Science.gov

Sample records for soil moisture analysis

  1. A soil Moisture Analysis System for ELDAS

    NASA Astrophysics Data System (ADS)

    Seuffert, G.; Viterbo, P.; Mahfouf, J.

    2002-12-01

    Within the framework of the European Land Data Assimilation system (ELDAS) a soil moisture analysis scheme is built for the optimal estimate of soil moisture. The aim is to combine different sources of information on soil moisture: 2m temperature, relative humidity,IR heating rate and microwave brightness temperature observations. The system is developed and tested with a single column model (SCM) version of the full ECMWF-numerical weather prediction model. The SCM is forced with ERA40 data, but precipitation and solar radiation are prescribed from observations to avoid errors in the forcing crucial for soil moisture. The soil moisture analysis is based on a 1DVAR system with a Kalman filter (KF) update of the background error covariance matrix. Additionally, an approach to adapt the model error covariance matrix at each cycle is tested (adaptive KF). In a first step only 2m temperature and relative humidity observations are assimilated. The model results for two different case studies (FIFE 1987 and MUREX (France) field experiments) show that the new assimilation system performs better than systems based on optimal interpolation (currently operational at ECMWF) or nudging (operational till 1999 at ECMWF). The main reason for the improved performance of the 1DVAR scheme is that in this framework the gain matrix depends on the synoptical situation rather than being fixed to statistically derived values. Current work includes the incorporation of IR heating rates and brightness temperatures into the system and testing with the MUREX and SGP97 data sets.

  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. 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...

  6. 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.

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

    TOXLINE Toxicology Bibliographic Information

    Lakhankar T; Jones AS; Combs CL; Sengupta M; Vonder Haar TH; Khanbilvardi R

    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.

  8. 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.

  9. Midlatitude soil moisture: an experimental and modeling analysis

    NASA Astrophysics Data System (ADS)

    Baudena, M.; Bevilacqua, I.; Canone, D.; Ferraris, S.; Previati, M.; Provenzale, A.

    2009-04-01

    Soil moisture has a key role for the internal dynamics of ecohydrological systems and for their relationships with the climate system. At continental midlatitudes, soil moisture was recognized as a key variable in determining the strength of summer droughts (Ferranti and Viterbo, 2006). Lack of observations of soil moisture (and evapotranspiration) has been recognized as a main limitation to further progress, e.g. in the field of land-atmosphere interactions (Seneviratne and Stöckli, 2008). Obtaining soil moisture estimates from indirect observations is therefore very important. Here we compare direct measurement of soil moisture and different modeling approaches. Soil water data at hourly temporal resolution were collected from 2005 to present in the monitoring station located in Grugliasco, Torino (campus of the Agricultural Faculty of University of Torino, Italy). The station is located in the northwestern part of the Po Valley. The site is equipped with an automatic meteorological station, an automatic TDR station with 160 vertical probes ranging from 150 mm to 2000 mm length, and 80 mercury column tensiometers. The vegetation at the site is composed of grasses and grapevines. The dataset is compared with the output of a simple punctual model for soil moisture averaged over the active soil layer. The model includes infiltration, evapotranspiration, runoff and leakage. Rainfall, atmospheric pressure and temperature and wind velocity at the site are used as external input of the model. The model allows a detailed temporal description of soil moisture dynamics, with resolution of a few hours, comparable with the temporal resolution of the data. The importance of the various mechanisms of the soil water balance, and the model sensitivity to the different parameters are tested against the data observed. References: Ferranti, L. and P. Viterbo, J. Climate, 19, 3659-3680 (2006). Seneviratne, S.I., and R. Stöckli, In: Climate Variability and Extremes during the Past 100 years, Brönnimann et al. (eds.), Adv. Global Change Research, 33, Springer Verlag (2008).

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Coulibaly, P.

    2012-12-01

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

  12. 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.

  13. 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...

  14. 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...

  15. A Global Analysis on Satellite Derived and DGVM Surface Soil Moisture Products.

    NASA Astrophysics Data System (ADS)

    de Jeu, R.; Rebel, K.; Ciais, P.; Dolman, H.; Viovy, N.; Piao, S.; Noblet-Ducoudré, N.

    2008-05-01

    We evaluated the soil moisture component in a global dynamic vegetation model through a comparison of a recently developed global remotely sensed product with the modeled soil moisture. Quarter degree daily AMSR-E surface soil moisture, as derived from the Land Parameter Retrieval Model, was compared to the ORCHIDEE Global Dynamic Vegetation Model (GDVM) soil moisture products for the years 2003 and 2004. The LPRM converted the AMSR-E low frequency brightness temperatures in soil moisture of the first centimetres and is based on a one layer radiative transfer model (omega-tau). It used an analytical solution for the optical depth in combination with a soil temperature model to solve for soil moisture content. LPRM soil moisture is validated extensively over a large variety of land surfaces and has an average uncertainty of about 6 Vol. %. The model ORCHIDEE consists of three submodels: the SVAT SECHIBA, the dynamic global vegetation model LPJ and STOMATE. SECHIBA describes the soil water budget, where the soil has been divided into two layer: the top layer and the bottom layer. The top layer moisture changes through precipitation and evaporation and drainage to the deeper layer and as output. The moisture content of the bottom layer changes through drainage, both input from above, and output to the deep soil, and also through evaporation. Both layers can have variable depth, depending on the in and outgoing fluxes. The top layer can also be non-existing when the output equals the input or is larger. A third soil parameter that has been evaluated is the root zone soil moisture, this is a combination of the two soil layers adjusted for the presence of roots. We find a strong similarity between satellite soil moisture and modeled DVGM soil moisture in semi arid and temperate regions with a low vegetation density and in regions where there is a pronounced seasonal precipitation signal. Surprisingly the highest correlations are obtained between the DVGM bottom layer and AMSR-E surface soil moisture. Regions with a distinct seasonal moisture signal in both products also reveal high correlations. Low correlations can be found in regions where LPRM soil moisture is more uncertain (i.e. in northern latitude regions with a large amount of water bodies and dense vegetated areas). Next, an autocorrelation analysis was performed on both the AMSR-E and DVGM soil moisture to study the high frequency moisture fluctuations. The autocorrelation correlation length lag days were calculated. DVGM soil moisture show different lags days for wet and dry regions, where the top layer soil moisture and AMSR-E-show large resemblance in dry regions and AMSR-E is closer related to the bottom soil layer in wet regions. The relation between DVGM and AMSR-E soil moisture is rather complex, which makes soil moisture assimilation in the DVGM using satellite soil moisture promising but not straightforward.

  16. Remote soil moisture measurements

    NASA Technical Reports Server (NTRS)

    Stockhoff, E. H.; Frost, R. T.; Buerger, E. J.

    1973-01-01

    The degree of polarization of visible sunlight reflected from bare soils in agricultural test areas in the southwestern United States was measured by an airborne photopolarimeter. Surface soil specimens provided data concerning the surface moisture of the soil to which the polarization data were compared. The results indicate the feasibility of measuring soil surface moisture by airborne polarimeter instrumentation.

  17. Sensitivity Analysis of Soil Moisture Retrieval Model for Active Microwave Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Lakhankar, T.; Jones, A. S.; Seo, D.; Khanbilvardi, R.

    2009-12-01

    In this study, soil moisture retrieval model and its adjoint were developed for an active microwave remote sensing sensors (1.26 GHz and 5.3 GHz frequency). The active microwave soil moisture retrieval model is an extension of the Integral Equation Model (IEM) to make it more suitable to land surface model data assimilation use. The active microwave soil moisture retrieval model is complex, and before it is applied to the variational retrieval of soil moisture in conjunction with a soil and land model, we analyzed the adjoint development and control parameters under a variety of vegetation and soil moisture conditions. The adjoint sensitivity analysis is inherently independent of the data assimilation problem and the associated specification of the background covariance. The adjoint sensitivities have an ability to attribute cause and effect in a multivariate analysis. In constructing the adjoint of the soil moisture retrieval model, all input variables and parameters were treated as candidate control variables. The perturbation analysis of all input variables, that allows relative variable response ranking were performed. A comprehensive linear perturbation analysis was performed using five leading control variables (surface roughness, surface height, soil moisture, vegetation water content, and vegetation canopy height). The relative component strength analysis was carried out to infer the dominance of control variables under various land surface conditions.

  18. 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

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

    PubMed Central

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

    2010-01-01

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

  20. 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 breaks were found between different datasets. The factors causing these scale breaks are consistent with the findings of the geostatistical analysis. Furthermore, the joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at the upper and lower bounds of soil moisture (at maximum porosity and wilting point of the soils) can have a large influence on the soil moisture patterns and their autocorrelation structure. Depending on the prevalent type of land use and the time of year, vegetation causes a decrease or an increase of spatial variability in the soil moisture pattern.

  1. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  3. 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.

  4. 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 ...

  5. 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...

  6. 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.

  7. Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

    NASA Astrophysics Data System (ADS)

    Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

    2010-05-01

    Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

  8. 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 observed at high friction velocity. The magnitude of the percentage reduction/increase in the sandblasting flux decreases with the increase of the friction velocity for both soil moisture and soil clay fraction. Furthermore, these variables are interdependent leading to a gradual decrease in the percentage increase in the sandblasting flux for higher soil moisture values.

  9. 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.

  10. 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...

  11. 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...

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  14. 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...

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  17. 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...

  18. 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. ...

  19. A New Model of Dielectric Analysis for Measurement Soil Moisture Water Content

    NASA Astrophysics Data System (ADS)

    Mukhlisin, Muhammad; Saputra, Almushfi; Raihan Taha, Mohd

    2013-04-01

    Measurement of soil water content (?) has become an important part of the analysis of various fields of study, especially those involving irrigation in agriculture, forestry, hydrology and land activity. The models for measuring soil water content (?) is usually based on the permittivity (?) value. Many previous studies have been proposed e.g., Top et al. 1980; Roth et al. 1992; Malicki et al. 1996; and Robinson et al. 2005. Measurements using electromagnetic methods typically utilize permittivity parameters to determine water content in the soil. This method was used due to the significantly of differences permittivity between soil and water. In this study, a new model of dielectric analysis for measurement soil moisture water content is proposed and then compared with the existing models as the performance evaluation of the model. Result obtained shows that the new proposed model fits secondary experimental data reasonably well over a wide range of soil types. It is therefore suggested the new proposed model be used for the measurement of soil water content.

  20. Assessing representative soil moisture at watershed scale of Maqu catchment using spatio-temporal statistical analysis

    NASA Astrophysics Data System (ADS)

    Bhatti, H. A.; Rientjes, T. H. M.; Verhoef, W.

    2012-04-01

    In this study the temporal stability concept by Vachaud et al. (1985) is selected to evaluate a soil moisture measuring network in the Maqu catchment (3200 km2) in the north eastern part of the Tibetan plateau. The network serves for validation of coarse scale (25-50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. Besides identifying the Representative Mean Soil Moisture (RMSM) station for each respective probe depth, we applied the concept to a time series of satellite based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E) to evaluate if a RMSM pixel can be identified from the pixels that overlay the catchment. Analysis in this study serve to evaluate how well the satellite based moisture estimates match to observation at the RMSM stations for respective depths. We aim to evaluate if the RMSM can be estimated by the satellite product so to broaden the procedure to validate satellite images. We used moisture data for the year 2009 for which data is available at 15 minutes interval using ECH2O EC-TM probes. For each probe depth a Mean Relative Difference (MRD) plot is created to identify stations that are characterized by mean, wet and dry moisture conditions. The spearman non-parametric test and pearson's correlation coefficient test are used to analyze the temporal persistence of the ranks of the measuring stations. The analysis is applied to each probe depth to evaluate the effect of the measuring depth on determining the catchment RMSM. Similar analysis is carried out on the satellite soil moisture observations that cover a full hydrological year to identify a RMSM pixel. The result of the analysis on the network showed that the station that indicates RMSM changes for each probe depth and thus a single station that indicates the catchment RMSM cannot be identified. Results on identifying a RMSM pixel shows that such pixel can be identified, however in our case, a station is not available in the pixel footprint area to evaluate if a RMSM station coincides with the RMSM pixel. Therefore, the network may require optimization to represent catchment average moisture conditions. So to evaluate how well station based RMSM is represented by a satellite time series, we inter-compared the time series of the RMSM station at respective probe depths to the time series of the single pixels that overlay the station. We calculated the Root Mean Square Error and Bias for all probe depth and results indicate that satellite observations best match to observations indicating RMSM for probes installed at 20 cm depth. The study also showed that for selecting the RMSM station in the Maqu catchment a minimum observation period should cover an annual cycle with clear dry and wet seasons.

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Passive microwave soil moisture research

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  7. 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.

  8. 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.

  9. 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 comparison between Metop ASCAT and altimeter sigma0 over Saharan Africa. Geographical correlated areas of agreement and disagreement corresponding to underlying terrain are identified. SMALT products provide a first order estimation of soil moisture in areas of very dry terrain, where other datasets are limited. Potential to improve and expand the technique has been found, although further work is required to produce products with the same accuracy confidence as more established techniques. The data are made freely available to the scientific community through the website http://tethys.eaprs.cse.dmu.ac.uk/SMALT

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

    PubMed Central

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

    2009-01-01

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

  11. Soil moisture controls beyond the Darcy scale

    NASA Astrophysics Data System (ADS)

    Gaur, N.; Mohanty, B.

    2013-12-01

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

  12. 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...

  13. Sensitivity Analysis of Distributed Soil Moisture Profiles by Active Distributed Temperature Sensing

    NASA Astrophysics Data System (ADS)

    Ciocca, F.; Van De Giesen, N.; Assouline, S.; Huwald, H.; Lunati, I.

    2012-12-01

    Monitoring and measuring the fluctuations of soil moisture at large scales in the filed remains a challenge. Although sensors based on measurement of dielectric properties such as Time Domain Reflectometers (TDR) and capacity-based probes can guarantee reasonable responses, they always operate on limited spatial ranges. On the other hand optical fibers, attached to a Distribute Temperature Sensing (DTS) system, can allow for high precision soil temperature measurements over distances of kilometers. A recently developed technique called Active DTS (ADTS) and consisting of a heat pulse of a certain duration and power along the metal sheath covering the optical fiber buried in the soil, has proven a promising alternative to spatially-limited probes. Two approaches have been investigated to infer distributed soil moisture profiles in the region surrounding the optic fiber cable by analyzing the temperature variations during the heating and the cooling phases. One directly relates the change of temperature to the soil moisture (independently measured) to develop specific calibration curve for the soil used; the other requires inferring the thermal properties and then obtaining the soil moisture by inversion of known relationships. To test and compare the two approaches over a broad range of saturation conditions a large lysimeter has been homogeneously filled with loamy soil and 52 meters of fiber optic cable have been buried in the shallower 0.8 meters in a double coil rigid structure of 15 loops along with a series of capacity-based sensors (calibrated for the soil used) to provide independent soil moisture measurements at the same depths of the optical fiber. Thermocouples have also been wrapped around the fiber to investigate the effects of the insulating cover surrounding the cable, and in between each layer in order to monitor heat diffusion at several centimeters. A high performance DTS has been used to measure the temperature along the fiber optic cable. Several soil moisture profiles have been generated in the lysimeter either varying the water table height or by wetting the soil from the top. The sensitivity of the ADTS method for heat pulses of different duration and power and ranges of spatial and temporal resolution are presented.

  14. 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...

  15. 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...

  16. 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...

  17. Analysis of impact of heterogeneity at landscape level in retrieval of soil moisture from low-frequency radars

    NASA Astrophysics Data System (ADS)

    Burgin, M.; Tabatabaeenejad, A.; Moghaddam, M.

