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Sample records for airborne soil moisture

  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. 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.

  3. 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.

  4. 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.

  5. Airborne gamma radiation measurements of soil moisture during FIFE: Activities and results

    NASA Technical Reports Server (NTRS)

    Peck, Eugene L.

    1992-01-01

    Soil moisture measurements were obtained during the summer of 1987 and 1989 near Manhattan, Kansas, using the National Weather Service (NWS) airborne gamma radiation system. A network of 24 flight lines were established over the research area. Airborne surveys were flown daily during two intensive field campaigns. The data collected was sufficient to modify the NWS standard operational method for estimating soil moisture for the Field Experiment (FIFE) flight lines. The average root mean square error of the soil moisture estimates for shorter FIFE flight lines was found to be 2.5 percent, compared with a reported value of 3.9 percent for NWS flight lines. Techniques were developed to compute soil moisture estimates for portions of the flight lines. Results of comparisons of the airborne gamma radiation soil moisture estimates with those obtained using the NASA Pushbroom Microwave Radiation (PBMR) system and hydrological model are presented. The airborne soil moisture measurements, and real averages computed using all remotely sensed and ground data, have been in support of the research of the many FIFE investigators whose overall goal was the upscale integration of models and the application of satellite remote sensing.

  6. Radon emanation and soil moisture effects on airborne gamma-ray measurements

    SciTech Connect

    Grasty, R.L.

    1997-09-01

    A theoretical model is developed to explain variations in airborne gamma-ray measurements over a calibration range near Ottawa, Ontario. The gamma-ray flux from potassium and the thorium decay series showed an expected decrease with increasing soil moisture. However, the gamma-ray flux from the uranium decay series was highest in the spring when the ground was water-saturated and even covered with snow. These results are explained through the build-up of radon and its associated gamma-ray-emitting decay products in the clay soil of the calibration range with increasing soil moisture. Similar results were found from airborne measurements over other clay soils. However, measurements over sandy soils showed that the count rates from all three radio elements increased with decreasing soil moisture. This difference between soil types was attributed to the lower radon emanation of the more coarse-grained sandy soils compared to finer-grained clay soils. The theoretical and experimental results demonstrate that any estimate of the natural gamma-ray field caused by radium in the ground must take into consideration the radon emanation coefficient of the soil. The radon diffusion coefficient of the soil must also be considered since it depends strongly on soil moisture. This has significant implications for the assessment of outdoor radiation doses using laboratory analyses of soil samples and the use of ground and airborne gamma-ray measurements for radon potential mapping.

  7. Remote sensing of soil moisture using airborne hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Institute for Technology Development (ITD) has developed an airborne hyperspectral sensor system that collects electromagnetic reflectance data of the terrain. The system consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near Infrare...

  8. Surface temperature and soil moisture retrieval in the Sahel from airborne multifrequency microwave radiometry

    SciTech Connect

    Calvet, J.C.

    1996-03-01

    Bipolarized microwave brightness temperatures of Sahel semiarid landscapes are analyzed at two frequencies: 5.05 and 36.5 GHz. These measurements were performed in Niger, West Africa, by the radiometer PORTOS in the framework of the Hydrologic Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), during the end of the rainy season (August--September 1992). The airborne microwave data were collected simultaneously with radiosoundings of the atmosphere, and ground measurements of surface temperature, soil moisture, and biomass of several vegetation types. After estimating the soil roughness parameters, it is shown that two kinds of vegetation canopies must be considered: sparse canopies and patchy canopies including bare soil strips. The mixed soil vegetation microwave emission is analyzed using a random continuous approach. The sparse canopy emission is efficiently described by considering the vegetation layer as homogeneous. Conversely, a simple soil-vegetation mixing equation must be used for the patchy canopies. The problem with retrieving the canopy temperature and the near-surface soil moisture is addressed. For every canopy, soil moisture retrieval is possible. Soil moisture maps are proposed. The canopy temperature can also be retrieved with good accuracy provided both vertical (v) and horizontal (h) polarizations are available. It is shown that the retrieved variables can be used to separate landscape units through a classification procedure.

  9. Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

    DTIC Science & Technology

    2011-01-01

    REPORT DATE (DD-MM-YYYY) 14-02-2012 2. REPORT TYPE Journal Article 3. DATES COVERED /From - To) 4. TITLE AND SUBTITLE Remote Sensing of Soil...Murchie, S. L., Oden, S. F, Hayes, J. R., Bell, J. F, Krein, S. J., and A. Mastandrea, 1997, "Near Infrared Spectrometer for the near Earth Asteroid

  10. Soil moisture estimates from the SMOS Validation Rehearsal Campaign in Valencia using EMIRAD airborne measurements

    NASA Astrophysics Data System (ADS)

    Saleh Contell, K.; López-Baeza, E.; Antolín, C.; Millán, C.; Cano, A.; Wigneron, J. P.; Balling, J.; Schmidl, S. S.; Skou, N.; Kerr, Y. H.; Richaume, P.; Juglea, S.; Delwart, S.; Bouzinac, C.; Wursteisen, P.

    2009-04-01

    The European Space Agency conducted a series of flights in 2008 over the main SMOS Validation sites in Europe, amongst them at the Valencia site. The scope of these campaigns was to help in the preparation of operational soil moisture outputs to be generated by the validation teams during the SMOS commissioning phase and beyond. For that purpose, several activities were scheduled at the Valencia site as part of the SMOS Validation Rehearsal campaign. These included: i) Airborne measurements at L-band to improve the parameterisation of the microwave model L-MEB (L-band Microwave Emssion model of the Biosphere) in the area, in order to improve the match between measured brightness temperatures by SMOS, and simulations using ground-truth soil moisture. ii) Intensive soil moisture sampling in a 10 km x 10 km area to support both current studies on soil moisture spatialisation based on SVAT modelling, and the definition of homogeneous land units for the future characterisation of soil moisture at the scale of a SMOS pixel (~ 50 km). The Valencia Site is located in SE Spain, about 80 km inland to the west of Valencia. Within the Valencia validation site, an area of 10 km x 10 km was selected for the experiment. The land use in this area is dominated by vineyards and bare soil (>70%), and orchards (~18 %). Flights over this area were conducted on four different days between April 22nd and May 2nd 2008. During that period, soil moisture near the surface (0-6 cm) slowly decreased with the last rainfall having occurred on April 20. Radiometric measurements were acquired by EMIRAD (L-band, 1.4 GHz) onboard the Skyvan aircraft. The flight plan, repeated across the four days, included 4 parallel lines crossing the 10 km x 10 km area at ~2300 m above the ground level. One diagonal flight was also performed at ~900 m above the ground level on each day. EMIRAD measured the L-band radiation emitted by the surface using two horns, one close to nadir, and the other one at 43 deg

  11. The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

    NASA Technical Reports Server (NTRS)

    Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.

    2006-01-01

    Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground

  12. 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

  13. Survey of L Band Tower and Airborne Sensor Systems Relevant to Upcoming Soil Moisture Missions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Basic research on the physics of microwave remote sensing of soil moisture has been conducted for almost thirty years using ground-based (tower- or truck-mounted) microwave instruments at L band frequencies. Early small point-scale studies were aimed at improved understanding and verification of mi...

  14. Airborne Active and Passive L-Band Observations in Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12)

    NASA Astrophysics Data System (ADS)

    Colliander, A.; Yueh, S. H.; Chazanoff, S.; Jackson, T. J.; McNairn, H.; Bullock, P.; Wiseman, G.; Berg, A. A.; Magagi, R.; Njoku, E. G.

    2012-12-01

    NASA's (National Aeronautics and Space Administration) Soil Moisture Active Passive (SMAP) Mission is scheduled for launch in October 2014. The objective of the mission is global mapping of soil moisture and freeze/thaw state. Merging of active and passive L-band observations of the mission will enable unprecedented combination of accuracy, resolution, coverage and revisit-time for soil moisture and freeze/thaw state retrieval. For pre-launch algorithm development and validation the SMAP project and NASA coordinated a field campaign named as SMAPVEX12 (Soil Moisture Active Passive Validation Experiment 2012) together with Agriculture and Agri-Food Canada in the vicinity of Winnipeg, Canada in June-July, 2012. The main objective of SMAPVEX12 was acquisition of data record that features long-time series with varying soil moisture and vegetation conditions (for testing the application of time-series approach) over aerial domain of multiple parallel lines (for spatial disaggregation studies). The coincident active and passive L-band data were acquired using the Passive Active L-band System (PALS), which is an airborne radiometer and radar developed for testing L-band retrieval algorithms. For SMAPVEX12 PALS was installed on a Twin Otter aircraft. The flight plan included flights at two altitudes. The higher altitude was used to map the whole experiment domain and the lower altitude was used to obtain measurements over a specific set of field sites. The spatial resolution (and swath) of the radar and radiometer from low altitude was about 600 m and from high altitude about 1500 m. The PALS acquisitions were complemented with high resolution (~10 m) L-band SAR measurements carried out by UAVSAR instrument on-board G-III aircraft. The campaign ran from June 7 until July 19. The PALS instrument conducted 17 brightness temperature and backscatter measurement flights and the UAVSAR conducted 14 backscatter measurement flights. The airborne data acquisition was supported by

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  16. 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.

  17. 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...

  18. Soil moisture modeling review

    NASA Technical Reports Server (NTRS)

    Hildreth, W. W.

    1978-01-01

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

  19. Airborne active and passive L-band measurements using PALS instrument in SMAPVEX12 soil moisture field campaign

    NASA Astrophysics Data System (ADS)

    Colliander, Andreas; Yueh, Simon; Chazanoff, Seth; Dinardo, Steven; O'Dwyer, Ian; Jackson, Thomas; McNairn, Heather; Bullock, Paul; Wiseman, Grant; Berg, Aaron; Magagi, Ramata; Njoku, Eni

    2012-10-01

    NASA's (National Aeronautics and Space Administration) Soil Moisture Active Passive (SMAP) Mission is scheduled for launch in late 2014. The objective of the mission is global mapping of soil moisture and freeze/thaw state. Merging of active and passive L-band observations of the mission will enable unprecedented combination of accuracy, resolution, coverage and revisit-time for soil moisture and freeze/thaw state retrieval. For pre-launch algorithm development and validation the SMAP project and NASA coordinated a field campaign named as SMAPVEX12 (Soil Moisture Active Passive Validation Experiment 2012) together with Agriculture and Agri-Food Canada, and other Canadian and US institutions in the vicinity of Winnipeg, Canada in June-July, 2012. The main objective of SMAPVEX12 was acquisition of a data record that features long time-series with varying soil moisture and vegetation conditions over an aerial domain of multiple parallel flight lines. The coincident active and passive L-band data was acquired with the PALS (Passive Active L-band System) instrument. The measurements were conducted over the experiment domain every 2-3 days on average, over a period of 43 days. The preliminary calibration of the brightness temperatures obtained in the campaign has been performed. Daily lake calibrations were used to adjust the radiometer calibration parameters, and the obtained measurements were compared against the raw in situ soil moisture measurements. The evaluation shows that this preliminary calibration of the data produces already a consistent brightness temperature record over the campaign duration, and only secondary adjustments and cleaning of the data is need before the data can be applied to the development and validation of SMAP algorithms.

  20. Utilization of Airborne and in Situ Data Obtained in SGP99, SMEX02, CLASIC and SMAPVEX08 Field Campaigns for SMAP Soil Moisture Algorithm Development and Validation

    NASA Technical Reports Server (NTRS)

    Colliander, Andreas; Chan, Steven; Yueh, Simon; Cosh, Michael; Bindlish, Rajat; Jackson, Tom; Njoku, Eni

    2010-01-01

    Field experiment data sets that include coincident remote sensing measurements and in situ sampling will be valuable in the development and validation of the soil moisture algorithms of the NASA's future SMAP (Soil Moisture Active and Passive) mission. This paper presents an overview of the field experiment data collected from SGP99, SMEX02, CLASIC and SMAPVEX08 campaigns. Common in these campaigns were observations of the airborne PALS (Passive and Active L- and S-band) instrument, which was developed to acquire radar and radiometer measurements at low frequencies. The combined set of the PALS measurements and ground truth obtained from all these campaigns was under study. The investigation shows that the data set contains a range of soil moisture values collected under a limited number of conditions. The quality of both PALS and ground truth data meets the needs of the SMAP algorithm development and validation. The data set has already made significant impact on the science behind SMAP mission. The areas where complementing of the data would be most beneficial are also discussed.

  1. Soil Moisture Workshop

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  2. Multiangular L-band Datasets for Soil Moisture and Sea Surface Salinity Retrieval Measured by Airborne HUT-2D Synthetic Aperture Radiometer

    NASA Astrophysics Data System (ADS)

    Kainulainen, J.; Rautiainen, K.; Seppänen, J.; Hallikainen, M.

    2009-04-01

    SMOS is the European Space Agency's next Earth Explorer satellite due for launch in 2009. It aims for global monitoring of soil moisture and ocean salinity utilizing a new technology concept for remote sensing: two-dimensional aperture synthesis radiometry. The payload of SMOS is Microwave Imaging Radiometer by Aperture Synthesis, or MIRAS. It is a passive instrument that uses 72 individual L-band receivers for measuring the brightness temperature of the Earth. From each acquisition, i.e. integration time or snapshot, MIRAS provides two-dimensional brightness temperature of the scene in the instrument's field of view. Thus, consecutive snapshots provide multiangular measurements of the target once the instrument passes over it. Depending on the position of the target in instrument's swath, the brightness temperature of the target at incidence angles from zero up to 50 degrees can be measured with one overpass. To support the development MIRAS instrument, its calibration, and soil moisture and sea surface salinity retrieval algorithm development, Helsinki University of Technology (TKK) has designed, manufactured and tested a radiometer which operates at L-band and utilizes the same two-dimensional methodology of interferometery and aperture synthesis as MIRAS does. This airborne instrument, called HUT-2D, was designed to be used on board the University's research aircraft. It provides multiangular measurements of the target in its field of view, which spans up to 30 degrees off the boresight of the instrument, which is pointed to the nadir. The number of independent measurements of each target point depends on the flight speed and altitude. In addition to the Spanish Airborne MIRAS demonstrator (AMIRAS), HUT-2D is the only European airborne synthetic aperture radiometer. This paper presents the datasets and measurement campaigns, which have been carried out using the HUT-2D radiometer and are available for the scientific community. In April 2007 HUT-2D participated

  3. 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.

  4. 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.

  5. SOIL moisture data intercomparison

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  6. A model of the 1.6 GHz scatterometer. [performance of airborne scatterometer used as microwave remote sensor of soil moisture

    NASA Technical Reports Server (NTRS)

    Wang, J. R.

