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Sample records for soil moisture analysis

  1. Global Soil Moisture Analysis at DWD

    NASA Astrophysics Data System (ADS)

    Lange, M.

    2012-04-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    PubMed

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

    2015-07-21

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  6. Rank Stability Analysis of Surface and Profile Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Microwave soil moisture measurements and analysis

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

    An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  10. Soil Moisture Project Evaluation Workshop

    NASA Technical Reports Server (NTRS)

    Gilbert, R. H. (Editor)

    1980-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  12. Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

  13. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using historical satellite surface soil moisture products, the Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available ground observations. In order to adapt...

  14. Geospatial Analysis of Near-Surface Soil Moisture Time Series Data Over Indian Region

    NASA Astrophysics Data System (ADS)

    Berwal, P.; Murthy, C. S.; Raju, P. V.; Sesha Sai, M. V. R.

    2016-06-01

    The present study has developed the time series database surface soil moisture over India, for June, July and August months for the period of 20 years from 1991 to 2010, using data products generated under Climate Change Initiative Programme of European Space Agency. These three months represent the crop sowing period in the prime cropping season in the country and the soil moisture data during this period is highly useful to detect the drought conditions and assess the drought impact. The time series soil moisture data which is in 0.25 degree spatial resolution was analyzed to generate different indicators. Rainfall data of same spatial resolution for the same period, generated by India Meteorological Department was also procured and analyzed. Geospatial analysis of soil moisture and rainfall derived indicators was carried out to study (1) inter annual variability of soil moisture and rainfall, (2) soil moisture deviations from normal during prominent drought years, (3) soil moisture and rainfall correlations and (4) drought exposure based on soil moisture and rainfall variability. The study has successfully demonstrated the potential of these soil moisture time series data sets for generating regional drought surveillance information products, drought hazard mapping, drought exposure analysis and detection of drought sensitive areas in the crop planting period.

  15. Understanding Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  18. Soil moisture modeling review

    NASA Technical Reports Server (NTRS)

    Hildreth, W. W.

    1978-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Soil Moisture Workshop

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  2. SOIL moisture data intercomparison

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  3. Estimating error cross-correlations in soil moisture data sets using extended collocation analysis

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    Global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multisource soil moisture retrievals into a unified data set. However, this requires an appropriate parameterization of the error structures of the underlying data sets. While triple collocation (TC) analysis has been widely recognized as a powerful tool for estimating random error variances of coarse-resolution soil moisture data sets, the estimation of error cross covariances remains an unresolved challenge. Here we propose a method—referred to as extended collocation (EC) analysis—for estimating error cross-correlations by generalizing the TC method to an arbitrary number of data sets and relaxing the therein made assumption of zero error cross-correlation for certain data set combinations. A synthetic experiment shows that EC analysis is able to reliably recover true error cross-correlation levels. Applied to real soil moisture retrievals from Advanced Microwave Scanning Radiometer-EOS (AMSR-E) C-band and X-band observations together with advanced scatterometer (ASCAT) retrievals, modeled data from Global Land Data Assimilation System (GLDAS)-Noah and in situ measurements drawn from the International Soil Moisture Network, EC yields reasonable and strong nonzero error cross-correlations between the two AMSR-E products. Against expectation, nonzero error cross-correlations are also found between ASCAT and AMSR-E. We conclude that the proposed EC method represents an important step toward a fully parameterized error covariance matrix for coarse-resolution soil moisture data sets, which is vital for any rigorous data assimilation framework or data merging scheme.

  4. Evapotranspiration Controls Imposed by Soil Moisture: A Spatial Analysis across the United States

    NASA Astrophysics Data System (ADS)

    Rigden, A. J.; Tuttle, S. E.; Salvucci, G.

    2014-12-01

    We spatially analyze the control over evapotranspiration (ET) imposed by soil moisture across the United States using daily estimates of satellite-derived soil moisture and data-driven ET over a nine-year period (June 2002-June 2011) at 305 locations. The soil moisture data are developed using 0.25-degree resolution satellite observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), where the 9-year time series for each 0.25-degree pixel was selected from three potential algorithms (VUA-NASA, U. Montana, & NASA) based on the maximum mutual information between soil moisture and precipitation (Tuttle & Salvucci (2014), Remote Sens Environ, 114: 207-222). The ET data are developed independent of soil moisture using an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased ET rates, suggesting that land-atmosphere feedback processes minimize this variance (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from meteorological data measured at 305 common weather stations that are approximately uniformly distributed across the United States. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture. We fit evaporation efficiency curves across the United States at each of the 305 sites during the summertime (May-June-July-August-September). Spatial patterns are visualized by mapping optimal curve fitting coefficients across the Unites States. An analysis of efficiency curves and their spatial patterns will be presented.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  6. The Soil Moisture Analysis Rainfall Tool (SMART): Correcting satellite-based precipitation using land data assimilation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Despite the obvious physical connection between surface soil moisture conditions and antecedent rainfall, relatively little attention has been paid to date on integrating surface water balance information obtained from both spaceborne surface soil moisture and precipitation retrievals. Recently, Cr...

  7. Estimating error cross-correlations in soil moisture data sets using extended collocation analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Soil Moisture Memory in Climate Models

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  10. Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

    NASA Astrophysics Data System (ADS)

    Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

    2016-04-01

    Soil moisture distribution usually presents extreme variation at multiple spatial scales. Image analysis could be a useful tool for investigating these spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to describe the local scaling of apparent soil moisture distribution and (ii) to define apparent soil moisture patterns from vertical planes of Vertisol pit images. Two soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. One was excavated in April/2011 and the other pit was established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. For more details see Cumbrera et al. (2012). Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, using the concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012). This method is based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. We have applied it to each soil image. The results show that, in spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used to study the dynamical change of soil moisture sampling in agreement with previous results (Millán et al., 2016). REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. Analysis of Satellite Retreived Active-Passive Merged Soil Moisture Distribution: A Case Study Over India.

    NASA Astrophysics Data System (ADS)

    Chakravorty, A.; Chahar, B. R.; Sharma, O. P.; Dhanya, C. T.

    2014-12-01

    Soil moisture is the source of water for evapotranspiration over the continents and it participates in both energy and water balance of the earth. Soil moisture participates in the energy cycle by managing the partitioning of the energy budget into latent and sensible heat, there by influencing the hydrological cycle. But to better understand the influence of soil moisture on the hydrological cycle, large scale monitoring is required. The objective of this study is to qualitatively analyze the active-passive merged soil moisture distribution, prepared under the ESA_CCI programme, against two AMSR-E soil moisture distributions, AMSR-E/NSIDC (National Snow and Ice Data Center) and AMSR-E/VUA(Virje Universiet Amstradam) and GLDAS_NOAH model simulations. The ESA_CCI soil moisture distribution is also compared with the GPCC monthly precipitation distribution to observe the representativeness of the precipitation seasonality in the satellite retrieved soil moisture. India has been selected as the study area, esp. the Central Indian region, as it has shown to be a soil moisture hot-spot for land-surface atmosphere interaction. The preliminary study show that both ESA_CCI and AMSR-E/VUA soil moisture distributions capture similar seasonal patterns in addition to processes like rainfall events and inter-annual variations. In addition to this it was also observed that the soil moisture distribution of ESA_CCI and AMSR-E/VUA are linearly related to each other for more than 50% of the land points. In case of ESA_CCI and AMSR-E/NSIDC, the soil moisture distributions are able to capture similar seasonal patterns but not the random events and they also do not show a strong linear relationship. We also analyze the effect of topography and vegetation distribution on the error charactristics of the satellite retrieved soil moisture distributions.

  13. Evaluation of assumptions in soil moisture triple collocation analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually-independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and ort...

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Temporal stability analysis of surface and subsurface soil moisture for a transect in artificial revegetation desert area, China

    NASA Astrophysics Data System (ADS)

    Wang, Xin-ping; Pan, Yan-xia; Zhang, Ya-feng; Dou, Deqiang; Hu, Rui; Zhang, Hao

    2013-12-01

    We studied the temporal stability characteristics of near-surface soil moisture.The strong temporal persistence existed for near-surface soil moisture.Identified representative locations well-represented the mean soil moisture content.The mean soil moisture contents can be predicted by other topography and soil factors.A priori identification of representative locations is presently infeasible for other fields.

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

    NASA Technical Reports Server (NTRS)

    Milstead, B. W.

    1975-01-01

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

  19. Geostatistical analysis of soil moisture distribution in a part of Solani River catchment

    NASA Astrophysics Data System (ADS)

    Kumar, Kamal; Arora, M. K.; Hariprasad, K. S.

    2016-03-01

    The aim of this paper is to estimate soil moisture at spatial level by applying geostatistical techniques on the point observations of soil moisture in parts of Solani River catchment in Haridwar district of India. Undisturbed soil samples were collected at 69 locations with soil core sampler at a depth of 0-10 cm from the soil surface. Out of these, discrete soil moisture observations at 49 locations were used to generate a spatial soil moisture distribution map of the region. Two geostatistical techniques, namely, moving average and kriging, were adopted. Root mean square error (RMSE) between observed and estimated soil moisture at remaining 20 locations was determined to assess the accuracy of the estimated soil moisture. Both techniques resulted in low RMSE at small limiting distance, which increased with the increase in the limiting distance. The root mean square error varied from 7.42 to 9.77 in moving average method, while in case of kriging it varied from 7.33 to 9.99 indicating similar performance of the two techniques.

  20. Applications of soil moisture information

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  1. Assimilation of SMOS brightness temperatures in the ECMWF EKF for the analysis of soil moisture

    NASA Astrophysics Data System (ADS)

    Munoz-Sabater, Joaquin

    2012-07-01

    Since November 2nd 2009, the European Centre for Medium-Range Weather Forecasts (ECMWF) has being monitoring, in Near Real Time (NRT), L-band brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA). The main objective of the monitoring suite for SMOS data is to systematically monitor the difference between SMOS observed brightness temperatures and the corresponding model equivalent simulated by the Community Microwave Emission Model (CMEM), the so-called first guess departures. This is a crucial step, as first guess departures is the quantity used in the analysis. The ultimate goal is to investigate how the assimilation of SMOS brightness temperatures over land improves the weather forecast skill, through a more accurate initialization of the global soil moisture state. In this presentation, some significant results from the activities preparing for the assimilation of SMOS data are shown. Among these activities, an effective data thinning strategy, a practical approach to reduce noise from the observed brightness temperatures and a bias correction scheme are of special interest. Firstly, SMOS data needs to be significantly thinned as the data volume delivered for a single orbit is too large for the current operational capabilities in any Numerical Weather Prediction system. Different thinning strategies have been analysed and tested. The most suitable one is the assimilation of SMOS brightness temperatures which match the ECMWF T511 (~40 km) reduced Gaussian Grid. Secondly, SMOS observational noise is reduced significantly by averaging the data in angular bins. In addition, this methodology contributes to further thinning of the SMOS data before the analysis. Finally, a bias correction scheme based on a CDF matching is applied to the observations to ensure an unbiased dataset ready for assimilation in the ECMWF surface analysis system. The current ECMWF operational soil moisture analysis

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  3. Comparative analysis of surface soil moisture retrieval using VSWI and TVDI in karst areas

    NASA Astrophysics Data System (ADS)

    Yan, Hongbo; Zhou, Guoqing; Lu, Xianjian

    2015-12-01

    Vegetation Supply Water Index (VSWI) and Temperature Vegetation dryness Index (TVDI) are two most commonly used methods for surface soil moisture (SSM) retrieval using electromagnetic spectrum of visible, near infrared and thermal infrared band. Both of them take into account the effect of vegetation index (VI) and surface temperature (Ts) on SSM. A comparative analysis of the ability and effect of the two methods for SSM retrieval in karst areas was carried out, using the remote sensing data of Landsat 8 OLI_TIRS. The study area is located in Guilin, which is a typical karst area. The experimental results show that TVDI is more suitable for SSM retrieval in karst areas.

  4. Radar scattering and soil moisture

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  5. SMALT - Soil Moisture from Altimetry

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Coopersmith, Evan J.; Bell, Jesse E.; Cosh, Michael H.

    2015-05-01

    Soil moisture estimates are valuable for hydrologic modeling, drought prediction and management, climate change analysis, and agricultural decision support. However, in situ measurements of soil moisture have only become available within the past few decades with additional sensors being installed each year. Comparing newer in situ resources with older resources, previously required a period of cross-calibration, often requiring several years of data collection. One new technique to improve this issue is to develop a methodology to extend the in situ record backwards in time using a soil moisture model and ancillary available data sets. This study will extend the soil moisture record of the U.S. Climate Reference Network (USCRN) by calibrating a precipitation-driven model during the most recent few years when soil moisture data are available and applying that model backwards temporally in years where precipitation data are available and soil moisture data are not. This approach is validated by applying the technique to the Soil Climate Analysis Network (SCAN) where the same model is calibrated in recent years and validated during preceding years at locations with a sufficiently long soil moisture record. Results suggest that if two or three years of concurrent precipitation and soil moisture time series data are available, the calibrated model's parameters can be applied historically to produce RMSE values less than 0.033 m3/m3. With this approach, in locations characterized by in situ sensors with short or intermittent data records, a model can now be used to fill the relevant gaps and improve the historical record as well.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Refinement of SMOS multi-angular brightness temperature toward soil moisture retrieval and its analysis over reference targets

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) satellite is scheduled for launch in 2014. It will provide global measurements of soil moisture with a 3-day revisit time and accuracy of 0.04 m3/m3 at three spatial resolutions; 40 km, 10 km and 3 km. Of these, the 40 km resolution soil moisture product, whi...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

    Peterson, John B. (Inventor)

    1982-01-01

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

  15. Soil Moisture from Altimetry - SMALT

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  18. Estimation of Surface Soil Moisture Using Fractal

    NASA Astrophysics Data System (ADS)

    Chen, Yen Chang; He, Chun Hsuan

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  20. Soil Moisture Retrieval from Aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1994-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objective of this study was to evaluate saflufenacil degradation and persistence in soils from rice regions under field capacity (non-flooded) and saturated (flooded) conditions. Saflufenacil dissolved in acetonitrile was added into pre-incubated samples at the rate of 2000 g ha-1. The amount of...

  4. The Impact of Soil Moisture Anomalies on the General Circulation: A Comprehensive Analysis over North America

    NASA Astrophysics Data System (ADS)

    Koster, R. D.; Chang, Y.; Wang, H.; Schubert, S. D.

    2015-12-01

    Recent work (Koster et al., 2014) has demonstrated the potential for a soil moisture anomaly to influence the general circulation (as characterized by the meridional wind at 250 mb) and to influence thereby the surface meteorological conditions in remote locations, even a thousand kilometers away. An in-depth look at this phenomenon is now afforded by a more comprehensive set of AGCM ensemble experiments. Each experiment is designed to quantify the impact of a specific local dry soil moisture anomaly, prescribed somewhere in North America, on the general circulation. The locations tested in the different experiments span much of the continent, allowing a comprehensive picture of the circulation's sensitivity to soil moisture anomalies. The main result is that while the sensitivity does vary with the imposed anomaly's geographical location, a dry anomaly in general tends to induce, just to the east, a northerly flow at 250 mb, with (at times) consequent impacts on surface meteorological variables. These results tend to be supported by reanalysis data. Koster, R. D., Y. Chang, and S. D. Schubert, 2014: A mechanism for land-atmosphere feedback involving planetary wave structures. J. Climate, 27, 9290-9301.