    2012-12-01

    Knowledge of soil moisture dynamics on a global scale is key in understanding the water and energy cycles. This understanding has critical impact on predicting future water resources and sustainability, and is invaluable across many disciplines such as hydrology, meteorology, and ecology, as well as in weather and climate prediction. To accommodate this need for global observations of surface soil moisture, NASA is developing the soil moisture active passive (SMAP) spaceborne mission carrying an L-band radar and radiometer to be launched in late 2014. The SMAP mission will carry both a radar and a radiometer allowing synergistic use of the two data types for soil moisture retrieval. Radar data are delivered at higher resolution (3 km) than the radiometer data (36 km), and allow finer analysis of the connection between land cover type and soil moisture. Most satellite resolution pixels contain highly heterogeneous scenes with small scale variability of soil moisture, soil texture, topography, and vegetation cover types. Traditional algorithms for radar soil moisture retrieval assume a homogeneous scene within each satellite resolution cell, which is not a reasonable assumption even for the 3 km resolution radar data from SMAP. This illuminates the need to develop spatial aggregation and disaggregation techniques using radar forward scattering models that assume homogeneity over finer scale sub-pixels and derive tailor-made models for their contribution to the coarse-scale satellite pixel for effective soil moisture retrieval. A physics-based remote sensing (radar) landscape simulator to analyze potentially large groups of georeferenced pixels by utilizing ancillary data has been developed. The inversion capability to compare different scaled retrieval results has been separately developed and shown to be suitable for retrieval of soil moisture values over a monospecies boreal forest in Canada. These tools facilitate the analysis of heterogeneity at landscape level by enabling the investigation of spatial aggregation and joint aggregation and disaggregation techniques. In this work, we build on preliminary findings and will further investigate and present results of a physics-based spatial aggregation strategy for a forested area. We will focus on retrieving soil moisture based on active radar measurements, which although at much finer resolution than a radiometer of the same frequency, is still at a coarse enough resolution to suffer from the effects of landscape heterogeneity. The total measured coarse-scale radar backscattering coefficient of a scene can be expressed as a weighted linear sum of the contributions of the fine-scale subpixels; these weights are functions of landscape parameters. By aggregating the radar backscattering coefficients of the simulated subpixels and disaggregating the measured radar backscattering coefficient of the coarse-scale pixel, we aim to find the total soil moisture of the satellite pixel. We adopt a block kriging strategy for radar backscattering coefficients using available ancillary data, followed by the development of an inversion strategy that takes into account the non-uniform contribution of different regions of the landscape. Thorough validation and error analysis will be shown through simulations as well as with the use of airborne radar data and ground-based observations.

  18. Hydrologic applications of SAR derived soil moisture

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1992-01-01

    The MACHYDRO-90 was a multi-sensor aircraft campaign conducted to study drainage basin hydrology and the role of soil moisture in defining hydrologic characteristics and patterns. The results from the synthetic aperture radar (SAR) are presented. Data were collected over a period in which the soil conditions changed from dry to wet and then through a drying period which was close to ideal. Radar backscatter data are compared to detailed soil moisture samples taken to define soil moisture gradients within a watershed. The analysis also includes 40-MHz bandwidth SAR data, which provide very high spatial resolution. It is shown these data can be interpreted for hydrology and their application to hydrologic modeling is discussed.

  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. Soil Moisture Estimation Using Hyperspectral SWIR Imagery

    NASA Astrophysics Data System (ADS)

    Lewis, D.

    2007-12-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-05-01

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

  4. 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.

  5. Microstrip Ring Resonator for Soil Moisture Measurements

    NASA Technical Reports Server (NTRS)

    Sarabandi, Kamal; Li, Eric S.

    1993-01-01

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

  6. 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...

  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. Modeling soil moisture memory in savanna ecosystems

    NASA Astrophysics Data System (ADS)

    Gou, S.; Miller, G. R.

    2011-12-01

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

  10. 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.

  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, closing soil gas pathways etc.). In the case of H2O exchange rate, values increased with increasing soil water contents (up to 0.15-0.20 cm3/cm3) and then remained approximately constant. Acknowledgement: Authors acknowledge the financial support of the Ministry of Agriculture of the Czech Republic No. QJ1230319

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

    NASA Astrophysics Data System (ADS)

    Zawadzki, Jaros?aw; K?dzior, Mateusz 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  14. Surface Soil Moisture Assimilation with SWAT

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Spectral Analysis of Soil Moisture Time Series From the NOAA-CREST Observation Site in Millbrook, NY

    NASA Astrophysics Data System (ADS)

    Bonhomme, A. C.; Tesfagiorgis, K. B.; Temimi, M.; Krakauer, N.

    2012-12-01

    Soil moisture is the water content located within the soil. It affects our weather and climate, agriculture, and irrigation. The study of soil moisture enables the study of runoff potential and flood control, soil erosion and slope failure, reservoir management, and water quality. The ultimate goal of this project is to examine the relationship of soil moisture to temperature and precipitation, as well as to statistically analyze the collected data. These measurements are provided by L-band (1.4 GHZ) microwave readings and soil moisture and temperature sensors (Stevens Digital Hydra Probe II) mounted at two locations (A and B) and depths of 2.5, 5, and 10 cm; here, we focus on the data provided by the sensors. These measurements include hourly data from the time of deployment of the soil moisture probes in November 2010. The probes are located close to the National Oceanic and Atmospheric Administration (NOAA) US Climate Reference Network (USCRN) Millbrook station, which measures soil moisture at depths down to 1 m as well as surface temperature and precipitation. To achieve this goal we analyze in situ observations from Millbrook, NY. We analyzed the relationship between precipitation and temperature as well as that of the soil moisture and diurnal temperature range. We then analyzed the correlation, lagged auto and cross correlation, and coherence of the different measurement time series. The soil moisture shows a great variation over time. We see a strong correlation coefficient between the different soil moisture data collected at the Millbrook site, and a weak correlation coefficient at the hourly scale of the precipitation data with the soil moisture data from Millbrook.

  16. 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.

  17. New Approaches for Soil Moisture Analysis over Complex Arctic Environments with PALSAR/ALOS

    NASA Astrophysics Data System (ADS)

    Longépé, N.; Necsoiu, M.; Tadono, T.; Shimada, M.

    2010-12-01

    Frozen ground is a sensitive indicator of how our home planet is changing. In this study, the relevance of L-band Synthetic Aperture Radar (SAR) data for extracting information on frozen ground is presented. Specifically, the study focused on the characterization of a permafrost active layer using polarimetric ALOS PALSAR imagery in two locations in Alaska: the Kobuk river valley and the Arctic National Wildlife Refuge. The adequacy between polarimetric EM model and radar data has been studied for a long time, especially over bare agricultural fields (Oh et al., 1992). The assessment of residual liquid water can be realized by means of a bare soil EM backscattering model. Over natural wild land areas such as the Arctic tundra, new approaches have to be proposed in order to tackle the effect of the vegetation and other irrelevant effects (sensor calibration, multiple scattering terms, etc.). As a result, traditional soil moisture retrieval has shown limited accuracy for operational use, even though promising methods have been recently investigated (Mattia et al., 2006; Verhoest et al., 2007). Two methodologies based on multi-temporal acquisitions are proposed in this study. In regards to the uncertainties of the vegetation effect or other irrelevant mechanisms, a first methodology is proposed in this study. An optimization on the Oh’s weights (Oh, 2004) and full-polarimetric PALSAR data is carried out by using priori information provided by the Advanced Microwave Scanning Radiometer (AMSR-E) onboard the Aqua satellite. By tuning PALSAR data and Oh’s weights, the effects of vegetation are counterbalanced. This method was tested over the Arctic National Wildlife Refuge (ANWR). The optimization results are found to be in good agreement with theoretical aspects: vegetation induces an increase of cross-polarized channel (anisotropic effect) and a decrease of co-polarized channels (attenuation mechanism). The soil moisture variation can be then retrieved in a consistent manner. The second methodology does not use any priori information from AMSR-E sensor to reduce the uncertainties. Over the second test site, the Kobuk river valley, nine single-polarized HH PALSAR scenes were used, four being acquired during the thawing period and five during the frozen period. Since the soil moisture content during the frozen events is close to zero, the roughness was estimated through the inversion of Oh’s model, assuming also some effects (e.g., Fresnel refraction) due to the overlying snow cover. In this assessment, the uncertainties about the snow densities and the soil moistures were modeled and integrated into the retrieval approach. The retrieved soil roughness and its associated uncertainty estimates based on the data acquired during the frozen season were further used to derive moisture variation during the thawing period.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  20. Depression of soil moisture freezing point

    SciTech Connect

    Fedorov, V.I.

    1996-12-01

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

  1. 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...

  2. Analysis of soil moisture condition under different land uses in the arid region of Horqin sandy land, northern China

    NASA Astrophysics Data System (ADS)

    Niu, C. Y.; Musa, A.; Liu, Y.

    2015-10-01

    Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff and evapotranspiration, which is important to crop growth and vegetation restoration in semiarid environments, such as Horqin sandy land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil to infiltration under different land use types in semiarid area. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of 2 years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy soils. The higher soil moisture content among different land uses was exhibited by the grassland, followed by cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water at the surface, in the root zone and at the deep soil layer indicated statistical differences for different types of land cover. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in the deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80-120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

  3. 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...

  4. Space-time soil moisture variability for two different land use types: analysis at the plot scale

    NASA Astrophysics Data System (ADS)

    Zuecco, Giulia; Borga, Marco; Penna, Daniele; Canone, Davide; Ferraris, Stefano

    2013-04-01

    Understanding space-time soil moisture variability at various scales is a key issue in hydrological research. At the plot scale soil moisture variability is expected to be explained by physical factors such as soil hydraulic properties, local topography and vegetation cover. This study aims to: i) characterize the spatial and temporal variability of soil moisture at the plot scale at two soil depths and for two different types of land use (meadow and vineyard); ii) investigate the role of vegetation cover on the seasonal variability of soil moisture; iii) assess the capability of a dynamic model to explain soil moisture variability and the control exerted by land use. The work is based on soil moisture data collected on a plot (about 200 m2) in Grugliasco (Po River basin, Northern Italy) by means of Time Domain Reflectometry (TDR) measurements. The plot is divided into two subplots: one covered by grapevine plants, the other covered homogeneously by grass. The soil is sandy, the slope is about 1%, and there is a buffer grass area about 20 m wide around the measurement field. The characteristics of the site allow to isolate the contribution of soil hydraulic properties and land use to space-time soil moisture variability. We used the data of 40 probes distributed in the two subplots, vertically inserted into the soil at 0-30 cm and 0-60 cm depths. Precipitation and temperature are recorded continuously on site. Statistics were computed based on soil moisture measurements collected continuously at daily time step over three years (2006-2008). Results show that soil moisture spatial patterns at the two sampling depths are highly correlated for both land uses. Higher values of mean soil moisture at 0-60 cm depth with respect to 0-30 cm for both types of land use likely reflect the evaporation processes affecting more the surface layer. Spatial mean soil moisture is always higher in the vineyard than in the meadow (especially at 0-30 cm depth), implying the influence of vegetation cover during the growing season. An exponential equation fits well the relationship between the spatial coefficient of variation and the mean soil moisture. An increasing variability of the coefficient of variation is observed during periods with high potential evapotranspiration rates (June-August). This is more evident for the grass site at 0-30 cm depth, highlighting again the important shading effect performed by the grapevine leaves. The application of a simple soil moisture dynamic model reveals a general good capability to capture soil moisture temporal dynamics at the plot scale. Moreover, the model reproduces consistently the observed relationships between soil moisture spatial mean and variability. Thus, the model provides a preliminary link between physical processes and statistical variability patterns. Keywords: soil moisture, plot scale, space-time variability, land use.

  5. Analysis of soil moisture condition under different land uses in arid region of Horqin Sandy Land, northern China

    NASA Astrophysics Data System (ADS)

    Niu, C.; Musa, A.; Liu, Y.

    2015-07-01

    Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff, and evapotranspiration, which is substantive meaning to crop growth and vegetation restoration in semiarid environments, such as the Horqin Sandy Land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil water to precipitation infiltration under different land use types in this semiarid region. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of two years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy land. The order of soil moisture (from high to low) among different land uses was grassland, cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water in surface, root zone and deep soil layer indicated statistical difference for different land covers. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80-120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

  6. Comparison of soil moisture dynamics across different land covers

    NASA Astrophysics Data System (ADS)

    Mittelbach, Heidi; Henschel, Florian; Seneviratne, Sonia I.

    2013-04-01

    The spatial and temporal variability of soil moisture and its dependency on local or regional scale characteristics, such as soil texture, land cover and topography as well as weather and climate anomalies, is a fundamental feature for environmental applications. In a recent study based on a network of grassland stations in Switzerland (Mittelbach and Seneviratne 2012), it was shown that the spatio-temporal variability of absolute soil moisture is clearly distinct from the spatio-temporal variability of temporal soil moisture anomalies, and that regional-scale patterns of soil moisture dynamics could clearly be identified at the scale of Switzerland. However, it has not yet been investigated whether these conclusions apply across land cover types. In the current study, we investigate differences in soil moisture dynamics at paired grassland-forest sites and their dependency either on dynamic or static site properties. The analysis is based on three-year continuous soil moisture measurements at three paired grassland and nearby forest sites of the SwissSMEX (http://www.iac.ethz.ch/url/research/SwissSMEX) soil moisture network. The three paired sites are located in different climatic regions of Switzerland. They are characterized by similar meteorological conditions but within the pairs differences in topography (elevation, slope, aspect) and soil properties are found. At all sites continuous measurements of soil moisture are available in four different depths, from 5 cm to 50 cm. The analyses of daily mean soil moisture at the single depths and integrated over the 50 cm soil column reveal different behaviour with respect to absolute soil moisture levels and temporal soil moisture dynamics between grassland and forest sites during the whole three-year period. Focusing on the recession of soil moisture during precipitation-free periods, a seasonal dependency is observed with strongest recession in summer for both land covers. However, a different behaviour is found in spring and autumn. While stronger recession is found over grassland in spring, the forest sites indicate stronger recession in autumn, with most pronounced differences at deeper depths. This investigation thus suggests that differences in soil moisture dynamics across land cover types depend on the dynamics of the vegetation cover and less on static site properties. Reference: Mittelbach, H., and S.I. Seneviratne, 2012: A new perspective on the spatio-temporal variability of soil moisture: temporal dynamics versus time invariant contributions. Hydrol. Earth Syst. Sci., 16, 2169-2179.

  7. 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...

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Development of an Aquarius Soil Moisture Product

    NASA Astrophysics Data System (ADS)

    Bindlish, R.; Jackson, T. J.; Zhao, T.; Cosh, M. H.

    2013-12-01

    Aquarius observations over land offer a new resource for measuring soil moisture from space. Our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to land applications through the retrieval of soil moisture. This research increases the value and impact of the Aquarius mission by including a broader scientific community, allowing the exploration of new algorithm approaches that exploit the active-passive observations, and will contribute to a better understanding of the Earth's climate and water cycle. The first stage of our Aquarius soil moisture research focused on the use of the radiometer data because of the extensive heritage that this type of observations has in soil moisture applications. The calibration of the Aquarius radiometer over the entire dynamic range is a key element for the successful implementation of the soil moisture algorithm. Results to date indicate that the Aquarius observations are well calibrated for ocean targets but have a warm bias over land. This bias needed to be addressed if the Aquarius observations are to be used in land applications. Our approach was to use the gain and offsets computed using the Soil Moisture Ocean Salinity (SMOS) comparisons to adjust the Aquarius brightness temperatures. The Single Channel Algorithm (SCA) was implemented using the Aquarius observations. SCA is also the baseline algorithm for the SMAP radiometer-only soil moisture product. Aquarius radiometer observations from the three beams (after bias/gain modification) along with the National Centers for Environmental Prediction (NCEP) surface temperature model forecast were then used to estimate soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters derived based on land cover. The spatial patterns of the soil moisture estimates are consistent with the climatology and with the other satellite missions (Advanced Microwave Scanning Radiometer-E and SMOS). The soil moisture and temperature products were validated using in situ observations from the Little Washita and Little River watershed soil moisture networks. Results show good performance by the algorithm for these land surface conditions for the period of August 2011-June-2013 (RMSE=0.031 m3/m3, Bias=0.007 m3/m3, and R=0.855). The validated radiometer soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The soil moisture product was implemented as part of the routine Aquarius data processing and will be available from National Snow and Ice Data Center both in swath and gridded formats in the near future. Acknowledgement: USDA is an equal opportunity employer.

  14. 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...

  15. 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.

  16. 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 globe, this study may have important applications in aiding water resources management in different regions.

  17. 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.

  18. 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.

