derived from SAR having value of (r2 = 0.60). Thus, the derived model is having good scope for soil moisture monitoring with present availability of SAR datasets.

  9. Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

    Science.gov (United States)

    Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

    2011-01-01

    Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  10. Impact of soil moisture on extreme maximum temperatures in Europe

    Directory of Open Access Journals (Sweden)

    Kirien Whan

    2015-09-01

    Full Text Available Land-atmosphere interactions play an important role for hot temperature extremes in Europe. Dry soils may amplify such extremes through feedbacks with evapotranspiration. While previous observational studies generally focused on the relationship between precipitation deficits and the number of hot days, we investigate here the influence of soil moisture (SM on summer monthly maximum temperatures (TXx using water balance model-based SM estimates (driven with observations and temperature observations. Generalized extreme value distributions are fitted to TXx using SM as a covariate. We identify a negative relationship between SM and TXx, whereby a 100 mm decrease in model-based SM is associated with a 1.6 °C increase in TXx in Southern-Central and Southeastern Europe. Dry SM conditions result in a 2–4 °C increase in the 20-year return value of TXx compared to wet conditions in these two regions. In contrast with SM impacts on the number of hot days (NHD, where low and high surface-moisture conditions lead to different variability, we find a mostly linear dependency of the 20-year return value on surface-moisture conditions. We attribute this difference to the non-linear relationship between TXx and NHD that stems from the threshold-based calculation of NHD. Furthermore the employed SM data and the Standardized Precipitation Index (SPI are only weakly correlated in the investigated regions, highlighting the importance of evapotranspiration and runoff for resulting SM. Finally, in a case study for the hot 2003 summer we illustrate that if 2003 spring conditions in Southern-Central Europe had been as dry as in the more recent 2011 event, temperature extremes in summer would have been higher by about 1 °C, further enhancing the already extreme conditions which prevailed in that year.

  11. Using a diagnostic soil-plant-atmosphere model for monitoring drought at field to continental scales

    Science.gov (United States)

    Drought assessment is a complex undertaking, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the