    1977-01-01

    The performance was studied of the 1.6 GHz airborne scatterometer system which is used as one of several Johnson Space Center (JSC) microwave remote sensors to detect moisture content of soil. The system is analyzed with respect to its antenna pattern and coupling, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principle and the sensitivity of the system, as well as data handling are also described. The finite cross-polarized gains of all four 1.6 GHz scatterometer antennae are found to have profound influence on the cross-polarized backscattered signal returns. If these signals are not analyzed properly, large errors could result in the estimate of the cross-polarized coefficient. It is also found necessary to make corrections to the variations of the aircraft parameters during data reduction in order to minimize the error in the coefficient estimate. Finally, a few recommendations are made to improve the overall performance of the scatterometer system.

  7. 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.

  8. Using Airborne Microwave Remotely Sensed Root-Zone Soil Moisture and Flux Measurements to Improve Regional Predictions of Carbon Fluxes in a Terrestrial Biosphere Model

    NASA Astrophysics Data System (ADS)

    Zhang, K.; Antonarakis, A. S.; Medvigy, D.; Burgin, M. S.; Crow, W. T.; Milak, S.; Jaruwatanadilok, S.; Truong-Loi, M.; Moghaddam, M.; Saatchi, S. S.; Cuenca, R. H.; Moorcroft, P. R.

    2013-12-01

    North American ecosystems are critical components of the global carbon cycle, exchanging large amounts of carbon dioxide and other gases with the atmosphere. Net ecosystem exchange (NEE) of CO2 between atmosphere and ecosystems quantifies these carbon fluxes, but current continental-scale estimates contain high levels of uncertainty. Root-zone soil moisture (RZSM) and its spatial and temporal heterogeneity influences NEE and improved estimates can help reduce uncertainty in NEE estimates. We used the RZSM measurements from the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission, and the carbon, water and energy fluxes observed by the eddy-covariance flux towers to constrain the Ecosystem Demography Model 2.2 (ED2.2) to improve its predictions of carbon fluxes. The parameters of the ED2.2 model were first optimized at seven flux tower sites in North America, which represent six different biomes, by constraining the model against a suite of flux measurements and forest inventory measurements through a Bayesian Markov-Chain Monte Carlo framework. We further applied the AirMOSS RZSM products to constrain the ED2.2 model to achieve better estimates of regional NEE. Evaluation against flux tower measurements and forest dynamics measurements shows that the constrained ED2.2 model produces improved predictions of monthly to annual carbon fluxes. The remote sensing based RZSM can further help improve the spatial patterns and temporal variations of model NEE. The results demonstrate that model-data fusion can substantially improve model performance and highlight the important role of RZSM in regulating the spatial and temporal heterogeneities of carbon fluxes.

  9. 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.

  10. 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

  11. 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

  12. Passive microwave soil moisture research

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  13. Early Soil Moisture Field Experiments

    NASA Astrophysics Data System (ADS)

    Schmugge, T.

    2008-12-01

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

  14. 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.

  15. Remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T.

    1976-01-01

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

  16. Estimation of Surface Soil Moisture Using Fractal

    NASA Astrophysics Data System (ADS)

    Chen, Yen Chang; He, Chun Hsuan

    2016-04-01

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

  17. Soil Moisture and Agromet Models

    DTIC Science & Technology

    1981-03-01

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

  18. 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...

  19. Soil Moisture State and Hydrologic Process

    NASA Astrophysics Data System (ADS)

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

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

  20. 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...

  1. 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.

  2. 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

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. 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), ...

  6. Studying dynamics of soil moisture patterns

    NASA Astrophysics Data System (ADS)

    Balcerak, Ernie

    2012-11-01

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

  7. 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.

  8. Microwave radiometric measurements of soil moisture in Italy

    NASA Astrophysics Data System (ADS)

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

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

  9. 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.

  10. 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.

  11. 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...

  12. 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...

  13. 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...

  14. 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.

  15. 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.

  16. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture.

  18. SMAP and SMOS soil moisture validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Passive microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  5. On-irrigator pasture soil moisture sensor

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  6. The Impact of Standing Water and Irrigation on AMSR-E Sensitivity to Soil Moisture over the NAFE'06 Experiment Area

    Technology Transfer Automated Retrieval System (TEKTRAN)

    AMSR-E sensitivity to soil moisture and its accuracy have been studied over a wide variety of surface conditions and weather regimes using both in situ measured data and aircraft derived soil moisture estimates. Several extensive soil moisture field campaigns involving ground and air-borne component...

  7. 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

  8. Microwave Remote Sensing of Soil Moisture for Estimation of Soil Properties

    NASA Technical Reports Server (NTRS)

    Mattikalli, Nandish M.; Engman, Edwin T.; Jackson, Thomas J.

    1997-01-01

    Surface soil moisture dynamics was derived using microwave remote sensing, and employed to estimate soil physical and hydraulic properties. The L-band ESTAR radiometer was employed in an airborne campaign over the Little Washita watershed, Oklahoma during June 10-18, 1992. Brightness temperature (TB) data were employed in a soil moisture inversion algorithm which corrected for vegetation and soil effects. Analyses of spatial TB and soil moisture dynamics during the dry-down period revealed a direct relationship between changes in TB, soil moisture and soil texture. Extensive regression analyses were carried out which yielded statistically significant quantitative relationships between ratio of percent sand to percent clay (RSC, a term derived to quantify soil texture) and saturated hydraulic conductivity (Ksat) in terms of change components of TB and surface soil moisture. Validation of results indicated that both RSC and Ksat can be estimated with reasonable accuracy. These findings have potential applications for deriving spatial distributions of RSC and Ksat over large areas.

  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. Potential application of satellite radar to monitor soil moisture

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

    The microwave backscattering characteristics of soils as a function of moisture content are reviewed as a basis for the evaluation of the applicability of satellite radar to soil moisture determinations. Results of experiments showing the dependence of the complex dielectric constant, power reflection coefficient and backscattering coefficient of soil on its volumetric moisture content are presented. Results of a research program using the truck-mounted University of Kansas microwave active spectrometer to determine if, by the proper choice of sensor frequency, polarization and incidence, the sensor dynamic range in response to moisture variations may be greater than its response to other variations are considered in detail, and the optimum conditions of frequency (between 4 and 5 GHz), angular incidence (between 7 and 20 deg from nadir) and polarization (HH) obtained are indicated. An empirical model for the backscattering coefficient as a function of gravimetric moisture content derived on the basis of the experimental data is presented, and it is noted that available airborne and spaceborne data confirm the results of the ground-based sensors.

  11. 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 ...

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  13. 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.

  14. Radar measurement of soil moisture content

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1974-01-01

    The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4- to 8-GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-ft truck-mounted boom was used to measure the return at ten frequency points across the 4- to 8-GHz band, at eight different look angles (0 through 70 deg), and for all polarization combinations. A total of 17 sets of data were collected covering the range from 4 to 36% soil moisture content by weight. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear, however, over the range from 15 to 30% moisture content for all angles, frequencies, polarizations and surface conditions.

  15. 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.

  16. 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

  17. 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.

  18. Dual frequency microwave radiometer measurements of soil moisture for bare and vegetated rough surfaces

    NASA Technical Reports Server (NTRS)

    Lee, S. L.

    1974-01-01

    Controlled ground-based passive microwave radiometric measurements on soil moisture were conducted to determine the effects of terrain surface roughness and vegetation on microwave emission. Theoretical predictions were compared with the experimental results and with some recent airborne radiometric measurements. The relationship of soil moisture to the permittivity for the soil was obtained in the laboratory. A dual frequency radiometer, 1.41356 GHz and 10.69 GHz, took measurements at angles between 0 and 50 degrees from an altitude of about fifty feet. Distinct surface roughnesses were studied. With the roughness undisturbed, oats were later planted and vegetated and bare field measurements were compared. The 1.4 GHz radiometer was less affected than the 10.6 GHz radiometer, which under vegetated conditions was incapable of detecting soil moisture. The bare surface theoretical model was inadequate, although the vegetation model appeared to be valid. Moisture parameters to correlate apparent temperature with soil moisture were compared.

  19. Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.

    1985-01-01

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

  20. 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...

  1. Assessing inhalation exposure from airborne soil contaminants

    SciTech Connect

    Shinn, J.H.

    1998-04-01

    A method of estimation of inhalation exposure to airborne soil contaminants is presented. this method is derived from studies of airborne soil particles with radioactive tags. The concentration of contaminants in air (g/m{sup 3}) can be derived from the product of M, the suspended respirable dust mass concentration (g/m{sup 3}), S, the concentration of contaminant in the soil (g/g), and E{sub f}, an enhancement factor. Typical measurement methods and values of M, and E{sub f} are given along with highlights of experiences with this method.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  3. 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...

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. 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.

  7. Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

    NASA Astrophysics Data System (ADS)

    van Wesemael, Bas; Nocita, Marco

    2016-04-01

    One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These

  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. Soil moisture needs in earth sciences

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  11. 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...

  12. Freeze/thaw and soil moisture effects on wind erosion

    NASA Astrophysics Data System (ADS)

    Wang, L.; Shi, Z. H.; Wu, G. L.; Fang, N. F.

    2014-02-01

    Wind erosion is very pronounced in semiarid regions during late winter-early spring and has major impacts on regional desertification and agriculture. In order to identify the effects of freeze/thaw and soil moisture on wind erosion, wind tunnel experiments were conducted to compare wind erosion effects under various soil moisture gradients in frozen and thawed soil. The variation of surface soil moisture after wind erosion and the effective soil particle size distribution was tested to explain the differences. The results showed that surface soil moisture content decreased in thawed soil and increased in frozen soil after wind erosion. The mean weight diameter, which increased with increasing soil moisture, was smaller in thawed soil than in frozen soil. The wind-driven sediment flux of frozen and thawed soil both decreased with increasing moisture, owing to the heavier soil particle weight and stronger interparticle bonding forces. The critical soil moisture content for suppressing wind erosion was around 2.34% for frozen soil and around 2.61% for thawed soil. The wind-driven sediment flux of thawed soil was always larger than that of frozen soil at the same moisture content, but this difference became negligible at moisture contents above 3.38%. We may speculate that wind erosion will be more severe in the future because of the lower soil moisture content and fewer soil freezing days as a result of global warming.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. SLAPex Freeze/Thaw 2015: The First Dedicated Soil Freeze/Thaw Airborne Campaign

    NASA Technical Reports Server (NTRS)

    Kim, Edward; Wu, Albert; DeMarco, Eugenia; Powers, Jarrett; Berg, Aaron; Rowlandson, Tracy; Freeman, Jacqueline; Gottfried, Kurt; Toose, Peter; Roy, Alexandre; Derksen, Chris; Royer, Alain; Belair, Stephane; Houser, Paul; McDonald, Kyle; Entin, Jared; Lewis, Kristen

    2016-01-01

    Soil freezing and thawing is an important process in the terrestrial water, energy, and carbon cycles, marking the change between two very different hydraulic, thermal, and biological regimes. NASA's Soil Moisture Active/Passive (SMAP) mission includes a binary freeze/thaw data product. While there have been ground-based remote sensing field measurements observing soil freeze/thaw at the point scale, and airborne campaigns that observed some frozen soil areas (e.g., BOREAS), the recently-completed SLAPex Freeze/Thaw (F/T) campaign is the first airborne campaign dedicated solely to observing frozen/thawed soil with both passive and active microwave sensors and dedicated ground truth, in order to enable detailed process-level exploration of the remote sensing signatures and in situ soil conditions. SLAPex F/T utilized the Scanning L-band Active/Passive (SLAP) instrument, an airborne simulator of SMAP developed at NASA's Goddard Space Flight Center, and was conducted near Winnipeg, Manitoba, Canada, in October/November, 2015. Future soil moisture missions are also expected to include soil freeze/thaw products, and the loss of the radar on SMAP means that airborne radar-radiometer observations like those that SLAP provides are unique assets for freeze/thaw algorithm development. This paper will present an overview of SLAPex F/T, including descriptions of the site, airborne and ground-based remote sensing, ground truth, as well as preliminary results.

  15. Active–passive soil moisture retrievals during the SMAP validation experiment 2012

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The goal of this study is to assess the performance of the active–passive algorithm for the NASA Soil Moisture Active Passive mission (SMAP) using airborne and ground observations from a field campaign. The SMAP active–passive algorithm disaggregates the coarse-resolution radiometer brightness tempe...

  16. Soil Moisture Variability Beneath a Melting Snowpack

    NASA Astrophysics Data System (ADS)

    Webb, R.; Fassnacht, S. R.

    2013-12-01

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

  17. SMAP validation of soil moisture products

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Soil moisture and temperature algorithms and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. An airborne study of microwave surface sensing and boundary layer heat and moisture fluxes for FIFE

    NASA Technical Reports Server (NTRS)

    Gogineni, S. P.

    1995-01-01

    The objectives of this work were to perform imaging radar and scatterometer measurements over the Konza Prairie as a part of the First International land surface climatology project Field Experiments (EIFE) and to develop an mm-wave radiometer and the data acquisition system for this radiometer. We collected imaging radar data with the University of Kansas Side-Looking Airborne Radar (SLAR) operating at 9.375 GHz and scatterometer data with a helicopter-mounted scatterometer at 5.3 and 9.6 GHz. We also developed a 35-GHz null-balancing radiometer and data acquisition system. Although radar images showed good delineation of various features of the FIFE site, the data were not useful for quantitative analysis for extracting soil moisture information because of day-to-day changes in the system transfer characteristics. Our scatterometer results show that both C and X bands are sensitive to soil moisture variations over grass-covered soils. Scattering coefficients near vertical are about 4 dB lower for unburned areas because of the presence of a thatch layer, in comparison with those for burned areas. The results of the research have been documented in reports, oral presentations, and published papers.

  20. 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...

  1. 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.

  2. 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

  3. 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

  4. SoilNet - A Zigbee based soil moisture sensor network

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

    Jackson, R. D. (Principal Investigator)

    1981-01-01

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

  8. 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

  9. Microwave Soil Moisture Retrieval Under Trees

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. 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...

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Traditional and microirrigation with stochastic soil moisture

    NASA Astrophysics Data System (ADS)

    Vico, Giulia; Porporato, Amilcare

    2010-03-01

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

  18. Airborne soil organic particles generated by precipitation

    NASA Astrophysics Data System (ADS)

    Wang, Bingbing; Harder, Tristan H.; Kelly, Stephen T.; Piens, Dominique S.; China, Swarup; Kovarik, Libor; Keiluweit, Marco; Arey, Bruce W.; Gilles, Mary K.; Laskin, Alexander

    2016-06-01

    Airborne organic particles play a critical role in Earth's climate, public health, air quality, and hydrological and carbon cycles. However, sources and formation mechanisms for semi-solid and solid organic particles are poorly understood and typically neglected in atmospheric models. Laboratory evidence suggests that fine particles can be formed from impaction of mineral surfaces by droplets. Here, we use chemical imaging of particles collected following rain events in the Southern Great Plains, Oklahoma, USA and after experimental irrigation to show that raindrop impaction of soils generates solid organic particles. We find that after rain events, sub-micrometre solid particles, with a chemical composition consistent with soil organic matter, contributed up to 60% of atmospheric particles. Our irrigation experiments indicate that intensive water impaction is sufficient to cause ejection of airborne soil organic particles from the soil surface. Chemical imaging and micro-spectroscopy analysis of particle physico-chemical properties suggest that these particles may have important impacts on cloud formation and efficiently absorb solar radiation. We suggest that raindrop-induced formation of solid organic particles from soils may be a widespread phenomenon in ecosystems such as agricultural systems and grasslands where soils are exposed to strong, episodic precipitation events.