  19. 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 with comparison between Metop ASCAT and altimeter sigma0 over Saharan Africa. Geographical correlated areas of agreement and disagreement corresponding to underlying terrain are identified. SMALT products provide a first order estimation of soil moisture in areas of very dry terrain, where other datasets are limited. Potential to improve and expand the technique has been found, although further work is required to produce products with the same accuracy confidence as more established techniques. The data are made freely available to the scientific community through the website http://tethys.eaprs.cse.dmu.ac.uk/SMALT

  20. 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 NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

  1. 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

  2. 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.

  3. Sensitivity of Soil Respiration to Variability in Soil Moisture and Temperature in a Humid Tropical Forest

    PubMed Central

    Wood, Tana E.; Detto, Matteo; Silver, Whendee L.

    2013-01-01

    Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflux from a humid tropical forest in Puerto Rico. We measured hourly soil CO2 efflux, temperature and moisture in control and exclusion plots (n?=?6) for 6-months. The variance of each time series was analyzed using orthonormal wavelet transformation and Haar-wavelet coherence. We found strong negative coherence between soil moisture and soil respiration in control plots corresponding to a two-day periodicity. Across all plots, there was a significant parabolic relationship between soil moisture and soil CO2 efflux with peak soil respiration occurring at volumetric soil moisture of approximately 0.375 m3/m3. We additionally found a weak positive coherence between CO2 and temperature at longer time-scales and a significant positive relationship between soil temperature and CO2 efflux when the analysis was limited to the control plots. The coherence between CO2 and both temperature and soil moisture were reduced in exclusion plots. The reduced CO2 response to temperature in exclusion plots suggests that the positive effect of temperature on CO2 is constrained by soil moisture availability. PMID:24312508

  4. 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...

  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. Soil moisture measurements from airborne SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jiancheng; Soares, Joao V.; Hess, Laura; Engman, Edwin T.; Vanzyl, Jakob J.

    1991-01-01

    The preliminary results of algorithm development and testing for soil moisture retrieval at high incidence angles are reported. Based on first-order surface backscattering models, a physically based algorithm for retrieval of soil moisture was developed and evaluated using NASA/JPL aircraft synthetic aperture radar (SAR) data. It shows that the copolarization ratio is sensitive to soil moisture change but not to surface roughness at high incidence angles. This algorithm performed well at L-band and should be useful. This study suggests that incidence angles greater than 40 degrees are optimal for such monitoring.

  8. 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).

  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. Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

    NASA Astrophysics Data System (ADS)

    Li, Fuqin; Crow, Wade T.; Kustas, William P.

    2010-02-01

    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, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2-5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE 3) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m 3 m -3). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m 3 m -3) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R2 correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE 3 study site.

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

    NASA Astrophysics Data System (ADS)

    Lakshmi, Venkat; Fang, Bin

    2014-05-01

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

  12. 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 ...

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  14. 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.

  15. Soil Moisture Patterns in a Small Forested Catchment: Hydropedological Investigations

    NASA Astrophysics Data System (ADS)

    Lin, H.

    2004-05-01

    Much effort by non-pedologists is hampered because soil distribution and processes are not well understood that site selection for sampling or monitoring and the design of modeling do not represent actual distribution and processes. To connect pedon and landscape phenomena, one of the keys lies in the distribution of various soils over the landscape (i.e., soil patterns). The fabric of soil over the landscape helps optimal sampling design as well as appropriate modeling of landscape hydrology. This strategy, reflected in hydropedological approaches, is important in understanding spatio-temporal dynamics of soil moisture over the landscape. We investigated surface and subsurface soil moisture patterns in a small forested catchment in central Pennsylvania through mapping and monitoring, and then explored the underlying mechanisms for such patterns. Soil distribution and topographic metrics were emphasized in correlating with the observed soil moisture patterns. The preliminary analysis indicated that the surface soil moisture acted as a signature of the hydrologic dynamics of this catchment, while the subsurface soil moisture was more spatio-temporally stable over the monitoring period.

  16. 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.

  17. Snow cover and soil moisture in mountains

    NASA Astrophysics Data System (ADS)

    Wever, N.; Lehning, M.

    2012-04-01

    Soil moisture is an important parameter of the climate system. It constrains evapotranspiration of plants and it functions as a storage of water, giving it an economic value, e.g. for agriculture. Furthermore, soil moisture is an important factor for predicting flood risk. In mountainous areas with a seasonal snow cover, the spatial distribution of snow depth is strongly influencing the spatial variation of soil moisture. To assess potential flooding situations during snow melt and rain on snow events in particular but for any heavy precipitation event in the mountains, it is important to understand the influence of the snow cover on soil status with respect to liquid and solid water. Only if this is known, the reaction of the soil i.e. amount of runoff, storage or melt, on additional water input can be assessed. For an operational assessment of the soil moisture state in the Swiss Alps at 140 measurement sites for snow and avalanche forecasting (IMIS network), the SNOWPACK model has been extended with a soil module, solving the Richards equation for the matrix flow. The modelling is validated with vertical profile measurements of soil moisture at meteorological stations in an Alpine catchment near Davos, Switzerland. It was found that the combination of a physical based snowpack model with a Richards equation solver seems to provide an adequate description of soil moisture fluctuations, especially in near surface layers. Soil moisture fluctuations, both measured and modelled, are strongly reduced when a snow cover is present. The measurements also revealed a strong increase in soil moisture, accompanied by a daily cycle in soil moisture during snow melt, extending down to 120cm depth. When soil properties from literature were assumed for the soil type in the vertical profile, the daily cycle in the model during snow melt was restricted mainly to the top layers, while observations show also a reaction in deeper layers. These observations are consistent with the assumption of the existence of preferential flow paths, which are not modelled by the Richards equation. This discrepancy between observations and model results during the melt phase may cause an underestimation of the soil storage capacity and an overestimation of the surface run-off in the model.

  18. Evaluation of the Second Global Soil Wetness Project soil moisture simulations: 1. Intermodel comparison

    NASA Astrophysics Data System (ADS)

    Guo, Zhichang; Dirmeyer, Paul A.

    2006-11-01

    Driven with the meteorological data sets based on the reanalyses and gridded observational data archived by the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II, eleven different land surface models generated global soil moisture data sets for the 10-year period (1986-1995) for the Second Global Soil Wetness Project (GSWP-2). We evaluate these model simulations against in situ observations over grasslands and agricultural regions in the former Soviet Union, United States (Illinois), China, and Mongolia from the Global Soil Moisture Data Bank in terms of their ability to estimate the actual column plant-available soil moisture in the top 1-m soil layer, to simulate the phasing of the annual cycle, and to represent observed interannual variability. Results from these 11 land surface models show that they reproduce reasonably well the observed interannual variability and phasing of the annual cycle. Statistical analysis also shows that the median root mean square of errors among these models ranges from 4 to 8 cm of soil moisture. Similar to what has been found in soil moisture simulations for GSWP-1, the absolute values of soil moisture are poorly simulated by most models. However, the models do a good job of reproducing the soil moisture anomalies. This suggests that the global soil wetness data set produced by GSWP-2 can be used for analyzing climate variability and initializing GCMs by using transform strategies. This also has relevance to subseasonal to seasonal forecasts since soil moisture anomalies may potentially have impact on precipitation.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Many decisions in agriculture are conditional to soil moisture. For instance in wet conditions, farming operations as soil tillage, organic waste spreading or harvesting may lead to degraded results and/or induce soil compaction. The development of a tool that allows the estimation of soil moisture is useful to help farmers to organize their field work in a context where farm size tends to increase as well as the need to optimize the use of expensive equipments. Soil water transfer models simulate soil moisture vertical profile evolution. These models are highly sensitive to site dependant parameters. A method to implement the mechanistic soil water and heat flow model (the TEC model) in a context of limited information (soil texture, climatic data, soil organic carbon) is proposed [Chanzy et al., 2008]. In this method the most sensitive model inputs were considered i.e. soil hydraulic properties, soil moisture profile initialization and the lower boundary conditions. The accuracy was estimated by implementing the method on several experimental cases covering a range of soils. Simulated soil moisture results were compared to soil moisture measurements. The obtained accuracy in surface soil moisture (0-30 cm) was 0.04 m3/m3. When a few soil moisture measurements are available (collected for instance by the farmer using a portable moisture sensor), significant improvement in soil moisture accuracy is obtained by assimilating the results into the model. Two assimilation strategies were compared and led to comparable results: a sequential approach, where the measurement were used to correct the simulated moisture profile when measurements are available and a variational approach which take moisture measurements to invert the TEC model and so retrieve soil hydraulic properties of the surface layer. The assimilation scheme remains however heavy in terms of computing time and so, for operational purposed fast code should be taken to simulate the soil moisture as with the Ross model [Ross, 2003, Crevoisier et al, 2009]. To meet the decision support context, we evaluated the model ability of evaluating the soil moisture level in comparison to a moisture threshold that splits soil conditions into desirable and undesirable cases. This threshold depends on soil properties, the farming operation and equipment characteristics. We evaluate the rate of making good decisions using either the TEC model with and without soil moisture measurements or an empirical algorithm that simulate the decision processes followed by farmers, currently. This later is a reference case that allows appreciating the adding value of using soil water transfer models. We found a significant improvement with a rate of success, which increases from 65% with the reference case to 90% when using the model with soil moisture assimilation. Chanzy, A., Mumen M., Richard, G.. (2008), Accuracy of top soil moisture simulation using a mechanistic model with limited soil characterization, Water Resources Research, 44(3), W03432. Crevoisier, D., Chanzy, A., Voltz M. (2009), Evaluation of the Ross Fast Solution of Richards' Equation in Unfavourable Conditions for Standard Finite Element Methods, Advances in Water Ressources, In revision. Ross, P. J. (2003). Modeling soil water and solute transport - Fast, simplified numerical solutions. Agronomy Journal 95:1352-1361.

  1. 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.

  2. Soil Moisture Experiments 2004 (SMEX04)

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.; Lettenmaier, D. P.

    2004-05-01

    Soil Moisture Experiments 2004 (SMEX04) will be conducted during the summer of 2004 to address overlapping science issues of the North American Monsoon Experiment (NAME) and soil moisture remote sensing programs. Surface boundary conditions play an important role in initiation and maintenance of the system that controls summer precipitation over much of the NAME region. 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 in the southwestern U.S. and northern Mexico. Surface soil moisture can change dramatically after rain events. This increased soil moisture after precipitation can increase evapotranspiration between storm events, which may contribute to enhanced convection and further precipitation. Soil moisture can vary both spatially, due to topography, soil, vegetation and precipitation variability, and temporally, due to differences in soil physical characteristics that control drainage and accumulated evapotranspiration. SMEX04 will focus on providing these critical soil moisture products using the new generation of satellite sensors supported by insitu observations and high-resolution aircraft mapping. Intensive study regions will be established over 50 by 75 km domains in southeastern Arizona and northwestern Mexico. Insitu observations will be collected over an extended time frame. Aircraft mapping and intensive regional ground sampling will be performed between mid-July and mid-August. The field campaign will at the same time contribute to the validation of these satellite products, expand our knowledge of the effects of key land surface features, establish algorithms for future satellite sensors, and explore the potential of new technologies.

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

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1976-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Ford, T.; Harris, L.; Quiring, S. M.

    2013-12-01

    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. 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 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 to 10 cm) and root zone (25 to 60 cm) soil moisture. An exponential decay filter is applied to estimate root zone soil moisture from near-surface observations. Reasonably skillful predictions of root zone soil moisture can be made using near-surface observations. The same method is then applied to evaluate whether soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to accurately estimate root zone soil moisture. We conclude that the exponential filter method is a useful approach for accurately predicting root zone soil moisture from SMOS surface retrievals.

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

    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. 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 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 to 10 cm) and root zone (25 to 60 cm) soil moisture. An exponential decay filter is applied to estimate root zone soil moisture from near-surface observations. Reasonably skillful predictions of root zone soil moisture can be made using near-surface observations. The same method is then applied to evaluate whether soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to accurately estimate root zone soil moisture. We conclude that the exponential filter method is a useful approach for accurately predicting root zone soil moisture from SMOS surface retrievals.

  6. 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.

  7. 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 signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to retrieve soil moisture over fairly large and thus inhomogeneous areas. The retrieval is carried out at nodes of a fixed Earth surface grid. To achieve this purpose, after checking input data quality and ingesting auxiliary data, the retrieval process per se can be initiated. This cannot be done blindly as the direct model will be dependent upon surface characteristics. It is thus necessary to first assess what is the dominant land use of a node. For this, an average weighing function (MEAN_WEF) which takes into account the "antenna" pattern is run over the high resolution land use map to assess the dominant cover type. This is used to drive the decision tree which, step by step, selects the type of model to be used as per surface conditions. All this being said and done the retrieval procedure starts if all the conditions are satisfied, ideally to retrieve 3 parameters over the dominant class (the so-called rich retrieval). If the algorithm does not converge satisfactorily, a new trial is made with less floating parameters ("poorer retrieval") until either results are satisfactory or the algorithm is considered to fail. The retrieval algorithm also delivers whenever possible a dielectric constant parameter (using the-so called cardioid approach). Finally, once the retrieval converged, it is possible to compute the brightness temperature at a given fixed angle (42.5°) using the selected forward models applied to the set of parameters obtained at the end of the retrieval process. So the output product of the level 2 soil moisture algorithm should be node position, soil moisture, dielectric constants, computed brightness temperature at 42.5°, flags and quality indices. The work around the ATBD also encompasses the making of breadboards and prototype, analysis of specific cases (snow, frozen soil, topography, floods, etc…), the making of data sets and validation verification exercises. During the presentation we will describe in more details the algorithm and accompanying work in particular decision tree principle and characteristics, the auxiliary data used and the special and "exotic" cases. We will also be more explicit on the algorithm validation and verification approaches together with the making of test data sets from existing and synthetic data. A glimpse of level 3 and 4 products will also be given.

  8. 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.

  9. 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...

  10. 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%.

  11. 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

  12. Soil moisture content estimation from passive temperature measurements

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  13. 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...

  14. 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...

  15. 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.

  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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

    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.

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

    PubMed

    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

  19. 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

  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. 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.

  2. 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.

  3. 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.

  4. Soil Moisture Estimation Using Inexpensive Radios

    NASA Astrophysics Data System (ADS)

    Niemeier, J. J.; Kruger, A.

    2011-12-01

    Technological advances and changes in licensing have made small, inexpensive radio modules commonplace. Today, these radios are used in a large number of wireless data- and control applications. A novel approach is to view such radio modules not only as communication devices, but also as small, inexpensive sources of radio frequency (RF) energy, which are useful for devising unconventional sensors. We have explored the possibility of using buried radios and the resulting RF links as distributed soil moisture sensors. We conducted a number of experiments that record the RF attenuation of the links over time. Estimating RF attenuation is straightforward, since the radio modules provide a received signal strength indication (RSSI). To provide reference data, we installed several time-domain reflectometry (TDR) soil moisture probes with accompanying temperature probes to monitor changes in soil moisture and soil temperature. We collocated tipping bucket rain gauges for monitoring rain events. We employed RF modules that operate at 900 MHz. Rather than burying the radios, we lowered the antennas into 2.5 cm PVC pipes that we drove into the ground to a depth of 60 cm. We seal both ends of the PVC pipe to prevent water from entering the tube. Our experimental data shows a clear relationship between soil moisture and RF attenuation. We developed a simple, yet effective, mathematical model to relate changes in RF attenuation to changes in soil moisture. One can easily achieve reliable links 2-3 m long, and we believe the technique holds promise as an economical method for distributed/integrated soil moisture estimation.

  5. 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 latter in the deepest layer. From this we conclude that the seasonal soil moisture variations dominate the memory close to the surface but these are dampened in lower layers where the memory is mainly affected by longer term variations.

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

    USGS Publications Warehouse

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

    2011-01-01

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

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 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.

  13. Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    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 ?-? is used in this study for the soil moisture retrieval. In ?-?, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (?). 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 ? 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  15. The role of biological soil crusts on soil moisture

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  16. Microwave radiometer measurements of soil moisture content

    NASA Technical Reports Server (NTRS)

    Newton, R. W.; Rouse, J. W., Jr.