  5. The Temperature in Microwave Soil Moisture Retrieval

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Soil moisture variability within remote sensing pixels

    NASA Astrophysics Data System (ADS)

    Charpentier, Michael A.; Groffman, Peter M.

    1992-11-01

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

  7. Interaction between soil moisture memory and different climate variables

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2015-04-01

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

  8. Role of soil moisture in maintaining droughts

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  9. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  11. Influence of soil moisture on soil respiration

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The aim of this work was to describe an impact of soil moisture on soil respiration. Study was performed on soil samples from morphologically diverse study site in loess region of Southern Moravia, Czech Republic. The original soil type is Haplic Chernozem, which was due to erosion changed into Regosol (steep parts) and Colluvial soil (base slope and the tributary valley). Soil samples were collected from topsoils at 5 points of the selected elevation transect and also from the parent material (loess). Grab soil samples, undisturbed soil samples (small - 100 cm3, and large - 713 cm3) and undisturbed soil blocks were taken. Basic soil properties were determined on grab soil samples. Small undisturbed soil samples were used to determine the soil water retention curves and the hydraulic conductivity functions using the multiple outflow tests in Tempe cells and a numerical inversion with HYDRUS 1-D. During experiments performed in greenhouse dry large undisturbed soil samples were wetted from below using a kaolin tank and cumulative water inflow due to capillary rise was measured. Simultaneously net CO2 exchange rate and net H2O exchange rate were measured using LCi-SD portable photosynthesis system with Soil Respiration Chamber. Numerical inversion of the measured cumulative capillary rise data using the HYDRUS-1D program was applied to modify selected soil hydraulic parameters for particular conditions and to simulate actual soil water distribution within each soil column in selected times. Undisturbed soil blocks were used to prepare thin soil sections to study soil-pore structure. Results for all soil samples showed that at the beginning of soil samples wetting the CO2 emission increased because of improving condition for microbes' activity. The maximum values were reached for soil column average soil water content between 0.10 and 0.15 cm3/cm3. Next CO2 emission decreased since the pore system starts filling by water (i.e. aggravated conditions for microbes

  12. Surface Soil Moisture Assimilation with SWAT

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    Zawadzki, Jarosław; Kȩdzior, Mateusz A.

    2014-09-01

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

  14. Analysis of spatial variability of near-surface soil moisture to increase rainfall-runoff modelling accuracy in SW Hungary

    NASA Astrophysics Data System (ADS)

    Hegedüs, P.; Czigány, S.; Pirkhoffer, E.; Balatonyi, L.; Hickey, R.

    2015-04-01

    Between September 5, 2008 and September 5, 2009, near-surface soil moisture time series were collected in the northern part of a 1.7 km2 watershed in SWHungary at 14 monitoring locations using a portable TDR-300 soil moisture sensor. The objectives of this study are to increase the accuracy of soil moisture measurement at watershed scale, to improve flood forecasting accuracy, and to optimize soil moisture sensor density. According to our results, in 10 of 13 cases, a strong correlation exists between the measured soil moisture data of Station 5 and all other monitoring stations; Station 5 is considered representative for the entire watershed. Logically, the selection of the location of the representative measurement point(s) is essential for obtaining representative and accurate soil moisture values for the given watershed. This could be done by (i) employing monitoring stations of higher number at the exploratory phase of the monitoring, (ii) mapping soil physical properties at watershed scale, and (iii) running cross-relational statistical analyses on the obtained data. Our findings indicate that increasing the number of soil moisture data points available for interpolation increases the accuracy of watershed-scale soil moisture estimation. The data set used for interpolation (and estimation of mean antecedent soil moisture values) could be improved (thus, having a higher number of data points) by selecting points of similar properties to the measurement points from the DEM and soil databases. By using a higher number of data points for interpolation, both interpolation accuracy and spatial resolution have increased for the measured soil moisture values for the Pósa Valley.

  15. Soil Moisture Monitoring at Watershed Scale in Eastern India

    NASA Astrophysics Data System (ADS)

    Panda, R. K.

    2015-12-01

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

  16. The impact of soil moisture inhomogeneities on modification of a mesoscale convective system: a budget-based model analysis

    NASA Astrophysics Data System (ADS)

    Adler, Bianca; Gantner, Leonhard; Kalthoff, Norbert

    2010-05-01

    In order to investigate the sensitivity of a mesoscale convective system (MCS) to soil moisture inhomogeneities in West Africa cloud-resolving simulations with the COSMO-Model initialized with European Centre for Medium-range Weather Forecasts analyses data were performed. Three scenarios were investigated: homogeneous soil type and soil moisture (HOM) and homogeneous soil type with a north-south oriented band of two degrees width with reduced soil moisture (BANDT) and with increased soil moisture (BANDM). In all experiments an MCS developed east of the band in the late afternoon. Precipitation related to the MCS was continuously strong in HOM. When the MCS approached the band with reduced soil moisture in BANDT precipitation decreased because of higher convective inhibition (CIN) ahead of the band. Reaching the drier band precipitation increased again. The moist band in BANDM caused an increase of precipitation ahead of the band and a decrease in the area with higher soil moisture caused by very high CIN values. Soil moisture inhomogeneities induced thermal circulations which led to modified conditions in the lower troposphere and to changes in CIN and accounted for the modification of precipitation of an MCS. In BANDT, precipitating cells already developed in the western part of the dry band in the late afternoon, where convergence, generated by thermal circulations and supported by downward mixing of momentum from the African Easterly Jet, triggered convection.

  17. ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Analysis and modelling of the temporal stability of throughfall and near-surface soil moisture at the plot scale in the Italian pre-Alps

    NASA Astrophysics Data System (ADS)

    Zuecco, Giulia; van Meerveld, Ilja; Penna, Daniele; Hopp, Luisa; Borga, Marco

    2016-04-01

    event and the start of the soil moisture measurements. The temporal stability of soil moisture was larger than the temporal stability of throughfall and they were also not significantly correlated. The patterns of temporal stability were also not related to canopy openness or LAI, suggesting that the spatial variability in throughfall is probably linked to small scale characteristics of the canopy. A soil moisture model was used to test which combination of soil properties and vegetation characteristics leads to uncorrelated patterns of temporal stability of throughfall and soil moisture. The application of the model revealed that a large spatial variability in saturated hydraulic conductivity that is correlated with the spatial variability in LAI and root fraction tends to strongly weaken the correlation between throughfall and soil moisture patterns. The analysis of field data combined with the model application suggests that in this specific forested hillslope the spatial organization of soil moisture is dominated by a combination of soil properties and vegetation characteristics, rather than by the throughfall spatial patterns. Keywords: throughfall; near-surface soil moisture; temporal stability; plot scale; spatial variability; forested hillslope.

  19. Soil-moisture sensors and irrigation management

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Soil moisture by extraction and gas chromatography

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  4. Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  5. Electrical methods of determining soil moisture content

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  6. Survey of methods for soil moisture determination

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  7. Evaluating ESA CCI soil moisture in East Africa

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  10. Measuring soil moisture with imaging radars

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  11. SMAP and SMOS soil moisture validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    Speranskaya, N. A.

    2009-04-01

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

  13. Soil moisture variability within remote sensing pixels

    SciTech Connect

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

    1992-11-30

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

  14. Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

    NASA Astrophysics Data System (ADS)

    Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

    2016-02-01

    Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    As soil moisture is an important driver for various climatic and hydrological processes, area-wide time series of soil moisture data are important for numerical weather predictions, for example at the European Centre for Medium-Range Weather Forecasts (ECMWF), as well as for climate and hydrological modeling. The Soil Moisture and Ocean Salinity (SMOS) satellite, launched in 2009, is an attempt to provide global soil moisture data in the required temporal resolution. SMOS records brightness temperatures in the L-Band at 1.4 GHz, which are converted into soil moisture through inverse modeling. This study uses reprocessed SMOS Level 2 soil moisture data from the year 2010 for a long-term validation in the Rur and Erft catchments in Northrhine-Westfalia, Germany. They are compared to time-series of soil moisture derived from Advanced Scatterometer (ASCAT) data. ASCAT is a real-aperture radar that measures surface backscattering coefficients in the C-band at 5.255 GHz with a resolution of 30 to 50 km. Through a time series-based change detection approach relative soil moisture is retrieved from the backscattering coefficients, which is then converted to absolute soil moisture with data on soil properties. The individual accuracy and suitability of both datasets for the further use in numerical weather prediction and hydrological modeling are analyzed with the help of a soil moisture reference calculated by WaSiM ETH, a grid-element-based hydrological model. The model was calibrated with soil moisture data from the wireless sensor network at two test sites in the study area. Regression between the in situ data and the model values shows good results, despite a small bias, with an overall RMSE coefficient of 0.05. Time-series of the observed and modeled data also indicate a good agreement. A first comparison of SMOS data with the soil moisture reference does not show a high correlation. Furthermore, the temporal development of the data is different for SMOS soil moisture

  16. Soil moisture sensing with microwave techniques

    NASA Technical Reports Server (NTRS)

    Schmugge, T.

    1980-01-01

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

  17. Investigation of remote sensing techniques of measuring soil moisture

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  18. SMALT - Soil Moisture from Altimetry project

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  20. Soil moisture monitoring for crop management

    NASA Astrophysics Data System (ADS)

    Boyd, Dale

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Pradhan, N. R.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  3. Soil moisture mapping for aquarius

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Spatio-Temporal Analysis of Model and Satellite Based Soil Moisture Estimations for Assessing Coupling Hot Spots in the Southern La Plata Basin

    NASA Astrophysics Data System (ADS)

    Bruscantini, C. A.; Karszenbaum, H.; Ruscica, R. C.; Spennemann, P.; Salvia, M.; Sorensson, A. A.; Grings, F. M.; Saulo, C.

    2015-12-01

    The southern La Plata Basin, located in southeastern South America (SESA), a region of great importance because of its hydrological characteristics, the fact that it has the largest population density and is one of the most productive regions in terms of agriculture, cattle raising and industry of the continent, has been identified as a strong hotspot between soil moisture (SM) and the atmosphere by different regional studies. Among them, Ruscica et al. (2014, Atmos. Sci. Let, Int. J. Climatol.), and Spennemann et al. (2015, Int. J. Climatol.) show, through different modeling approaches, the presence of strong soil moisture-precipitation and evapotranspiration interactions during austral summer in SESA, revealing similar hotspots. Nevertheless these studies have diverse limitations related to model assumptions and to vegetation parameterizations, as well as the lack of observational data for the evaluation of models performance (Ferguson and Wood, 2011, J. of Hydrometeorology). On the other hand, in the last decade several instruments on board satellites are providing soil moisture products globally and in a continuous way. A recent work by Grings et al. (2015, IEEE JSTARS, in press), done over the Pampas Plains in SESA showed characteristic soil moisture patterns that follow the Standardized Precipitation Index (SPI) under extreme wet and dry conditions In order to deepen and overcome some of the mentioned model limitations, this work adds satellite soil moisture and vegetation products in the spatio-temporal analysis of the regions of strong soil moisture-atmosphere interactions. The main objectives and related outcomes are: the verification of already identified regions where soil moisture anomalies may have an influence on subsequent precipitation, evapotranspiration and temperature anomalies, and the study of their seasonal characteristics and land cover influences.

  5. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

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

  6. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

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

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

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

    PubMed Central

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

    2009-01-01

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

  9. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1996-01-01

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

  10. Introducing a Soil Moisture Scaling Triangle

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2014-12-01

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

  11. Evaluating Soil Moisture Status Using an e-Nose

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    Kuhn, N. J.; Strunk, R.

    2012-04-01

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

  16. Soil moisture estimation from radar altimetry

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  18. Radar for Measuring Soil Moisture Under Vegetation

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  20. Estimating root zone soil moisture using near-surface observations from SMOS

    NASA Astrophysics Data System (ADS)

    Ford, T. W.; Harris, E.; Quiring, S. M.

    2014-01-01

    Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Root zone soil moisture is more important, particularly in vegetated regions. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and the soil moisture at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5-10 cm) and root zone (25-60 cm) soil moisture. An exponential decay filter is used to estimate root zone soil moisture using near-surface soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite. Root zone soil moisture derived from SMOS surface retrievals is compared to in situ soil moisture observations in the United States Great Plains. The SMOS-based root zone soil moisture had a mean R2 of 0.57 and a mean Nash-Sutcliffe score of 0.61 based on 33 stations in Oklahoma. In Nebraska, the SMOS-based root zone soil moisture had a mean R2 of 0.24 and a mean Nash-Sutcliffe score of 0.22 based on 22 stations. Although the performance of the exponential filter method varies over space and time, we conclude that it is a useful approach for estimating root zone soil moisture from SMOS surface retrievals.

  1. Impact of climate change on soil thermal and moisture regimes in Serbia: An analysis with data from regional climate simulations under SRES-A1B.

    PubMed

    Mihailović, D T; Drešković, N; Arsenić, I; Ćirić, V; Djurdjević, V; Mimić, G; Pap, I; Balaž, I

    2016-11-15

    We considered temporal and spatial variations to the thermal and moisture regimes of the most common RSGs (Reference Soil Groups) in Serbia under the A1B scenario for the 2021-2050 and 2071-2100 periods, with respect to the 1961-1990 period. We utilized dynamically downscaled global climate simulations from the ECHAM5 model using the coupled regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model). We analysed the soil temperature and moisture time series using simple statistics and a Kolmogorov complexity (KC) analysis. The corresponding metrics were calculated for 150 sites. In the future, warmer and drier regimes can be expected for all RSGs in Serbia. The calculated soil temperature and moisture variations include increases in the mean annual soil temperature (up to 3.8°C) and decreases in the mean annual soil moisture (up to 11.3%). Based on the KC values, the soils in Serbia are classified with respect to climate change impacts as (1) less sensitive (Vertisols, Umbrisols and Dystric Cambisols) or (2) more sensitive (Chernozems, Eutric Cambisols and Planosols). PMID:27473773

  2. Soil moisture at local scale: Measurements and simulations

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio

    2014-08-01

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

  3. Microwave radiometric measurements of soil moisture in Italy

    NASA Astrophysics Data System (ADS)

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

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

  4. The prototype SMOS soil moisture Algorithm

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. Microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  7. Effect of soil moisture on chlorine deposition.

    PubMed

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

    2014-02-28

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

  8. Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.

    1985-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  10. Surface and Profile Soil Moisture Spatial Analysis During an Excessive Rainfall Period in the Southern Great Plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this work we analyze the temporal stability of soil moisture content across the 61,000 ha Little Washita River Experimental Watershed (LWREW) and at a field scale of 64 ha as part of the remote sensing Cloud and Land Surface Interaction Campaign (CLASIC07) during June 2007 in south-central Oklaho...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    -CNR institute in Tito Scalo (south Italy). One measurement every two days were performed on average, in particular 44 sampling events during 80 days. In both case we present a correlation and a regression analysis conducted both on punctual measurements and on their spatial averages. The results show that the resistivity method can be conveniently applied for soil moisture retrieval with a fairly good accuracy. The capability of this technique to obtain information for the whole soil profile suggests its use to better investigate the role of soil moisture dynamics at catchment scale and its influence on the rainfall-runoff processes.

  15. Physical controls of soil moisture variability at multiple scales

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Mohanty, B.