  19. 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.

  20. Estimation of soil moisture from diurnal surface temperature observations

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  2. 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...

  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

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

    PubMed

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

    2002-12-01

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

  5. Microbiology and Moisture Uptake of Desert Soils

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

  6. Assessment of Soil Moisture and Fixatives Performance in Controlling Wind Erosion of Contaminated Soil at the Hanford Site

    SciTech Connect

    Lagos, L.E.; Gudavalli, R.K.

    2008-07-01

    scale. Soil samples with varying moisture (W/W %) content and soil samples treated with fixatives, selected from a wide range of commercially available products, were exposed to a wind speeds ranging from 10 - 30 miles per hour (MPH). During these experiments, amount of soil displaced due to the wind forces, the amount of airborne particulates generated, and the moisture loss were measured to better understand the performance of selected fixatives and soil moisture. Results obtained during the study showed that there is a significant reduction in wind erosion and airborne particles generation by increasing the soil moisture for the velocities tested. Similar trend was observed when the soil samples treated with fixatives were exposed to the same range of velocities (10 - 30 MPH). (authors)

  7. 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.

  8. 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.

  9. Capacitive Soil Moisture Sensor for Plant Watering

    NASA Astrophysics Data System (ADS)

    Maier, Thomas; Kamm, Lukas

    2016-04-01

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

  10. 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.

  11. 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.

  12. 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

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

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-06-01

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

  14. Remote sensing of vegetation and soil moisture

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  15. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  16. Soil Moisture Monitoring at Watershed Scale in Eastern India

    NASA Astrophysics Data System (ADS)

    Panda, R. K.

    2015-12-01

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

  17. 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.

  18. Use of Ultrasonic Technology for Soil Moisture Measurement

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Quiring, S. M.

    2011-12-01

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

  20. 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.

  1. Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications

    NASA Astrophysics Data System (ADS)

    Shin, Yongchul; Mohanty, Binayak P.

    2013-10-01

    Soil moisture (SM) at the local scale is required to account for small-scale spatial heterogeneity of land surface because many hydrological processes manifest at scales ranging from cm to km. Although remote sensing (RS) platforms provide large-scale soil moisture dynamics, scale discrepancy between observation scale (e.g., approximately several kilometers) and modeling scale (e.g., few hundred meters) leads to uncertainties in the performance of land surface hydrologic models. To overcome this drawback, we developed a new deterministic downscaling algorithm (DDA) for estimating fine-scale soil moisture with pixel-based RS soil moisture and evapotranspiration (ET) products using a genetic algorithm. This approach was evaluated under various synthetic and field experiments (Little Washita-LW 13 and 21, Oklahoma) conditions including homogeneous and heterogeneous land surface conditions composed of different soil textures and vegetations. Our algorithm is based on determining effective soil hydraulic properties for different subpixels within a RS pixel and estimating the long-term soil moisture dynamics of individual subpixels using the hydrological model with the extracted soil hydraulic parameters. The soil moisture dynamics of subpixels from synthetic experiments matched well with the observations under heterogeneous land surface condition, although uncertainties (Mean Bias Error, MBE: -0.073 to -0.049) exist. Field experiments have typically more variations due to weather conditions, measurement errors, unknown bottom boundary conditions, and scale discrepancy between remote sensing pixel and model grid resolution. However, the soil moisture estimates of individual subpixels (from the airborne Electronically Scanned Thinned Array Radiometer (ESTAR) footprints of 800 m × 800 m) downscaled by this approach matched well (R: 0.724 to -0.914, MBE: -0.203 to -0.169 for the LW 13; R: 0.343-0.865, MBE: -0.165 to -0.122 for the LW 21) with the in situ local scale soil

  2. 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).

  3. Correlation of microwave sensor returns with soil moisture

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  4. Recent Enhancements in the North American Soil Moisture Database (NASMD)

    NASA Astrophysics Data System (ADS)

    Chavez, N.; Galvan, J., III; Quiring, S. M.; Ford, T.

    2014-12-01

    The North American Soil Moisture Database (soilmoisture.tamu.edu) is a high-quality observational soil moisture database that contains data from >1800 stations. In the last year we have enhanced the database by identifying sites in Mexico and expanding the database to also include soil temperature data. Here we provide an overview of how the in situ soil moisture and soil temperature observations are assembled, quality controlled and harmonized prior to being incorporated in the NASMD. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  8. Spatiotemporal analyses of soil moisture from point to footprint scale in two different hydroclimatic regions

    NASA Astrophysics Data System (ADS)

    Joshi, Champa; Mohanty, Binayak P.; Jacobs, Jennifer M.; Ines, Amor V. M.

    2011-01-01

    This paper presents time stability analyses of soil moisture at different spatial measurement support scales (point scale and airborne remote sensing (RS) footprint scale 800 m × 800 m) in two different hydroclimatic regions. The data used in the analyses consist of in situ and passive microwave remotely sensed soil moisture data from the Southern Great Plains Hydrology Experiments 1997 and 1999 (SGP97 and SGP99) conducted in the Little Washita (LW) watershed, Oklahoma, and the Soil Moisture Experiments 2002 and 2005 (SMEX02 and SMEX05) in the Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percent silt, percent sand, and soil texture) and topography (elevation and slope) are significant physical controls jointly affecting the spatiotemporal evolution and time stability of soil moisture at both point and footprint scales. In Iowa, using point-scale soil moisture measurements, the WC11 field was found to be more time stable (TS) than the WC12 field. The common TS points using data across the 3 year period (2002-2005) were mostly located at moderate to high elevations in both the fields. Furthermore, the soil texture at these locations consists of either loam or clay loam soil. Drainage features and cropping practices also affected the field-scale soil moisture variability in the WC fields. In Oklahoma, the field having a flat topography (LW21) showed the worst TS features compared to the fields having gently rolling topography (LW03 and LW13). The LW13 field (silt loam) exhibited better time stability than the LW03 field (sandy loam) and the LW21 field (silt loam). At the RS footprint scale, in Iowa, the analysis of variance (ANOVA) tests show that the percent clay and percent sand are better able to discern the TS features of the footprints compared to the soil texture. The best soil indicator of soil moisture time stability is the loam soil texture. Furthermore, the hilltops (slope ˜0%-0.45%) exhibited the best TS

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

    NASA Astrophysics Data System (ADS)

    Kanniah, Kasturi; Siang, Kang Chuen

    2016-07-01

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

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

    USGS Publications Warehouse

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Pan, Feifei; Nieswiadomy, Michael

    2016-11-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Wang, J. R.

    1992-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Salehzadeh, Amir

    1990-01-01

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

  19. 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.

  20. Soil moisture determination study. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1979-01-01

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

  1. 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...

  2. 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...

  3. Soil moisture remote sensing: State of the science

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Use of soil moisture sensors for irrigation scheduling

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Evaluating ESA CCI soil moisture in East Africa

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  7. Challenges in Interpreting and Validating Satellite Soil Moisture Information

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. 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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. The global distribution and dynamics of surface soil moisture

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  11. 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...

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

    PubMed

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

    2009-07-01

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

  13. 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

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

    NASA Astrophysics Data System (ADS)

    Chrisman, B.; Zreda, M.

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  16. 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...

  17. GNSSProbe, penetrating GNSS signals for measuring soil moisture

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  20. 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.

  1. 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.

  2. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  4. A Time Series Approach for Soil Moisture Estimation

    NASA Technical Reports Server (NTRS)

    Kim, Yunjin; vanZyl, Jakob

    2006-01-01

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

  5. Research on the Spatial Variability of Soil Moisture

    NASA Astrophysics Data System (ADS)

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

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

  6. Soil moisture downscaling using a simple thermal based proxy

    NASA Astrophysics Data System (ADS)

    Peng, Jian; Loew, Alexander; Niesel, Jonathan

    2016-04-01

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

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

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator)

    1977-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Heathman, Gary Claude

    2001-10-01

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

  9. Soil Moisture Measurement System For An Improved Flood Warning

    NASA Astrophysics Data System (ADS)

    Schaedel, W.; Becker, R.

    Precipitation-runoff processes are correlated with the catchment's hydrological pre- conditions that are taken into account in some hydrological models, e.g. by pre- precipitation index. This statistically generated variable is unsuitable in case of ex- treme flood events. Thus a non-statistical estimation of the catchment's preconditions is of tremendous importance for an improvement in reliability of flood warning. This can be achieved by persistent operational observation of the catchment's soil mois- ture condition. The soil moisture acts as a state variable controlling the risk of surface runoff, which is assumed to provoke critical floods. Critical soil moisture conditions can be identified by measurements in certain areas representative for the catchment. Therefore a measurement arrangement that does not effect the structure of soils is realised with twin rod probes. Spatial resolution algorithms result in soil moisture profiles along the probe rods. In this set up a quasi three dimensional soil moisture distribution can be interpolated with point measurements of up to 47 twin rod probes per cluster, connected via multiplexer. The large number of probes per cluster is of use for detailed observation of small-scaled moisture variability. As regionalized grid cell moisture the cluster information calibrates the default, state depending soil moisture distribution of the catchment. This distribution is explained by diverse soil moisture influencing properties, which are found by Landsat satellite image. Therefore the im- age is processed with principal component analysis to extract the soil moisture distri- bution. The distribution is calibrated by the detailed measurements, acting as ground based truth. Linear multiple regression operated on the calibrated distribution identi- fies the mentioned properties. In this fashion the catchment status can be determined and combined with precipitation forecasts, thus allowing for the comprehensive risk calculation of

  10. 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

  11. The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

    NASA Technical Reports Server (NTRS)

    Nloku, E.; Entekhabi, D.; O'Neill, P.

    2012-01-01

    The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status

  12. Mapping Seasonal Evapotranspiration and Root Zone Soil Moisture using a Hybrid Modeling Approach over Vineyards

    NASA Astrophysics Data System (ADS)

    Geli, H. M. E.

    2015-12-01

    Estimates of actual crop evapotranspiration (ETa) at field scale over the growing season are required for improving agricultural water management, particularly in water limited and drought prone regions. Remote sensing data from multiple platforms such as airborne and Landsat-based sensors can be used to provide these estimates. Combining these data with surface energy balance models can provide ETa estimates at sub- field scale as well as information on vegetation stress and soil moisture conditions. However, the temporal resolution of airborne and Landsat data does not allow for a continuous ETa monitoring over the course of the growing season. This study presents the application of a hybrid ETa modeling approach developed for monitoring daily ETa and root zone available water at high spatial resolutions. The hybrid ETa modeling approach couples a thermal-based energy balance model with a water balance-based scheme using data assimilation. The two source energy balance (TSEB) model is used to estimate instantaneous ETa which can be extrapolated to daily ETa using a water balance model modified to use the reflectance-based basal crop coefficient for interpolating ETa in between airborne and/or Landsat overpass dates. Moreover, since it is a water balance model, the soil moisture profile is also estimated. The hybrid ETa approach is applied over vineyard fields in central California. High resolution airborne and Landsat imagery were used to drive the hybrid model. These images were collected during periods that represented different vine phonological stages in 2013 growing season. Estimates of daily ETa and surface energy balance fluxes will be compared with ground-based eddy covariance tower measurements. Estimates of soil moisture at multiple depths will be compared with measurements.

  13. 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.

  14. 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

  15. Classification and soil moisture determination of agricultural fields

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  16. 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.

  17. 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

  18. Soil moisture sensor calibration for organic soil surface layers

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    A series of soil moisture experiments were conducted in 2003 (SMEX03) to develop enhanced datasets necessary to improve spatiotemporal characterization of soil moisture and to enhance satellite-based retrievals. One component of this research was conducted in South Central Georgia of the US, from June 17th to July 21st (SMEX03 GA). This study analyzes measurements of soil moisture and temperature collected during SMEX03 GA. A network of in situ soil moisture measurement devices, established to provide validation data for the satellite collections and for long-term estimation of soil moisture conditions throughout the region, provided continuous measurements at 19 sites. Additional soil moisture and temperature validation data were collected daily from 49 field sites. These sites represented a diversity of land covers including forest, cotton, peanut, and pasture. Precipitation that occurred prior to June 22nd and from June 29th through July 2nd produced drying conditions from June 23rd to June 28th and gradual wetting from June 29th through July 2nd. Soil moisture in the top 0-1 cm of the soil was found to be more responsive to precipitation and to have greater variability than soil moisture at the 0-3 or 3-6 cm layers. Within different land covers, soil moisture followed the same trends, but varied with land use. Pasture sites were consistently the wettest while row-crop sites were normally the driest. Good agreement was observed between soil moisture measurements collected with the in situ network and the 49 SMEX sites. For the study period, soil moisture across the entire 50 km by 75 km region and five of the six 25 km by 25 km EASE-Grids demonstrated time stable characteristics. Time stability analysis and statistical tests demonstrated the in situ stations had a small dry bias as compared to the SMEX03 GA measurements. These results indicate that the in situ network will be a good resource for long-term calibration of remotely sensed soil moisture and provide

  1. Airborne soil particulates as vehicles for Salmonella contamination of tomatoes.

    PubMed

    Kumar, Govindaraj Dev; Williams, Robert C; Al Qublan, Hamzeh M; Sriranganathan, Nammalwar; Boyer, Renee R; Eifert, Joseph D

    2017-02-21

    The presence of dust is ubiquitous in the produce growing environment and its deposition on edible crops could occur. The potential of wind-distributed soil particulate to serve as a vehicle for S. Newport transfer to tomato blossoms and consequently, to fruits, was explored. Blossoms were challenged with previously autoclaved soil containing S. Newport (9.39log CFU/g) by brushing and airborne transfer. One hundred percent of blossoms brushed with S. Newport-contaminated soil tested positive for presence of the pathogen one week after contact (P<0.0001). Compressed air was used to simulate wind currents and direct soil particulates towards blossoms. Airborne soil particulates resulted in contamination of 29% of the blossoms with S. Newport one week after contact. Biophotonic imaging of blossoms post-contact with bioluminescent S. Newport-contaminated airborne soil particulates revealed transfer of the pathogen on petal, stamen and pedicel structures. Both fruits and calyxes that developed from blossoms contaminated with airborne soil particulates were positive for presence of S. Newport in both fruit (66.6%) and calyx (77.7%). Presence of S. Newport in surface-sterilized fruit and calyx tissue tested indicated internalization of the pathogen. These results show that airborne soil particulates could serve as a vehicle for Salmonella. Hence, Salmonella contaminated dust and soil particulate dispersion could contribute to pathogen contamination of fruit, indicating an omnipresent yet relatively unexplored contamination route.