    1980-01-01

    A unique set of radiometer measurements is presented, recorded during a 1000-h day and night monitoring of irrigated fields from fully saturated to completely dry. Radiometer measurements were recorded at 2.8-cm (X-band) and 21.4-cm (L-band) wavelengths for a range of incident angles from nadir to 50 deg. Soil moisture and soil temperature profile measurements were recorded to a depth of 15 cm. The test site was located in east-central Texas on a clay soil (Miller clay). Three bare-surface plots were used, each having a distinctly different surface roughness. Vegetated plots were also measured. The data quantify the sensitivity of microwave radiometer measurements to soil moisture variations, the effect of surface roughness on the measurement, and the influence of surface vegetation.

  17. Remote detection of soil surface moisture

    NASA Technical Reports Server (NTRS)

    Stockhoff, E. H.; Frost, R. T.

    1974-01-01

    Polarimetric data concerning soil surface moisture were obtained during a series of flights over the Imperial Valley, California, and Phoenix, Arizona, during March 1972. A polarimeter was installed in NASA's Convair-990 aircraft, Galileo, above a window in the floor of the aft cargo compartment in such a manner that it could view from 42 deg ahead of, to 42 deg to the rear of the nadir. It had a 3 deg field of view and a 10 nm bandwidth centered at 641 nm. The moisture content of the solid surface for fields viewed by the polarimeter was measured by determining the angle through which the light had been scattered by the soil and by observing the degree of polarization of this light produced during its interaction with the soil. The polarimeter measures this degree of polarization in terms of Stokes parameters. Ground-truth samples of soil were obtained at several depths along the flight path.

  18. 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.

  19. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  20. SOIL MOISTURE EXPERIMENTS IN 2002 AND 2003

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. 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. 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 ...

  3. 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

  4. SOIL MOISTURE EXPERIMENTS 2003 (SMEX03)

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. 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.

  6. SMOS CATDS level 3 Soil Moisture products

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  7. 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.

  8. Minimizing the Impact of Measurement Uncertainty in Predicting Profile Soil Moisture from Noisy Surface Measurements

    NASA Astrophysics Data System (ADS)

    Kornelsen, K. C.; Paulin, C. D.

    2012-12-01

    Soil moisture is an important hydrological state variable which influences the partition between infiltration and runoff, provides thermal inertia in the climate system and strongly influences the distribution of vegetation. Unfortunately, accounting for the high space-time variability of soil moisture resulting from the inherent heterogeneity of soil, topography and land cover is still a weakness in many hydrological models. This limitation can be partially overcome with recent technological advances, such as the Soil Moisture and Ocean Salinity (SMOS) mission and the Advanced Microwave Scanning Radiometer- EOS (AMSR-E) soil moisture products. SMOS and AMSR-E have allowed for operational observations of coarse scale distributed soil moisture in the top 5cm of soil with a realized accuracy between 0.03 and 0.10 cm3cm-3. Despite these advances, a gap in the data still exists with respect to soil moisture in the root zone, which is more strongly related to many hydrological processes than surface soil moisture. The shallow penetration and uncertain nature of satellite soil moisture measurements gives rise to a requirement for methods to extrapolate profile soil moisture from uncertain surface soil moisture measurements. The extension of surface soil moisture into the root zone is typically accomplished through the assimilation of surface soil moisture into a hydrological model, where the covariance matrix and model physics update the soil profile. Artificial neural networks provide an efficient alternative to classical model data assimilation and can provide robust estimates of root zone soil moisture based on high-order non-linear data interactions. The presented research will contrast rootzone soil moisture predicted from feed forward neural networks, a numerical Richards equation model (HYDRUS-1D) and the prior models with assimilated noisy surface measurements using the Ensemble Kalman Filter (EnKF). A sensitivity analysis reveals that artificial neural networks are less impacted by uncertain surface measurements than model predictions and data assimilation minimizes the impact of all soil moisture extension methods at all levels of uncertainty. Artificial neural networks also have a run time advantage over a comparable model method by predicting soil moisture in a time span which is an order of magnitude faster than the model. Due to the importance of root zone soil moisture in bio-hydro-meteorological cycles, it is expected that accurate estimates of profile soil moisture will enhance energy flux and runoff partitioning in future hydrological applications.

  9. 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.

  10. 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...

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    Soil moisture is a key element in the global cycles of water, energy, and carbon. Knowledge on the spatial and temporal distribution of the soil moisture content (SMC) is therefore essential for a number of hydrological applications as well as earth sciences like meteorology or climatology (Heathman et al., 2003). In the last few years there has been an increasing interest towards the estimation of SMC at local scales using active microwave sensors (Barret et al., 2009). Compared to passive microwave sensors, SAR offers the potential to provide data at high spatial resolution (modern sensors can acquire images with up to approximately 1 m), which is particularly important in mountainous areas. So far, these areas have been considered only marginally in research and only pioneer studies can be found in the literature (Brocca et al., 2012; Bertoldi et al. 2013). In this work we analyzed the temporal and spatial dynamics of the surface SMC (0 - 5 cm depth) on the basis of ground data collected by fixed meteorological stations located in the emerging Long-Term Ecological Research (LTER) site Mazia Valley (Province of Bolzano, South Tyrol, Italy), SAR data from ENVISATs ASAR sensor, wide swath (WS) mode (acquired between 2005 and 2012), and SMC estimates from the hydrological model GEOtop (Endrizzi et al., 2013). The SMC retrieval process was based on the support vector regression (SVR) method introduced by Pasolli et al. (2011). The training of the algorithm was based on data acquired in 2010. Furthermore, the SAR backscatter and derived SMC have been compared with time-series derived from the distributed hydrological model GEOtop. The differences in terms of temporal and spatial dynamic have been analyzed. The main goal of this work is to evaluate the spatial and temporal patterns of SAR derived SMC at field scale and to correlate them with ground information. This is a preparatory study to establish a methodology for the retrieval of SMC with high spatial and temporal sampling and to improve retrieval accuracies by integrating temporal information from different sources of ancillary data and from SAR time-series. It was found that the dynamics of both, temporal and spatial SMC patterns obtained from various data sources (ASAR, GEOtop and meteorological stations), show a similar general temporal behaviour that indicates the robustness of the retrieval algorithm with ASAR WS. However, depending on land cover, soil type and local topographic conditions different spatial patters can be found between SMC estimations coming from ASAR and from the GEOtop model. Introducing information on the temporal behaviour of the SAR signal proves to be a promising method for increasing the confidence and accuracy in estimating SMC, complementing hydrological model predictions. Following steps were identified as critical for the retrieval process: the topographic correction and geocoding of SAR data and the calibration of the meteorological stations. Both factors can have significant influence on the quality of SMC estimation. The accuracy of meteorological input and soil parameterization were identified as the most crucial challenges for SMC derived from hydrological modeling. References Barrett, B. W., E. Dwyer, and P. Whelan. "Soil moisture retrieval from active spaceborne microwave observations: An evaluation of current techniques." Remote Sensing 1, no. 3 (2009): 210-242. Bertoldi, G., S. Della Chiesa, C. Notarnicola, L. Pasolli, G. Niedrist, and U. Tappeiner. "Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT 2 images and hydrological modeling." Journal of Hydrology (2014). under revision. Brocca, L., A. Tarpanelli, T. Moramarco, F. Melone, S. M. Ratto, M. Cauduro, S. Ferraris et al. "Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations." Vadose Zone Journal (2013). Endrizzi, S., S. Gruber, M. Dall'Amico, and R. Rigon. "GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects." Geoscientific Model Development Discussions 6, no. 4 (2013): 6279-6341. Heathman, G. C., P. J. Starks, L. R. Ahuja, and T. J. Jackson. "Assimilation of surface soil moisture to estimate profile soil water content." Journal of Hydrology 279, no. 1 (2003): 1-17. Pasolli, L., C. Notarnicola, L. Bruzzone, G. Bertoldi, S. Della Chiesa, V. Hell, G. Niedrist. "Estimation of Soil Moisture in an Alpine catchment with RADARSAT2 Images." Applied and Environmental Soil Science 2011 (2011)

  13. 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...

  14. 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...

  15. Soil moisture ground truth, Lafayette, Indiana, site; St. Charles Missouri, site; Centralia, Missouri, site

    NASA Technical Reports Server (NTRS)

    Jones, E. B.

    1975-01-01

    The soil moisture ground-truth measurements and ground-cover descriptions taken at three soil moisture survey sites located near Lafayette, Indiana; St. Charles, Missouri; and Centralia, Missouri are given. The data were taken on November 10, 1975, in connection with airborne remote sensing missions being flown by the Environmental Research Institute of Michigan under the auspices of the National Aeronautics and Space Administration. Emphasis was placed on the soil moisture in bare fields. Soil moisture was sampled in the top 0 to 1 in. and 0 to 6 in. by means of a soil sampling push tube. These samples were then placed in plastic bags and awaited gravimetric analysis.

  16. 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.

  17. 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 and used to derive the one-way canopy transmissivity. Using a simple radiative transfer model, this information was combined with horizontally polarized 6.6 GHz SMMR observations to derive a 9-year time series of soil moisture for all of Spain at a one quarter degree spatial scale. Both day and night SMMR observations were used independently, in order to check the consistency of the results. A first order Fourier Transform was performed on the mean monthly soil moisture values to identify major characteristics of time series such as trend, amplitude, and phase shift.

  18. 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 vegetation opacity and single scattering albedo. One goal of our current research is to determine whether the tau-omega model can work for tree canopies given the increased scatter from trees compared to grasses and crops, and. if so, what are effective values for tau and omega for trees.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  1. 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.

  2. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  4. Urban soil moisture affecting local air temperature

    NASA Astrophysics Data System (ADS)

    Wiesner, Sarah; Ament, Felix; Eschenbach, Annette

    2015-04-01

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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  8. 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.

  9. Methods of measuring soil moisture in the field

    USGS Publications Warehouse

    Johnson, A.I.

    1962-01-01

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

  10. 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.

  11. 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 nocturnal evaporation was negligible during dry time periods, it was quite significant (up to 30% of the daily cumulative flux) during nights following rain events. Overall this study allows us to better understand the mechanisms underlying soil moisture dynamics in desert playas as well as evaporation following occasional rain events.

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

    NASA Astrophysics Data System (ADS)

    Jia, Yu-Hua; Shao, Ming-An

    2014-11-01

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

  13. 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.

  14. 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.

  15. Absolute and relative soil moisture spatial-temporal variability over large areas in Europe

    NASA Astrophysics Data System (ADS)

    Zucco, Graziano; Brocca, Luca; Moramarco, Tommaso; Seneviratne, Sonia; Mittelbach, Heidi

    2013-04-01

    Knowledge about soil moisture spatial-temporal variability over large areas is fundamental for improving our understanding of land-atmosphere interaction and hydrological processes. The analysis of soil moisture spatial-temporal variability can be carried out considering the absolute (original) soil moisture values, usually expressed in volumetric terms (m³/m³), or relative values, such as the percent of saturation (dimensionless) or temporal anomalies with respect to a long-term mean value (in the same units as the absolute soil moisture values). Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum (absolute) values, even though in relative terms their temporal patterns are very similar. Therefore, a large fraction of the spatial variability of soil moisture might be time invariant, i.e., only due to the differences in the range of variability between sites (Mittelbach and Seneviratne, 2012). In these cases, the analysis considering absolute and relative soil moisture values can provide very different results thus highlighting the requirement of a new perspective in the analysis of soil moisture variability. In fact, if soil moisture observations are used within modelling approaches (for hydrological, meteorological or climatic studies), the variability of relative soil moisture values is much of interest (Seneviratne et al., 2010; Brocca et al., 2012). By considering absolute soil moisture values only, misleading conclusions might be drawn with respect to climate-relevant spatiotemporal features of soil moisture. In this study, in situ observations from different soil moisture networks in Italy, Spain, France and Germany are collected and analyzed to investigate the soil moisture variability over large areas (500-5000 km²). Specifically, the statistical and temporal stability classical analyses of soil moisture have been carried out for both absolute and relative values. The comparison of the results with the different approaches highlights the relative contribution of time invariant and time varying components on soil moisture variability. Moreover, the effect of the variability of the soil texture, land use and climatic conditions of the analyzed soil moisture networks is discussed. Overall, in accordance with a previous study (Mittelbach and Seneviratne, 2012), we obtained that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to relative soil moisture values. Therefore, similar analysis should be carried out for past and present soil moisture data sets for better addressing their use within modelling studies. References Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S., 2012: Assimilation of surface and root-zone ASCAT soil moisture products into rainfall-runoff modelling. IEEE Transactions on Geoscience and Remote Sensing, 50(7), 2542-2555. Mittelbach, H., and S.I. Seneviratne, 2012: A new perspective on the spatio-temporal variability of soil moisture: temporal dynamics versus time invariant contributions. Hydrol. Earth Syst. Sci., 16, 2169-2179. Seneviratne, S I, Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., and Orlowsky, B., 2010: Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3-4), 125-161.

  16. 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.

  17. 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 moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

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

    NASA Astrophysics Data System (ADS)

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

    2008-08-01

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

  19. 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 also be used in designing effective soil moisture field campaigns.

  20. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories or vegetation cover types are statistically meaningful. The proposed model is applied to the radar images from the Passive Active L-band System (PALS) collected during (SMAPVEX12). SMAPVEX12 lasted for 47 days, during which soil moisture varied significantly. The proposed model was applied to all of the collected images (17 images) during this time span. Optimized sampling site characteristics will be analyzed with surface characteristics and the trade off between the number of samples and estimated sampling error examined.

  2. Ultrasonic Velocity Variations with Soil Composition for Moisture Measurement

    NASA Technical Reports Server (NTRS)

    Metzl, R.; Choi, J.; Aggarwal, M. D.; Manu, A.

    1998-01-01

    Soil moisture content may be measured by many methods, but the presently available techniques all have drawbacks when used in ground truth measurements for remote sensing. Ultrasonic velocity varies with soil moisture content, and may be used as the basis of a new measurement technique. In order to characterize a sensor capable of field use, soil particle size distribution data are compared to ultrasonic velocity in a variety of soils over a wide moisture range.

  3. 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.

  4. 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...

  5. Research on Regional Spatial Variability of Soil Moisture Based on GIS

    NASA Astrophysics Data System (ADS)

    Fan, Yongcun; Zhang, Changli; Fang, Junlong; Tian, Lei

    As one of soil dynamics properties, soil moisture content is an important factor of soil fertility which counts for much to crop growth situation and scientific irrigation management. A design plan of regional spatial variation of soil moisture measurement was introduced. Its main job includes the use of differential GPS technology for each sampling points in farmland, collecting data of high-precision geo-spatial information and soil moisture in farmland resorting on measure instruments of soil moisture, communicating the data between measuring instrument and portable data analysis devices or computer with cable or wireless network based on ZigBee technology, analyzing data of experimental farmland of the topography and terrain, processing and interpolating data of soil moisture content.

  6. Detecting soil moisture impacts on convective initiation in Europe

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher

    2015-04-01

    Climate models suggest that soil moisture feedbacks on precipitation can play an important role in shaping the climate of some regions of the world. However, observational studies to evaluate models have produced a diverse range of conclusions, depending on scale, methodology, region etc. Our recent global study (Taylor et al, Nature 2012) showed that afternoon rain is more likely to develop over dry soils than nearby (50-100km) wetter areas. This is in contrast to typical global and regional models which favour a positive feedback. One key part of the feedback is the sensitivity of convective initiation to surface fluxes. Whilst some studies consider this in a purely one-dimensional sense, others have argued that spatial variability in fluxes plays an important role in convective triggering, via mesoscale circulations. In semi-arid Africa at least, there is an emerging observational and modelling consensus that it is the spatial heterogeneity of soil moisture which is the key to its influence on deep convective initiation. This study presents the first comprehensive observational analysis over Europe linking convective initiation to soil moisture, based on satellite observations. It builds on our previous global analysis, which indicated over Europe a weak but significant favouring of afternoon rain over locally drier soil at the 50 km scale. Higher space and time resolution satellite datasets are employed in the current study, which can shed light on the dominant mechanisms responsible. Afternoon convective initiations are defined by rapidly cooling cloud-tops using Meteosat images available every 15 minutes. To minimise the impact of fixed triggers such as mountains and coastlines, the analysis is restricted to flat inland regions, which means that most of the 2962 cases are located in central and eastern Europe. Land surface conditions preceding the initiation are characterised by MODIS land surface temperature and ASCAT soil moisture data, whilst wind conditions are taken from ERA-Interim reanalysis. The results show that convective initiations are favoured on the downwind side of dry surfaces, close to wetter areas. The signal is clearest following dry periods and under light winds, consistent with forcing by a mesoscale circulation. Overall, the detected signal in Europe is weaker than in previous African analysis, but key spatial characteristics are essentially the same. This implies that the previous observation of afternoon rain favoured over drier soil in Europe is associated with heterogeneous soil moisture, rather than dry soil per se.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Fang, B.; Lakshmi, V.