    2013-12-01

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

  16. Soil Moisture Characterization for Biogenic Emissions Modeling in Texas

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    PubMed Central

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

    2015-01-01

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

  18. Measuring soil moisture with imaging radars

    SciTech Connect

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

    1995-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  20. Evaluation of soil moisture sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Comparing soil moisture memory in satellite observations and models

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

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

  2. Soil moisture in sessile oak forest gaps

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  4. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1973-01-01

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

  5. Soil moisture needs in earth sciences

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1992-01-01

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

  6. Effects of soil moisture on the diurnal pattern of pesticide emission: Numerical simulation and sensitivity analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate prediction of pesticide volatilization is important for the protection of human and environmental health. Due to the complexity of the volatilization process, sophisticated predictive models are needed, especially for dry soil conditions. A mathematical model was developed to allow simulati...

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

    NASA Astrophysics Data System (ADS)

    Pan, Feifei; Nieswiadomy, Michael; Qian, Shuan

    2015-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  11. Spatiotemporal variations of soil moisture in the Tarim River basin, China

    NASA Astrophysics Data System (ADS)

    Su, Buda; Wang, Anqian; Wang, Guojie; Wang, Yanjun; Jiang, Tong

    2016-06-01

    Based on in situ soil moisture and river runoff records in the Tarim River basin, usability of the long term Essential Climate Variable (ECV) soil moisture dataset is validated in the arid climatic region of China. The spatio-temporal variation of soil moisture and its possible influencing factors in the 1988-2013 is also preliminary analyzed in the current paper. Results reveal that the ECV soil moisture can capture the large scale dynamics of regional water cycle quite satisfactorily, showing good agreement with in situ observations in their seasonal and interannual variability. In the period of 1988-2013, the ECV soil moisture shows obvious increasing trends in the northwest and the southwest parts of the Tarim River basin, particularly in spring (March-May) and autumn (September-November). Statistical analysis further suggests that the variations of soil moisture in the Tarim River basin are more controlled by precipitation, and temperature is less effective in controlling of soil moisture variations.

  12. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

  13. Microwave soil moisture retrieval under trees

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Soil Moisture From Satellite Radar Altimetry (SMALT)

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  15. Soil Moisture Active Passive Validation Experiment 2008

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Estimating Subcanopy Soil Moisture with RADAR

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  17. SMAP validation of soil moisture products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Soil moisture and temperature algorithms and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Impact of Soil Moisture Initialization on Seasonal Weather Prediction

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    NASA Technical Reports Server (NTRS)

    1980-01-01

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

  3. SoilNet - A Zigbee based soil moisture sensor network

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  5. Preliminary assessment of soil moisture over vegetation

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1986-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture is a key element in the global cycles of water, energy, and carbon. Knowledge on the spatial and temporal distribution of the soil moisture content (SMC) is therefore essential for a number of hydrological applications as well as earth sciences like meteorology or climatology (Heathman et al., 2003). In the last few years there has been an increasing interest towards the estimation of SMC at local scales using active microwave sensors (Barret et al., 2009). Compared to passive microwave sensors, SAR offers the potential to provide data at high spatial resolution (modern sensors can acquire images with up to approximately 1 m), which is particularly important in mountainous areas. So far, these areas have been considered only marginally in research and only pioneer studies can be found in the literature (Brocca et al., 2012; Bertoldi et al. 2013). In this work we analyzed the temporal and spatial dynamics of the surface SMC (0 - 5 cm depth) on the basis of ground data collected by fixed meteorological stations located in the emerging Long-Term Ecological Research (LTER) site Mazia Valley (Province of Bolzano, South Tyrol, Italy), SAR data from ENVISATs ASAR sensor, wide swath (WS) mode (acquired between 2005 and 2012), and SMC estimates from the hydrological model GEOtop (Endrizzi et al., 2013). The SMC retrieval process was based on the support vector regression (SVR) method introduced by Pasolli et al. (2011). The training of the algorithm was based on data acquired in 2010. Furthermore, the SAR backscatter and derived SMC have been compared with time-series derived from the distributed hydrological model GEOtop. The differences in terms of temporal and spatial dynamic have been analyzed. The main goal of this work is to evaluate the spatial and temporal patterns of SAR derived SMC at field scale and to correlate them with ground information. This is a preparatory study to establish a methodology for the retrieval of SMC with high spatial and

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

    NASA Technical Reports Server (NTRS)

    Jackson, R. D. (Principal Investigator)

    1981-01-01

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

  8. Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using a decade of high-quality ground-based soil moisture observations acquired from the United States Department of Agriculture’s Soil Climate Analysis Network (SCAN), we calculate the mutual information content between multiple soil moisture variables and near-future vegetation condition to examin...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Microwave soil moisture estimation in humid and semiarid watersheds

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  12. Estimating Soil Moisture from Satellite Microwave Observations

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  13. Microwave Soil Moisture Retrieval Under Trees

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture is a key element in the global cycles of water, energy, and carbon. Knowledge on the spatial and temporal distribution of the soil moisture content (SMC) is therefore essential for a number of hydrological applications as well as earth sciences like meteorology or climatology (Heathman et al., 2003). In the last few years there has been an increasing interest towards the estimation of SMC at local scales using active microwave sensors (Barret et al., 2009). Compared to passive microwave sensors, SAR offers the potential to provide data at high spatial resolution (modern sensors can acquire images with up to approximately 1 m), which is particularly important in mountainous areas. So far, these areas have been considered only marginally in research and only pioneer studies can be found in the literature (Brocca et al., 2012; Bertoldi et al. 2013). In this work we analyzed the temporal and spatial dynamics of the surface SMC (0 - 5 cm depth) on the basis of ground data collected by fixed meteorological stations located in the emerging Long-Term Ecological Research (LTER) site Mazia Valley (Province of Bolzano, South Tyrol, Italy), SAR data from ENVISATs ASAR sensor, wide swath (WS) mode (acquired between 2005 and 2012), and SMC estimates from the hydrological model GEOtop (Endrizzi et al., 2013). The SMC retrieval process was based on the support vector regression (SVR) method introduced by Pasolli et al. (2011). The training of the algorithm was based on data acquired in 2010. Furthermore, the SAR backscatter and derived SMC have been compared with time-series derived from the distributed hydrological model GEOtop. The differences in terms of temporal and spatial dynamic have been analyzed. The main goal of this work is to evaluate the spatial and temporal patterns of SAR derived SMC at field scale and to correlate them with ground information. This is a preparatory study to establish a methodology for the retrieval of SMC with high spatial and

  15. Analysis of the TIR (8-13 ㎛) Emissivity Dependence on Soil Moisture in the Context of the SMOS Mission

    NASA Astrophysics Data System (ADS)

    Valor, E.; Mira, M.; Coll, C.; Caaselles, V.; Rubio, E.; Galve, J. M.; Niclos, R.; Sanchez, J. M.; Boluda, R.

    2010-12-01

    The influence of soil texture on emissivity is well known from experimental studies; however, up to now, few published works analyze the soil moisture (SM) effect on thermal emissivities. The SMOS mission is a good opportunity to address this study by combining data coming from different satellite-borne sensors: the MIRAS SM measurements and LSEs provided by instruments such as MODIS and ASTER. We conducted a laboratory experiment as a preparatory task before the availability of the first SMOS acquisitions. TIR emissivities of soils with different textures were measured for several SM contents under controlled conditions using the Box method and a high-precision multi-channel TIR radiometer. The results showed a common increase of emissivity with SM. The highest emissivity variations were observed in sandy soils, especially in 8-9 μm. A general and unique relationship were obtained considering several soil properties (i.e., organic matter, quartz, and carbonate contents), predicting TIR emissivities from SM with standard estimation errors less than ±0.008.

  16. Tree Species Specific Soil Moisture Patterns and Dynamics

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture is a critical variable in many kinds of applications including agriculture, water management, meteorology or climatology. This is especially true in the Mediterranean context, where soil moisture plays an important role in water resources management and hydrometeorological risks such as floods and droughts. Unfortunately, this variable is not widely observed in situ, so we lack data on its time evolution and spatial structure. Remote sensing has been used to estimate surface soil moisture because it provides comprehensive data over large surfaces. In this study we compared two different surface soil moisture remote sensing products; one derived from active microwave data of the ASCAT scatterometer instrument onboard METOP and the other from passive microwave data of the SMOS mission the first dedicated to estimate soil moisture. SMOS measuring frequency (1.4 GHz) is theoretically more suited to measure soil moisture than ASCAT measuring frequency (5.255 GHz) because of its lower vegetation effects. On the other hand, ASCAT- like instruments have been providing measurements for more than 2 decades and have been a key input in building the CCI Soil Moisture Variable. In order to get the best global soil moisture products it is thus essential to understand their respective performances and restrictions. The comparison has been carried out in Catalonia where we have implemented the SURFEX/ISBA land-surface model, which we forced with the SAFRAN meteorological analysis system. A downscaling algorithm has been also implemented and validated over the area to provide SMOS derived soil moisture fields at 1 km spatial resolution. Catalonia is located in the northeast of the Iberian Peninsula and its climate is typically Mediterranean, mild in winter and warm in summer. The Pyrenees and the neighbouring areas have a high-altitude climate, with minimum temperatures below 0º C, annual rainfall above 1000 mm and abundant snow during the winter. Along the coast

  20. Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modeling

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-08-01

    Assimilation of satellite soil moisture and streamflow data into a distributed hydrologic model has received increasing attention over the past few years. This study provides a detailed analysis of the joint and separate assimilation of streamflow and Advanced Scatterometer (ASCAT) surface soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed particle filter-Markov chain Monte Carlo (PF-MCMC) method. Performance is assessed over the Salt River Watershed in Arizona, which is one of the watersheds without anthropogenic effects in Model Parameter Estimation Experiment (MOPEX). A total of five data assimilation (DA) scenarios are designed and the effects of the locations of streamflow gauges and the ASCAT soil moisture on the predictions of soil moisture and streamflow are assessed. In addition, a geostatistical model is introduced to overcome the significantly biased satellite soil moisture and also discontinuity issue. The results indicate that: (1) solely assimilating outlet streamflow can lead to biased soil moisture estimation; (2) when the study area can only be partially covered by the satellite data, the geostatistical approach can estimate the soil moisture for those uncovered grid cells; (3) joint assimilation of streamflow and soil moisture from geostatistical modeling can further improve the surface soil moisture prediction. This study recommends that the geostatistical model is a helpful tool to aid the remote sensing technique and the hydrologic DA study.

  1. A method for estimating soil moisture availability

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1985-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  3. Effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge: A Field observation and analysis

    USGS Publications Warehouse

    Zhang, Y.-K.; Schilling, K.E.

    2006-01-01

    The effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge were studied with water level measurements collected from two monitoring wells over a period of 122 days. The two wells were installed under similar conditions except that one was drilled on the east side of a creek which was covered with grass, and the other on the west side of the creek which was burned into a bare ground. Substantial differences in water level fluctuations were observed at these two wells. The water level in the east grass (EG) well was generally lower and had much less response to rainfall events than the west no-grass (WNG) well. Grass cover lowered the water table, reduced soil moisture through ET losses, and thus reduced groundwater recharge. The amount of ET by the grass estimated with a water table recession model decreased exponentially from 7.6 mm/day to zero as the water table declined from near the ground surface to 1.42 m below the ground surface in 33 days. More groundwater recharge was received on the WNG side than on the EG side following large rainfall events and by significant slow internal downward drainage which may last many days after rainfall. Because of the decreased ET and increased R, significantly more baseflow and chemical loads may be generated from a bare ground watershed compared to a vegetated watershed. ?? 2005 Elsevier Ltd All rights reserved.

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

    NASA Technical Reports Server (NTRS)

    Wang, J. R.

    1992-01-01

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

  5. NASA Soil Moisture Active Passive (SMAP) Applications

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. Soil moisture at watershed scale: Remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Fang, Bin; Lakshmi, Venkat

    2014-08-01

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

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

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  9. Soil Moisture Dynamics and Evaporation in Arid Intermountain Environments

    NASA Astrophysics Data System (ADS)

    Hang, C.; Pardyjak, E.; Nadeau, D. F.; Jensen, D. D.; Hoch, S.

    2014-12-01

    Mountain flows have been studied for several decades now and it is safe to say that their main features are well understood under steady conditions and over idealized terrain. The Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program was designed to better understand atmospheric fluid dynamics across all scales over realistic mountainous terrain as well as under transient and steady conditions. As part of MATERHORN, a large field campaign was conducted in May 2013. The main study area, a playa site, covers an area of several hundred square kilometers. It is mostly devoid of vegetation, characterized by a flat surface, shallow water table and a heterogeneous soil moisture spatial distribution even in dry conditions. Recent studies have shown that soil moisture plays a critical role in the dynamics of mountain flows, but a detailed understanding of these has not been sufficiently quantified. The objectives of this study are thus: 1) to quantify the spatial heterogeneity of soil moisture on the playa site; 2) to describe how soil moisture affects the surface energy balance; 3) to identify the key controlling mechanisms on evaporation after a rain event in an arid area; 4) to explore the existence of nocturnal evaporation and investigate its main driving factors. To do this, we applied the gravimetric method to measure volumetric water content in the surface soil layer (0 - 2 cm and 4 - 6 cm) twice per 24-h intensive observation period at 17 sites evenly distributed on a 180 x 240 m grid. Near-surface atmospheric variables as well as ground heat-flux were also measured by a flux tower located close to the soil sampling sites. Preliminary data analysis reveals that the highest spatial variability in surface soil moisture is found under dry conditions. Our results also show that decreasing surface albedo with increasing soil moisture sustained a powerful positive feedback loop promoting large evaporation rates. Finally, it was found that while

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

    NASA Technical Reports Server (NTRS)

    Bolten, John D.; Lakshmi, Venkat

    2009-01-01

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

  11. [Soil moisture dynamics under broad-leaved Korean pine forest in Changbai Mountains].

    PubMed

    Yang, Hong; Pei, Tiefan; Guan, Dexin; Jin, Changjie; Wang, Anzh

    2006-04-01

    The located observation on the soil moisture dynamics under broad-leaved Korean pine forest in Changbai Mountains in 1990 - 1992 and 2003 showed that the seasonal variation of soil moisture content could be divided into five periods, i. e., gathering water stage in spring, consuming water stage in arid season, holding water stage in rainy season, losing water stage in autumn, and relatively stable stage of soil moisture in winter-spring. By using standard deviation and variation coefficient, the vertical layers of soil moisture were divided into rapid change layer, active layer, and sub-active layer. Correlation analysis was applied to analyze the relationships of moisture content among different soil layers and the correlation between soil moisture and precipitation in the same period. PMID:16836083

  12. Assimilation of Passive and Active Microwave Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, Kurt C.; Coulibaly, Paulin

    2014-04-01

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

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

    USGS Publications Warehouse

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

    2008-01-01

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

  15. Evolution of physical controls for soil moisture in humid and subhumid watersheds

    NASA Astrophysics Data System (ADS)

    Gaur, Nandita; Mohanty, Binayak P.