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

    NASA Astrophysics Data System (ADS)

    Fontes, Adan Fimbres

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

  3. Downscaling soil moisture using multisource data in China

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  4. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. Evaluating Soil Moisture Status Using an e-Nose

    PubMed Central

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Welker, J. E.

    1984-01-01

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

  8. 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.

  9. 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.

  10. A quantitative comparison of soil moisture inversion algorithms

    NASA Technical Reports Server (NTRS)

    Zyl, J. J. van; Kim, Y.

    2001-01-01

    This paper compares the performance of four bare surface radar soil moisture inversion algorithms in the presence of measurement errors. The particular errors considered include calibration errors, system thermal noise, local topography and vegetation cover.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

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

    PubMed

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

    2016-03-15

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

  13. Soil moisture at local scale: Measurements and simulations

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio

    2014-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Ochsner, T.; Venterea, R. T.

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Choi, Minha; Jacobs, Jennifer M.

    2007-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Zaman, B.; McKee, M.

    2009-12-01

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

  19. Compact, Lightweight Dual-Frequency Microstrip Antenna Feed for Future Soil Moisture and Sea Surface Salinity Missions

    NASA Technical Reports Server (NTRS)

    Yueh, Simon; Wilson, William J.; Njoku, Eni; Dinardo, Steve; Hunter, Don; Rahmat-Samii, Yahya; Kona, Keerti S.; Manteghi, Majid

    2006-01-01

    The development of a compact, lightweight, dual-frequency antenna feed for future soil moisture and sea surface salinity (SSS) missions is described. The design is based on the microstrip stacked-patch array (MSPA) to be used to feed a large lightweight deployable rotating mesh antenna for spaceborne L-band (approx.1 GHz) passive and active sensing systems. The design features will also enable applications to airborne soil moisture and salinity remote sensing sensors operating on small aircrafts. This paper describes the design of stacked patch elements and 16-element array configuration. The results from the return loss, antenna pattern measurements and sky tests are also described.

  20. 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.

  1. Predicting root zone soil moisture using surface data

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Hahn, Sebastian; Wagner, Wolfgang

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Pradhan, N. R.

    2015-12-01

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

  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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. 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) ...

  10. 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 ...

  11. Comparing and Combining Surface Soil Moisture Products from AMSR2

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Dijkstra, F. A.; Cheng, W.

    2005-12-01

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

  16. 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 – ...

  17. Soil moisture retrieval from Sentinel-1 satellite data

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  18. Compact, Lightweight Dual- Frequency Microstrip Antenna Feed for Future Soil Moisture and Sea Surface Salinity Missions

    NASA Technical Reports Server (NTRS)

    Yueh, Simon H.; Wilson, William J.; Njoku, Eni; Hunter, Don; Dinardo, Steve; Kona, Keerti S.; Manteghi, Majid; Gies, Dennis; Rahmat-Samii, Yahya

    2004-01-01

    The development of a compact, lightweight, dual frequency antenna feed for future soil moisture and sea surface salinity (SSS) missions is described. The design is based on the microstrip stacked-patch array (MSPA) to be used to feed a large lightweight deployable rotating mesh antenna for spaceborne L-band (approx. 1 GHz) passive and active sensing systems. The design features will also enable applications to airborne sensors operating on small aircrafts. This paper describes the design of stacked patch elements, 16-element array configuration and power-divider beam forming network The test results from the fabrication of stacked patches and power divider were also described.

  19. The effects of soil moisture, surface roughness, and vegetation on L-band emission and backscatter

    NASA Technical Reports Server (NTRS)

    Wang, James R.; Shiue, J. C.; Engman, Edwin T.; Schmugge, Thomas J.; Mo, Tsan

    1987-01-01

    Measurements performed with SIR-B at 1.28 GHz and an airborne multiple-beam push-broom radiometer at 1.4 GHz over agricultural fields near Fresno, California are examined. A theoretical model (Kirchhoff approximation) was used to assess the effects of surface roughness and vegetation (alfalfa and lettuce) with respect to the responses of microwave emission and backscatter to soil-moisture variations. It is found that the surface roughness plays a dominant role compared to the vegetation cover in the microwave backscatter.

  20. 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

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

    PubMed

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

    2013-10-01

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

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

    PubMed

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

    2014-06-01

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

  3. 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

  4. 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.

  5. Assessment of the SMAP Passive Soil Moisture Product

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  6. 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.

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Data from NSF's EarthScope Plate Boundary Observatory (PBO), and similar GPS networks worldwide, can be used to monitor the terrestrial water cycle. GPS satellites transmit L-band microwave signals, which are affected by water at Earth's surface. GPS signals take two paths: (1) the "direct" signal travels from the satellite to the antenna; (2) the "reflected" signal interacts with the Earth's surface before travelling to the antenna. The direct signal is used by geophysicists to measure position of the antenna, while the effects of reflected signals are generally ignored. Recently, our group has developed a technique to retrieve terrestrial water cycle variables from GPS reflections. The sensing footprint is intermediate in scale between in situ and remote sensing observations. Soil moisture, snow depth, and an index of vegetation water content are estimated from data collected at over 400 PBO sites. The products are updated daily and are available online. This presentation provides a description of the soil moisture product. Near-surface soil moisture is estimated at more than 100 sites in the PBO H2O network. At each site, a geodetic-quality GPS antenna records the interference pattern between the direct and ground-reflected GPS signals in signal-to-noise ratio (SNR) interferograms. The ground-reflected GPS signal is altered by changes in the permittivity of the ground surface, which is primarily a function of its water content. Temporal changes in the SNR interferogram, primarily its phase, are indicative of changes in soil moisture. SNR phase data are converted to soil moisture using relationships determined using an electrodynamic model. Soil moisture is not retrieved when there is snow or significant vegetation (> ~1 kg m-2 of vegetation water), as both affect SNR phase. When there is moderate vegetation, a correction is applied to the phase data before conversion to soil moisture. The effect of vegetation on SNR phase and the exact relationship between SNR

  10. Soil moisture - precipitation feedbacks in observations and models (Invited)

    NASA Astrophysics Data System (ADS)

    Taylor, C.

    2013-12-01

    There is considerable uncertainty about the strength, geographical extent, and even the sign of feedbacks between soil moisture and precipitation. Whilst precipitation trivially increases soil moisture, the impact of soil moisture, via surface fluxes, on convective rainfall is far from straight-forward, and likely depends on space and time scale, soil and synoptic conditions, and the nature of the convection itself. In considering how daytime convection responds to surface fluxes, large-scale models based on convective parameterisations may not necessarily provide reliable depictions, particularly given their long-standing inability to reproduce a realistic diurnal cycle of convection. On the other hand, long-term satellite data provide the potential to establish robust relationships between soil moisture and precipitation across the world, notwithstanding some fundamental weaknesses and uncertainties in the datasets. Here, results from regional and global satellite-based analyses are presented. Globally, using 3-hourly precipitation and daily soil moisture datasets, a methodology has been developed to compare the statistics of antecedent soil moisture in the region of localised afternoon rain events (Taylor et al 2012). Specifically the analysis tests whether there are any significant differences in pre-event soil moisture between rainfall maxima and nearby (50-100km) minima. The results reveal a clear signal across a number of semi-arid regions, most notably North Africa, indicating a preference for afternoon rain over drier soil. Analysis by continent and by climatic zone reveals that this signal (locally a negative feedback) is evident in other continents and climatic zones, but is somewhat weaker. This may be linked to the inherent geographical differences across the world, as detection of a feedback requires water-stressed surfaces coincident with frequent active convective initiations. The differences also reflect the quality and utility of the soil moisture

  11. Integrating Microwave and Optical Data for Monitoring Soil Moisture

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Rahmani, Abdolaziz; Golian, Saeed; Brocca, Luca

    2016-06-01

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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  17. 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

  18. 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

  19. Physically plausible prescription of land surface model soil moisture

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. 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.

  1. 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

  2. A physically based hydrological connectivity algorithm for describing spatial patterns of soil moisture in the unsaturated zone

    NASA Astrophysics Data System (ADS)

    Kim, Jonggun; Mohanty, Binayak P.

    2017-02-01

    Hydrologic connectivity has been proposed as an important concept for understanding local processes in the context of catchment hydrology. It can be useful for characterizing the soil moisture variability in complex heterogeneous landscapes. The current land surface models (e.g., Community Land Model, CLM) could not completely account for flow path continuity and connected patterns of subsurface properties in the unsaturated zone. In this study, we developed a physically based hydrologic connectivity algorithm based on dominant physical controls (e.g., topography, soil texture, and vegetation) to better understand the spatially distributed subsurface flow and improve the parameterization of soil hydraulic properties in hydrological modeling. We investigated the effects of mixed physical controls on soil moisture spatial variability and developed hydrologic connectivity using various thresholds. The connectivity was used for identifying the soil moisture variability and applied in a distributed land surface model (CLM) for calibrating soil hydraulic properties and improving model performance for estimating spatially distributed soil moisture. The proposed concept was tested in two watersheds (Little Washita in Oklahoma and Upper South Skunk in Iowa) comparing estimated soil moisture with the airborne remote sensing data (Electronically Scanning Thinned Array Radiometer and Polarimetric Scanning Radiometer). Our finding demonstrated that the spatial variations of soil moisture could be described well using physically based hydrologic connectivity, and the land surface model performance was improved by using the calibrated (distributed) soil hydraulic parameters. In addition, we found that the calibrated soil hydraulic parameters significantly affect model outputs not only on the water cycle but also on surface energy budgets.

  3. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  5. 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.

  6. 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.

  7. 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

  8. Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling

    NASA Astrophysics Data System (ADS)

    Mattia, F.; Satalino, G.; Pauwels, V. R. N.; Loew, A.

    2009-03-01

    The objective of the study is to investigate the potential of retrieving superficial soil moisture content (mv) from multi-temporal L-band synthetic aperture radar (SAR) data and hydrologic modelling. The study focuses on assessing the performances of an L-band SAR retrieval algorithm intended for agricultural areas and for watershed spatial scales (e.g. from 100 to 10 000 km2). The algorithm transforms temporal series of L-band SAR data into soil moisture contents by using a constrained minimization technique integrating a priori information on soil parameters. The rationale of the approach consists of exploiting soil moisture predictions, obtained at coarse spatial resolution (e.g. 15-30 km2) by point scale hydrologic models (or by simplified estimators), as a priori information for the SAR retrieval algorithm that provides soil moisture maps at high spatial resolution (e.g. 0.01 km2). In the present form, the retrieval algorithm applies to cereal fields and has been assessed on simulated and experimental data. The latter were acquired by the airborne E-SAR system during the AgriSAR campaign carried out over the Demmin site (Northern Germany) in 2006. Results indicate that the retrieval algorithm always improves the a priori information on soil moisture content though the improvement may be marginal when the accuracy of prior mv estimates is better than 5%.

  9. Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling

    NASA Astrophysics Data System (ADS)

    Mattia, F.; Satalino, G.; Pauwels, V. R. N.; Loew, A.

    2008-12-01

    The objective of the study is to investigate the potential of retrieving superficial soil moisture content (mv) from multi-temporal L-band synthetic aperture radar (SAR) data and hydrologic modelling. The study focuses on assessing the performances of an L-band SAR retrieval algorithm intended for agricultural areas and for watershed spatial scales (e.g. from 100 to 10 000 km2). The algorithm transforms temporal series of L-band SAR data into soil moisture contents by using a constrained minimization technique integrating a priori information on soil parameters. The rationale of the approach consists of exploiting soil moisture predictions, obtained at coarse spatial resolution (e.g. 15-30 km2) by point scale hydrologic models (or by simplified estimators), as a priori information for the SAR retrieval algorithm that provides soil moisture maps at high spatial resolution (e.g. 0.01 km2). In the present form, the retrieval algorithm applies to cereal fields and has been assessed on simulated and experimental data. The latter were acquired by the airborne E-SAR system during the AgriSAR campaign carried out over the Demmin site (Northern Germany) in 2006. Results indicate that the retrieval algorithm always improves the a priori information on soil moisture content though the improvement may be marginal when the accuracy of prior mv estimates is better than 5%.

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

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Stacke, Tobias

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Tawfik, Ahmed B.

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  13. 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.

  14. BOREAS HYD-6 Ground Gravimetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  18. Soil Moisture Experiments 2004 and 2005 Results and Plans

    NASA Astrophysics Data System (ADS)

    Jackson, T. J.

    2005-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  1. Airborne-Measured Spatially-Averaged Temperature and Moisture Turbulent Structure Parameters Over a Heterogeneous Surface

    NASA Astrophysics Data System (ADS)

    Platis, Andreas; Martinez, Daniel; Bange, Jens

    2014-05-01

    Turbulent structure parameters of temperature and humidity can be derived from scintillometer measurements along horizontal paths of several 100 m to several 10 km. These parameters can be very useful to estimate the vertical turbulent heat fluxes at the surface (applying MOST). However, there are many assumptions required by this method which can be checked using in situ data, e.g. 1) Were CT2 and CQ2 correctly derived from the initial CN2 scintillometer data (structure parameter of density fluctuations or refraction index, respectively)? 2) What is the influence of the surround hetereogeneous surface regarding its footprint and the weighted averaging effect of the scintillometer method 3) Does MOST provide the correct turbulent fluxes from scintillometer data. To check these issues, in situ data from low-level flight measurements are well suited, since research aircraft cover horizontal distances in very short time (Taylor's hypothesis of a frozen turbulence structure can be applyed very likely). From airborne-measured time series the spatial series are calculated and then their structure functions that finally provide the structure parameters. The influence of the heterogeneous surface can be controlled by the definition of certain moving-average window sizes. A very useful instrument for this task are UAVs since they can fly very low and maintain altitude very precisely. However, the data base of such unmanned operations is still quite thin. So in this contribution we want to present turbulence data obtained with the Helipod, a turbulence probe hanging below a manned helicopter. The structure parameters of temperature and moisture, CT2 and CQ2, in the lower convective boundary layer were derived from data measured using the Helipod in 2003. The measurements were carried out during the LITFASS03 campaign over a heterogeneous land surface around the boundary-layer field site of the Lindenberg Meteorological Observatory-Richard-Aßmann-Observatory (MOL) of the

  2. 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).