    2012-12-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  14. Remote sensing of vegetation and soil moisture

    NASA Technical Reports Server (NTRS)

    Kong, J. A.; Shin, R. T. (principal investigators)

    1983-01-01

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

  15. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  16. 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 ...

  17. 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...

  18. Soil Moisture Data Assimilation for High Resolution SAR Data

    NASA Astrophysics Data System (ADS)

    Lakhankar, T.; Jones, A. S.; Vonder Haar, T. H.

    2008-05-01

    This work focuses on development of a variational data assimilation method for soil moisture estimation. The active microwave observational operator is complex, and before it is applied to the variational retrieval of soil moisture in conjunction with a soil and land model, we first focus on the adjoint development and on the related analysis of control parameters under a variety of conditions. This type of analysis relates directly to the sensitivity of microwave radiance observations to properties of the medium that is being observed. The adjoint sensitivity analysis is inherently independent of the data assimilation problem and the associated specification of the background covariance. The adjoint sensitivities have an ability to attribute cause and effect in a multivariate analysis. The active microwave observational operator is an extension of the Integral Equation Model (IEM) to make it more suitable to land surface model data assimilation use. The adjoint model is developed, and the information content of active microwave measurements sensitive to the land surface and soil parameters is analyzed. Various observational operator results and sensitivity analyses will be presented, demonstrating significant effectiveness of the operator for soil moisture data assimilation studies. This study focuses on the use of active satellite microwave observations (ASCAT, RADARSAT-1, 2 and ERS-1, 2). In constructing the adjoint of the forward model, all input variables and parameters were treated as candidate control variables. The base states were selected to be representative of nominal conditions. In addition, two linear perturbation model variants are also defined for better physical insight: a polarization (VV, HH, VH) difference perturbation operator and a frequency (1.8 GHz and 5.3 GHz) difference perturbation operator. The perturbation analysis of all input variables allows a relative variable response ranking to be performed. A comprehensive linear perturbation analysis is used to select five control variables (surface roughness, surface height, soil moisture, soil temperature, soil composition). The relative component strength analysis is used to deducing dominant control variable. The analysis indicates that the sensitivity ranking of the control variables is sensitive to the linear operator measure (e.g., frequency differences, and polarization difference).

  19. Temporal dynamics and spatial heterogeneity of soil moisture in a northern temperate deciduous forest

    NASA Astrophysics Data System (ADS)

    He, L.; Ivanov, V. Y.; Vogel, C. S.; Bohrer, G.; Moghaddam, M.

    2010-12-01

    Soil moisture in forest environments is variable both in time and space, strongly influencing water and energy fluxes between the land surface and the atmosphere. However, few continuous, deep profile soil moisture datasets exist for temperate forest environments. Our study has initiated measurements of soil moisture in a heterogeneous deciduous forest environment of Northern Michigan in April 2009. Our research site is at the Forest Accelerated Succession ExperimenT (FASET) at the University of Michigan Biological Station (UMBS) where canopy structure was manipulated to represent a large disturbance and a successional phase shift by girdling all mid-successional canopy-dominant aspen and birch trees over 33 Ha. The nearby UMBS-AmeriFlux tower site serves as the un-manipulated control. In total, forty four sensors were deployed at four different locations. They provide half-hourly data on soil water content and temperature over the 3m-deep profiles at multiple depths ( 5, 15, 30, 60, 100, 200 and 300cm). In this study, we examine the temporal dynamics of deep-profile soil moisture and correlation between near-surface and deeper layer soil moisture. Through the analysis of data over the observational period we demonstrate that soil moisture was influenced by differences in canopy structure. Specifically, deep soil moisture (integrated over the root zone or deeper than 300 cm) has been consistently larger at the experimental than at the control site. Furthermore, correlation analysis between near-surface soil moisture and deeper layer soil moisture over the four sites provides inferences pointing to the non-uniqueness of the relationship that has an important implication for remotely sensed near-surface soil moisture. In addition to continuous point measurements, periodic observations of near-surface soil moisture during growing-season were conducted at two nested 50m X 50m plots and at long transects in the footprints of the AmeriFlux and FASET towers. This dataset was used to characterize the evolution of spatial heterogeneity of soil moisture states in the forest environment. By combining high resolution point-scale soil moisture profile data with periodic near-surface soil moisture measurements, this study has also examined the representativeness of point-scale measurement with regards to the spatially mean soil moisture state.

  20. 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, ...

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Zribi, M.; Chahbi, A.; Shabou, M.; Lili-Chabaane, Z.; Duchemin, B.; Baghdadi, N.; Amri, R.; Chehbouni, A.

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  7. 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 Bowen ratio station), and spatially distributed soil moisture ground-truth data needed to assess the ASAR imagery are collected over the whole basin through the TDR technique and the gravimetric method. The objectives of this work are to: 1) test the high resolution ASAR imagery accuracy for producing maps of surface soil moisture patterns at the catchment scale, 2) develop and test an operational assimilation system for robust root-zone soil moisture predictions at the basin scale. The developed assimilation system will have two components, 1) ASAR observations will be merged with the model for robust surface soil moisture estimates though the Ensemble Kalman Filter, and 2) the surface soil moisture estimates will then drive an assimilation engine for robust root-zone soil moisture predictions.

  8. Passive microwaves for soil moisture monitoring

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  9. 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).

  10. SAR-derived soil moisture measurements for bare fields

    NASA Technical Reports Server (NTRS)

    Shi, Jiancheng; Soares, Joao V.; Hess, Laura; Engman, Edwin T.; Van Zyl, Jakob J.

    1991-01-01

    The results of algorithm development and testing for soil moisture retrieval at high incidence angles are reported. Based on first-order surface backscattering models, a physically based algorithm for retrieval of soil moisture has been developed and evaluated using NASA/JPL aircraft SAR (synthetic aperture radar) data. It shows that the co-polarization ratio is sensitive to soil moisture change but not to surface roughness at high incidence angles. This algorithm performed well at L-band and should be useful for repetitive, large-area soil moisture monitoring, without requiring surface roughness measurements. This study suggests that incidence angles greater than 40 deg are optimal for such monitoring.

  11. Preliminary validation of RADARSAT-2 surface soil moisture estimates

    NASA Astrophysics Data System (ADS)

    Hendrickx, Jan M. H.; Rabus, Bernard; Romero, Diana C.; Wehn, Hans; Harrison, J. Bruce J.; Hong, Sung-ho; Borchers, Brian

    2009-05-01

    Soil moisture conditions influence practically all aspects of Army activities and are increasingly affecting its systems and operations. Regional distributions of high resolution soil moisture data will provide critical information on operational mobility, performance of landmine and UXO sensors, and meteorological conditions at the km scale. The objective of this study is to calibrate RADARSAT-2 surface soil moisture estimates with field measurements in the semi-arid Middle Rio Grande Valley of New Mexico. RADARSAT-2 was launched in December 2007 and is the first SAR sensor to offer an operational quad-polarization mode. This mode allows to generate soil moisture (and cm-scale surface roughness) maps from single data sets. Future combination of such maps into time series will lead to further accuracy enhancement through additional exploitation of soil moisture evolution constraints. We present RADARSAT-2 soil moisture maps, field soil moisture measurements, and soil moisture maps derived from optical imagery. In addition, future work is proposed that may contribute to enhanced algorithms for soil moisture mapping using RADARSAT-2.

  12. 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.

  13. High Latitude Soil Moisture Observations to Study Climate Variations and to Evaluate Climate Models

    NASA Astrophysics Data System (ADS)

    Robock, A.; Vinnikov, K. Y.; Luo, L.; Mu, M.

    2002-12-01

    Soil moisture is an important variable in the climate system. Understanding and predicting variations of surface temperature, drought, and flood depend critically on knowledge of soil moisture variations, as do impacts of climate change and seasonal climate forecasting. An observational data set of actual in situ measurements is crucial for model development and evaluation, and as ground truth for remote sensing. The Global Soil Moisture Data Bank is a web site (http://climate.envsci.rutgers.edu/soil_moisture) dedicated to collection, dissemination, and analysis of soil moisture data from around the globe, and is a resource for the remote sensing, climate modeling and climate analysis communities. We currently have soil moisture observations for over 400 stations from a large variety of global climates, including from the former Soviet Union, China, Mongolia, India, and the US, but not many from high latitude locations. We will describe two examples of different uses of these data sets. We have used the data to examine the impact of explicitly including frozen soil in land surface models on the partition of snow melt into runoff and infiltration, as a continuation of analysis of the PILPS Phase 2(d) experiment in Valdai, Russia, and to examine the role of soil moisture in serving as a memory for snow cover anomalies to influence the Asian summer monsoon. We find that inclusion of frozen soil is important for accurate simulations of soil temperature, but not as important for soil moisture in high latitudes, since the soil tends to be saturated and there is insufficient capacity for a large influence on infiltration. There is no evidence for soil moisture serving as snow cover memory.

  14. 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.

  15. [Soil moisture dynamics of apple orchard in Loess Plateau dryland].

    PubMed

    Zhao, Gang; Fan, Ting-lu; Li, Shang-zhong; Zhang, Jian-jun; Wang, Yong; Dang, Yi; Wang, Lei

    2015-04-01

    The soil moisture of 0-500 cm soil layer in a dryland orchard at its full fruit period was measured from 2009 to 2013 to explore the soil moisture dynamics. Results indicated that soil water consumption mainly occurred in the soil layer of 0-300 cm in normal rainfall year and below the 300 cm soil layer when the annual rainfall was less than 400 mm. The soil moisture in the 200-300 cm soil layer fluctuated most and was affected by rainfall and apple consumption. Seasonal drought usually happened between April and late June, while the accumulation of soil moisture mainly occurred in the rainy season from July to mid-October to alleviate the drought effectively in next spring. PMID:26259464

  16. 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 ( ?°) 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. 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.

  20. 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.

  1. 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).

  2. 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...

  3. 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.

  4. 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 moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.

  5. SMOS Soil moisture Cal val activities

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  6. Spatial Downscaling of Remotely Sensed Soil Moisture Using Support Vector Machine in Northeast Asia

    NASA Astrophysics Data System (ADS)

    Choi, M.; Moon, H.; Kim, D.

    2014-12-01

    Recent advances in remote sensing of soil moisture have broadened the understanding of spatiotemporal behavior of soil moisture and contributed to major improvements in the associated research fields. However, large spatial coverage and short timescale notwithstanding, low spatial resolution of passive microwave soil moisture data has been frequently treated as major research problem in many studies, which suggested statistical or deterministic downscaling method as a solution to obtain targeted spatial resolutions. This study suggests a methodology to downscale 10 km and 25 km daily L3 volumetric soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) in 2013 in Northeast Asia using Support Vector Machine (SVM). In the presented methodology, hydrometeorological variables observed from satellite remote sensing which have physically significant relationship with soil moisture are chosen as predictor variables to estimate soil moisture in finer resolution. Separate downscaling algorithms optimized for seasonal conditions are applied to achieve more accurate results of downscaled soil moisture. A comparative analysis between in-situ and downscaled soil moisture is also conducted for quantitatively assessing its accuracy. Further application can be carried out in hydrological modeling or prediction of extreme weather phenomena in fine spatial resolution based on the results of this study.

  7. 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.

  8. Managing soil moisture on waste burial sites

    SciTech Connect

    Anderson, J.E.; Ratzlaff, T.D.; Nowak, R.S.; Markham, O.D.

    1991-11-01

    Shallow land burial is a common method of disposing of industrial, municipal, and low-level radioactive waste. The exclusion of water from buried wastes is a primary objective in designing and managing waste disposal sites. If wastes are not adequately isolated, water from precipitation may move through the landfill cover and into the wastes. The presence of water in the waste zone may promote the growth of plant roots to that depth and result in the transport of toxic materials to above-ground foliage. Furthermore, percolation of water through the waste zone may transport contaminants into ground water. This report presents results from a field study designed to assess the the potential for using vegetation to deplete soil moisture and prevent water from reaching buried wastes at the Idaho National Engineering Laboratory (INEL). Our results show that this approach may provide an economical means of limiting the intrusion of water on waste sites.

  9. SCALING SURFACE SOIL MOISTURE IN THE WALNUT GULCH EXPERIMENTAL WATERSHED

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The estimation of surface soil moisture in semi-arid and arid regions is complicated by the inherent heterogeneous precipitation patterns and ephemeral surface water characteristics. Large-scale sampling is inefficient for long term monitoring of surface soil moisture, especially with the goal of c...

  10. 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 ...

  11. Filtration and assimilation of soil moisture satellite data

    NASA Astrophysics Data System (ADS)

    Bogoslovskiy, Nikolay N.; Erin, Sergei I.; Borodina, Irina A.; Kizhner, Lubov I.

    2015-11-01

    This paper presents two data filtration methods. These methods are used for filtration of satellite soil moisture measurement data. A comparison with in-situ soil moisture measurement data shows an improvement in data quality after application of the filters. First results of satellite data assimilation with a global model of numerical weather forecasting are given.

  12. 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...

  13. 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...

  14. 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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. WindSat Soil Moisture Algorithm and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Soil Moisture Retrieval Using the Aquarius/SAC-D Instruments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aquarius/SAC-D will share common elements with several current and future satellite missions that provide soil moisture. Passive microwave soil moisture retrieval using low frequencies is currently performed using Aqua Advanced Microwave Scanning Radiometer-E (AMSR-E) (C/X-band). This will extended ...

  18. Timescales of Soil Moisture Anomalies: Results from Two GCMs

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Milly, P. C. D.; Schlosser, C. Adam; Suarez, Max J.

    1999-01-01

    Soil moisture anomalies dissipate over timescales that may span weeks to months. Characterizing the geographical and seasonal variations in these timescales can have important practical benefit; significant soil moisture "memory" allows long-lead forecasts of soil moisture, which have been found in recent studies to be essential for useful Ion--lead forecasts of precipitation in many regions. In this talk, we will present and compare the soil moisture timescales derived in two separate general circulation model (GCM) studies. Both studies employ multiple ensembles of short-term climate simulations. Timescales at a given point are effectively estimated by determining how quickly the soil moisture distribution generated in one ensemble of simulations (characterized by a unique set of initial soil moisture conditions) approaches that produced by another ensemble (characterized by a different set of initial soil moisture conditions). The talk will include a discussion of why the timescales produced by the two GCMs differ in some regions, and it will also describe the impact of soil moisture memory on simulated precipitation.

  19. Variability in Corn Response to Nitrogen – Influence of Soil Moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Corn yield response to N fertilizer applications has been observed to co-vary with soil moisture as related to topographic position. The objective of this study was to evaluate the variability in corn response to N under relatively wet and dry soil moisture regimes as determined by topography. A fie...

  20. 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...

  1. 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 ...

  2. 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...

  3. 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...

  4. Creation and destruction of soil moisture variability by vegetation

    NASA Astrophysics Data System (ADS)

    Guswa, A. J.

    2011-12-01

    Vegetation canopies introduce spatial variability into soil moisture by localizing and concentrating throughfall and stemflow. In the soil, the self-limiting process of plant uptake acts to undo this variability and homogenize soil moisture. Root compensation (increased uptake from wetter regions) and hydraulic redistribution (movement of water from wetter to drier soils via plant roots) enhance this homogenization process. This work investigates the interplay between these processes that create and destroy soil moisture variability via a stochastic modeling framework for both wet and dry climates. Precipitation events arrive as a Poisson process in time, and spatial patterns of throughfall are taken to be temporally persistent. Plant uptake is represented with an electric circuit analog that captures the effects of root compensation as well as hydraulic redistribution. Effects of vegetation on soil-moisture variability and partitioning of hydrologic fluxes are depend on the magnitude of heterogeneity introduced via throughfall, the strength of root processes, and other climate, plant, and soil characteristics.