    2013-03-01

    The covariability of soil moisture with soil, vegetation, topography, and precipitation is linked by physical relationships. The influence of each of these interdependent physical controls on soil moisture spatial distribution depends on the nature of heterogeneity present in the domain and evolves with time and scale. This paper investigates the effect of three physical controls, i.e., topography (slope), vegetation (type), and soil (texture), on soil moisture spatial distribution in the Little Washita and Walnut Creek watersheds in Oklahoma and Iowa, respectively, at two support scales. Point-support-scale data collected from four soil moisture campaigns (SMEX02, SMEX03, SMEX05, and CLASIC07) and airborne-scale data from three soil moisture campaigns (SGP97, SGP99, and SMEX02) were used in this analysis. The effect of different physical controls on the spatial mean and variability of soil moisture was assessed using Kruskal-Wallis and Shannon entropy respectively. It was found that at both (point and airborne) support scales, nonuniform precipitation (forcing) across the domain can mask the effect of the dominant physical controls on the soil moisture distribution. In order to isolate land-surface controls from the impact of forcing, the effect of precipitation variability was removed. After removing the effect of precipitation variability, it was found that for most soil moisture conditions, soil texture as opposed to vegetation and topography is the dominant physical control at both the point and airborne scales in Iowa and Oklahoma. During a very wet year (2007), however, the effect of topography on the soil moisture spatial variability overrides the effect of soil texture at the point support scale. These findings are valuable for developing any physically based scaling algorithms to upscale or downscale soil moisture between the point and watershed scales in the studied watersheds in humid and subhumid regions of the Great Plains of USA. These results may

  16. Uncertainty in SMAP Soil Moisture Measurements Caused by Dew

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Microbiology and Moisture Uptake of Desert Soils

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

  18. Capacitive Soil Moisture Sensor for Plant Watering

    NASA Astrophysics Data System (ADS)

    Maier, Thomas; Kamm, Lukas

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Rahmani, Abdolaziz; Golian, Saeed; Brocca, Luca

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Waite, W. P. (Principal Investigator)

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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

  6. Comparison of deep soil moisture in two re-vegetation watersheds in semi-arid regions

    NASA Astrophysics Data System (ADS)

    Yang, Lei; Chen, Liding; Wei, Wei; Yu, Yang; Zhang, Handan

    2014-05-01

    Soil moisture stored below rainfall infiltration depth is a reliable water resource for plant growth in semi-arid ecosystems. Along with the large-scale ecological restoration in Chinese Loess Plateau, identifying the ecohydrological response to human-introduced vegetation restoration has become an important issue in current research. In this study, soil moisture data in depth of 0-5 m was obtained by field observation and geostatistical method in two neighboring re-vegetation watersheds. Profile characteristics and spatial pattern of soil moisture was compared between different land use types, transects, and watersheds. The results showed that: (1) Introduced vegetation drastically decreased deep soil moisture when compared with farmland and native grassland. No significant differences in deep soil moisture were found between different introduced vegetation types. (2) An analysis of differences in soil moisture for different land use patterns indicated that land use had significant influence on deep soil moisture spatial variability. Land use structure determined the soil moisture condition and its spatial variation. (3) Vegetation restoration with introduced plants diminished the spatial heterogeneity of deep soil moisture on watershed scale. The improvement of land use management was suggested to improve the water management and maintain the sustainability of vegetation restoration.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    ) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.

  8. Concerning the relationship between evapotranspiration and soil moisture

    NASA Technical Reports Server (NTRS)

    Wetzel, Peter J.; Chang, Jy-Tai

    1987-01-01

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

  9. Remote sensing of soil moisture with microwave radiometers

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-06-01

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

  11. Remote sensing of vegetation and soil moisture

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  12. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  13. Mesoscale Monitoring of Soil Moisture Across a Statewide Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

    2012-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

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

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

    1983-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Long-term trend and variability of soil moisture over East Asia

    NASA Astrophysics Data System (ADS)

    Cheng, Shanjun; Guan, Xiaodan; Huang, Jianping; Ji, Fei; Guo, Ruixia

    2015-09-01

    The variability of soil moisture over East Asia was analyzed using a long-term data set from the Global Land Data Assimilation System. Overall, a clear decreasing trend occurred over a period of 63 years, with pronounced drying over northeast China, north China, part of Mongolia, and Russia near lake Baikal. Statistical analyses show that decreasing precipitation and global warming have different effects on the decrease in soil moisture. The qualitative analysis and quantitative contributions illustrated that soil drying is driven primarily by decreasing precipitation and is enhanced almost twofold by increasing temperatures. As soil moisture decreases, the positive feedback between soil moisture and temperature may result in future water shortages. Following the Representative Concentration Pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) simulation scenarios of Coupled Model Intercomparison Project phase 5, the model-predicted soil moisture demonstrated a continuously decreasing trend during the 21st century.

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

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

  20. Use of Ultrasonic Technology for Soil Moisture Measurement

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Quiring, S. M.

    2011-12-01

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

  4. Soil moisture impacts on convective precipitation in Oklahoma

    NASA Astrophysics Data System (ADS)

    Ford, Trenton W.

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

  5. On the spatio-temporal dynamics of soil moisture at the field scale

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Huisman, J. A.; Pachepsky, Y.; Montzka, C.; van der Kruk, J.; Bogena, H.; Weihermüller, L.; Herbst, M.; Martinez, G.; Vanderborght, J.

    2014-08-01

    In this paper, we review the state of the art of characterizing and analyzing spatio-temporal dynamics of soil moisture content at the field scale. We discuss measurement techniques that have become available in recent years and that provide unique opportunities to characterize field scale soil moisture variability with high spatial and/or temporal resolution. These include soil moisture sensor networks, hydrogeophysical measurement techniques, novel remote sensing platforms, and cosmic ray probes. Techniques and methods to analyze soil moisture fields are briefly discussed and include temporal stability analysis, wavelet analysis and empirical orthogonal functions. We revisit local and non-local controls on field scale soil moisture dynamics and discuss approaches to model these dynamics at the field scale. Finally, we address the topic of optimal measurement design and provide an outlook and future research perspectives.

  6. BOREAS HYD-1 Volumetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  7. Understanding tree growth in response to moisture variability: Linking 32 years of satellite based soil moisture observations with tree rings

    NASA Astrophysics Data System (ADS)

    Albrecht, Franziska; Dorigo, Wouter; Gruber, Alexander; Wagner, Wolfgang; Kainz, Wolfgang

    2014-05-01

    Climate change induced drought variability impacts global forest ecosystems and forest carbon cycle dynamics. Physiological drought stress might even become an issue in regions generally not considered water-limited. The water balance at the soil surface is essential for forest growth. Soil moisture is a key driver linking precipitation and tree development. Tree ring based analyses are a potential approach to study the driving role of hydrological parameters for tree growth. However, at present two major research gaps are apparent: i) soil moisture records are hardly considered and ii) only a few studies are linking tree ring chronologies and satellite observations. Here we used tree ring chronologies obtained from the International Tree ring Data Bank (ITRDB) and remotely sensed soil moisture observations (ECV_SM) to analyze the moisture-tree growth relationship. The ECV_SM dataset, which is being distributed through ESA's Climate Change Initiative for soil moisture covers the period 1979 to 2010 at a spatial resolution of 0.25°. First analyses were performed for Mongolia, a country characterized by a continental arid climate. We extracted 13 tree ring chronologies suitable for our analysis from the ITRDB. Using monthly satellite based soil moisture observations we confirmed previous studies on the seasonality of soil moisture in Mongolia. Further, we investigated the relationship between tree growth (as reflected by tree ring width index) and remotely sensed soil moisture records by applying correlation analysis. In terms of correlation coefficient a strong response of tree growth to soil moisture conditions of current April to August was observed, confirming a strong linkage between tree growth and soil water storage. The highest correlation was found for current April (R=0.44), indicating that sufficient water supply is vital for trees at the beginning of the growing season. To verify these results, we related the chronologies to reanalysis precipitation and

  8. Relating TRMM precipitation radar land surface backscatter response to soil moisture in the Southern United States

    NASA Astrophysics Data System (ADS)

    Puri, Sumit; Stephen, Haroon; Ahmad, Sajjad

    2011-05-01

    SummarySoil moisture is an important variable in the hydrological cycle and plays a vital role in agronomy, meteorology, and hydrology. It regulates the exchange of water and heat between land surface and atmosphere and thus plays an important role in the development of weather patterns. It is difficult to obtain a comprehensive spatio-temporal map of soil moisture because of expensive installation of soil moisture measuring instruments. In this paper, a model to estimate soil moisture ( m s) using Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) backscatter ( σ°) and Normalized Difference Vegetation Index (NDVI) is developed for the Southern United States. Soil moisture data from Soil and Climate Analysis Network (SCAN) stations is used to calibrate and validate the model. The estimated values of m s compare well with the ground measurements of soil moisture. The model works well for various landcovers but works best for low density vegetated areas (closed shrubland). All the soil moisture estimates in this landcover have an absolute error of less than 8%. The model performance deteriorates with increase in vegetation density (crops and forest). Overall, the model performance is satisfactory for all landcover types with RMSE less than 6.3% and absolute error of 10% or less for 90% of the estimates. Estimation of soil moisture over a large area with low error provides another use of TRMMPR data.

  9. Inflatable Antenna Microwave Radiometer for Soil Moisture Measurement

    NASA Technical Reports Server (NTRS)

    Bailey, M. C.; Kendall, Bruce M.; Schroeder, Lyle C.; Harrington, Richard F.

    1993-01-01

    Microwave measurements of soil moisture are not being obtained at the required spatial Earth resolution with current technology. Recently, new novel designs for lightweight reflector systems have been developed using deployable inflatable antenna structures which could enable lightweight real-aperture radiometers. In consideration of this, a study was conducted at the NASA Langley Research Center (LaRC) to determine the feasibility of developing a microwave radiometer system using inflatable reflector antenna technology to obtain high spatial resolution radiometric measurements of soil moisture from low Earth orbit and which could be used with a small and cost effective launch vehicle. The required high resolution with reasonable swath width coupled with the L-band measurement frequency for soil moisture dictated the use of a large (30 meter class) real aperture antenna in conjunction with a pushbroom antenna beam configuration and noise-injection type radiometer designs at 1.4 and 4.3 GHz to produce a 370 kilometer cross-track swath with a 10 kilometer resolution that could be packaged for launch with a Titan 2 class vehicle. This study includes design of the inflatable structure, control analysis, structural and thermal analysis, antenna and feed design, radiometer design, payload packaging, orbital analysis, and electromagnetic losses in the thin membrane inflatable materials.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    We present a method to derive soil moisture from the multi-frequency sensor Advanced Microwave Scanning Radiometer 2 (AMSR-2). Its predecessor, the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), has already provided Earth scientists with a consistent and continuous global soil moisture dataset. However, the AMSR-2 sensor has one big advantage in relation to the AMSR-E sensor; is has an additional channel in the C-band frequency (7.3 GHz). This channel creates the opportunity to have a better screening for Radio Frequency Interference (RFI) and could eventually lead to improved soil moisture retrievals. The soil moisture retrievals from AMSR-2 we present here use the Land Parameter Retrieval Model (LPRM) in combination with a new radio frequency interference masking method. We used observations of the multi-frequency microwave radiometer onboard the Tropical Rainfall Measuring Mission (TRMM) satellite to intercalibrate the brightness temperatures in order to improve consistency between AMSR-E and AMSR-2. Several scenarios to accomplish synergy between the AMSR-E and AMSR-2 soil moisture products were evaluated. A global comparison of soil moisture retrievals against ERA Interim re-analysis soil moisture demonstrates the need for an intercalibration procedure. Several different scenarios based on filtering were tested and the impact on the soil moisture retrievals was evaluated against two independent reference soil moisture datasets (reanalysis and in situ soil moisture) that cover the observation periods of the AMSR-E and AMSR-2 sensors. Results show a high degree of consistency between both satellite products and two independent reference products for the soil moisture products. In addition, the added value of an additional frequency for RFI detection is demonstrated within this study with a reduction of the total contaminated pixels in the 6.9 GHz of 66% for horizontal observations and even 85% for vertical observations when 7.3 and 10

  11. Evaluation and Application of Remotely Sensed Soil Moisture Products

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kanniah, Kasturi; Siang, Kang Chuen

    2016-07-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

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

  15. Spatial and temporal variability of soil moisture on the field with and without plants*

    NASA Astrophysics Data System (ADS)

    Usowicz, B.; Marczewski, W.; Usowicz, J. B.

    2012-04-01

    Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil

  16. Remote sensing as a tool in assessing soil moisture

    NASA Technical Reports Server (NTRS)

    Carlson, C. W.

    1978-01-01

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

  17. Impact of Surface Soil Moisture of Pesticide Volatilization Fluxes

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. SMOS Soil moisture Cal val activities

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  20. Joint microwave and infrared studies for soil moisture determination

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

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

  1. A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole

    NASA Astrophysics Data System (ADS)

    Yang, Kun; Qin, Jun; Zhao, Long; Chen, Yingying; Han, Menglei

    2013-04-01

    Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatial/temporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we established a dense monitoring network on central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0, 0.3, 0.1 degree) and four soil depths (0~5cm, 10cm, 20cm, and 40cm). The experimental area is characterized by low biomass, large soil moisture dynamic range and typical freeze-thaw cycle. The network consists of 56 stations with their elevation varying over 4470 ~ 4950 m. Soil texture and soil organic matters are measured at each station, as auxiliary parameters of this network. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. As the highest soil moisture network in the world, our network meets the requirement for evaluating a variety of soil moisture products and for soil moisture scaling. It also directly contributes to the "water-ice-air-ecosystem-human" interaction theme of the "Third Pole Environment" Program. The data will be publicized via the International Soil Moisture Network. Publication: Zhao, L., K. Yang, J. Qin, Y-Y Chen, W-J Tang, C. Montzka, H. Wu, C-G Lin, M-L Han, and H. Vereecken., 2012: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology DOI: 10.1016/j.jhydrol.2012.12.033.

  2. Spatial and temporal variability of soil moisture-atmosphere coupling on global scale

    NASA Astrophysics Data System (ADS)

    Schwingshackl, Clemens; Hirschi, Martin; Seneviratne, Sonia I.

    2016-04-01

    Climate in different regions of the world is affected by a variety of processes. One important factor influencing climatic conditions is the energy partitioning at the land surface into latent, sensible and ground heat fluxes. In some regions of the world, the magnitude of latent heat flux is dependent on available soil moisture. In these regions, one finds an essentially linear relation between soil moisture and evaporative fraction (i.e. the fraction of net radiation that goes into latent heat flux). However, the coupling strength at distinct locations can change in the course of the year or during particular weather conditions when the soil dries out. Using re-analysis and observation-based data we identify regions with strong coupling between soil moisture and evaporative fraction and investigate temporal variations of the coupling strength. Moreover, we determine the critical soil moisture value that separates the regime in which evaporative fraction is independent of soil moisture from that in which both variables are linearly coupled. Since the coupling between soil moisture and evaporative fraction influences strongly the energy partitioning at the surface, it affects as well the magnitude of sensible heat flux. Especially during dry spells, decreasing soil moisture and concomitant decreasing evaporative fraction cause increasing sensible heat flux, which might further lead to higher surface air temperatures. We investigate the strength of the single couplings (soil moisture → latent heat flux → sensible heat flux → temperature) in order to quantify the influence of soil moisture on surface air temperature. This allows us to comprehensively analyse temporal and spatial variations of the soil moisture-temperature coupling strength.