  3. Sensing soil moisture and vegetation using GNSS-R polarimetric measurement

    NASA Astrophysics Data System (ADS)

    Jia, Yan; Savi, Patrizia

    2017-02-01

    GNSS-Reflectometry is an efficient tool for remote sensing and plays a key role in several applications. The estimation of soil moisture and vegetation in the land field is attracting widespread interest in hydrology, climatology and carbon cycles. In order to investigate the scattering polarization properties from different types of surface environments, an airborne measurement was performed, equipped with a new 4-channel prototype for collecting the direct, reflected left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP) signals. Both the reflected LHCP and RHCP signals were acquired at the same time by a dual polarization antenna. A data averaging procedure was used to reduce the incoherent part of the received power and two reflected signals were normalized by direct signals obtained from each front-end (FE). Then three polarimetric observables were used to analyze vegetation biomass and soil moisture fluctuations. It was concluded that the polarimetric ratio (PR) is sensitive to soil moisture content (SMC) and considerably independent of roughness and vegetation biomass. The trunk component is confirmed to be the most important factor affecting the amplitude of scattering polarizations. Furthermore, the measurement results showed that the PR variation between different elevation angles was affected by roughness and biomass. The PR variation in forests with big biomass shows the least amount of changes when compared to other geographical environments. The results show another possibility of further geophysical parameter evaluations employing polarimetric applications in GNSS-R.

  4. Effects of varying soil moisture contents and vegetation canopies on microwave emissions

    NASA Technical Reports Server (NTRS)

    Burke, H.-H. K.; Schmugge, T. J.

    1982-01-01

    Results of NASA airborne passive microwave scans of bare and vegetated fields for comparison with ground truth tests are discussed and a model for atmospheric scattering of radiation by vegetation is detailed. On-board radiometers obtained data at 21, 2.8, and 1.67 cm during three passes over each of 46 fields, 28 of which were bare and the others having wheat or alfalfa. Ground-based sampling included moisture in five layers down to 15 cm in addition to soil temperature. The relationships among the brightness temperature and soil moisture, as well as the surface roughness and the vegetation canopy were examined. A model was developed for the dielectric coefficient and volume scattering for a vegetation medium. L- to C-band data were found useful for retrieving soil information directly. A surface moisture content of 5-35% yielded an emissivity of 0.9-0.7. The data agreed well with a combined multilayer radiative transfer model with simple roughness correction.

  5. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. Airborne soil organic particles generated by precipitation

    SciTech Connect

    Wang, Bingbing; Harder, Tristan H.; Kelly, Stephen T.; Piens, Dominique S.; China, Swarup; Kovarik, Libor; Keiluweit, Marco; Arey, Bruce W.; Gilles, Mary K.; Laskin, Alexander

    2016-05-02

    Airborne organic particles play a critical role in the Earth’s climate1, public health2, air quality3, and hydrological and carbon cycles4. These particles exist in liquid, amorphous semi-solid, or solid (glassy) phase states depending on their composition and ambient conditions5. However, sources and formation mechanisms for semi- solid and solid organic particles are poorly understood and typically neglected in atmospheric models6. Here we report field evidence for airborne solid organic particles generated by a “raindrop” mechanism7 pertinent to atmosphere – land surface interactions (Fig. 1). We find that after rain events at Southern Great Plains, Oklahoma, USA, submicron solid particles, with a composition consistent with soil organic matter, contributed up to 60% of atmospheric particles in number. Subsequent experiments indicate that airborne soil organic particles are ejected from the surface of soils caused by intensive rains or irrigation. Our observations suggest that formation of these particles may be a widespread phenomenon in ecosystems where soils are exposed to strong, episodic precipitation events such as agricultural systems and grasslands8. Chemical imaging and micro-spectroscopy analysis of their physico-chemical properties suggests that airborne soil organic particles may have important impacts on cloud formation and efficiently absorb solar radiation and hence, are an important type of particles.

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

    NASA Astrophysics Data System (ADS)

    Shinoda, Masato; Nandintsetseg, Banzragch

    2011-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Albertson, J. D.; Montaldo, N.

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

  9. Assimilating AMSR-E data for soil moisture estimation

    NASA Astrophysics Data System (ADS)

    Li, X.; Koike, T.

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

  10. [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.

  11. 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

  12. 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

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

    PubMed

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

    2016-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. 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.

  16. Overview on calibration and validation activities for ESA's Soil Moisture and Ocean Salinity mission

    NASA Astrophysics Data System (ADS)

    Mecklenburg, S.; Bouzinac, C.; Delwart, S.

    2009-04-01

    The Soil Moisture and Ocean Salinity (SMOS) mission is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the current lack of global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations will also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The SMOS launch is foreseen for summer 2009. A major undertaking in any environmental science related satellite mission are the calibration and validation activities. Calibration is an important prerequisite to the performance verification, which demonstrates that the instrument meets its requirements. It is also important for the validation of geophysical parameters, such as soil moisture and sea surface salinity. The validation of the data will be handled through a combination of ESA led activities and national efforts. The SMOS Validation and Retrieval Team (SVRT) comprises the scientific contributions that will be made by the projects selected in response to the SMOS calibration and validation Announcement of Opportunity in 2005 as well as the two level 2 Expert Support Laboratories being involved in the development of the soil moisture and sea surface salinity data products. For the validation of the soil moisture data products ESA's activities will focus on two main sites, the Valencia Anchor Station, located in the East of Spain, and the Upper Danube Catchment, located in the South of Germany. In preparation to the SMOS commissioning phase, airborne rehearsal campaigns were conducted in spring 2008 over both aforementioned key sites. These will be coupled with a SMOS matchup generation exercise to verify that the methodology proposed actually meets the foreseen

  17. Overview on calibration and validation activities for ESA's Soil Moisture and Ocean Salinity Mission

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Susanne; Bouzinac, Catherine; Delwart, Steven

    2010-05-01

    The Soil Moisture and Ocean Salinity (SMOS) mission, launched on 2 November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the current lack of global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations will also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. A major undertaking in any environmental science related satellite mission are the calibration and validation activities. Calibration is an important prerequisite to the performance verification, which demonstrates that the instrument meets its requirements. It is also important for the validation of geophysical parameters, such as soil moisture and sea surface salinity. The validation of the data will be handled through a combination of ESA led activities and national efforts. The SMOS Validation and Retrieval Team (SVRT) comprises the scientific contributions that will be made by the projects selected in response to the SMOS calibration and validation Announcement of Opportunity in 2005 as well as the two level 2 Expert Support Laboratories being involved in the development of the soil moisture and sea surface salinity data products. For the validation of the soil moisture data products ESA's activities will focus on two main sites, the Valencia Anchor Station, located in the East of Spain, and the Upper Danube Catchment, located in the South of Germany. In preparation to the SMOS commissioning phase, airborne rehearsal campaigns were conducted in spring 2008 over both aforementioned key sites and will be repeated, in collaboration with the French Space Agency CNES, in spring 2010. These will be coupled with a SMOS matchup generation

  18. 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.

  19. AirMOSS P-Band Radar Retrieval of Subcanopy Soil Moisture Profile

    NASA Astrophysics Data System (ADS)

    Tabatabaeenejad, A.; Burgin, M. S.; Duan, X.; Moghaddam, M.

    2013-12-01

    Knowledge of soil moisture, as a key variable of the Earth system, plays an important role in our under-standing of the global water, energy, and carbon cycles. The importance of such knowledge has led NASA to fund missions such as Soil Moisture Active and Passive (SMAP) and Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS). The AirMOSS mission seeks to improve the estimates of the North American Net Ecosystem Exchange (NEE) by providing high-resolution observations of the root zone soil moisture (RZSM) over regions representative of the major North American biomes. AirMOSS flies a P-band SAR to penetrate vegetation and into the root zone to provide estimates of RZSM. The flights cover areas containing flux tower sites in regions from the boreal forests in Saskatchewan, Canada, to the tropical forests in La Selva, Costa Rica. The radar snapshots are used to generate estimates of RZSM via inversion of a scattering model of vegetation overlying soils with variable moisture profiles. These retrievals will be used to generate a time record of RZSM, which will be integrated with an ecosystem demography model in order to estimate the respiration and photosynthesis carbon fluxes. The aim of this work is the retrieval of the moisture profile over AirMOSS sites using the collected P-band radar data. We have integrated layered-soil scattering models into a forest scattering model; for the backscattering from ground and for the trunk-ground double-bounce mechanism, we have used a layered small perturbation method and a coherent scattering model of layered soil, respectively. To estimate the soil moisture profile, we represent it as a second-order polynomial in the form of az2 + bz + c, where z is the depth and a, b, and c are the coefficients to be retrieved from radar measurements. When retrieved, these coefficients give us the soil moisture up to a prescribed depth of validity. To estimate the unknown coefficients of the polynomial, we use simulated

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

    NASA Technical Reports Server (NTRS)

    King, C.

    1973-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  3. The soil moisture active passive (SMAP) mission and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) satellite will be launched by the National Aeronautics and Space Administration in October 2014. This satellite is the culmination of basic research and applications development over the past thirty years. During most of this period, research and development o...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. WindSat Global Soil Moisture Retrieval and Validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A physically based six-channel land algorithm is developed to simultaneously retrieve the global soil moisture, vegetation water content and land surface temperature. The algorithm is based on a maximum-likelihood estimation and uses WindSat passive microwave data at 10, 18.7 and 37 GHz. The global ...

  6. SMAP Validation and Accuracy Assessment of Soil Moisture Products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Introduction: The Soil Moisture Active Passive (SMAP) mission was launched in January, 2015 and will begin its calibration and validation (Cal/Val) phase in May, 2015. This will begin with a focus on instrument measurements, brightness temperature and backscatter, and evolve to the geophysical produ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. A comparison of soil moisture sensors for space flight applications

    NASA Technical Reports Server (NTRS)

    Norikane, J. H.; Prenger, J. J.; Rouzan-Wheeldon, D. T.; Levine, H. G.

    2005-01-01

    Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

    Wilheit, T. T.

    1978-01-01

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

  11. Overview of the NASA soil moisture active/passive mission

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active Passive (SMAP) Mission is currently in design Phase C and scheduled for launch in October 2014. Its mission concept is based on combined L-band radar and radiometry measurements obtained from a shared, rotating 6-meter antennae. These measurements will be used to retrie...

  12. The Soil Moisture Active Passive (SMAP) applications activity

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP mea...

  13. Uncertainties of soil moisture in historical simulations and future projections

    NASA Astrophysics Data System (ADS)

    Cheng, Shanjun; Huang, Jianping; Ji, Fei; Lin, Lei

    2017-02-01

    Uncertainties of soil moisture in historical simulations (1920-2005) and future projections (2006-2080) were investigated by using the outputs from the Coupled Model Intercomparison Project Phase 5 and Community Earth System Model. The results showed that soil moisture climatology varies greatly among models despite the good agreement between the ensemble mean of simulated soil moisture and the Global Land Data Assimilation System data. The uncertainties of initial conditions and model structure showed similar spatial patterns and magnitudes, with high uncertainties in dry regions and low uncertainties in wet regions. In addition, the long-term variability of model structure uncertainty rapidly decreased before 1980 and increased thereafter, but the uncertainty in initial conditions showed an upward trend over the entire time span. The model structure and initial conditions can cause uncertainties at all time scales. Despite these large uncertainties, almost all of the simulations showed significant decreasing linear trends in soil moisture for the 21st century, especially in the Mediterranean region, northeast and southwest South America, southern Africa, and southwestern USA.

  14. Introduction to Soil Moisture Experiments 2004 (SMEX04)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Land surface antecedent boundary conditions may control the onset and intensity of the summer monsoon rainfall in the southwestern U.S. and northern Mexico. The influence of the land surface is relayed through surface evaporation and associated surface cooling (dependent on soil moisture), terrain, ...

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  16. Why different passive microwave algorithms give different soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several algorithms have been used to retrieve surface soil moisture from brightness temperature observations provided by low frequency microwave satellite sensors such as the Advanced Microwave Scanning Radiometer on NASA EOS satellite Aqua (AMSR-E). Most of these algorithms have originated from the...

  17. Toward Global Soil Moisture Estimation By Satellite Precipitation Radars

    NASA Astrophysics Data System (ADS)

    Seto, S.; Oki, T.; Musiake, K.

    A soil moisture estimation algorithm using Tropical Rainfall Measuring Mission (TRMM) / Precipitation Radar (PR) is developed to be applied at global scale. In our algorithm, the backscattering coefficients at land surface (denoted as 0) observed by PR is used. As 0 is attenuated by strong rainfall, the data observed during rainfall is not included in our calculation (the percentage if observation is done while it is raining is as small as 5 percent in global average). Soil moisture estimation algorithms by active microwave sensors have been proposed by other researches, though, they are mainly applied to Synthetic Aperture Radars (SAR). TRMM/PR has poor spatial resolution compared with SAR, but the observation frequency (temporal resolution) is as high as passive microwave sensors. On behalf of such high observation frequency, our algorithm can be applied at daily scale which is suitable to analyze soil mois- ture variation. Though TRMM/PR observes by different incident angles from 0 to 18 degree, our algorithm is basically designed for 0(12) (0 observed by 12 degree). Assuming that observed 0 is composed of s (the backscattering at bare soil) and v 0 0 (the backscattering at vegetation layer), it is shown that the sensitivity of 0 to soil moisture is higher by smaller incident angle and the sensitivity of 0 to vegetation cover ratio is lower when observed by 12 degree. If the temporal change of vegetation is not significant, 0 observed by among 3 to 18 degree is well correlated with 0(12). In such case, 0 is converted to 0(12) by linear regression to increase the number of sample per day. The algorithm is firstly applied to Oklahoma in central United States and validated using in-situ soil moisture data. In Oklahoma, the effect of vegetation growth is not significant, then the soil moisture estimates well correspond with in-situ data. Contrastedly, in the Sahel of Africa which shows strong seasonal vegetation cy- cle, 0 obseved by only around 12 degree can be

  18. Influence of soil moisture on C incorporation and preservation in soil

    NASA Astrophysics Data System (ADS)

    Majumder, B.; Gocke, M.; Kuzyakov, Y.; Wiesenberg, G.