  5. 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.

  6. 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 illustrates the possibility that rate-of-change of soil moisture and VPD measurement could be employed to highlight plant stress conditions.

  7. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. 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.

  11. Geophysical mapping of variations in soil moisture

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  12. USING SOIL MOISTURE TO DETERMINE WHEN TO SUBSOIL

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Degradation and persistence of metolachlor in soil: effects of concentration, soil moisture, soil depth, and sterilization.

    PubMed

    Rice, Pamela J; Anderson, Todd A; Coats, Joel R

    2002-12-01

    The present study evaluated the influence of soil depth, soil moisture, and concentration on the persistence and degradation of metolachlor in soil. Greater percentages of metolachlor persisted in subsurface soils than in surface soil regardless of the soil moisture or initial herbicide concentration. Larger quantities of bound residues and extractable degradation products were found in the surface soils as a result of the increased soil sorption and biodegradation of metolachlor associated with the surface soil, which had more organic matter. Saturated soil favored the dissipation of metolachlor and the formation of soil-bound residues. Significantly greater quantities of a dechlorinated metabolite were measured in the saturated surface soil compared to the unsaturated soil. Mineralization of metolachlor to CO2 and volatilization of metolachlor or metolachlor degradates was minimal in surface and subsurface soils at both soil moistures and herbicide concentrations. Increased metolachlor concentrations did not inhibit microbial activity; however, the greater rate of application did result in the reduced percentage of applied [14C]metolachlor that was bound to surface or subsurface soil. A significant reduction in the quantity of extractable metolachlor degradates and unextractable soil-bound residues in sterile soil revealed the significance of biodegradation to the dissipation of metolachlor in soil. PMID:12463559

  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 compared with observed data from our SASMAS field sites.

  17. Remotely sensed soil moisture input to a hydrologic model

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  18. 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 spans from 2005 to 2011. The results of our study provide some insights on model structure requirements supporting an optimal usage of in situ measured and remotely sensed soil moisture data for operational hydrology.

  19. 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 different forcing data.

  20. 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.

  1. 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 of "bound water" (water present in the cell wall), which in turn affected the strength of the cellulose fibrils that provide tensile strength. This phenomenon, which is the reason any wet wood is weaker than dry wood, results in a 50% difference in root tensile strength within the range of soil moisture measured in the field. We used a one-dimensional finite difference model to explore the effects of soil moisture on root cohesion. Our model shows that changes in the distribution of root biomass represent the primary control on root cohesion (representing up to 50% of intra-specific variability in root cohesion). Local changes in soil moisture result in ~20% change in the overall root cohesion. Our work suggest a feed-forward process in precipitation (and thus soil moisture), root strength changes, and debris flow hazard.

  2. Validation of soil moisture and surface fluxes in EURO-CORDEX simulations as part of a land-atmosphere coupling analysis

    NASA Astrophysics Data System (ADS)

    Knist, Sebastian; Goergen, Klaus; Keune, Jessica; Poorthuis, Lukas; Colette, Augustin; Margarida Cardoso, Rita; Fealy, Rowan; Fernandez, Jesus; Garcia-Diez, Markel; Katragkou, Eleni; Mayer, Stephanie; Soares, Pedro; Sobolowski, Stefan; Vautard, Robert; Sarrach-Wagi, Kirsten; Wulfmeyer, Volker; Simmer, Clemens

    2014-05-01

    Land-atmosphere coupling is highly important to understand e.g. many of the processes involved in regional climate change and its impacts. A main science question is in which way the land surface influences the atmosphere and how the strength of this coupling may be quantified. Such complex land-atmosphere interactions are e.g. sensitive to small scale surface heterogeneities that are better captured by higher resolution regional climate model runs that are supposed to provide an added value when it comes to the reproduction of extremes and associated impacts. As part of a land-atmosphere coupling analysis, where we investigate the coupling strength and its spatial and temporal variability based on ERA-Interim re-analysis driven multiscale EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) validation runs, the present study shows, how well the spatial patterns and temporal evolutions of surface moisture and surface energy fluxes are reproduced in these simulations. The analysis is done on a subset of eight WRF RCM simulations that are part of the EURO-CORDEX ensemble. We evaluate daily model results from 1990 to 2008 at spatial resolutions of about 48 km (EUR-44) and 12 km (EUR-11) for the complete European model domain. The model simulations are compared to the Essential Climate Variables (ECV) Soil Moisture satellite data product of the ESA Climate Change Initiative regridded with a nearest neighbor resampling to the EUR-44 and the EUR-11 grid, respectively. Due to data coverage, the data intercomparison is done on a grid-cell-basis for all individual days with a matching satellite observation for annual and seasonal time spans. Related to the soil moisture-temperature feedback this quantity is highly important for flux partitioning. In order to evaluate those fluxes and thereby the reproduction of boundary layer processes by the models, latent and sensible heat fluxes are compared for individual locations against flux tower measurements of the FLUXNET dataset. An important prerequisite for a valid intercomparison is e.g. a match of the dominant land use as used by the land surface schemes in the RCMs with the station site. As most RCMs in the intercomparison use the NOAH LSM with MODIS land use and USGS GTOPO topographic data, our intercomparison does not necessarily give an information on the quality of the LSM but is rather intended to investigate the overall effects of the complex interplay of several processes.

  3. Evaluation of GSWP-2 Soil Moisture Simulations and its Implication for Seasonal Prediction

    NASA Astrophysics Data System (ADS)

    Guo, Z.; Dirmeyer, P. A.

    2006-05-01

    Driven with the meteorological data sets based on the reanalyses and gridded observational data archived by the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II, eleven different land surface models generated global soil moisture data sets for the 10-year period (1986-1995) for the Second Global Soil Wetness Project (GSWP-2). We also integrate one land model with a dozen different combinations of meteorological forcing data and vegetation parameters. We evaluate these model simulations against in situ observations over grasslands and agricultural regions in the former Soviet Union, United States (Illinois), China, and Mongolia from the Global Soil Moisture Data Bank in terms of their ability to estimate the actual column plant-available soil moisture in the top 1m soil layer, to simulate the phasing of the annual cycle, and to represent observed interannual variability. Comparison of the eleven land surface models show that they reproduce reasonably well the observed interannual variability and phasing of the annual cycle. Statistical analysis also shows that the median root mean square of errors ranges from 4-8 cm among these models. Similar to what has been found in soil moisture simulations for GSWP-1, the absolute values of soil moisture are poorly simulated by most models. However, the models do a fairly good job of reproducing the soil moisture anomalies. This suggests that the global soil wetness data set produced by GSWP-2 can be used for analyzing climate variability and initializing GCMs by using certain transform strategies. This also has relevance to sub-seasonal to seasonal forecasts since simulation of soil moisture anomalies might be more important than that for actual monthly mean values due to the persistence of soil moisture anomalies and its potential impact on future precipitation. Sensitivity of soil moisture simulations to different external data show that the skill of soil moisture simulations is very sensitive to the quality of meteorological forcing, and hybridization of reanalysis products with observational data substantially improves soil moisture simulations. The soil moisture simulations are most sensitive to the quality in products of precipitation, radiation, and vegetation class. The range of skill changes is as large as that resulting from different land surface models driven with the same meteorological forcing. If differences among versions of meteorological forcing fields are representative of uncertainties in our knowledge of these drivers of the land surface climate, then impact of that uncertainty on land surface hydrology is as large as that resulting from the uncertainty in land surface models itself.

  4. 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.

  5. Response of grassland ecosystems to prolonged soil moisture deficit

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. The Effects of Wildfire on Soil Moisture Dynamics

    NASA Astrophysics Data System (ADS)

    Kanarek, M.; Cardenas, M.

    2013-12-01

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

  7. High-resolution soil moisture mapping in Afghanistan

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  8. 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.

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

    USGS Publications Warehouse

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

    1996-01-01

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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the ? = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, ?, and powered to an exponent ? > 0 (? =1: linear model; ? ? 1: power model). Both soil moisture data the satellite retrieved (? = ?sat) and the estimates (? = ?est) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was always the lowest; the accuracy in estimating the event soil loss of a models with erosivity factor that includes the estimated runoff is always overcome by at least one model that uses the antecedent soil moisture ? in the erosivity index; the power models generally, at Masse, work better than the linear. The more accurate models are that with the estimated antecedent soil moisture, ?est, when all the database is used and with the satellite retrieved soil moisture, ?sat, when only the wet periods' events are considered. In fact it was also verified that much of the inaccuracy of the tested models is due to summer rainfall events, probably because of the particular characteristics that the soil assumes in the dry period (superficial crusts causing higher runoff): in this cases, high soil losses are observed in association to low values of soil moisture, while the simulated runoff assume low values too, since they are based on the antecedent wetness conditions. Thus, the analyses were repeated excluding the summer events. As expected, the performance of all the models increases, but still the use of ? provides the best results. The results of the analysis open interesting scenarios in the use of USLE-derived models for the unit event soil loss estimation at large scale. In particular the use of the soil moisture to correct the rainfall erosivity factor acquires a great practical importance, since it is a relatively simple measurable data and moreover because remote sensing soil moisture data are widely available and useful in large-scale erosion assessment. Bagarello, V., Di Piazza, G. V., Ferro, V., Giordano, G., 2008. Predicting unit soil loss in Sicily, south Italy. Hydrol. Process. 22, 586-595. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Todisco, F., Vergni, L., 2013. Predicting event soil loss form bare plots at two Italian sites. Catena 109, 96-102. Brocca, L., Melone, F., Moramarco, T., 2011. Distributed rainfall-runoff modeling for flood frequency estimation and flood forecasting. Hydrol. Process. 25, 2801-2813. Kinnell, P. I. A., Risse, L. M., 1998. USLE-M: empirical modeling rainfall erosion through runoff and sediment concentration. Soil Sci. Soc. Am. J. 62, 1667-1672. Todisco, F., Vergni, L., Mannocchi, F., Bomba, C., 2012. Calibration of the soil loss measurement at the Masse experimental station. Catena 91, 4-9. Wischmeier, W. H., Smith, D. D., 1978. Predicting rainfall-erosion losses - A guide to conservation planning. Agriculture Handbook 537, United Stated Department of Agriculture.

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

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  14. 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.

  15. 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.

  16. 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.

  17. Optimal averaging of soil moisture predictions from ensemble land surface model simulations

    NASA Astrophysics Data System (ADS)

    Crow, Wade T.; Su, Chun-Hsu; Ryu, Dongryeol; Tugrul Yilmaz, M.

    2015-04-01

    The correct interpretation of ensemble 3 soil moisture 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 new technique for obtaining such information using an instrumental variable (IV) regression approach and comparisons against a long-term surface soil moisture dataset obtained from satellite remote sensing. Application of the approach to multi-model ensemble soil moisture output from the North American Land Data Assimilation System (NLDAS-2), and multi-satellite European Space Agency (ESA) Soil Moisture (SM) Essential Climate Variable (ECV) dataset, allows for the calculation of optimal weighting coefficients for individual members of a the NLDAS-2 ensemble and a biased-minimized estimate of uncertainty in a deterministic soil moisture analysis derived via such optimal weighted averaging. As such, it provides key information required to accurately condition soil moisture expectations using information gleaned from a multi-model 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  19. A comparison of methods for a priori bias correction in soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

    Data assimilation is increasingly being 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: (1) parameter estimation to calibrate the land model to the climatology of the soil moisture observations and (2) 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.

  20. 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.

  1. 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.

  2. A statistical retrieval algorithm for root zone soil moisture

    NASA Astrophysics Data System (ADS)

    Lindau, Ralf; Simmer, Clemens

    2014-11-01

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

  3. Soil Moisture Profile Estimation From Active Microwave Earth Observations

    NASA Astrophysics Data System (ADS)

    Troch, P. A.; van Loon, E. E.

    This paper discusses the potential of retrieving information about the soil moisture profile from measurements of the surface soil moisture content through active mi- crowave observations of the Earth. In a series of laboratory experiments using multi- frequency radar observations of bare surfaces, Mancini et al. (1999) have shown that accurate surface soil moisture retrieval by means of C and L band active microwave observations is feasible. Hoeben and Troch (2000) combined active microwave obser- vations of the surface soil moisture content and 1D dynamic modeling of the unsat- urated zone in a data assimilation framework to show that this allows the retrieval of the root zone soil moiture profile. They showed that even in the presence of model and observation noise and infrequent observations, accurate retrieval of the entire soil moisture profile is possible for bare soil. Van Loon and Troch (2002) developed a ro- bust 4D data assimilation procedure applicable at the catchment scale. Their 4DDA is based on Tikhonov regularization or generalized cross-validation. Recently, this pro- cedure has been extended to operate in recursive mode, making the algorithm more general applicable for soil moisture data assimilation at the catchment scale. Possible applications of this algorithm in the context of ENVISAT ASAR instrument will be discussed.

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

    USGS Publications Warehouse

    Georgakakos, Konstantine P.; Smith, Diane E.

    2000-01-01

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

  5. 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 based on the here proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but in that case proof of value for the acquisition of instantaneous large-scale soil moisture estimates.

  6. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Evaluation of multi-model simulated soil moisture in NLDAS-2

    NASA Astrophysics Data System (ADS)

    Xia, Youlong; Sheffield, Justin; Ek, Michael B.; Dong, Jiarui; Chaney, Nathaniel; Wei, Helin; Meng, Jesse; Wood, Eric F.

    2014-05-01

    The North American Land Data Assimilation System (NLDAS) phase 2 (NLDAS-2) has generated 31-years (1979-2008) of water and energy products from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC). The soil moisture data from these models have been used for operational drought monitoring activities, but so far have not yet been comprehensively evaluated. In this study, three available in situ soil moisture observation data sets in the United States were used to evaluate the model-simulated soil moisture for different time scales varying from daily to annual. First, we used the observed multiple layer monthly and annual mean soil moisture from the Illinois Climate Network to evaluate 20-years (January 1985-December 2004) of model-simulated soil moisture in terms of skill and analysis of error statistics. Second, we utilized 6-years (1 January 1997-31 December 2002) of daily soil moisture observed from 72 sites over the Oklahoma Mesonet network to assess daily and monthly simulation skill and errors for 3 model soil layers (0-10 cm, 10-40 cm, 40-100 cm). Third, we extended the daily assessment to sites over the continental United States using 8-years (1 January 2002-31 December 2009) of observations for 121 sites from the Soil Climate Analysis Network (SCAN). Overall, all models are able to capture wet and dry events and show high skill (in most cases, anomaly correlation is larger than 0.7), but display large biases when compared to in situ observations. These errors may come from model errors (i.e., model structure error, model parameter error), forcing data errors, and in situ soil moisture measurement errors. For example, all models simulate less soil moisture due to lack of modeled irrigation and ground water processes in Illinois, Oklahoma, and the other Midwest states.

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

    For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the current Soil Moisture and Ocean Salinity (SMOS) and future Soil Moisture Active and Passive (SMAP) satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and WindSat have been used to retrieve surface soil moisture using multi-channel observations obtained at higher microwave frequencies. While AMSR-E and WindSat lack an L-band channel, they are able to leverage multi-channel microwave observations to estimate additional land surface parameters. In particular, the availability of Ka-band observations allows AMSR-E and WindSat to obtain coincident surface temperature estimates required for the retrieval of surface soil moisture. In contrast, SMOS and SMAP carry only a single frequency radiometer and therefore lack an instrument suited to estimate the physical temperature of the Earth. Instead, soil moisture algorithms from these new generation satellites rely on ancillary sources of surface temperature (e.g. re-analysis or near real time data from weather prediction centres). A consequence of relying on such ancillary data is the need for temporal and spatial interpolation, which may introduce uncertainties. Here, two newly-developed, large-scale soil moisture evaluation techniques, the triple collocation (TC) approach and the Rvalue data assimilation approach, are applied to quantify the global-scale impact of replacing Ka-band based surface temperature retrievals with Modern Era Retrospective-analysis for Research and Applications (MERRA) surface temperature output on the accuracy of WindSat and AMSR-E based surface soil moisture retrievals. Results demonstrate that under sparsely vegetated conditions, the use of MERRA land surface temperature instead of Ka-band radiometric land surface temperature leads to a relative decrease in skill (on average 9.7%) of soil moisture anomaly estimates. However the situation is reversed for highly vegetated conditions where soil moisture anomaly estimates show a relative increase in skill (on average 13.7%) when using MERRA land surface temperature. In addition, a pre-processing technique to shift phase of the modelled surface temperature is shown to generally enhance the value of MERRA surface temperature estimates for soil moisture retrieval. Finally, a very high correlation (R2 = 0.95) and consistency between the two evaluation techniques lends further credibility to the obtained results.