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

    PubMed

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

    2015-08-01

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

  4. Summer soil moisture spatiotemporal variability in southeastern Arizona

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. SMOS Soil Moisture Validation with Dense and Sparse Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Enhancing agricultural forecasting using SMOS surface soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Soil Moisture Algorithm Validation with Ground Based Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Field observations of soil moisture variability across scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Diurnal variation of diazinon volatilization: Soil moisture effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Global Evaluation of Remotely-Sensed Soil Moisture Retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. VALIDATION OF SATELLITE-BASED SOIL MOISTURE ALGORITHMS

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. WindSat Soil Moisture Algorithm and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Soil moisture determination study. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1979-01-01

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

  20. SMOS Soil Moisture Product Validation In Croplands

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Muro, G.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

    2014-06-01

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

  4. Microwave and gamma radiation observations of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Goodchild, Martin; Kühn, Karl; Jenkins, Dick

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals

    NASA Astrophysics Data System (ADS)

    Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.

    2009-04-01

    Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  12. Geophysical mapping of variations in soil moisture

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    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

  17. GNSSProbe, penetrating GNSS signals for measuring soil moisture

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  19. On the effects of hydrological model structure on soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Corato, Giovanni; Matgen, Patrick; Giustarini, Laura; Fenicia, Fabrizio

    2013-04-01

    Nowadays, satellite sensors allow obtaining soil moisture estimates at global scale with an adequate temporal and spatial resolution, thereby offering a theoretical chance to improve flood-forecasting systems based on rainfall-runoff models. In fact, the knowledge of antecedent soil moisture conditions plays a crucial role in predicting catchment response to rainfall events. In the literature, several studies have focused on the assimilation of soil moisture data into hydrological models. The results of these studies tend to show that an improvement in discharge and soil moisture forecasts can be obtained when the assimilated information originates from accurate in situ measurements. When dealing with the assimilation of remote sensing-derived soil moisture data, the reported results are more controversial. There is no doubt that the performances of soil moisture data assimilation studies depend on many factors: data assimilation scheme, hydrological model structure, accuracy and resolution of soil moisture data. As of today, these dependences are not well understood and the disparity of outcomes in past studies arguably reflects the differences in the design of the experiments. In this general context, the aim of this study is to investigate the effects of hydrological model structures on soil moisture data assimilation performance. The analysis focuses on the vertical "stratification" of the soil column in a conceptual hydrological model. We consider multiple structures that differ by the number of soil reservoirs and their respective sizes. The recently introduced SUPERFLEX hydrological modelling framework is used to this end. In fact, this framework allows building and modifying multiple hydrological models by combining three basic building blocks: reservoirs, lag functions and junctions. As a data assimilation scheme, the particle filter was considered. The area of interest is the Alzette catchment (1200 km2), located in Luxembourg, while the analysed period

  20. Optimal exploitation of AMSR-E signals for improving soil moisture estimation through land data assimilation

    NASA Astrophysics Data System (ADS)

    Zhao, L.; Yang, K.; Qin, J.; Chen, Y.

    2012-04-01

    Regional soil moisture can be estimated by assimilating satellite microwave brightness temperature into a land surface model (LSM). This study explores how to improve soil moisture estimation based on sensitivity analyses when assimilating AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) brightness temperatures. By assimilating a lower and higher frequency-combination, the land data assimilation system (LDAS) used in this study first estimates model parameters in a calibration pass, and then estimates soil moisture in an assimilation pass. The ground truth of soil moisture was collected at a soil moisture network deployed in a Mongolian semiarid area. Analyzed are the effects of different polarizations (horizontal and vertical), satellite overpass times (nighttime and daytime), and different frequency (from 6.9 GHz to 36.5 GHz) combinations on the accuracy of soil moisture estimation by the LDAS. The analyses indicate that assimilating the horizontal polarization underestimates soil moisture and assimilating the daytime signals produces obviously overestimates soil moisture. The former is perhaps due to the high sensitivity of the horizontal polarization to land surface heterogeneity, and the latter is due to the effective soil temperature for microwave emission in the daytime being close to the one at several centimeters soil depth but not to the surface skin temperature. Therefore, assimilating the nighttime vertical polarizations in the LDAS is recommended. A further analysis shows that assimilating different frequency-combinations produces different soil moisture estimates and none is always superior to the others, because different frequency signals may be contaminated by varying clouds and/or water vapor with different degrees. So, an ensemble estimation based on frequency-combinations was proposed to filter off, to some extent, the stochastic frequency-dependent biases. The ensemble estimation performs more robust when driven by

  1. Sensitivity of Residual Soil Moisture Content in VIC Model Soil Property Parameterizations for Sub-arctic Discontinuous Permafrost Watersheds

    NASA Astrophysics Data System (ADS)

    Endalamaw, A. M.; Bolton, W. R.; Hinzman, L. D.; Morton, D.; Cable, J.

    2015-12-01

    analysis reveals that, although residual soil moisture is sensitive for both sub-basins, the low permafrost sub-basin is more sensitive than the high permafrost dominated sub-basin. This may be due to the dry mineral soil layer and higher transpiration by the deciduous plants in the low-permafrost ecosystem.

  2. Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali

    NASA Astrophysics Data System (ADS)

    de Rosnay, P.; Gruhier, C.; Timouk, F.; Baup, F.; Mougin, E.; Hiernaux, P.; Kergoat, L.; LeDantec, V.

    2009-08-01

    SummaryThis paper presents the ground soil moisture measurements performed over the so-called Gourma meso-scale site in Mali, Sahel, in the context of the African Monsoon Multidisciplinary Analysis (AMMA) project. The Gourma meso-scale soil moisture network is part of a complete land surface processes observing and modelling strategy and is associated to vegetation and meteorological field measurements as well as soil moisture remote sensing. It is spanning 2° in latitude between 15°N and 17°N. In 2007, it includes 10 soil moisture stations, of which three stations also have meteorological and flux measurements. A relevant spatial sampling strategy is proposed to characterise soil moisture at different scales including local, kilometer, super-site and meso-scales. In addition to the local stations network, transect measurements were performed on different coarse textured (sand to sandy-loam) sites, using portable impedance probes. They indicate mean value and standard deviation (STD) of the surface soil moisture (SSM) at the kilometer scale. This paper presents the data set and illustrates soil moisture spatial and temporal features over the Sahelian Gourma meso-scale site for 2005-2006. Up-scaling relation of SSM is investigated from (i) local to kilometer scale and (ii) from local to the super site scale. It is shown to be stable in space and time (2005-2006) for different coarse textured sites. For the Agoufou local site, the up-scaling relation captures SSM dynamics at the kilometer scale with a 0.9% accuracy in volumetric soil moisture. At the multi-site scale, an unique up-scaling relation is shown to be able to represent kilometer SSM for the coarse textured soils of the meso-scale site with an accuracy of 2.2% (volumetric). Spatial stability of the ground soil moisture stations network is also addressed by the Mean Relative Difference (MRD) approach for the Agoufou super site where five soil moisture stations are available (about 25 km×25 km). This

  3. Soil moisture and the persistence of North American drought

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Hales, T.; Ford, C. R.

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  6. A Time Series Approach for Soil Moisture Estimation

    NASA Technical Reports Server (NTRS)

    Kim, Yunjin; vanZyl, Jakob

    2006-01-01

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

  7. The influence of soil moisture deficits on Australian heatwaves

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator)

    1977-01-01

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

  9. Response of grassland ecosystems to prolonged soil moisture deficit

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long x 0.60 m width x 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after three days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a KodakTM digital camera. The mean image size was 1600 x 945 pixels with one physical pixel ≈ 373 μm of the photographed soil pit. Each soil image was analyzed using two prefractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Γ1) and Shannon entropy at the unit scale (S1). All prefractal scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with prefractal parameters can be incorporated within site-specific agriculture toolbox. While fractal exponents condense information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates. Key words: Image analysis, fractal scaling, apparent soil moisture, Vertisols Acknowledgements This work has been

  12. The Effects of Wildfire on Soil Moisture Dynamics

    NASA Astrophysics Data System (ADS)

    Kanarek, M.; Cardenas, M.

    2013-12-01

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

  13. The Murrumbidgee soil moisture monitoring network data set

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the λ = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, θ, and powered to an exponent α > 0 (α =1: linear model; α ≠ 1: power model). Both soil moisture data the satellite retrieved (θ = θsat) and the estimates (θ = θest) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was

  16. Soil moisture storage and hillslope stability

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2014-05-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  20. Remote Sensing of Soil Moisture based on Dynamic Vegetation Scattering Properties for AMSR sensors

    NASA Astrophysics Data System (ADS)

    Du, J.; Kimball, J. S.; Jones, L. A.

    2015-12-01

    Accurate mapping of soil moisture and its spatial-temporal variations are of great significance to scientific studies on global water, energy and carbon cycles as well as operational applications including flood and drought monitoring, water resources management and crop yield forecasts. An approach for deriving volumetric soil moisture using satellite passive microwave radiometry from the Advanced Microwave Scanning Radiometers AMSR-E and AMSR2 was developed in this study. The algorithm adopts a weighted averaging strategy for soil moisture estimation based on a dynamic selection of empirically determined vegetation single-scatter albedo values. The resulting soil moisture retrievals demonstrate more realistic global patterns and seasonal dynamics relative to the baseline University of Montana (UMT) soil moisture product. Quantitative analysis of the new approach against in situ soil moisture measurements over four global study regions also indicates significant improvement over the baseline algorithm, with coefficients of determination (R2) between the retrievals and in-situ measurements increasing by approximately 16.9% and 41.5% respectively; and bias-corrected RMSEs decreasing by about 25.0% and 38.2% for respective ascending and descending orbital data records. Initial comparisons between soil moisture retrievals from AMSR2 and SMAP indicate coherent global and seasonal patterns.

  1. Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

    NASA Technical Reports Server (NTRS)

    Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

    1998-01-01

    Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

  2. Uncertainties of seasonal surface climate predictions induced by soil moisture biases in the La Plata Basin

    NASA Astrophysics Data System (ADS)

    Sorensson, Anna; Berbery, E. Hugo

    2015-04-01

    This work examines the evolution of soil moisture initialization biases and their effects on seasonal forecasts depending on the season and vegetation type for a regional model over the La Plata Basin in South America. WRF/Noah model simulations covering multiple cases during a two-year period are designed to emphasize the conceptual nature of the simulations at the expense of statistical significance of the results. Analysis of the surface climate shows that the seasonal predictive skill is higher when the model is initialized during the wet season and the initial soil moisture differences are small. Large soil moisture biases introduce large surface temperature biases, particularly for Savanna, Grassland and Cropland vegetation covers at any time of the year, thus introducing uncertainty in the surface climate. Regions with Evergreen Broadleaf Forest have roots that extend to the deep layer whose moisture content affects the surface temperature through changes in the partitioning of the surface fluxes. The uncertainties of monthly maximum temperature can reach several degrees during the dry season in cases when: (a) the soil is much wetter in the reanalysis than in the WRF/Noah equilibrium soil moisture, and (b) the memory of the initial value is long due to scarce rainfall and low temperatures. This study suggests that responses of the atmosphere to soil moisture initialization depend on how the initial wet and dry conditions are defined, stressing the need to take into account the characteristics of a particular region and season when defining soil moisture initialization experiments.

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

    NASA Astrophysics Data System (ADS)

    Ryu, D.; Akuraju, V.

    2013-12-01

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

  4. The impact of soil moisture initialization on seasonal precipitation in West Africa

    NASA Astrophysics Data System (ADS)

    Sealy, Andrea Michelle

    The objective of the study is to investigate the impact of soil moisture on seasonal precipitation in the West African Sahel. The relationship between late spring soil moisture and summer precipitation is examined based on data analysis and model simulations. An Empirical Orthogonal Function (EOF) analysis was conducted of twenty-four years (1981-2004) of monthly average soil moisture data from the National Centers for Environmental Prediction-Department of Energy Atmospheric Model Intercomparison Project (NCEP-DOE AMIP-II) Reanalysis (R-2). From the EOF analysis, only non-El Nino/non-La Nina (neutral) years with contrasting soil moisture anomaly fields were examined as possible case studies for what will be referred to as realistic model integrations. The model integrations were four months long initialized from May 1 st 2004 over a domain of 17.5°W-25°E, 10°S-20°N. For the realistic model integrations the soil moisture fields from 2004 and 1990 were selected for the control and perturbation runs respectively. 2004 was chosen as the year for the control model integration where all atmosphere and all land states would be from that specific year. For the perturbation run, the atmospheric and land states were from 2004 (the same as the control run), however the initial soil moisture was obtained from the 1990 soil moisture field. 1990 and 2004 resembled the first two leading modes of soil moisture variability from the EOF analysis. Additionally, idealized model integrations were conducted to assess the model sensitivity, that is, how the model simulated the behavior of surface fields such as sensible and latent heat fluxes, humidity, temperature and precipitation as a result of perturbations in initial soil moisture. For the idealized model integrations simplified cases were used where one of the model integrations was initialized with minimum soil water content and the other initialized with maximum soil water content. The results from the realistic and

  5. Remote monitoring of soil moisture using airborne microwave radiometers

    NASA Technical Reports Server (NTRS)

    Kroll, C. L.

    1973-01-01

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

  6. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  9. Long-term soil moisture variability from a new P-E water budget method

    NASA Astrophysics Data System (ADS)

    Zeng, N.; Yoon, J.; Mariotti, A.; Swenson, S. C.

    2006-05-01

    Basin-scale soil moisture is traditionally estimated using either land-surface model forced by observed meteorological variables or atmospheric moisture convergence from atmospheric analysis and observed runoff. Interannual variability from such methods suffer from major uncertainties due to the sensitivity to small imperfections in the land-surface model or the atmospheric analysis. Here we introduce a novel P-E method in estimating basin-scale soil moisture, or more precisely apparent land water storage (AWS). The key input variables are observed precipitation and runoff, and reconstructed evaporation. We show the results for the tropics using the example of the Amazon basin. The seasonal cycle of diagnosed soil moisture over the Amazon is about 200mm, compares favorably with satellite estimate from the GRACE mission, thus lending confidence both in this method and the usefulness of space gravity based large-scale soil moisture estimate. This is about twice as large as estimates from several traditional methods, suggesting that current models tend to under estimate the soil moisture variability. One of the advantage of the P-E method is to retrive long-term variability of the basin-scale soil moisture (including interannual and decadal time scales), which can provide valuable information to understand climate variability and to predict future climate condition. However, validation on reconstructed evaporation is very difficult due to lack of observation. The interannual variability in AWS in the Amazon basin is about 150mm, also consistent with GRACE data, but much larger than model results. We also apply this P-E method to the midlatitude Mississippi basin and discuss the impact of major 20th century droughts such as the dust bowl period on the long-term soil moisture variability. The results suggest the existence of soil moisture memories on decadal time scales, significantly longer than typically assumed seasonal timescales.

  10. Field Observations of Soil Moisture Variability across Scales

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  11. A New Scale Based 'Heterogeneity Matrix' for Improving Soil Moisture Spatial Scaling

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B. P.