    2012-04-01

    Sequestration of atmospheric C into soil is only mediated by plant. Plant leaf can use atmospheric C by photosynthesis, thereafter this C is translocated into soil through plant root exudates and root fragments. With changing climatic conditions like decreasing rainfall especially during growing seasons of plants, water availability is thought to raise as limiting factor for plant growth and thus sequestration of C. However, little is known about the pathway of translocation of C from atmosphere to soil at different moisture regimes. To quantify atmospheric C incorporation in plant and its preservation into soil via the rhizosphere, a laboratory experiment on Juncus effusus, which is adapted to very moist conditions, was conducted. The plants were kept at levels of 70 and 100% soil moisture (relative to field capacity, which was adjusted daily to a difference of 30% between high and low moisture levels) for several months. C uptake by plants and translocation towards soil was traced 3, 7, 14 and 21 days after 14CO2 pulse labeling in bulk carbon and lipid fractions of plants and soils. J. effusus produced higher leaf and root biomass at 100% moisture as compared to 70% soil moisture. Consequently, rhizosphere-dry mass increased with increasing root biomass. Considering whole pot (plant & soil together), 14C proportion of shoots decreased and that of roots increased successively from 3 to 21 days after labelling due to translocation of C from shoots to roots. 14C content of rhizosphere was observed to be highest at day 14 after labeling at 100% soil moisture, implied an exceptional increase of root exudates, whereas root exudation was less in 70% soil moisture. As a result of C translocation from roots to soil, 14C content of soil increased until day 7 after labeling. Thereafter, soil 14C content decreased more sharply with time at 100% soil moisture than at 70% moisture. Moreover, to gain quantitative knowledge of 14C preservation, a comparatively recalcitrant C

  19. [Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

    PubMed

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

    2015-08-01

    Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

  20. Radon diffusion coefficients in soils of varying moisture content

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  1. Preliminary calibration of GPS signals and its effects on soil moisture estimation

    NASA Astrophysics Data System (ADS)

    Wan, Wei; Li, Huang; Chen, Xiuwan; Luo, Peng; Wan, Jiahuan

    2013-04-01

    In recent years, Global Navigation Satellite Systems Reflectometry (GNSS-R) is developed to estimate soil moisture content (SMC) as a new remote sensing tool. Signal error of Global Positioning System (GPS) bistatic radar is an important factor that affects the accuracy of SMC estimation. In this paper, two methods of GPS signal calibration involving both the direct and reflected signals are introduced, and a detailed explanation of the theoretical basis for such methods is given. An improved SMC estimation model utilizing calibrated GPS L-band signals is proposed, and the estimation accuracy is validated using the airborne GPS data from the Soil Moisture Experiment in 2002 (SMEX02). We choose 21 sites with soybean and corn in the Walnut Creek region of the US for validation. The sites are divided into three categories according to their vegetation cover: bare soil, mid-vegetation cover (Mid-Veg), and high-vegetation cover (High-Veg). The accuracy of SMC estimation is 11.17% for bare soil and 8.12% for Mid-Veg sites, much better than that of the traditional model. For High-Veg sites, the effect of signal attenuation due to vegetation cover is preliminarily taken into consideration and a linear model related to Normalized Difference Vegetation Indices (NDVI) is adopted to obtain a factor for rectifying the "over-calibration", and the error for High-Veg sites is finally reduced to 3.81%.

  2. Modeling Soil Moisture in the Mojave Desert

    USGS Publications Warehouse

    Miller, David M.; Hughson, Debra; Schmidt, Kevin M.

    2008-01-01

    The Mojave Desert is an arid region of southeastern California and parts of Nevada, Arizona, and Utah; the desert occupies more than 25,000 square miles (fig. 1). Ranging from below sea level to over 5,000 feet (1,524 m) in elevation, the Mojave Desert is considered a ?high desert.? On the west and southwest it is bounded by the Sierra Nevada, the San Gabriel, and the San Bernardino Mountains. These imposing mountains intercept moisture traveling inland from the Pacific Ocean, producing arid conditions characterized by extreme fluctuations in daily temperatures, strong seasonal winds, and an average annual precipitation of less than six inches. The Mojave Desert lies farther south and at a lower elevation than the cooler Great Basin Desert and grades southward into the even lower and hotter Sonoran Desert.

  3. 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.

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

    PubMed

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

    2011-11-01

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

  5. 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.

  6. The International Soil Moisture Network - A data hosting facility for in situ soil moisture measurements in support of SMOS cal/val

    NASA Astrophysics Data System (ADS)

    Dorigo, Wouter; Hahn, Sebastian; Hohensinn, Roland; Paulik, Christoph; Wagner, Wolfgang; Drusch, Matthias; van Oevelen, Peter

    2010-05-01

    In situ soil moisture observations are crucial for validating SMOS and other satellite based soil moisture products. In order to support valid conclusions about the accuracy of such products the in situ soil moisture observations used need to be available for many locations worldwide and have to be intercomparable. So far, the latter requirement is usually not met as the different locally and regionally operating networks apply neither a standard measurement technique nor a standard protocol. The need for international cooperation in constructing centralized and homogenized global soil moisture data sets has been recognized by the international community. To support the validation of satellite soil moisture products the International Soil Moisture Working Group (ISMWG) has suggested constructing a standardized global data base of in-situ soil moisture measurements. Further, the creation of multi-source soil moisture datasets, including in situ observations, was included in the GEO 2009-2011 Work Plan under sub-task WA-08-01a led by GEWEX (Global Energy and Water Cycle Experiment) and ESA (European Space Agency). As fruit of this initiative and in support of SMOS calibration and validation activities, ESA decided to support the development of the International Soil Moisture Network. The International Soil Moisture Network is a web based data hosting facility for collecting and redistributing in situ soil moisture measurements from existing soil moisture networks. Incoming data are carefully checked for their quality and homogenized before being stored in the database. A web interface allows the user to easily query and download the data. Special care has been taken to make downloads compliant with international data and metadata standards such as GEWEX CEOP, ISO 19115, and INPIRE of the European Commission. This presentation provides insight in the design considerations, implementation, functionalities and outputs of the data hosting facility. The International Soil

  7. Seasonal soil moisture patterns in contrasting habitats in the Willamette Valley, Oregon

    EPA Science Inventory

    Changing seasonal soil moisture regimes caused by global warming may alter plant community composition in sensitive habitats such as wetlands and oak savannas. To evaluate such changes, an understanding of typical seasonal soil moisture regimes is necessary. The primary objective...

  8. Ground truth report 1975 Phoenix microwave experiment. [Joint Soil Moisture Experiment

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1975-01-01

    Direct measurements of soil moisture obtained in conjunction with aircraft data flights near Phoenix, Arizona in March, 1975 are summarized. The data were collected for the Joint Soil Moisture Experiment.

  9. Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

    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; Shi, J. C.

    2011-01-01

    The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

  10. Dielectric properties of soils as a function of moisture content

    NASA Technical Reports Server (NTRS)

    Cihlar, J.; Ulaby, F. T.

    1974-01-01

    Soil dielectric constant measurements are reviewed and the dependence of the dielectric constant on various soil parameters is determined. Moisture content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as soil dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric soil water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three soil textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and soil texture.

  11. Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.

    PubMed

    Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören

    2014-01-01

    Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics.

  12. Comparison of Multiple Satellite Soil Moisture Products Using In-Situ Soil Moisture Observations Over the Continental United States

    NASA Astrophysics Data System (ADS)

    Chavez, N.; Galvan, J., III; McRoberts, D. B.; Quiring, S. M.; Ford, T.

    2015-12-01

    We evaluate the skill of multiple satellite-derived soil moisture products using in-situ soil moisture observations from over 50 long-record stations in the continental United States. The satellite products compared include AMSR-E, ASCAT, SMOS, TMI, ESA CCI, and SMAP. Daily volumetric water content and percentiles of volumetric water content from each satellite product is compared with the observations from the corresponding station. We evaluate the similarity between the satellite and in-situ products with regard to the climate and biome conditions of the area as well as the representativeness of the in-situ station for the satellite footprint. We find moderate-to-strong correspondence between all satellite products and in-situ soil moisture observations. Differences between the satellite and observation datasets are attributed to varying land cover conditions, snow cover, and the spatial mismatch of the point observation with the satellite product grid cell. In general, our results suggest that the satellite products evaluated can accurately capture temporal variability of soil moisture near the surface, but do show systematic offsets at several stations across the study region.

  13. Remote Satellite Soil Moisture Mapping for the ERDC Countermine Simulation Test Bed

    DTIC Science & Technology

    2010-03-01

    river beds, deserts, riparian areas and forests; 2. Development of a reliable downscaling procedure for Landsat soil moisture maps (30 m) to Quickbird...on roads and in river beds, deserts, riparian areas and forests; 2. Development of a reliable downscaling procedure for Landsat soil moisture maps... river the QuickBird soil moisture seems to be too low (Figures 7, 8, 9, 10, 11, 12) while on the asphalt road the soil moisture is estimated too high (13

  14. The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

    PubMed

    Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

    2017-05-01

    Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr(-1) , but also highlight regions of uncertainty

  15. Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

    NASA Astrophysics Data System (ADS)

    Yatheendradas, S.; Vivoni, E.

    2007-12-01

    A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

  16. Early results of the Soil Moisture Active Passive Validation Experiment (SMAPVEX15)

    NASA Astrophysics Data System (ADS)

    Cosh, M. H.; Jackson, T. J.; Colliander, A.; Goodrich, D. C.; Holifield Collins, C.; McKee, L.; Kim, S.; Yueh, S. H.

    2015-12-01

    In August of 2015, the Soil Moisture Active Passive Validation Experiment (SMAPVEX15) was conducted to provide a high resolution soil moisture dataset for the calibration/validation of the Soil Moisture Active Passive Mission (SMAP). The Upper San Pedro River Basin and the USDA-ARS Walnut Gulch LTAR Watershed provides the infrastructure for the experiment with its extensive soil moisture and soil temperature network. A total of seven aircraft flights are planned for the Passive Active L-Band Scanning instrument (PALS) to provide a high resolution soil moisture map for a variety of soil moisture conditions across the domain. Extensive surface roughness, vegetation and soil rock fraction mapping was conducted to provide a ground truth estimate of the many ancillary datasets used in the SMAP soil moisture algorithms. A review of the methodologies employed in the experiment, as well as initial findings will be discussed.

  17. 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

  18. Characterization of the spatial-temporal variability of soil moisture by remote sensing

    NASA Astrophysics Data System (ADS)

    Kim, Gwangseob

    1999-11-01

    Characterization of spatial and temporal variabilities of soil moisture, spectral formalism of soil moisture estimation and sampling error simulation study were conducted to understand soil moisture field and to establish global monitoring strategy. Linear relation between soil moisture and porosity is dramatically improved with increasing pixel size although linear relation between soil moisture and soil properties is very weak. The relation between field variance and aggregation area follows power law between log scale 4 and 7. Scaling analysis indicates that the power law exponent becomes smaller with increasing area, which allows the assumption that the soil moisture field is stationary in large area. Variogram analysis shows that the stationarity of soil moisture field is changed by meteorological condition. Spectrum of soil moisture field shows there is no dominant spatial frequency. Two-dimensional correlogram of the soil moisture and brightness temperature fields shows strong anisotropy. Correlation structure of the soil moisture field is changed by drying or rainfall process. Average correlation length of the soil moisture consists of Long'-14km and Lat'-36km. Autoregressive exogenous model (ARX) with lag-1 correlation coefficient 0.9 is suggested for temporal soil moisture model. The Monsoon '90 soil moisture data indicate that diurnal cycle causes 1--4% sampling error. (5 a.m.--9a.m.: 1%, 1 p.m.--3 p.m.: 4%). North-Nakamoto formalism (1989) was used to compute the sampling error for the soil moisture field estimation. The space-time discrete design filter was evaluated and it is applicable to all kinds of sampling design. Missing temporal measurements in SGP '97 soil moisture field make it difficult to estimate the spectra directly from observed record. The soil moisture spectrum was estimated using rainfall and soil moisture models tuned parameter to SGP '97 data. Estimated sampling error of daily electronically scanned thinned army radiometer (ESTAR

  19. 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.

  20. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    EPA Science Inventory

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  1. Online Vegetation Parameter Estimation in Passive Microwave Regime for Soil Moisture Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing observations in the passive microwave regime can be used to estimate surface soil moisture over land at global and regional scales. Soil moisture is important to applications such as weather forecasting, climate and agriculture. One approach to estimating soil moisture from remote sen...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Evaluation of SMOS soil moisture products over the CanEx-SM10 area

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

  4. Potential of bias correction for downscaling passive microwave and soil moisture data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

  5. The SMAP In Situ Soil Moisture Sensor Testbed: Comparing in situ sensors for satellite validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One of the most valuable tools in validating satellite based soil moisture estimates, such as those from the Soil Moisture Active Passive (SMAP) mission are large scale in situ networks. Global validation involves networks operated by many different organizations. Existing in situ soil moisture netw...

  6. Evaluation of the SMAP radiometer lever 2 pre-launch soil moisture algorithms using SMOS data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objectives of the upcoming SMAP (Soil Moisture Active Passive) satellite mission include global measurements of soil moisture at 40 km, 10 km and 3 km resolutions with a 3-day revisit time at an accuracy of 0.04 m3/m3. The 40 km resolution soil moisture product is based primarily on the passiv...

  7. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Precipitation estimation using L-Band and C-Band soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Early results of the Soil Moisture Active Passive Validation Experiment (SMAPVEX15)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In August of 2015, the Soil Moisture Active Passive Validation Experiment (SMAPVEX15) was conducted to provide a high resolution soil moisture dataset for the calibration/validation of the Soil Moisture Active Passive Mission (SMAP). The Upper San Pedro River Basin and the USDA-ARS Walnut Gulch LTAR...

  12. SMOS soil moisture validation with U.S. in situ newworks

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Canadian experiment for soil moisture in 2010 (CanEx-SM10): Overview and preliminary results

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to the Soil Moisture and Ocean Salinity (SMOS) mission validation and the pre-launch assessment of the proposed Soil Moisture and ...

  14. Upscaling of soil moisture measurements in NW Italy

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  15. Effect of management and soil moisture regimes on wetland soils total carbon and nitrogen in Tanzania

    NASA Astrophysics Data System (ADS)

    Kamiri, Hellen; Kreye, Christine; Becker, Mathias

    2013-04-01

    Wetland soils play an important role as storage compartments for water, carbon and nutrients. These soils implies various conditions, depending on the water regimes that affect several important microbial and physical-chemical processes which in turn influence the transformation of organic and inorganic components of nitrogen, carbon, soil acidity and other nutrients. Particularly, soil carbon and nitrogen play an important role in determining the productivity of a soil whereas management practices could determine the rate and magnitude of nutrient turnover. A study was carried out in a floodplain wetland planted with rice in North-west Tanzania- East Africa to determine the effects of different management practices and soil water regimes on paddy soil organic carbon and nitrogen. Four management treatments were compared: (i) control (non weeded plots); (ii) weeded plots; (iii) N fertilized plots, and (iv) non-cropped (non weeded plots). Two soil moisture regimes included soil under field capacity (rainfed conditions) and continuous water logging compared side-by-side. Soil were sampled at the start and end of the rice cropping seasons from the two fields differentiated by moisture regimes during the wet season 2012. The soils differed in the total organic carbon and nitrogen between the treatments. Soil management including weeding and fertilization is seen to affect soil carbon and nitrogen regardless of the soil moisture conditions. Particularly, the padddy soils were higher in the total organic carbon under continuous water logged field. These findings are preliminary and a more complete understanding of the relationships between management and soil moisture on the temporal changes of soil properties is required before making informed decisions on future wetland soil carbon and nitrogen dynamics. Keywords: Management, nitrogen, paddy soil, total carbon, Tanzania,

  16. A method to downscale soil moisture to fine resolutions using topographic, vegetation, and soil data

    NASA Astrophysics Data System (ADS)

    Ranney, Kayla J.; Niemann, Jeffrey D.; Lehman, Brandon M.; Green, Timothy R.; Jones, Andrew S.