  10. 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.

  11. 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 enhanced modeling and prediction.

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

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.

    2007-12-01

    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 and the relatively coarse resolution of satellite observations present significant challenges for scaling and the design of these field campaigns. Earlier experiments, in particular Washita'92, established the credibility of large scale application of microwave remote sensing. Of particular significance was the demonstration of synthetic aperture radiometry (now the core technology of the Soil Moisture Ocean Salinity, SMOS, mission), spatial mapping and consistent retrievals, and the temporal information content of repeat observations in deriving soil hydraulic properties. Basic concepts were expanded in both space and time in experiments such as SGP97 that attempted to integrate the soil moisture observations in the broader framework of land surface hydrology. These types of campaigns have expanded globally. Within the U.S. in recent years they have focused on two issues; establishing the foundations of a future active-passive soil moisture satellite mission and the development and validation of current satellite soil moisture algorithms. Experiments involving a range of spatial domains (point, field, region) and geographical domains have contributed to establishing scaling relationships for both measurements and processes. Future experiments must continue to address the needs of planned soil moisture missions such as SMOS and Aquarius. As the Soil Moisture Active Passive (SMAP) mission concept continues to develop, there will be an increasing need to test and refine algorithms and in the post-launch time frame, there will be a need for validation products. These needs must be integrated with broader science objectives (to the degree it is possible) in order to secure the required resources. Efforts should be made to find communality with other missions and other research programs.

  13. Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

    NASA Technical Reports Server (NTRS)

    Reichle, R. H.

    2010-01-01

    Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

  14. 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. ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. Measurement of soil moisture trends with airborne scatterometers

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J. (Principal Investigator)

    1978-01-01

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

  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 and soil types. Additionally, measurements from an L-band radiometer from ESA (European Space Agency), ELBARA-II, installed in the area to monitor SMOS validation conditions over a vineyard crop are available. Furthermore, MODIS, LANDSAF and SMOS products are used to define realistic initial conditions for sensitivity simulations. The results of these simulations are investigated, compared and conclusions drawn. The investigation covers the autumn period of 2012, September to November, and we will particularly focus on selected stages where extreme rain events occurred in our study area.

  3. Sensitivity of the soil moisture initialization in the genesis of two simulated mesoscale convective systems

    NASA Astrophysics Data System (ADS)

    Cheng, William Yau Yin

    This study examines the sensitivity of the horizontal heterogeneities of the soil moisture initialization (SMI) in the cloud-resolving grid of two real-data mesoscale convective system (MCS) simulations during their genesis phase. We used a nested grid setup similar to some of the current realtime forecast models. Both systems were quasi-stationary. One system (Case 980726) formed in the Texas/Oklahoma border with a lifetime of 9h. The second system (Case 990802), with origins in western Oklahoma, also had a lifetime of 9h. Soil moisture for the cloud-resolving grid was derived from the Antecedent Precipitation Index (API) using 4-km grid spacing precipitation data for a three-month period. In order to test the sensitivity of the heterogeneities of the SMI in the cloud-resolving grid, (i) Barnes objective analysis was used to alter the resolution of the SMI, (ii) the amplitude of the soil moisture field was reduced by 50%, (iii) the position of a soil moisture anomaly was altered, and (iv) two experiments with homogeneous soil moisture (31% and 50% saturation) were performed. Large-scale forcing provided the favorable environment for convection to develop, but the distribution of the soil moisture determined where convection was likely to occur. The soil moisture anomalies generated physiographic-induced mesoscale systems (PIMSs), analogous to sea breeze, due to differential surface heating, and they assisted in organizing the convection as the MCS was developing. The larger soil moisture anomalies were more influential in initiating and/or interacting with convection. As the initial soil moisture was smoothed, the PIMSs associated with the larger soil moisture anomalies started to strengthen, but as the smoothing reached a cutoff wavelength of 80 km, the PIMSs began to weaken. Although the effects of the smaller soil moisture anomalies were not negligible in initiating and/or enhancing convective precipitation, they tended to lose their signatures with the smoothing operation. In the experiments, a negative feedback existed between wet soil and convective precipitation which tended to suppress convection over wet soil but favored convection at the periphery of the wet soil.

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

    NASA Astrophysics Data System (ADS)

    Zribi, Mehrez; Baghdadi, Nicolas

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  6. 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.

  7. [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

  8. 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- dimensional diffusion equation verified that soil sorption under unsaturated condition should not be represented by sorption measured under saturated condition. Effect of soil moisture on sorption and thus volatilization should be considered in modeling.

  9. 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.

  10. The NASA Soil Moisture Active Passive (SMAP) Mission Status

    NASA Astrophysics Data System (ADS)

    Entekhabi, D.; Yueh, S. H.; O'Neill, P. E.; Entin, J. K.; Kellogg, K.; Njoku, E. G.

    2014-12-01

    NASA's Soil Moisture Active Passive (SMAP) mission, the first planned Tier 1 Earth Science Decadal Survey flight, will provide high-resolution, frequent-revisit global mapping of soil moisture and freeze/thaw state. The mission will use low-frequency microwave radar and radiometer measurements (L-band) to produce high resolution global maps of surface soil moisture. The radiometer provides greater sensitivity to soil moisture but at low resolution (40 km). The radar provides higher resolution information with lower sensitivity. The SMAP active-passive surface soil moisture product is a combination of the two measurements with 9 km resolution that is refreshed every 2 to 3 days globally. The SMAP project will also provide root-zone soil moisture and Net Ecosystem Exchange (NEE) information produced by merging observations with models. The status of the satellite observatory and plans for the calibration and validation of SMAP products are presented. The schedule for data release is shown and planned science and applications analyses are outlined.

  11. Estimating surface soil moisture using ENVISAT RA-2 altimetry measurements

    NASA Astrophysics Data System (ADS)

    Frappart, F.; Fatras, C.; Mougin, E.; Grippa, M.

    2011-12-01

    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. Satellite altimetry, initially designed to make accurate measurements of the sea surface topography, has recently demonstrated a strong capability to provide valuable information for land hydrology. It exhibited abilities for measuring water level variations of lakes, rivers, and floodplains. The radar altimetry backscattering coefficient was also related to surface properties, especially soil moisture and surface roughness, and their temporal evolution. We analyzed 8 years of backscattering coefficients variations from Envisat in Ku and S bands over the AMMA meso-scale site in Gourma, Sahel, and related them to the nature of the soil and its hydrological status (presence of moisture, open water, ...). Comparisons were made with in situ superficial soil moisture measurements and satellite-derived soil moisture estimates. Good correlations were found especially over sandy surfaces, showing the ability of radar altimetry for detecting soil moisture in semi-arid regions.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  13. New insights in catchment processes via distributed soil moisture measurements and 3D hydrological modeling

    NASA Astrophysics Data System (ADS)

    Bogena, H. R.; Sciuto, G.; Rosenbaum, U.; Herbst, M.; Huisman, J. A.; Vereecken, H.; Diekkrueger, B.

    2010-12-01

    Hydrological analysis is often limited by the number of data available. Usually, discharge data and only little point information concerning soil moisture status are available. This might give a good representation of the temporal variability of runoff, but it does not provide insights into the spatial dynamics of soil moisture and water fluxes within the catchment. The small forested Wüstebach catchment (~27 ha) has been instrumented with a wireless sensor network consisting of 150 nodes and more than 1200 soil moisture sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [1]. This unique data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution. We present first results of a geostatistical analysis of the data and an application of the integrated surface/subsurface 3D finite element model HydroGeoSphere model to investigate the scale dependency of the temporal dynamics of soil moisture patterns. A variogram analysis showed that the sum of the sub-scale variability and the measurement error is close to time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil moisture, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to root water uptake, lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. The temporal patterns of runoff discharge were reproduced by the HydroGeoSphere model in a satisfying way. The observed soil moisture patterns were used to analyze the simulation quality. Generally, the model accuracy increased with decreasing spatial discretisation. The spatial discretisation of the model also had a larger effect on the water balance than the scaling of soil properties, which was attributed to the model equation describing transpiration dependency on water status and was not considered to be related to the scale dependency of hydrological processes. These findings demonstrate that the conceptual model (deciding on equations) is as important as the perceptual model (deciding on the processes). References: [1] Bogena, H.R., M. Herbst, J.A. Huisman, U. Rosenbaum, A. Weuthen, and H. Vereecken (2010): Potential of wireless sensor networks for measuring soil water content variability. Vadose Zone J., doi:10.2136/vzj2009.0173.

  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. The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates

    NASA Astrophysics Data System (ADS)

    Seyyedi, H.; Anagnostou, E. N.

    2011-12-01

    This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Cisty, Milan; Suchar, Martin; Bajtek, Zbynek

    2010-05-01

    Information's about soil water content are in the planning of water resources and management very valuable. Modeling and predicting soil water transfer is very important in agriculture or hydrology - e.g. for purposes of the effective irrigation management. Many tried and proven methods of estimating or measuring soil moisture are available. The choice of the method which in particular case is eligible, depends on a variety of factors such as accuracy, cost, and ease of use. One of the most important hydro physical characteristics of soil is water retention curve (WRC), which is input to various hydraulic and hydrological models and reflects the energy dependence of soil water and the water content, e.g. the relationship between soil moisture and moisture potential. The method of determining the water retention curve points in laboratory conditions is very expensive, time consuming and labor intensive. In soil physics, therefore, were developed methods for determining soil hydro physical characteristics from easier obtained characteristics - soil granularity composition, organic matter content and bulk density. For these models (or relations) have been established title pedotransfer functions (PTF). These functions specify different soil characteristics and properties from relationship with another. The submitted work compares the creation of such functional dependencies using neural networks, hybrid self-organizing map (SOM) and support vector machines (SVM) model and standard multi-linear regression method. The SVMs formulate a quadratic optimization problem that avoids local minima problems, which makes them often superior to traditional (iterative) learning algorithms such as multi-layer perceptron (MLP) type of neural network. Input data are taken from Zahorská lowland in Slovakia. It was taken 140 soil samples from various localities of Zahorská lowland on finding soil characteristics and on the expression of water retention curve points. Sandy soils are prevailing in this area. Main input data were percentage of granularity categories I to IV according to Kopecky method, reduced volume weight (?d) and measured humidity for potentials hw = -2.5; -56, -209, -558, -976, -3060, -15300 cm specified in laboratory in the overpressure equipment for testing the regression made with abovementioned methods. To compare the results between measured and modeled data by various data driven methods, was accomplished an analysis using correlation coefficient and other statistical characteristics. This evaluation revealed most accurate results by using hybrid SOM-SVM model, in comparison with a conventional multi-layer artificial neural networks, multi-linear regression and standalone SVM model. Greater stability and need of less time devoted to calculations was observed in computation using SVM methodology, since the MLP training sometimes stuck in a local minimum so the training process has to be reset and run many times. This work was supported by the Slovak Research and Development Agency under the contract No. LPP-0319-09.

  18. Evaporation and Condensation of Moisture in a Mole-Plowed Soil

    NASA Astrophysics Data System (ADS)

    Alishaev, M. G.

    2015-11-01

    Consideration is given to temperature waves, traveling in a soil from its surface, with account for phase transitions of moisture and for the influence exerted by mole passages made by a special technology. It is pointed out that evaporation and condensation, rather than a flux of soil air, introduce noticeable corrections into the distribution of the soil layer temperature. An analysis of the problem and evaluating solutions are given and a technique of calculation of the moisture condensed in mole passages and in the rooty layer of soil is suggested. Weather data for Yuzhno-Sukhokumsk are used. The results are applicable to the climatic conditions of the Prikaspiiskaya (Near-Caspian) semidesert.

  19. 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

  20. 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 ...

  1. 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) ...

  2. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  4. 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.

  5. Indirect Measurement of Evapotranspiration from Soil Moisture Depletion

    NASA Astrophysics Data System (ADS)

    Li, M.; Chen, Y.

    2007-12-01

    Direct and in situ measurement of evapotranspiration (ET), such as the eddy covariance (EC) method, is often expensive and complicated, especially over tall canopy. In view of soil water balance, depletion of soil moisture can be attributed to canopy ET when horizontal soil moisture movement is negligible and percolation ceases. This study computed the daily soil moisture depletion at the Lien-Hua-Chih (LHC) station (23°55'52"N, 120°53'39"E, 773 m elevation) from July, 2004 to June, 2007 to estimate daily ET. The station is inside an experimental watershed of a natural evergreen forest and the canopy height is about 17 m. Rainfall days are assumed to be no ET. For those days with high soil moisture content, normally 2 to 3 days after significant rainfall input, ET is estimated by potential ET. Soil moistures were measured by capacitance probes at -10 cm, - 30 cm, -50 cm, -70 cm, and -90 cm. A soil heat flux plate was placed at -5 cm. In the summer of 2006, a 22 m tall observation tower was constructed. Temperature and relative humidity sensors were placed every 5 m from ground surface to 20 m for inner and above canopy measurements. Net radiation and wind speed/directions were also installed. A drainage gauge was installed at -50 cm to collect infiltrated water. Continuous measurements of low response instruments were recorded every 30-minute averaged from 10-minute samplings. A nearby weather station provides daily pan evaporation and precipitation data. Since the response of soil water variations is relatively slow to the fluctuations of atmospheric forcing, only daily ET is estimated from daily soil moisture depletion. The annual average precipitation is 2902 mm and the annual average ET is 700 mm. The seasonal ET patterns of the first two water years are similar. The third year has a higher ET because soil moisture was recharged frequently by rainfall In order to examine the applicability of this approach, an EC system, including a 3-D sonic anemometer (Young 81000) and a krypton hygrometer (Campbell KH20), were practiced for LH and SH measurements at the top of the tower. During wet seasons (summer and autumn), fogs and afternoon thunderstorms often caused failures of the EC system. The ETs directly measured by the EC are slightly higher than those estimated from soil moisture depletions. Spatial soil moisture heterogeneity is suspected to be the cause of such discrepancies.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  10. Soil moisture monitoring methods: Strengths and limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    PubMed

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

    2013-02-01

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

  15. 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

  16. ESTIMATING CORN GRAIN YIELD FROM TEMPORAL VARIATIONS OF SOIL MOISTURE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture is often sited as the principal factor controlling yield response in rain-fed agricultural production systems. During the past two decades, a great deal of research has been conducted that attempts to describe the spatial and temporal variability of crop yield as a function of soil pr...

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  18. 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 Sciences.

  19. 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.

  20. 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.

  1. 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.

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

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Larson, Kristine; Small, Eric; Chew, Clara

    2015-04-01

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

  6. 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 ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

  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. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  12. SIMULTANEOUS SOIL MOISTURE AND CONE INDEX MEASUREMENT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil compaction can restrict root growth and water infiltration resulting in yield reduction. Maps of yield monitor data aid in visualization of variations in yield without identifying underlying factors for these variations. Soil penetration resistance can help identify areas where soil physical ch...

  13. 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.

  14. 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.

  15. Soil Moisture Background Error Covariance Estimation in a Land-Atmosphere Coupled Model

    NASA Astrophysics Data System (ADS)

    Lin, L. F.; Ebtehaj, M.; Flores, A. N.; Wang, J.; Bras, R. L.