    2012-12-01

    Soil moisture is a dynamic state variable of interest to agronomists, hydrologists and climate modelers alike. But the spatial scales at which they require soil moisture data are very different from each other. Past studies have established that the spatial structure of soil moisture is dependent upon the heterogeneity in physical controls, namely, precipitation, soil, vegetation and topography of the region. However, the spatial structure of soil moisture has also been found to be severely affected by scale. In order to estimate the spatial structure of soil moisture at different scales, it is important to first identify an effective scale based representation of heterogeneity with respect to its effect on soil moisture spatial distribution. In this study, we are attempting to devise a 3x3 heterogeneity matrix to accurately represent the existing heterogeneity in a region at the field, watershed and regional scale. Heterogeneity in terms of soil, vegetation and topography is being investigated for 2 hydro-climates (humid and sub-humid). An exhaustive sensitivity analysis using the Community Land -Surface Model (CLM) is being conducted to determine the most appropriate scale based parameters (like NDVI, % sand, slope etc.) that can represent the different physical controls. The statistical entropy of each chosen parameter will be used to represent the heterogeneity magnitude of a particular physical control which will form the diagonal of the heterogeneity matrix. The remainder elements of the matrix will be estimated as the joint entropy and will represent the correlation between the different physical controls.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Using magnetic susceptibility to discriminate between soil moisture regimes in selected loess and loess-like soils in northern Iran

    NASA Astrophysics Data System (ADS)

    Valaee, Morteza; Ayoubi, Shamsollah; Khormali, Farhad; Lu, Sheng Gao; Karimzadeh, Hamid Reza

    2016-04-01

    This study used discriminant analysis to determine the efficacy of magnetic measures for discriminating between four soil moisture regimes in northern Iran. The study area was located on loess deposits and loess-like soils containing similar parent material. Four soil moisture regimes including aridic, xeric, udic, and aquic were selected. A total of 25 soil profiles were drug from each regime and composite soil samples were collected within the moisture control section. A set of magnetic measures including magnetic susceptibility at low (χlf) and high (χhf) frequencies, frequency-dependent magnetic susceptibility (χfd), saturation isothermal remnant magnetization (SIRM), and isothermal remnant magnetization (IRM100 mT, IRM 20 mT) were measured in the laboratory. Dithionite citrate bicarbonate (Fed) and acid oxalate (Feo) contents of all soil samples were also determined. The lowest and highest χlf and χhf were observed in aquic and udic moisture regimes, respectively. A similar trend was obtained for Fed and Fed-Feo. The significant positive correlation between Fed and SIRM (r = 0.60; P < 0.01) suggested the formation of stable single domains (SSD) due to pedogenic processes. The results of discriminant analysis indicated that a combination of magnetic measures could successfully discriminate between the selected moisture regimes in the study area (average accuracy = 80%). It can thus be concluded that magnetic measures could be applied as a powerful indicator for differentiation of soil moisture regimes in the study area.

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

    NASA Technical Reports Server (NTRS)

    Welker, J. E.

    1984-01-01

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

  19. Soil moisture and evapotranspiration predictions using Skylab data

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Rysbaiuly, Bolatbek; Adamov, Abilmazhin

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

    Zribi, Mehrez; Baghdadi, Nicolas

    2015-04-01

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

  4. Landscape Controls on Monsoon Soil Moisture Distribution in Northern Sonora, Mexico

    NASA Astrophysics Data System (ADS)

    Gutierrez, H. A.; Vivoni, E. R.; Aragon, C. A.; Wyckoff, R.; Rinehart, A.; Watts, C.; Rodriguez, J. C.; Jackson, T. J.

    2004-12-01

    It is widely known that topographic and ecosystem variability exert a strong signature on the surface soil moisture distribution over regional scales, yet there is little observational evidence available to quantify this relationship, in particular over arid and semiarid areas. To properly determine the topographic and vegetation effects on soil moisture, and potentially use terrain and land-cover data to downscale remote sensing data, a spatially-extensive field sampling of soil moisture in regions of topographic variability is required. The SMEX04-NAME field campaign in northern Sonora, Mexico provides a unique opportunity for understanding the linkages between topographic position and the statistical properties of soil moisture during the North American Monsoon season in a sparsely observed region. In this study, we present a preliminary analysis of the data collected from both an in-situ network of soil moisture sensors and a two-week field campaign over a west-to-east transect in mountainous northern Sonora. The time evolution of topographic profiles of observed hydrometeorological quantities (rainfall, relative humidity, air temperature, pressure) and surface hydrologic properties (soil moisture, soil temperature) will be presented. We utilize available spatial data sets on the regional topography, soil types and vegetation distributions to quantify the linkage between monsoonal soil moisture, topography and ecosystem pattern. A preliminary comparison will also be made between hydrometeorological and surface hydrologic data and terrain attributes (elevation, slope, aspect, curvature) within a watershed encompassing the study transect. The topographic and vegetation data sets will then be used to interpolate field data and create soil moisture maps that can be aggregated to the aircraft and satellite footprint resolutions for conducting areal average comparisons to remotely sensed observations.

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

    NASA Astrophysics Data System (ADS)

    Ochsner, T.; Venterea, R. T.

    2009-12-01

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

  6. Improved soil moisture balance methodology for recharge estimation

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

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

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Holmes, Thomas

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. Analysis of water application efficiency and emission uniformity of drip irrigation systems based on space-time analysis of soil moisture patterns in soils

    NASA Astrophysics Data System (ADS)

    Shabeeb, Ahmeed; Taha, Uday; dragonetti, giovanna; Lamaddalena, Nicola; Coppola, Antonio

    2016-04-01

    In order to evaluate how efficiently and uniformly drip irrigation systems can deliver water to emitters distributed around a field, we need some methods for measuring/calculating water application efficiency (WAE) and emission uniformity (EU). In general, the calculation of the WAE and of other efficiency indices requires the measurement of the water stored in the root zone. Measuring water storage in soils allows directly saying how much water a given location of the field retains having received a given amount of irrigation water. And yet, due to the difficulties of measuring water content variability under an irrigation system at field scale, it is quite common using EU as a proxy indicator of the irrigation performance. This implicitly means assuming that the uniformity of water application is immediately reflected in an uniformity of water stored in the root zone. In other words, that if a site receive more water it will store more water. Nevertheless, due to the heterogeneity of soil hydrological properties the same EU may correspond to very different distributions of water stored in the soil root zone. 1) In the case of isolated drippers, the storages measured in the soil root zone layer shortly after an irrigation event may be or not different from the water height applied at the surface depending on the vertical/horizontal development of the wetted bulbs. Specifically, in the case of dominant horizontal spreading the water storage is expected to reflect the distribution of water applied at the surface. To the contrary, in the case of relatively significant vertical spreading, deep percolation fluxes (fluxes leaving the root zone) may well induce water storages in the root zone significantly different from the water applied at the surface. 2) The drippers and laterals are close enough that the wetted bulbs below adjacent drippers may interact. In this case, lateral fluxes in the soil may well induce water storages in the root zone which may be

  10. [Response of nitrification/denitrification and their associated microbes to soil moisture change in paddy soil].

    PubMed

    Liu, Ruo-Xuan; He, Ji-Zheng; Zhang, Li-Mei

    2014-11-01

    To investigate the effect of moisture change on nitrification and denitrification and their corresponding functional microbes, an acidic paddy soil from Taoyuan, Hunan Province was selected as the study object, and soil microcosm experiment containing 4 different water holding capacity (WHC) levels (30% WHC, 60% WHC, 90% WHC, and waterlog) was set up in this study. Results showed that no active nitrification and denitrification occurred in 30% WHC treatment as there were no obvious ammonia consumption and nitrate accumulation, while nitrification was active in 60% WHC and 90% WHC treatments as indicated by the obvious accumulation of nitrate in those two treatments. Meanwhile, significant ammonia consumption and N2O emission were only observed in 90% WHC treatment, implying that a much stronger nitrification in 90% WHC treatment than in 60% WHC treatment and the co-occurrence of nitrification and denitrification in 90% WHC treatment. In waterlog treatment, relatively lower N2O emission was detected and no obvious nitrification was detected, corresponding to a significant lower soil Eh in this treatment than in the other three non-waterlog treatments. Except the early stage of incubation (7 d), the abundance of nirS, nirK and ammonia-oxidizing bacteria (AOB) amoA genes showed similar responses to soil moisture change over time. Except the slight decrease in waterlog treatment, the abundances of the three genes increased significantly as the soil moisture increased, and the highest abundances of nirS, nirK, and amoA gene were observed in 90% WHC treatment in which the highest nitrification and denitrification activity was detected. T-RFLP analysis showed that the community composition of nirS gene-containing denitrifiers changed significantly in response to soil moisture change after two weeks, and soil Eh and C(w) were the main factors affecting the community composition of denitrifiers. PMID:25639106

  11. Volatilization of EPTC as affected by soil moisture

    NASA Astrophysics Data System (ADS)

    Fu, Liqun

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

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

    SciTech Connect

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

    2010-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    USGS Publications Warehouse

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

    2009-01-01

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

  15. Validation and trend analysis of ECV soil moisture data on cropland in North China Plain during 1981-2010

    NASA Astrophysics Data System (ADS)

    Wang, Sisi; Mo, Xingguo; Liu, Suxia; Lin, Zhonghui; Hu, Shi

    2016-06-01

    Global time series of the Essential Climate Variable (ECV) soil mositure (SM) is being developed from passive and active satellite microwave sensors at a coarse spatial resolution with Climate Change Initiative program funded by European Space Agency. This study aims to validate the reliability of ECV SM dataset, and attempts are made to analyze SM trends in cropland. Firstly, in-situ SM measurements during crop growing seasons from 1992 to 2010 for 228 stations across China and 21 stations over cropland of North China Plain (NCP) were employed to validate ECV SM product. Then, the spatiotemporal variations of ECV SM were analyzed during growing period of winter wheat (April-June) and summer maize (July-September) from 1981 to 2010 in NCP. Finally, the possible relationship between SM, precipitation, evapotranspiration and NDVI were explored. Results showed that ECV SM could generally capture the seasonal SM dynamics. The average triple collocation random error of ECV SM in China was 0.052 m3 m-3 while the error in cropland ranged from 0.003 to 0.156 m3 m-3. The averaged Spearman correlation coefficient between ECV SM and all in-situ observations was 0.42 (p < 0.01) in China and 0.43 (p < 0.01) for cropland over NCP. Spatially, ECV SM was decreasing in most areas during wheat season, whereas the trends of ECV SM were positive in south and negative in north during maize season in NCP, being consistent with the precipitation fluctuation. Overall, ECV SM is potentially suitable for trend analysis in NCP and its validations and analysis will be helpful for further enhancement of the ECV SM product.

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

    NASA Astrophysics Data System (ADS)

    Capecchi, V.; Gozzini, B.

    2012-04-01

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

  17. Preliminary results of SAR soil moisture experiment, November 1975

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.; Chang, A. T. C.; Schmugge, T. J.; Salomonson, V. V.; Wang, J. R.

    1979-01-01

    The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

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

    PubMed Central

    Dente, Laura; Su, Zhongbo; Wen, Jun

    2012-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

    Cisty, Milan; Suchar, Martin; Bajtek, Zbynek

    2010-05-01

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

  4. Root Water Uptake and Soil Moisture Pattern Dynamics - Capturing Connections, Controls and Causalities

    NASA Astrophysics Data System (ADS)

    Blume, T.; Heidbuechel, I.; Hassler, S. K.; Simard, S.; Guntner, A.; Stewart, R. D.; Weiler, M.

    2015-12-01

    We hypothesize that there is a shift in controls on landscape scale soil moisture patterns when plants become active during the growing season. Especially during the summer soil moisture patterns are not only controlled by soils, topography and related abiotic site characteristics but also by root water uptake. Root water uptake influences soil moisture patterns both in the lateral and vertical direction. Plant water uptake from different soil depths is estimated based on diurnal fluctuations in soil moisture content and was investigated with a unique setup of 46 field sites in Luxemburg and 15 field sites in Germany. These sites cover a range of geologies, soils, topographic positions and types of vegetation. Vegetation types include pasture, pine forest (young and old) and different deciduous forest stands. Available data at all sites includes information at high temporal resolution from 3-5 soil moisture and soil temperature profiles, matrix potential, piezometers and sapflow sensors as well as standard climate data. At sites with access to a stream, discharge or water level is also recorded. The analysis of soil moisture patterns over time indicates a shift in regime depending on season. Depth profiles of root water uptake show strong differences between different forest stands, with maximum depths ranging between 50 and 200 cm. Temporal dynamics of signal strength within the profile furthermore suggest a locally shifting spatial distribution of root water uptake depending on water availability. We will investigate temporal thresholds (under which conditions spatial patterns of root water uptake become most distinct) as well as landscape controls on soil moisture and root water uptake dynamics.

  5. Comparing and Combining Surface Soil Moisture Products from AMSR2

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    SciTech Connect

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

    1995-01-01

    Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth`s surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil are compared to observations of soil moisture, literally {open_quotes}ground truth,{close_quotes} snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity, may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring - SSiB incorrectly puts all the snowmelt into runoff. 34 refs., 19 figs., 3 tabs.

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

    PubMed

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

    2013-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  9. Variation Of Soil Moisture Patterns In Response To Anthropogenic Land Disturbances In A Semiarid Regional Landscape

    NASA Astrophysics Data System (ADS)

    Camarena, C.; Ren, J.; Jones, K.; Hempel, A.

    2005-12-01

    This project focuses on examination of the effects of various land management practices on soil moisture for semiarid regional landscapes. The project is at the Wellhausen Ranch Research Station located near Laredo, TX. This ranch has undergone various land disturbances such as root plowing and cattle overgrazing that have caused damage to the vegetation and natural communities. Two research sites were chosen within the ranch, one disturbed by root plowing and one undisturbed, to represent various land use environment. Soil moisture analysis was performed, using the WatchDog Irrigation System, to identify the effects of temperature, vegetation, diurnal, and seasonal effect on the soil moisture patterns. In addition, three soil moisture probes were placed on the same location at three different depths, 3, 5, and 8 inches, below the surface, to evaluate the soil moisture profile in vertical direction. Statistical analysis such as ANOVA, Friedman's test, and the sign test was conducted and the results suggested that soil moisture is influenced by land disturbances significantly in a semiarid regional landscape.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  11. Evaluation of polarimetric SAR parameters for soil moisture retrieval

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  12. Aircraft scatterometer observations of soil moisture on rangeland watersheds

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. In order to determine the value of the satellite data to NWS operations, the streamflow generated by HL-RDHM with and without soil moisture assimilation will be compared to USGS gauge data. Furthermore, we will apply the satellite-based soil moisture data with the FFG algorithm to evaluate how many hits, misses and false alarms are generated. This study will evaluate the value of remote sensing data in constraining the state of the system for main-stem and flash flood forecasting.

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

    NASA Astrophysics Data System (ADS)

    Dijkstra, F. A.; Cheng, W.

    2005-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  16. Soil moisture retrieval from Sentinel-1 satellite data

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  19. Bulk Density and Soil Moisture Sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Soil moisture monitoring methods: Strengths and limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Future Soil Moisture Satellite Missions and Research Needs

    NASA Astrophysics Data System (ADS)

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

    2001-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  3. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    NASA Astrophysics Data System (ADS)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

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

    SciTech Connect

    Luo, Yan; Houser, Paul; Anantharaj, Valentine G; Fan, Xingang; De Lannoy, Gabrielle; Zhan, Xiwu

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Yan, B.; Dickinson, R. E.

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  9. Optimal averaging of soil moisture predictions from ensemble land surface model simulations

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Su, C.-H.; Ryu, D.; Yilmaz, M. T.