    2015-02-01

    Soil moisture can be estimated over large regions with spatial resolutions greater than 500 m, but many applications require finer resolutions (10-100 m). Several methods use topographic data to downscale, but vegetation and soil patterns can also be important. In this paper, a downscaling model that uses fine-resolution topographic, vegetation, and soil data is presented. The method is tested at the Cache la Poudre catchment where detailed vegetation and soil data were collected. Additional testing is performed at the Tarrawarra and Nerrigundah catchments where limited soil data are available. Downscaled soil moisture patterns at Cache la Poudre improve when vegetation and soil data are used, and model performance is similar to an EOF method. Using interpolated soil data at Tarrawarra and Nerrigundah decreases model performance and results in worse performance than an EOF method, suggesting that soil data needs greater spatial detail and accuracy to be useful for downscaling.

  17. The 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-tier projects recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is in formulation phase and it is scheduled for launch in 2014. The SMAP mission is designed to produce high-resolution and accurate global mapping of soil moisture and its freeze/thaw state using an instrument architecture that incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer. The simultaneous radar and radiometer measurements will be combined to derive global soil moisture mapping at 9 [km] resolution with a 2 to 3 days revisit and 0.04 [cm3 cm-3] (1 sigma) soil water content accuracy. The radar measurements also allow the binary detection of surface freeze/thaw state. The project science goals address in water, energy and carbon cycle science as well as provide improved capabilities in natural hazards applications.

  18. Remote sensing of soil moisture using Loran-C signals

    NASA Astrophysics Data System (ADS)

    Feng, Yi; Astin, Ivan

    2014-05-01

    Accurate knowledge of wide-area soil moisture is essential for atmospheric and hydrological studies. In recent years, efforts worldwide have focused on the use of microwave imaging sensors on-board satellites such as SMOS to derive this information from the interpreted brightness temperature of the Earth. However, the frequency of data retrieved this way is often limited by the revisit period of the remote sensing platforms. In this study, we explore the feasibility of using 100 kHz Loran-C radio navigation signals, transmitted continuously from ground-based stations, for the estimation of soil moisture on wide-areas. This technique is based on the measured time delay of the surface wave component, which is influenced by land surface and atmospheric dynamics. It was found that variations in the propagation time of Loran-C surface waves may be representative of short-term ground electrical conductivity changes along the propagation path, which are believed to have a direct link with soil properties. Using Loran-C time delays measured at the University of Bath, it has been shown that the proposed method, combined with model data, can be used for the remote sensing of soil moisture where improved temporal sampling is required. This allows for further validation and improvement.

  19. Emission and distribution of fumigants as affected by soil moistures in three different textured soils.

    PubMed

    Qin, Ruijun; Gao, Suduan; Ajwa, Husein

    2013-01-01

    Water application is a low-cost strategy to control emissions of soil fumigant to meet the requirements of the stringent environmental regulations and it is applicable for a wide range of commodity groups. Although it is known that an increase in soil moisture reduces emissions, the range of soil moisture for minimizing emissions without risking pest control, is not well defined for various types of soils. With two column studies, we determined the effect of different soil moisture levels on emission and distribution of 1,3-dichloropropene and chloropicrin in three different textured soils. Results on sandy loam and loam soils showed that by increasing soil moisture from 30% to 100% of field capacity (FC), peak fluxes were lowered by 77-88% and their occurrences were delayed 5-15 h, and cumulative emissions were reduced 24-49%. For the sandy soil, neither peak fluxes nor the cumulative emissions were significantly different when soil moisture increased from 30% to 100% FC. Compared to the drier soils, the wetter soils retained consistently higher fumigant concentrations in the gas-phase, suggesting efficacy may not be impacted in these soils. The air-filled porosity positively and linearly correlated with the cumulative emission loss across all soil types indicating that it may serve as a good indicator for estimating emissions. These laboratory findings can be further tested under field conditions to conclude what irrigation regime should be used for increasing soil water content before fumigant application that can achieve maximum emission reduction and uniform fumigant distribution with high exposure index values.

  20. Microstrip Antenna for Remote Sensing of Soil Moisture and Sea Surface Salinity

    NASA Technical Reports Server (NTRS)

    Ramhat-Samii, Yahya; Kona, Keerti; Manteghi, Majid; Dinardo, Steven; Hunter, Don; Njoku, Eni; Wilson, Wiliam; Yueh, Simon

    2009-01-01

    This compact, lightweight, dual-frequency antenna feed developed for future soil moisture and sea surface salinity (SSS) missions can benefit future soil and ocean studies by lowering mass, volume, and cost of the antenna system. It also allows for airborne soil moisture and salinity remote sensors operating on small aircraft. While microstrip antenna technology has been developed for radio communications, it has yet to be applied to combined radar and radiometer for Earth remote sensing. The antenna feed provides a key instrument element enabling high-resolution radiometric observations with large, deployable antennas. The design is based on the microstrip stacked-patch array (MSPA) used to feed a large, lightweight, deployable, rotating mesh antenna for spaceborne L-band (approximately equal to 1 GHz) passive and active sensing systems. The array consists of stacked patches to provide dual-frequency capability and suitable radiation patterns. The stacked-patch microstrip element was designed to cover the required L-band center frequencies at 1.26 GHz (lower patch) and 1.413 GHz (upper patch), with dual-linear polarization capabilities. The dimension of patches produces the required frequencies. To achieve excellent polarization isolation and control of antenna sidelobes for the MSPA, the orientation of each stacked-patch element within the array is optimized to reduce the cross-polarization. A specialized feed-distribution network was designed to achieve the required excitation amplitude and phase for each stacked-patch element.

  1. Soil moisture effects during bioventing in fuel-contaminated arid soils

    SciTech Connect

    Zwick, T.C.; Leeson, A.; Hinchee, R.E.; Hoeppel, R.E.; Bowling, L.

    1995-12-31

    This study evaluated the effects of soil moisture addition on microbial activity during bioventing of dry, sandy soils at the Marine Corps Air Ground Combat Center (MCAGCC), Twentynine Palms, California. Soils at the site have been contaminated to a depth of approximately 80 ft (24 m) with gasoline, JP-5 jet fuel, and diesel fuel. Based on the low soil moisture measured at the site (2 to 3% by weight), it was determined that soil moisture may be limiting biodegradation. To evaluate the effect that moisture addition had on microbial activity under field conditions, a subsurface drip irrigation system was installed above the fuel hydrocarbon plume. Irrigation water was obtained from two monitoring wells on the site, where groundwater was approximately 192 ft (59 m) below ground surface. Advancement of the wetting front was monitored. In situ respiration rates increased significantly after moisture addition. The results of this study provide evidence for the potential applicability of moisture addition in conjunction with bioventing for site remediation in arid environments. Further work is planned to investigate optimization of moisture addition.

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

    USGS Publications Warehouse

    Zhang, Li; Ji, Lei; Wylie, Bruce 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.

  3. A Proposed Extension to the Soil Moisture and Ocean Salinity Level 2 Algorithm for Mixed Forest and Moderate Vegetation Pixels

    NASA Technical Reports Server (NTRS)

    Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward

    2011-01-01

    The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  5. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  6. The influence of soil moisture on magnetic susceptibility measurements

    NASA Astrophysics Data System (ADS)

    Maier, G.; Scholger, R.; Schön, J.

    2006-06-01

    An important methodological question for magnetic susceptibility measurements is if a variation of the soil conductivity, as a result of a change in soil moisture, influences the measured susceptibility values. An answer to this question is essential because an accurate magnetic susceptibility mapping requires a grid of comparable magnetic susceptibility values, which indicate the magnetic iron-mineral contents of the soils. Therefore, in the framework of the MAGPROX project (EU-Project EVK2-CT-1999-00019), the study aims at investigating the influence of soil moisture and the possible correlation between magnetic susceptibility and electric conductivity. This approach was realised by model experiments in the laboratory and a field monitoring experiment, which was performed in an analogical manner as the model. For the laboratory experiment, a plastic tub with a water in- and outflow system and installed lines of electrodes was used. The measurements were carried out with layers of different magnetic material within the experimental sand formation under varying water saturation conditions. For the field experiment, which was carried out from July to December 2003, two test sites were selected. The magnetic susceptibility was measured by means of the recently developed vertical soil profile kappa meter SM400 and a commonly used Bartington MS2D probe. The electric resistivity was recorded using a 4-point light system (laboratory) and a ground conductivity meter EM38 (field). The knowledge of the resistivity of the sand formation enabled an estimation of porosity and water saturation in consideration of the Archie equations. The laboratory experiment results showed a very slight variation of measured magnetic susceptibility under different degrees of moisture, indicating mainly the influence from the diamagnetic contribution of the water volume. A measurement error in connection with the measurement method, for example caused by an interfering effect of soil

  7. Active and passive microwave measurements of soil moisture in FIFE

    NASA Technical Reports Server (NTRS)

    Wang, J. R.; Gogineni, S. P.; Ampe, J.

    1992-01-01

    During the intensive field campaigns of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in May-October of 1987, several nearly simultaneous measurements were made with low-altitude flights of the L-band radiometer and C- and X-band scatterometers over two transects in the Konza Prairie Natural Research Area, some 8 km south of Manhattan, Kansas. These measurements showed that although the scatterometers were sensitive to soil moisture variations in most regions under the flight path, the L-band radiometer lost most of its sensitivity in regions unburned for many years. The correlation coefficient derived from the regression between the radar backscattering coefficient and the soil moisture was found to improve with the increase in antenna incidence angle. This is attributed to a steeper falloff of the backscattering coefficient as a function of local incidence at angles near nadir than at angles greater than 30 deg.

  8. A nonlinear coupled soil moisture-vegetation model

    NASA Astrophysics Data System (ADS)

    Liu, Shikuo; Liu, Shida; Fu, Zuntao; Sun, Lan

    2005-06-01

    Based on the physical analysis that the soil moisture and vegetation depend mainly on the precipitation and evaporation as well as the growth, decay and consumption of vegetation a nonlinear dynamic coupled system of soil moisture-vegetation is established. Using this model, the stabilities of the steady states of vegetation are analyzed. This paper focuses on the research of the vegetation catastrophe point which represents the transition between aridness and wetness to a great extent. It is shown that the catastrophe point of steady states of vegetation depends mainly on the rainfall P and saturation value v0, which is selected to balance the growth and decay of vegetation. In addition, when the consumption of vegetation remains constant, the analytic solution of the vegetation equation is obtained.

  9. Spacecraft Environmental Testing SMAP (Soil, Moisture, Active, Passive)

    NASA Technical Reports Server (NTRS)

    Fields, Keith

    2014-01-01

    Testing a complete full up spacecraft to verify it will survive the environment, in which it will be exposed to during its mission, is a formidable task in itself. However, the ''test like you fly'' philosophy sometimes gets compromised because of cost, design and or time. This paper describes the thermal-vacuum and mass properties testing of the Soil Moisture Active Passive (SMAP) earth orbiting satellite. SMAP will provide global observations of soil moisture and freeze/thaw state (the hydrosphere state). SMAP hydrosphere state measurements will be used to enhance understanding of processes that link the water, energy, and carbon cycles, and to extend the capabilities of weather and climate prediction models. It will explain the problems encountered, and the solutions developed, which minimized the risk typically associated with such an arduous process. Also discussed, the future of testing on expensive long lead-time spacecraft. Will we ever reach the ''build and shoot" scenario with minimal or no verification testing?

  10. Soil moisture sensing via swept frequency based microwave sensors.

    PubMed

    Pelletier, Mathew G; Karthikeyan, Sundar; Green, Timothy R; Schwartz, Robert C; Wanjura, John D; Holt, Greg A

    2012-01-01

    There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI) that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR). The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT). The measurement is comparable to time domain transmissometry (TDT) with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument's ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/-105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r(2) = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the SFI instrument over

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    DTIC Science & Technology

    1988-05-01

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

  13. Airborne soil organic particles generated by precipitation

    SciTech Connect

    Wang, Bingbing; Harder, Tristan H.; Kelly, Stephen T.; Piens, Dominique S.; China, Swarup; Kovarik, Libor; Keiluweit, Marco; Arey, Bruce W.; Gilles, Mary K.; Laskin, Alexander

    2016-05-02

    Airborne organic particles play a critical role in Earth’s climate1, public health2, air quality3, and hydrological and carbon cycles4. However, sources and formation mechanisms for semi-solid and solid organic particles5 are poorly understood and typically neglected in atmospheric models6. Laboratory evidence suggests that fine particles can be formed from impaction of mineral surfaces by droplets7. Here, we use chemical imaging of particles collected following rain events in the Southern Great Plains, Oklahoma, USA and after experimental irrigation to show that raindrop impaction of soils generates solid organic particles. We find that after rain events, sub-micrometre solid particles, with a chemical composition consistent with soil organic matter, contributed up to 60% of atmospheric particles. Our irrigation experiments indicate that intensive water impaction is sufficient to cause ejection of airborne soil organic particles from the soil surface. Chemical imaging and micro-spectroscopy analysis of particle physico-chemical properties suggest that these particles may have important impacts on cloud formation and efficiently absorb solar radiation. Lastly, we suggest that raindrop-induced formation of solid organic particles from soils may be a widespread phenomenon in ecosystems such as agricultural systems and grasslands where soils are exposed to strong, episodic precipitation events8.

  14. Airborne soil organic particles generated by precipitation

    DOE PAGES

    Wang, Bingbing; Harder, Tristan H.; Kelly, Stephen T.; ...

    2016-05-02

    Airborne organic particles play a critical role in Earth’s climate1, public health2, air quality3, and hydrological and carbon cycles4. However, sources and formation mechanisms for semi-solid and solid organic particles5 are poorly understood and typically neglected in atmospheric models6. Laboratory evidence suggests that fine particles can be formed from impaction of mineral surfaces by droplets7. Here, we use chemical imaging of particles collected following rain events in the Southern Great Plains, Oklahoma, USA and after experimental irrigation to show that raindrop impaction of soils generates solid organic particles. We find that after rain events, sub-micrometre solid particles, with a chemicalmore » composition consistent with soil organic matter, contributed up to 60% of atmospheric particles. Our irrigation experiments indicate that intensive water impaction is sufficient to cause ejection of airborne soil organic particles from the soil surface. Chemical imaging and micro-spectroscopy analysis of particle physico-chemical properties suggest that these particles may have important impacts on cloud formation and efficiently absorb solar radiation. Lastly, we suggest that raindrop-induced formation of solid organic particles from soils may be a widespread phenomenon in ecosystems such as agricultural systems and grasslands where soils are exposed to strong, episodic precipitation events8.« less

  15. Using Remotely-Sensed Estimates of Soil Moisture to Infer Spatially Distributed Soil Hydraulic Properties

    NASA Astrophysics Data System (ADS)

    Santanello, J. A.; Peters-Lidard, C.; Garcia, M.; Mocko, D.