    2014-12-01

    The objective of this study is to estimate space-time dynamics of the soil moisture background error in a coupled land-atmosphere model for better understanding the land-atmosphere interactions and soil moisture dynamics through data assimilation. To this end, we conducted forecast experiments in eight calendar years from 2006 to 2013 using the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model and estimated the background error statistics based on the National Meteorological Center (NMC) methodology. All the WRF-Noah simulations were initialized with the National Centers for Environmental Prediction (NCEP) FNL operational global analysis dataset. In our study domain, covering the contiguous United States, the results show that the soil moisture background error exhibits strong seasonal and regional patterns, with the highest magnitude occurring during the summer at the top soil layer over most regions of the Great Plains. It is also revealed that the soil moisture background errors are strongly biased at some regions, especially Southeastern United States, and bias impacts the magnitude of the error from top to bottom soil layer in an increasing order. Moreover, we also found that the estimated background error is not sensitive to the selection of WRF physics schemes of microphysics, cumulus parameterization, and land surface model. Overall, this study enhances our understanding on the space-time variability of the soil moisture background error and promises more accurate land-surface state estimates via variational data assimilation.

  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 agricultural crop land until two years before the measurements were carried out, this anisotropy is obviously caused by the former cultivation of the land. Finally, we present a second technique to determine moisture of the topsoil by GPR using the same principle as remote sensing: the reflection of electromagnetic waves at the soil surface and determination of reflection amplitude. We use a 1 GHz horn antenna that is operated 0.5 m above the ground surface. As this method is based on a completely different physical principle than the first one, it provides an independent revision of our results. Even though, lateral resolution is not that high as when using the groundwave technique and the depth of investigation is not exactly the same, we get similar results showing the same pattern and characteristics at both sites.

  17. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101-103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10-3-10-1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-pixel version of a distributed catchment hydrologic model and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

  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 ground processing designs.

  19. Validation of surface soil moisture from AMSR-E using auxiliary spatial data in the transboundary Indus Basin

    NASA Astrophysics Data System (ADS)

    Cheema, M. J. M.; Bastiaanssen, W. G. M.; Rutten, M. M.

    2011-07-01

    SummaryInformation on soil moisture is vital to describe various hydrological processes. Soil moisture parameters are normally measured using buried sensors in the soil. Alternatively, spatial and temporal characteristics of surface soil moisture are estimated through satellites. Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) is one of such satellites that estimate surface soil moisture in an operational context. These estimates need validation prior to use in various hydrological and water management applications. Such validations are normally carried out using field measurements of soil moisture. This is not technically feasible in vast river basins such as the Indus Basin and for pixel sizes of 25 km × 25 km with non-homogeneous soils and land use. Therefore, AMSR-E data interpreted with Njoku model and posted by the National Snow and Ice Data Center (NSIDC) for the Indus Basin is evaluated by comparing it against auxiliary spatial data. The auxiliary data exists of (i) land use, (ii) rainfall from the Tropical Rainfall Measuring Mission (TRMM) satellite, (iii) seasonality of vegetation from SPOT-Vegetation and (iv) saturated water content ( ? sat) inferred from soil maps. A strong relationship was observed between rainfall and surface soil moisture in the land use class "rainfed". Spearman's rank correlation coefficient ( r s) between the soil moisture and rainfall ranged from 0.14 to 0.55 with a mean of 0.36. For irrigated land uses, r s ranged from -0.04 to 0.52 with a mean of 0.29 due to control of soil moisture by irrigation water supply. The temporal analysis of soil moisture data with vegetation time series showed resemblance with growth phenology. Higher Pearson's correlation coefficient ( r) between the soil moisture and vegetation development was found for time lags of a few weeks. The daily maximum values estimated by AMSR-E ranged from 0.08 to 0.38 cm 3 cm -3. The maximum values were near, but below ? sat limits for different soil types. AMSR-E captured the flooding processes during July and August 2010 by showing the soil moisture values to approximate the saturated soil moisture content for areas that are reported to be flooded. This suggests that the absolute AMSR-E soil moisture data from NSIDC are accurate in the upper range of land wetness. It is concluded that AMSR-E surface soil moisture data exhibits spatio-temporal behavior, and the trends agree with auxiliary spatial data sets.

  20. Soil moisture retrieval by active/passive microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Wu, Shengli; Yang, Lijuan

    2012-09-01

    This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

  1. 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 Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

  2. A Spatially Coherent Global Soil Moisture Product with Improved Temporal Resolution

    NASA Technical Reports Server (NTRS)

    Jeu, Richard A. M. De; Holmes, Thomas R. H.; Parinussa, Robert M.; Owe, Manfred

    2014-01-01

    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 Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Tawfik, Ahmed B.

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

  6. 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

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  10. 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, 123, 280-297. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.

  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 update data sets on soil moisture retention, especially during long periods of drought. As such, description of the soil cover water balance will be more elaborate as the soil moisture profile will be described in terms of temporal and spatial variability. Moreover, this field data set can lend support on the evaluation of the potential use of mine wastes as cover materials with respect to their hydrologic and geochemical properties.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

  14. 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.

  15. 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.

  16. 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).

  17. Automatic, real-time monitoring of soil moisture in a remote field area with time domain reflectometry

    NASA Astrophysics Data System (ADS)

    Herkelrath, W. N.; Hamburg, S. P.; Murphy, Fred

    1991-05-01

    A multiplexing time domain reflectoinetry (TDR) system for real-time monitoring of volumetric soil moisture content was developed. The system was tested at a remote field site in the Hubbard Brook Experimental Forest in New Hampshire. The average value of soil moisture content in the top 500 mm of soil was measured every 4 hours for 1 year at 12 locations within a 12- by 18-m plot. The system functioned well except when the air temperature dropped below -15°C, which caused the data logger tape recorder to stop. Calibrations run on undisturbed soil cores did not compare well with published curves developed for mineral soils, probably because of high soil organic matter content. The standard error of estimate of soil moisture content, indicated by the calibrations, was 0.02 cm3/cm3. The standard deviation of repeated moisture content measurements made in the field was 0.003 cm3/cm3. The effect of cable length on the TDR signal was investigated. It was found that long cables tend to attenuate the signal, ultimately making the measurement impractical. However, cable length had little effect on the calibration up to a length of 27 m. The coefficient of variation of the moisture content measurements taken at any given time ranged from 0.12 to 0.21 during the test period. As predicted by a stochastic analysis of soil moisture flow in heterogeneous soil, the spatial variability of the measurements decreased as average soil moisture increased.

  18. Soil sample moisture content as a function of time during oven drying for gamma-ray spectroscopic measurements

    NASA Astrophysics Data System (ADS)

    Benke, R. R.; Kearfott, K. J.

    1999-02-01

    In routine gamma-ray spectroscopic analysis of collected soil samples, procedure often calls to remove soil moisture by oven drying overnight at a temperature of 100°C [1]. Oven drying not only minimizes the gamma-ray self-attenuation of soil samples due to the absence of water during the gamma-ray spectroscopic analysis, but also allows for a straightforward calculation of the specific activity of radionuclides in soil, historically based on the sample dry weight. Because radon exhalation is strongly dependent on moisture [2, 3], knowledge of the oven-drying time dependence of the soil moisture content, combined with radon exhalation measurements during oven drying and at room temperature for varying soil moisture contents, would allow conclusions to be made on how the oven-drying radon exhalation rate depends on soil moisture content. Determinations of the oven-drying radon exhalation from soil samples allow corrections to be made for the immediate laboratory gamma-ray spectroscopy of radionuclides in the natural uranium decay chain. This paper presents the results of soil moisture content measurements during oven drying and suggests useful empirical fits to the moisture data.

  19. 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, Intraannual changes, Atmospheric parameters, Eastern Spain Acknowledgements The research projects GL2008-02879/BTE, LEDDRA 243857 and RECARE FP7 project 603498 supported this research. References: Azorin-Molina, C., Connell, B.H., Baena-Calatrava, R. 2009. Sea-breeze convergence zones from AVHRR over the Iberian Mediterranean Area and the Isle of Mallorca, Spain. Journal of Applied Meteorology and Climatology 48 (10), 2069-2085. Azorin-Molina, C., Vicente-Serrano, S. M., Cerdà, A. 2013. Soil moisture changes in two experimental sites in Eastern Spain. Irrigation versus rainfed orchards under organic farming. EGU, Geophysical Research Abstracts, EGU2013-13286. Bodí, M.B., Mataix-Solera, J., Doerr, S.H. & Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments, 52, 319-337. García-Fayos, P. García-Ventoso, B. Cerdà, A. 2000. Limitations to Plant establishment on eroded slopes in Southeastern Spain. Journal of Vegetation Science, 11- 77- 86. Ghafoor, A., Murtaza, G., Rehman, M. Z., Saifullah Sabir, M. 2012. Reclamation and salt leaching efficiency for tile drained saline-sodic soil using marginal quality water for irrigating rice and wheat crops. Land Degradation & Development, 23: 1 -9. DOI 10.1002/ldr.1033 Johnston, C. R., Vance, G. F., Ganjegunte, G. K. 2013. Soil properties changes following irrigation with coalbed natural gas water: role of water treatments, soil amendments and land suitability. Land Degradation & Development, 24: 350- 362. DOI 10.1002/ldr.1132 Qadir, M., Noble, A. D., Chartres, C. 2013. Adapting to climate change by improving water productivity of soil in dry areas. Land Degradation & Development, 24: 12- 21. DOI 10.1002/ldr.1091 Ziadat, F. M., and Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

  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. Prediction of runoff and soil moistures at the watershed scale: Effects of model complexity and parameter assignment

    NASA Astrophysics Data System (ADS)

    Downer, Charles W.; Ogden, Fred L.

    2003-03-01

    The application of physically based hydrologic models implies they properly simulate processes at the computational scale. A chief criticism is that model predictions are compared only to discharge data. The physically based, hydrologic model CASC2D is reformulated such that soil moistures and fluxes can be computed using Richards' equation. The gridded surface subsurface hydrologic analysis (GSSHA) model is calibrated and verified against outlet discharge measurements during the growing season. The verified model is used to simulate an extended period during which measurements of soil moisture are available. Though soil moisture data are not used in the calibration and verification efforts, the model reproduces both the trends and the magnitude of soil moisture during the growing season. With additional formulation enhancements, soil moistures during the nongrowing season are also reproduced within a root-mean-square error of 0.1. However, more work is needed to understand the underprediction of runoff during the nongrowing season.

  2. 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...

  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. De-noising of microwave satellite soil moisture time series

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

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

    2014-09-01

    For the problem of low water and fertilizer use efficiency caused by nitrate nitrogen lea- ching into deep soil layer and soil desiccation in dryland apple orchard, characteristics of soil moisture were investigated by means of hand tamping in order to find a new approach in improving the water and fertilizer use efficiency in the apple orchard. Two artificial impermeable layers of red clay and dark loessial soil were built in soil, with a thickness of 3 or 5 cm. Results showed that artificial impermeable layers with the two different thicknesses were effective in reducing or blocking water infiltration into soil and had higher seepage controlling efficiency. Seepage controlling efficiency for the red clay impermeable layer was better than that for the dark loessial soil impermeable layer. Among all the treatments, the red clay impermeable layer of 5 cm thickness had the highest bulk density, the lowest initial infiltration rate (0.033 mm · min(-1)) and stable infiltration rate (0.018 mm · min(-1)) among all treatments. After dry-wet alternation in summer and freezing-thawing cycle in winter, its physiochemical properties changed little. Increase in years did not affect stable infiltration rate of soil water. The red clay impermeable layer of 5 cm thickness could effectively increase soil moisture content in upper soil layer which was conducive to raise the water and nutrient use efficiency. The approach could be applied to the apple production of dryland orchard. PMID:25757307

  6. 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 estimated. Results indicate that this algorithm can successfully estimate surface soil moisture with an RMSE of 0.05 cm3 cm-3 or lower for many of the antennas that comprise the Plate Boundary Observatory (PBO) network.

  7. Analysis of surface moisture variations within large field sites

    NASA Technical Reports Server (NTRS)

    Bell, K. R.; Blanchard, B. J.; Witczak, M. W.; Schmugge, T. J.

    1979-01-01

    A statistical analysis was made on ground soils to define the general relationship and ranges of values of the field moisture relative to both the variance and coefficient of variation for a given test site and depth increment. The results of the variability study show that: (1) moisture variations within any given large field area are inherent and can either be controlled nor reduced; (2) neither a single value of the standard deviation nor coefficient of variation uniquely define the variability over the complete range of mean field moisture contents examined; and (3) using an upper bound standard deviation parameter clearly defines the maximum range of anticipated moisture variability. 87 percent of all large field moisture content standard deviations were less than 3 percent while about 96 percent of all the computed values had an upper bound of sigma=4 percent for these intensively sampled fields. The limit of accuracy curves of mean soil moisture measurements for large field sites relative to the required number of samples were determined.

  8. Plants and their relationship to soil moisture and tracer movement

    SciTech Connect

    Perkins, B.; DePoorter, G.L.

    1985-11-01

    To obtain a better understanding of the mechanisms for possible movement of radionuclides or other toxic materials from waste burial sites in arid to semiarid regions, changes in soil moisture and tracer (Co, Cs, Sr, and tritium) movement were compared for bare vs vegetated soils. During the course of two growing seasons, comparing vegetated with bare soils, plant transpiration processes significantly reduced the soil moisture. In the vegetated soils, most of the Co, Cs, and Sr remained in the region of original emplacement. In bare soils, Co and Cs underwent minimum movement, but the peak concentration of Sr moved downward. For all tracers in the vegetated soils, there was some evidence that slight amounts of tracer had been absorbed in the plant roots and brought to the surface through plant translocation processes. In all cases, there was no significant upward movement of Co, Cs, and Sr. For tritium, the vegetated soils, compared with the bare soils, retained the maximum inventories near the original emplacement location. Although all soils showed some tritium loss, it was greatest in the vegetated soils. A literature review associated with the experiment indicated that plant species alone does not determine rooting depth, rate of transpiration, nutrient uptake, and other plant-associated processes. Environmental conditions are just as important as plant species and must be included in modeling plant-related effects. More data are needed on the effects of tracer concentration, soil water composition, variations in precipitation with time and intensity, evaporation rates, variations in soil composition, soil microorganisms, other invertebrates and vertebrates that inhabit soils, litter decay, and colloid movement on contaminant movement under conditions of unsaturated flow.

  9. [Investigation of polarization characteristics of soil surface with low vegetation cover and different soil moisture].

    PubMed

    Zhang, Qiao; Sun, Xiao-bing; Hong, Jin

    2010-11-01

    Compared with the spectral detection method, polarization detection could obtain more information of the target. For example, the polarization detection could be applied to interpret the refractive index and the surface roughness of the object, or retrieve the soil moisture, etc. Polarization detection provides a new approach to quantitative retrieval of soil moisture, and this is very important in agriculture, hydrology, meteorology and ecology. The polarization characteristics of soil surface with low vegetation cover,which is a example of mixed pixel in remote sensing, were researched with experiments, and the relationship between the polarization characteristics and soil moisture was also explored. The results showed that the polarization characteristics of soil surface with low vegetation cover are mainly determined by the area of bare soil, and are strongly relevant with the soil moisture. For the results of experiments in this paper, the IDOLP of soil surface with low vegetation cover increased with increasing soil moisture when the viewing angle of instrument was between 20 degree and 60 degree, while the incident angle of light source was fixed at 40 degree. This paper offered a new method to retrieve moisture content of soil with low vegetation cover. PMID:21284189

  10. 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.

  11. 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.

  12. [Factors influencing soil moisture at different scales of the Lhasa River basin, China].

    PubMed

    Fu, Guo-zhen; Bai, Wan-qi; Yao, Li-nao

    2015-07-01

    The scale difference and role of factors influencing soil moisture regime are the basis of scale dependency study. This study, which selected farmland soils in the Lhasa River basin of the Tibetan Plateau as the research object, identified the main factors affecting the soil moisture using ecological redundancy analysis (RDA) and statistic analysis methods, based on data obtained by remote sensing technology and field surveys. The soil layers of 0-20, 20-40 and 40-60 cm were collected with the soil-drilling method at each of 115 sampling sites distributed in the whole basin of the Lhasa River and 49 sampling sites in one of its sub-watersheds. The results showed that soil moisture content in the Lhasa River basin, under the influence of climate and altitude, increased from southwest to northeast, and was higher in the lower soil layer than the upper layer due to water supplement by lateral seepage of the river. At sub-watershed scale, farmland soil water content decreased with increasing the altitude and slope, and soil water storage capacity decreased with increasing the gravel content. The results were a significant support for the farmland expansion to higher altitude, adjustment of cropping structure, land consolidation, and construction of irrigation facilities in the region. PMID:26710640

  13. 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