    2015-11-01

    The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble's mutual error covariance. Here we propose a technique for obtaining such information using an instrumental variable (IV) regression approach and comparisons against a long-term surface soil moisture data set acquired from satellite remote sensing. Application of the approach to multimodel ensemble soil moisture output from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) and European Space Agency (ESA) Soil Moisture (SM) Essential Climate Variable (ECV) data set allows for the calculation of optimal weighting coefficients for individual members of the NLDAS-2 LSM ensemble and a biased-minimized estimate of uncertainty in a deterministic soil moisture analysis derived via optimal averaging. As such, it provides key information required to accurately condition soil moisture expectations using information gleaned from a multimodel LSM ensemble. However, existing continuity and rescaling concerns surrounding the generation of long-term, satellite-based soil moisture products must likely be resolved before the proposed approach can be applied with full confidence.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

    Rainfall and soil moisture are two key elements in modeling the interactions between the land surface and the atmosphere. Accurate and high-resolution real-time precipitation is crucial for monitoring and predicting the onset of floods, and allows for alert and warning before the impact becomes a disaster. Assimilation of remote sensing data into a flood-forecasting model has the potential to improve monitoring accuracy. Space-borne microwave observations are especially interesting because of their sensitivity to surface soil moisture and its change. In this study, we assimilate satellite soil moisture retrievals using the Variable Infiltration Capacity (VIC) land surface model, and a dynamic assimilation technique, a particle filter, to adjust the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) real-time precipitation estimates. We compare updated precipitation with real-time precipitation before and after adjustment and with NLDAS gauge-radar observations. Results show that satellite soil moisture retrievals provide additional information by correcting errors in rainfall bias. The assimilation is most effective in the correction of medium rainfall under dry to normal surface conditions, while limited/negative improvement is seen over wet/saturated surfaces. On the other hand, high-frequency noises in satellite soil moisture impact the assimilation by increasing rainfall frequency. The noise causes larger uncertainty in the false-alarmed rainfall over wet regions. A threshold of 2 mm day-1 soil moisture change is identified and applied to the assimilation, which masked out most of the noise.

  12. Using data assimilation techniques to calibrate soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the λ = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, θ, and powered to an exponent α > 0 (α =1: linear model; α ≠ 1: power model). Both soil moisture data the satellite retrieved (θ = θsat) and the estimates (θ = θest) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    USGS Publications Warehouse

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

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (?? SD) soil respiration rate in the DNR forests was (9.0 ?? 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ?? 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ?? 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities. ?? 2006 Institute of Botany, Chinese Academy of

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. Soil Moisture Estimation under Vegetation Applying Polarimetric Decomposition Techniques

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    mean square differences and categorical scores were used to evaluate the goodness of the results. This analysis wants to draw global picture of the performance of SM2RAIN algorithm in absence of errors in soil moisture and rainfall data. First preliminary results over Europe have shown that SM2RAIN performs particularly well over southern Europe (e.g., Spain, Italy and Greece) while its performances diminish by moving towards Northern latitudes (Scandinavia) and over Alps. The results on a global scale will be shown and discussed at the conference session. REFERENCES Brocca, L., Melone, F., Moramarco, T., Wagner, W. (2013). A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters, 40(5), 853-858. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141. Chen F, Crow WT, Ryu D. (2014) Dual forcing and state correction via soil moisture assimilation for improved rainfall-runoff modeling. J Hydrometeor, 15, 1832-1848. Crow, W.T., van den Berg, M.J., Huffman, G.J., Pellarin, T. (2011). Correcting rainfall using satellite-based surface soil moisture retrievals: the soil moisture analysis rainfall tool (SMART). Water Resour Res, 47, W08521. Dee, D. P.,et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteorol. Soc., 137, 553-597 Massari, C., Brocca, L., Moramarco, T., Tramblay, Y., Didon Lescot, J.-F. (2014). Potential of soil moisture observations in flood modelling: estimating initial conditions and correcting rainfall. Advances in Water Resources, 74, 44-53.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  2. Spatiotemporal analyses of soil moisture from point to footprint scale in two different hydroclimatic regions

    NASA Astrophysics Data System (ADS)

    Joshi, Champa; Mohanty, Binayak P.; Jacobs, Jennifer M.; Ines, Amor V. M.

    2011-01-01

    This paper presents time stability analyses of soil moisture at different spatial measurement support scales (point scale and airborne remote sensing (RS) footprint scale 800 m × 800 m) in two different hydroclimatic regions. The data used in the analyses consist of in situ and passive microwave remotely sensed soil moisture data from the Southern Great Plains Hydrology Experiments 1997 and 1999 (SGP97 and SGP99) conducted in the Little Washita (LW) watershed, Oklahoma, and the Soil Moisture Experiments 2002 and 2005 (SMEX02 and SMEX05) in the Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percent silt, percent sand, and soil texture) and topography (elevation and slope) are significant physical controls jointly affecting the spatiotemporal evolution and time stability of soil moisture at both point and footprint scales. In Iowa, using point-scale soil moisture measurements, the WC11 field was found to be more time stable (TS) than the WC12 field. The common TS points using data across the 3 year period (2002-2005) were mostly located at moderate to high elevations in both the fields. Furthermore, the soil texture at these locations consists of either loam or clay loam soil. Drainage features and cropping practices also affected the field-scale soil moisture variability in the WC fields. In Oklahoma, the field having a flat topography (LW21) showed the worst TS features compared to the fields having gently rolling topography (LW03 and LW13). The LW13 field (silt loam) exhibited better time stability than the LW03 field (sandy loam) and the LW21 field (silt loam). At the RS footprint scale, in Iowa, the analysis of variance (ANOVA) tests show that the percent clay and percent sand are better able to discern the TS features of the footprints compared to the soil texture. The best soil indicator of soil moisture time stability is the loam soil texture. Furthermore, the hilltops (slope ˜0%-0.45%) exhibited the best TS

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  5. The Multi-Level and Multi-Scale Factor Analysis for Soil Moisture Information Extraction by Multi-Source Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Yu, F.; Li, H. T.; Jia, Y.; Han, Y. S.; Gu, H. Y.

    2013-07-01

    The research on coupling both data source is very important for improving the accuracy of Image information interpretation and target recognition. In this paper a classifier is presented, which is based on integration of both active and passive remote sensing data and the Maximum Likelihood classification for inversion of soil moisture and this method is tested in Heihe river basin, a semi-arid area in the north-west of china. In the algorithm the wavelet transform and IHS are combined to integrate TM3, TM4, TM5 and ASAR data. The method of maximum distance substitution in local region is adopted as the fusion rule for prominent expression of the detailed information in the fusion image, as well as the spectral information of TM can be retained. Then the new R, G, B components in the fusion image and the TM6 is taken as the input to the Maximum Likelihood classification, and the output corresponds to five different categories according to different grades of soil moisture. The field measurements are carried out for validation of the method. The results show that the accuracy of completely correct classification is 66.3%, and if the discrepancy within one grade was considered to be acceptable, the precision is as high as 92.6%. Therefore the classifier can effectively be used to reflect the distribution of soil moisture in the study area.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  8. Physically plausible prescription of land surface model soil moisture

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  9. Remote sensing of soil moisture with microwave radiometers

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Schimel, J.

    2013-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  15. A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Tibetan Plateau and Its Applications

    NASA Astrophysics Data System (ADS)

    Yang, K.

    2013-12-01

    . Vereecken., 2013: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology, 482, 92-104 doi:10.1016/j.jhydrol.2012.12.033.

  16. Small-scale soil moisture determination with GPR

    NASA Astrophysics Data System (ADS)

    Igel, Jan; Preetz, Holger

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  19. A spatially coherent global soil moisture product with improved temporal resolution

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard A. M.; Holmes, Thomas R. H.; Parinussa, Robert M.; Owe, Manfred

    2014-08-01

    Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11 km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures. The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN). The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian

  20. Enhanced soil moisture drying in transitional regions under a warming climate

    NASA Astrophysics Data System (ADS)

    Cheng, Shanjun; Huang, Jianping

    2016-03-01

    We analyzed global trends of soil moisture for the period 1948-2010 using the Global Land Data Assimilation System data set. Soil moisture was dominated by negative trends, with pronounced drying over East Asia and the Sahel. Spatial analysis according to climatic region revealed that the most obvious drying occurred over transitional regions between dry and wet climates. The noticeable drying first took place in the humid transitional regions and extended to the dry transitional regions, beginning in the 1980s. The variability of soil moisture was notably related to the changes in precipitation and temperature, but with different roles. For the global average, precipitation had a dominant effect on the variability of soil moisture at interannual to decadal time scales, but temperature was the main cause of the long-term trend of soil moisture on the whole. The enhanced soil drying in the transitional regions was primarily caused by global warming, which is illustrated by regression analysis and the land surface model.

  1. Different responses of MODIS-derived NDVI to root-zone soil moisture in semi-arid and humid regions

    NASA Astrophysics Data System (ADS)

    Wang, Xianwei; Xie, Hongjie; Guan, Huade; Zhou, Xiaobing

    2007-06-01

    SummarySurface representation of the root-zone soil moisture is investigated so that feasibility of using optical remote sensing techniques to indirectly map root-zone soil moisture is assessed. Specifically, covariation of root-zone soil moisture with the normalized difference of vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) is studied at three sites (New Mexico, Arizona, and Texas) selected from the Soil Climate Analysis Network (SCAN). The three sites represent two types of vegetation (shrub and grass) and two types of climate conditions: semi-arid (New Mexico and Arizona) and humid (Texas). Collocated deseasonalized time series of soil moistures at five depths (5 cm, 10 cm, 20 cm, 50 cm, and 100 cm) and NDVI (8-day composite in 250 m resolution) during the period of February 2000 through April 2004 were used for correlation analysis. Similar analysis was also conducted for the raw time series for comparison purposes. The linear regression of both the deseasonalized time series and the raw time series was used to estimate root-zone soil moisture. Results show that (1) the deseasonalized time series results in consistent and significant correlation (0.46-0.55) between NDVI and root-zone soil moisture at the three sites; (2) vegetation (NDVI) at the humid site needs longer time (10 days) to respond to soil moisture change than that at the semi-arid sites (5 days or less); (3) the time-series of root-zone soil moisture estimated by a linear regression model based on deseasonalized time series accounts for 42-71% of the observed soil moisture variations for the three sites; and (4) in the semi-arid region, root-zone soil moisture of shrub-vegetated area can be better estimated using NDVI than that of grass-vegetated area.

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

    NASA Astrophysics Data System (ADS)

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

    1999-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Stacke, Tobias

    2013-04-01

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

  4. Radar estimates of soil moisture over the Konza Prairie

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  5. BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  6. Results of soil moisture flights during April 1974

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

  7. [Spatial heterogeneity of soil moisture and its relationships with environmental factors at small catchment level].

    PubMed

    Shi, Zhi-Hua; Zhu, Hua-De; Chen, Jia; Fang, Nu-Fang; Ai, Lei

    2012-04-01

    Taking the Wulongchi catchment of Danjiangkou in central China as a case, the soil moisture regime in the observation period from April to October, 2008 was divided into different dry-wet time periods by two way indicator species analysis (TWINSPAN), and the environmental factors that had significant effects on the spatial pattern of soil moisture in different dry-wet time periods were selected by forward selection and Monte Carlo tests. The redundancy analysis (RDA) was adopted to identify the relationships between the distribution pattern of soil moisture and the environmental factors in different time periods, and the partial RDA was applied to quantitatively analyze the effects of environmental factors, spatial variables, and their interactions on the variation pattern of the soil moisture. The soil moisture regime in the observation period was divided into 7 types, and grouped into 4 time periods, i. e. , dry, semi-arid, semi-humid, and humid. In dry period, land use type was the dominant factor affecting the spatial pattern of soil moisture, and the soil thickness, relative elevation, profile curvature, soil bulk density, and soil organic matter content also had significant effects. In semi-arid period, soil thickness played dominant role, and land use type, topographic wetness index, soil bulk density, and profile curvature had significant effects. In semi-humid period, topographic wetness index was the most important affecting factor, and the land use type and the sine value of aspect played significant roles. In humid period, the topographic compound index and the sine value of aspect were the dominant factors, whereas the relative elevation and catchment area were the important factors. In the four time periods, there was a better consistency between the spatial distribution pattern of soil moisture and the environmental ecological gradient. From dry period to humid period, the independent effects of environmental factors on soil moisture pattern

  8. Soil Moisture Extremes Observed by METOP ASCAT: Was 2012 an Exceptional Year?

    NASA Astrophysics Data System (ADS)

    Wagner, Wolfgang; Paulik, Christoph; Hahn, Sebastian; Melzer, Thomas; Parinussa, Robert; de Jeu, Richard; Dorigo, Wouter; Chung, Daniel; Enenkel, Markus

    2013-04-01

    In summer 2012 the international press reported widely about the severe drought that had befallen large parts of the United States. Yet, the US drought was only one of several major droughts that occurred in 2012: Southeastern Europe, Central Asia, Brazil, India, Southern Australia and several other regions suffered from similarly dry soil conditions. This raises the question whether 2012 was an exceptionally dry year? In this presentation we will address this question by analyzing global soil moisture patterns as observed by the Advanced Scatterometer (ASCAT) flown on board of the METOP-A satellite. We firstly compare the 2012 ASCAT soil moisture data to all available ASCAT measurements acquired by the instrument since the launch of METOP-A in November 2006. Secondly, we compare the 2012 data to a long-term soil moisture data set derived by merging the ASCAT soil moisture data with other active and passive microwave soil moisture retrievals as described by Liu et al. (2012) and Wagner et al. (2012) (see also http://www.esa-soilmoisture-cci.org/). A first trend analysis of the latter long-term soil moisture data set carried out by Dorigo et al. (2012) has revealed that over the period 1988-2010 significant trends were observed over 27 % of the area covered by the data set, of which 73 % were negative (soil drying) and only 27 % were positive (soil wetting). In this presentation we will show how the inclusion of the years 2011 and 2012 affects the areal extent and strengths of these significant trends. REFERENCES Dorigo, W., R. de Jeu, D. Chung, R. Parinussa, Y. Liu, W. Wagner, D. Fernández-Prieto (2012) Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7. Liu, Y.Y., W.A. Dorigo, R.M. Parinussa, R.A.M. de Jeu, W. Wagner, M.F. McCabe, J.P. Evans, A.I.J.M. van Dijk (2012) Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. The role of soil moisture on the coevolution of soil and vegetation in mountain grasslands

    NASA Astrophysics Data System (ADS)

    Bertoldi, Giacomo; Claudia, Notarnicola; Brenner, Johannes; Castelli, Mariapina; Greifeneder, Felix; Niedrist, Georg; Seeber, Julia; Tappeiner, Ulrike

    2016-04-01

    One of the key variables controlling the organization of vegetation and the coevolution of soils and landforms is soil moisture content (SMC). For this reason, understanding the controls on the spatial and temporal patterns of SMC is essential to predict how perturbations in vegetation and climate will affect mountain ecosystem functioning. In this contribution, we focus on the dynamic of surface SMC of water-limited alpine grasslands in the Long Term Ecological Research area Mazia Valley in the European Alps. We analyze the impacts of different land managements (meadows versus pastures) and its relationships with climate and topography. The area has been equipped since 2009 with a network of more than 20 stations, measuring SMC and climatic variables and with two eddy-covariance stations, measuring surface fluxes over meadows and pastures. Monthly biomass production data have been collected and detailed soil and spatial soil moisture surveys are available. Moreover, high spatial resolution SMC maps have been derived from satellites Synthetic Aperture Radar Radar (SAR) images (Sentinel 1 and RADARSAT2 images). Both ground surveys and remote sensing observations show persistent landscape-level patterns. Meadows, in general located in flatter areas, tend to be wetter. This leads to higher vegetation productivity and to the development of soils with higher water holding capacity, thus to a positive feedback on SMC. In contrast, pastures, located on steeper slopes with lower vegetation density and higher soil erosion, tend to be drier, leading to a negative feedback on SMC and soil development. This co-evolution of land cover and SMC leads therefore to persistent spatial patterns. In order to understand quantitatively such linked interactions, a sensitivity analysis has been performed with the GEOtop hydrological model. Results show how both abiotic (mainly slope and elevation) and anthropogenic (irrigation and soil management) factors exert a significant control on

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

    SciTech Connect

    Buckley, R.

    2001-06-27

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

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

    NASA Astrophysics Data System (ADS)

    Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

    2014-05-01

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

  13. Soil Moisture Experiments 2004 and 2005 Results and Plans

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.

    2005-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  19. Regions of strong coupling between soil moisture and precipitation.

    PubMed

    Koster, Randal D; Dirmeyer, Paul A; Guo, Zhichang; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C T; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David; Liu, Ping; Lu, Cheng-Hsuan; Malyshev, Sergey; McAvaney, Bryant; Mitchell, Ken; Mocko, David; Oki, Taikan; Oleson, Keith; Pitman, Andrew; Sud, Y C; Taylor, Christopher M; Verseghy, Diana; Vasic, Ratko; Xue, Yongkang; Yamada, Tomohito

    2004-08-20

    Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts. PMID:15326351

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Moradkhani, Hamid; Yan, Hongxiang

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  4. Alberta Soil Moisture Analyses using CaLDAS

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  5. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. The Effects of Landscape Heterogeneity on Brightness Temperature and Soil Moisture Retrieval

    NASA Astrophysics Data System (ADS)

    Neelam, M.; Mohanty, B.

    2013-12-01

    Soil moisture is a key variable to describe energy-water budgets at land surface. Passive remote sensing has played a crucial role in monitoring soil moisture from space. However, due to technical constrains and gaps in scientific understanding, the goal of 4% soil moisture accuracy are not obtained yet. With the advancement of technology and integration of radar/radiometer measurements, some of the measurement errors can be reduced. Nevertheless, the scientific understanding of the effects of landscape heterogeneity and its error contribution to soil moisture retrieval is lacking. In this paper, we have performed a synthetic study using tau-omega model, to understand the effects of within pixel heterogeneity in terms of different land cover types. This work focuses on understanding the effects of land cover type such as fresh/saline, vegetation density and type, percentage of clay on accuracy of soil moisture retrieval. Heterogeneous pixels cannot be characterized through simple averaging of contributing parameters, as these parameters exhibit non-linear behavior. For example, the brightness temperature observed for total VWC < 4.5 kg/m2 of mixed pixel with different vegetation types is far less than the average brightness temperature observed for individual vegetation types summing to total VWC. Such analysis is extended to different landcover types, to better address the effects of heterogeneity on soil moisture retrieval. Thus an attempt to develop an effective averaging technique to address the effect of nonlinear behavior on brightness temperature is made. The technique is tested by determining soil moisture accuracy obtained using retrieval algorithm.

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

    NASA Astrophysics Data System (ADS)

    Mecklenburg, S.; Kerr, Y. H.

    2015-12-01

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

  8. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate

    NASA Astrophysics Data System (ADS)

    Srivastava, Prashant K.; Han, Dawei; Rico Ramirez, Miguel A.; Islam, Tanvir

    2013-08-01

    Soil moisture is one of the important variables in hydrological modelling, which is now possible to be measured with remote sensing. This study is an attempt to evaluate the Soil Moisture and Ocean Salinity (SMOS) satellite derived soil moisture for hydrological applications at a catchment scale. The Soil Moisture Deficit (SMD) derived from a Probability Distribution Model is used as a benchmark for all comparisons. Three approaches are used for the evaluation of SMOS soil moisture. The first approach is based on ROSETTA pedotransfer functions (PTFs), while second and the third are based on linear/non-linear and seasonal algorithms particularly for growing and non-growing seasons respectively. The field capacity and permanent wilting point estimated from the simulated Water Retention Curve (WRC) through ROSETTA are used for the transformation of SMOS data into SMD. The growing seasons used in this study belong to the months from March to November, while the non-growing seasons comprise of months from December to February. The highest performance is given by a combined growing and non-growing season algorithms with the Nash Sutcliffe Efficiencies (NSEs) of 0.75 and RMSE = 0.01 m3/m3 followed by the linear and non-linear algorithms (NSE = 0.40-0.42; RMSE = 0.02 m3/m3). The worst performance is revealed by the PTFs indicating that it should be used with caution for direct coarse scale SMOS applications (NSE = -24.98 to -40.23) and need more treatments regarding the spatial and depth wise mismatch. The overall analysis reveals that SMOS soil moisture is of reasonable quality in estimating Soil Moisture Deficit at a catchment level with a local adjustment algorithm combining growing and non-growing seasons.

  9. Influence of soil moisture-carbon cycle interactions on the terrestrial carbon cycle over Europe

    NASA Astrophysics Data System (ADS)

    Mystakidis, Stefanos; Davin, Edouard L.; Gruber, Nicolas; Seneviratne, Sonia I.

    2016-04-01

    Water availability is a crucial limiting factor for terrestrial ecosystems, but relatively few studies have quantitatively assessed the influence of soil moisture variability on the terrestrial carbon cycle. Here, we investigate the role of soil moisture variability and state in the contemporary terrestrial carbon cycle over Europe. For this we use a Regional Earth System Model (RESM) based on the COSMO-CLM Regional Climate Model, coupled to the Community Land Model version 4.0 (CLM4.0) and its carbon-nitrogen module. The simulation setup consists of a control simulation over the period 1979-2010 in which soil moisture is interactive and three sensitivity simulations in which soil moisture is prescribed to a mean, a very dry or a very wet seasonal cycle without inter-annual variability. The cumulative net biome productivity varies markedly between the different experiments ranging from a strong sink of up to 6PgC in the wet experiment to a source of up to 1.2PgC in the dry experiment. Changes in the land carbon uptake are driven by a combination of two factors: the direct impact of soil moisture on plant's carbon uptake (essentially in southern Europe) and an indirect effect through changes in temperature affecting ecosystem respiration (mainly in central and northern Europe). We find that removing temporal variations in soil moisture dampens interannual variations in terrestrial carbon fluxes (Gross Primary Productivity, respiration, Net Biome Productivity) by more than 50% over most of Europe. Moreover, the analysis reveals that on annual scale about two-thirds of central Europe and about 70% of southern Europe display statistically significant effect of drying and/or wetting on the terrestrial carbon budget and its components. Our findings confirm the crucial role of soil moisture in determining the magnitude and the inter-annual variability in land CO2 uptake which is a key contributor to the year-to-year variations in atmospheric CO2 concentration.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Using Soil Moisture as a Guide in Controlling the Amount of Irrigated Water on Grass Lawns

    NASA Astrophysics Data System (ADS)

    Boateng, S.; Koenig, J.

    2007-05-01

    Soil moisture content is one of the factors that controls the infiltration capacity of soils. Precipitation and irrigation increase soil moisture which in turn reduces infiltration capacity. This results in increased runoff during subsequent storm events. Increased stormwater runoff may cause adverse environmental problems such as increased soil erosion, increased bed and suspended loads in streams, and increased non-point source pollution. Monitoring soil moisture on irrigated plots can be used as a guide for efficient use of irrigated water. Thus, irrigation systems only will be turned on when soil moisture falls below a threshold value for the respective soil type. However, landscapers at Northern Kentucky University (NKU) schedule the irrigation of grass lawns without taking into consideration the level of soil moisture. This has resulted in incidences of irrigation of the lawns during or immediately after a heavy storm event. Effective monitoring of the soil moisture of irrigated fields has been shown to help in controlling cost of irrigation and conserving valuable resources. This can be achieved by using instruments such as tensiometers and neutron probes to monitor soil moisture (Manning, 1992). On an irrigated field such as a grass lawn, the ideal condition will be to maintain soil moisture between field capacity and wilting point. The objective of this study is to investigate the effect of soil texture and slope on the amount of irrigated water used on selected grass lawns on NKU campus at Highland Heights, Kentucky. The grass lawns were selected based on low slope (0 to 10¬0), medium slope (10¬0 to 15¬0), and high slope (more than 15¬0 ). Two plots were selected for each slope category. The soil texture of each grass lawn was determined by performing standard particle size distribution analysis of samples taken during the installation of the tensiometers. A survey instrument and a GIS software were used to analyze the slopes. The tensiometers were

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Soil Moisture Remote Sensing using GPS-Interferometric Reflectometry

    NASA Astrophysics Data System (ADS)

    Chew, Clara

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

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

    PubMed

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

    2016-09-01

    The variation in intensity of 1.78MeV silicon, 6.13MeV oxygen, and 2.22MeV hydrogen prompt gamma rays from soil samples due to the addition of 5.1, 7.4, 9.7, 11.9 and 14.0wt% water was studied for 14MeV incident neutron beams utilizing a LaBr3:Ce gamma ray detector. The intensities of 1.78MeV and 6.13MeV gamma rays from silicon and oxygen, respectively, decreased with increasing sample moisture. The intensity of 2.22MeV hydrogen gamma rays increases with moisture. The decrease in intensity of silicon and oxygen gamma rays with moisture concentration indicates a loss of 14MeV neutron flux, while the increase in intensity of 2.22MeV gamma rays with moisture indicates an increase in thermal neutron flux due to increasing concentration of moisture. The experimental intensities of silicon, oxygen and hydrogen prompt gamma rays, measured as a function of moisture concentration in the soil samples, are in good agreement with the theoretical results obtained through Monte Carlo calculations. PMID:27337651

  17. Soil moisture applications of the heat capacity mapping mission

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

    Results are presented of ground, aircraft and satellite investigations conducted to evaluate the potential of the Heat Capacity Mapping Mission (HCMM) to monitor soil moisture and the depth of shallow ground water. The investigations were carried out over eastern South Dakota to evaluate the relation between directly measured soil temperatures and water content at various stages of canopy development, aircraft thermal scanner measurements of apparent canopy temperature and the reliability of actual HCMM data. The results demonstrate the possibility of evaluating soil moisture on the basis of HCMM apparent canopy temperature and day-night soil temperature difference measurements. Limitations on the use of thermal data posed by environmental factors which influence energy balance interactions, including phase transformations, wind patterns, topographic variations and atmospheric constituents are pointed out.

  18. A Flexible Moisture Content Probe for Unsaturated Soil Column Experiments

    SciTech Connect

    E. D. Mattson; K. E. Baker; C. D. Palmer; J. M Svoboda

    2006-05-01

    A commercially available soil moisture capacitance probe was modified by replacing rigid electrode traces with non-intrusive, flexible circuit board trace electrodes that can be attached to the interior of soil column walls. This new design minimizes soil packing difficulties and potential bias in flow pathways commonly associated with rigid probe installations in column experiments. Testing showed that the modified probe design provides reproducible output independent of sample bulk density. The electrical conductivity of the pore-water solution, however, affects the probe response. For cases where the specific conductance of the pore-water solution is constant, the probe can be calibrated. The flexible electrodes offer a simple means of minimizing sensor intrusion into laboratory soil columns while providing reproducible voltage output that is a function of moisture content.

  19. Multi-scale analysis of the impact of increased spatial resolution of soil moisture and atmospheric water vapour on convective precipitation

    NASA Astrophysics Data System (ADS)

    Khodayar, S.; Schaedler, G.; Kalthoff, N.

    2010-09-01

    The distribution of water vapour in the planetary boundary layer (PBL) and its development over time is one of the most important factors affecting precipitation processes. Despite the dense radiosonde network deployed during the Convective and Orographically-induced Precipitation Study (COPS), the high spatial variability of the water vapour field was not well resolved with respect to the detection of the initiation of convection. The first part of this investigation focuses on the impact of an increased resolution of the thermodynamics and dynamics of the PBL on the detection of the initiation of convection. The high spatial resolution was obtained using the synergy effect of data from the networks of radiosondes, automatic weather stations, synoptic stations, and especially Global Positioning Systems (GPSs). A method is introduced to combine GPS and radiosonde data to obtain a higher resolution representation of atmospheric water vapour. The gained spatial resolution successfully improved the representations of the areas where deep convection likelihood was high. Location and timing of the initiation of convection were critically influenced by the structure of the humidity field in the boundary-layer. The availability of moisture for precipitation is controlled by a number of processes including land surface processes, the latter are strongly influenced by spatially variable fields of soil moisture (SM) and land use. Therefore, an improved representation of both fields in regional model systems can be expected to produce better agreement between modelled and measured surface energy fluxes, boundary layer structure and precipitation. SM is currently one of the least assessed quantities with almost no data from operational monitoring networks available. However, during COPS an innovative measurement approach using a very high number of different SM sensors was introduced. The network consisted of newly developed low-cost SM sensors installed at 43 stations. Each

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

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

    PubMed

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

    2012-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  4. Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China

    NASA Astrophysics Data System (ADS)

    Feng, Huihui; Liu, Yuanbo

    2014-06-01

    Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, -0.08% and 0.27%, accounting for 7.26%, -3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    PubMed

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

    2005-03-01

    Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range. PMID:15934177

  7. Introduction to Soil Moisture Experiments 2004 (SMEX04)

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Validation of the ASAR Global Monitoring Mode Soil Moisture Product

    Technology Transfer Automated Retrieval System (TEKTRAN)

    It is well established in literature that integration of land surface variables such as soil moisture into forecasting models will lead to improved hydrologic prediction. Furthermore, most hydrological processes are best monitored at spatial scales of 1 km or higher. However, current and future pas...

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

    NASA Technical Reports Server (NTRS)

    Wilheit, T. T.

    1978-01-01

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

  10. The Soil Moisture Active Passive (SMAP) applications activity

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP mea...

  11. WindSat Global Soil Moisture Retrieval and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. SMOS Soil Moisture Validation with U.S. Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    For microwave remote sensing from space we must consider the one to forty km scale, which presents challenges. Soil moisture product validation for SMOS, as well as similar passive microwave satellite instruments, is a challenging. The disparity in spatial scale between conventional measurements of ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Why different passive microwave algorithms give different soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several algorithms have been used to retrieve surface soil moisture from brightness temperature observations provided by low frequency microwave satellite sensors such as the Advanced Microwave Scanning Radiometer on NASA EOS satellite Aqua (AMSR-E). Most of these algorithms have originated from the...

  15. Overview of the NASA soil moisture active/passive mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active Passive (SMAP) Mission is currently in design Phase C and scheduled for launch in October 2014. Its mission concept is based on combined L-band radar and radiometry measurements obtained from a shared, rotating 6-meter antennae. These measurements will be used to retrie...

  16. SMAPVEX08: Soil Moisture Active Passive Validation Experiment 2008

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive Mission (SMAP) is currently addressing issues related to the development and selection of retrieval algorithms as well as refining the mission design and instruments. Some of these issues require resolution as soon as possible. Several forums had identified specific ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. THE HYDROS AND SMOS SATELLITES: GLOBAL SOIL MOISTURE MAPPING

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Within the next five years two satellites will be launched that are designed specifically to map and monitor global soil moisture. Each of these is an exploratory mission and a step toward an operational satellite. Each satellite uses highly innovative but different technologies. The first of these ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  2. Combined Passive Active Soil Moisture Observations During CLASIC

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Soil Moisture Active Passive Satellite Status and Recent Validation