    2006-05-01

    Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the unsaturated (vadose) zone of the soil are not easy to estimate or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface and hydrologic models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for semi-operational estimation of soil moisture for vehicle mobility assessments. Estimates of 0-5 cm soil moisture derived from radar imagery were acquired over the Walnut Gulch watershed in Arizona. The resultant fields of soil moisture were then used to calibrate a land surface model and infer information on the soil hydraulic properties of the region. Specifically, a well-established parameter estimation routine was incorporated into the Noah land surface model, and run at very high spatial resolutions during the Monsoon 90 field experiment. Optimizations of sand, clay, and silt percentages for each soil type were then related to specific hydraulic parameters using pedotransfer functions. By estimating a more continuous range of widely applicable soil properties such as sand and clay percentages, rather than prescribing soil texture classes or attempting multi-objective optimizations over large parameter sets as in previous studies, the accuracy and consistency of the resulting properties could be more easily assessed. In addition, the strong influence of temporal and spatial patterns in precipitation is addressed, and the methodology is tested using a more recent radar-based soil moisture product and independent dataset at Walnut Gulch. Overall, results demonstrate the potential for this method to gain physically meaningful information on soil properties given limited microwave retrievals from remote sensing.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  17. Orbiting passive microwave sensor simulation applied to soil moisture estimation

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator); Clark, B. V.; Pitchford, W. M.; Paris, J. F.

    1979-01-01

    A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate soil water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to soil moisture improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.

  18. 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.

  19. Radar response to vegetation. [soil moisture mapping via microwave backscattering

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.

    1975-01-01

    Active microwave measurements of vegetation backscatter were conducted to determine the utility of radar in mapping soil moisture through vegetation and mapping crop types. Using a truck-mounted boom, spectral response data were obtained for four crop types (corn, milo, soybeans, and alfalfa) over the 4-8 GHz frequency band, at incidence angles of 0 to 70 degrees in 10-degree steps, and for all four linear polarization combinations. Based on a total of 125 data sets covering a wide range of soil moisture, content, system design criteria are proposed for each of the aforementioned objectives. Quantitative soil moisture determination was best achieved at the lower frequency end of the 4-8 GHz band using HH polarized waves in the 5- to 15-degree incidence angle range. A combination of low and high frequency measurements are suggested for classifying crop types. For crop discrimination, a dual-frequency dual-polarization (VV and cross) system operating at incidence angles above 40 degrees is suggested.

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  3. Soil Surface Moisture from Cryosat2 and Sentinel-3 Satellite Radar Altimetry

    NASA Astrophysics Data System (ADS)

    Berry, P. A. M.; Balmbra, R.

    2016-08-01

    Measuring soil moisture using remote sensing techniques has been a key application for many years; however, these techniques encounter difficulties in arid and semi-arid terrain. Satellite altimetry presents an attractive option for retrieval of soil surface moisture in these areas [1:2]. Surface soil moisture has now been successfully retrieved from Cryosat2 data as part of the EU LOTUS project; the key to retrieving accurate soil surface moisture estimates is the development of very detailed Dry Earth Models (DREAMS). Soil moisture time series have been derived from Cryosat2 and Jason2 data over the Simpson, Tenere and Kalahari deserts; cross-comparison of the results and validation with independent remote sensed soil moisture data is presented. These results show that the detailed along- track estimates that can be achieved from satellite radar altimetry have a unique contribution to make to soil moisture retrieval in arid and semi-arid terrain.

  4. 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

  5. Investigating local controls on soil moisture temporal stability using an inverse modeling approach

    NASA Astrophysics Data System (ADS)

    Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

    2013-04-01

    A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

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

    PubMed

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

    2016-01-01

    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

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

    PubMed Central

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

    2016-01-01

    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

  9. Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

    USGS Publications Warehouse

    Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

    2011-01-01

    Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

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

    NASA Astrophysics Data System (ADS)

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

    2008-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  12. Soil moisture effects on the carbon isotopic composition of soil respiration

    EPA Science Inventory

    The carbon isotopic composition ( 13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low soil moisture or by low atmospheric humidity. Air humidity has also been shown to correlate with the 13C of soil respiration, which suggests indir...

  13. Effects of Soil Temperature and Moisture on Soil Respiration on the Tibetan Plateau

    PubMed Central

    Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying

    2016-01-01

    Understanding of effects of soil temperature and soil moisture on soil respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two soil moistures (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow. PMID:27798671

  14. A method to downscale soil moisture to fine-resolutions using topographic, vegetation, and soil data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture can be estimated over large regions with spatial resolutions greater than 500 m, but many applications require finer resolutions (10 – 100 m grid cells). Several methods use topographic data to downscale, but vegetation and soil patterns can also be important. In this paper, a downsc...

  15. Soil moisture's underestimated role in climate change impact modelling in low-energy systems.

    PubMed

    le Roux, Peter Christiaan; Aalto, Juha; Luoto, Miska

    2013-10-01

    Shifts in precipitation regimes are an inherent component of climate change, but in low-energy systems are often assumed to be less important than changes in temperature. Because soil moisture is the hydrological variable most proximally linked to plant performance during the growing season in arctic-alpine habitats, it may offer the most useful perspective on the influence of changes in precipitation on vegetation. Here we quantify the influence of soil moisture for multiple vegetation properties at fine spatial scales, to determine the potential importance of soil moisture under changing climatic conditions. A fine-scale data set, comprising vascular species cover and field-quantified ecologically relevant environmental parameters, was analysed to determine the influence of soil moisture relative to other key abiotic predictors. Soil moisture was strongly related to community composition, species richness and the occurrence patterns of individual species, having a similar or greater influence than soil temperature, pH and solar radiation. Soil moisture varied considerably over short distances, and this fine-scale heterogeneity may contribute to offsetting the ecological impacts of changes in precipitation for species not limited to extreme soil moisture conditions. In conclusion, soil moisture is a key driver of vegetation properties, both at the species and community level, even in this low-energy system. Soil moisture conditions represent an important mechanism through which changing climatic conditions impact vegetation, and advancing our predictive capability will therefore require a better understanding of how soil moisture mediates the effects of climate change on biota.

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

    NASA Astrophysics Data System (ADS)

    Kim, Sanghyun

    2016-05-01

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

  17. Winter soil respiration in a humid temperate forest: The roles of moisture, temperature, and snowpack

    NASA Astrophysics Data System (ADS)

    Contosta, Alexandra R.; Burakowski, Elizabeth A.; Varner, Ruth K.; Frey, Serita D.

    2016-12-01

    Winter soil respiration at midlatitudes can comprise a substantial portion of annual ecosystem carbon loss. However, winter soil carbon dynamics in these areas, which are often characterized by shallow snow cover, are poorly understood due to infrequent sampling at the soil surface. Our objectives were to continuously measure winter CO2 flux from soils and the overlying snowpack while also monitoring drivers of winter soil respiration in a humid temperate forest. We show that the relative roles of soil temperature and moisture in driving winter CO2 flux differed within a single soil-to-snow profile. Surface soil temperatures had a strong, positive influence on CO2 flux from the snowpack, while soil moisture exerted a negative control on soil CO2 flux within the soil profile. Rapid fluctuations in snow depth throughout the winter likely created the dynamic soil temperature and moisture conditions that drove divergent patterns in soil respiration at different depths. Such dynamic conditions differ from many previous studies of winter soil microclimate and respiration, where soil temperature and moisture are relatively stable until snowmelt. The differential response of soil respiration to temperature and moisture across depths was also a unique finding as previous work has not simultaneously quantified CO2 flux from soils and the snowpack. The complex interplay we observed among snow depth, soil temperature, soil moisture, and CO2 flux suggests that winter soil respiration in areas with shallow seasonal snow cover is more variable than previously understood and may fluctuate considerably in the future given winter climate change.

  18. Soil moisture retrieval from WindSat using the single channel algorithm toward a blended global soil moisture product from multiple microwave sensors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil moisture has long been recognized as one of the critical land surface initial conditions for numerical weather, climate hydrological predictions, particularly for transition zones between dry and humid climates. However, none of the currently existing soil moisture products has been used operat...

  19. Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The diversity of in situ soil moisture network protocols and instrumentation led to the development of a testbed for comparing in situ soil moisture sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each station ...

  20. 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...

  1. 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...

  2. Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter

    NASA Astrophysics Data System (ADS)

    Montzka, Carsten; Moradkhani, Hamid; Weihermüller, Lutz; Franssen, Harrie-Jan Hendricks; Canty, Morton; Vereecken, Harry

    2011-03-01

    SummaryIn a synthetic study we explore the potential of using surface soil moisture measurements obtained from different satellite platforms to retrieve soil moisture profiles and soil hydraulic properties using a sequential data assimilation procedure and a 1D mechanistic soil water model. Four different homogeneous soil types were investigated including loamy sand, loam, silt, and clayey soils. The forcing data including precipitation and potential evapotranspiration were taken from the meteorological station of Aachen (Germany). With the aid of the forward model run, a synthetic data set was designed and observations were generated. The virtual top soil moisture observations were then assimilated to update the states and hydraulic parameters of the model by means of a particle filtering data assimilation method. Our analyses include the effect of assimilation strategy, measurement frequency, accuracy in surface soil moisture measurements, and soils differing in textural and hydraulic properties. With this approach we were able to assess the value of periodic spaceborne observations of top soil moisture for soil moisture profile estimation and identify the adequate conditions (e.g. temporal resolution and measurement accuracy) for remotely sensed soil moisture data assimilation. Updating of both hydraulic parameters and state variables allowed better predictions of top soil moisture contents as compared with updating of states only. An important conclusion is that the assimilation of remotely-sensed top soil moisture for soil hydraulic parameter estimation generates a bias depending on the soil type. Results indicate that the ability of a data assimilation system to correct the soil moisture state and estimate hydraulic parameters is driven by the non linearity between soil moisture and pressure head.

  3. Influence of soil moisture on sorption and degradation of hexazinone and simazine in soil.

    PubMed

    García-Valcárcel, A I; Tadeo, J L

    1999-09-01

    Sorption and degradation rates of hexazinone and simazine on soil were determined in a sandy loam soil incubated, during 44 days, at 25 degrees C with moisture contents ranging from 4% to 18%. Herbicide levels in soil solution were also measured, after extraction of this solution by a centrifugation method. All experiments were conducted with treated soil in plastic columns, and the results showed that this method is suitable for the simultaneous study of pesticide sorption and degradation in soil at different environmental conditions. In general, sorption of both herbicides was higher for aged herbicide residues compared to recently applied herbicides, and soil subjected to drying and rewetting cycles had the highest sorption values. K(f) values ranged from 0.5 to 1.2 for simazine and from 0.2 to 0.4 for hexazinone. Degradation rates increased with soil moisture content for both herbicides, and drying-rewetting of soil yielded degradation rates slower than that obtained at 10% soil moisture content. Hexazinone concentration in soil solution decreased with incubation time faster than simazine.

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

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-08-01

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

  5. Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota

    NASA Technical Reports Server (NTRS)

    Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

    1981-01-01

    Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.

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

    NASA Technical Reports Server (NTRS)

    Bolten, John; Crow, Wade

    2012-01-01

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

  7. Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks worldwide

    NASA Astrophysics Data System (ADS)

    Brocca, L.; Zucco, G.; Mittelbach, H.; Moramarco, T.; Seneviratne, S. I.

    2014-07-01

    The analysis of the spatial-temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. 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. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250-150,000 km2). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time-invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Priesack, Eckart; Schuh, Max

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  12. Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture

    NASA Astrophysics Data System (ADS)

    Chen, Fan; Crow, Wade T.; Starks, Patrick J.; Moriasi, Daniel N.

    2011-04-01

    This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions of root-zone soil moisture, evapotranspiration, and stream flow within the 341 km 2 Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthetic twin experiments assimilating surface soil moisture is shown to effectively update SWAT upper-layer soil moisture predictions and provide moderate improvement to lower layer soil moisture and evapotranspiration estimates. However, insufficient SWAT-predicted vertical coupling results in limited updating of deep soil moisture, regardless of the SWAT parameterization chosen for root-water extraction. Likewise, a real data assimilation experiment using ground-based soil moisture observations has only limited success in updating upper-layer soil moisture and is generally unsuccessful in enhancing SWAT stream flow predictions. Comparisons against ground-based observations suggest that SWAT significantly under-predicts the magnitude of vertical soil water coupling at the site, and this lack of coupling impedes the ability of the EnKF to effectively update deep soil moisture, groundwater flow and surface runoff. The failed attempt to improve stream flow prediction is also attributed to the inability of the EnKF to correct for existing biases in SWAT-predicted stream flow components.

  13. Remote Sensing Observations of Snow and Soil Moisture for Snowmelt Flood Predictions in the Red River of the North Basin

    NASA Astrophysics Data System (ADS)

    Tuttle, S. E.; Jacobs, J. M.; Vuyovich, C.; Cho, E.; Restrepo, P. J.; Jia, X.; Cosh, M. H.; Deweese, M. M.; Connelly, B.; Buan, S.

    2015-12-01

    The northward-flowing Red River of the North Basin (RRB), located in eastern North Dakota and western Minnesota, is vulnerable to frequent floods due to its flat terrain and low permeability soil. A vast majority of floods in the basin occur during the snowmelt season, when the winter snowpack thaws and spring rains fall onto saturated soils. This causes the Red River to spill over shallow banks and across the floodplain. The region has sparse in situ observations of snow and soil moisture, making flood prediction in the RRB difficult. Remote sensing data can help to capture magnitude, timing, and spatial distribution of watershed scale snow, soil moisture, and snowmelt parameters in the RRB, which will allow for better characterization of the watershed's hydrologic state. This research examines snow water equivalent (SWE; from the AMSR-E, AMSR2, and SSM/I satellite instruments), soil moisture (from AMSR-E, SMOS, and SMAP), and snow covered area (SCA; from MODIS), along with modeled SWE and snow depth from NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) SNOw Data Assimilation System (SNODAS). These data are compared with observations from local and federal snow surveys, NOHRSC Airborne Gamma Radiation Snow Survey Program flights, NOAA National Climate Data Center (NCDC) cooperative network sites, Natural Resource Conservation Service (NRCS) Soil Climate Analysis Network (SCAN) sites, and the North Central River Forecast Center's (NCRFC) model states, in order to determine data quality as well as strengths and weaknesses of satellite observations for RRB flood forecasting. Future analyses will include evaluation of freeze/thaw state information from the Soil Moisture Active-Passive (SMAP) satellite, and explore the potential for flood forecasting improvement by updating state variables of the NOAA National Weather Service (NWS) operational forecasting models with remotely sensed fields.

  14. Effects of soil moisture content on upland nitrogen loss

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  15. NASA's Soil Moisture Active and Passive (SMAP) Mission

    NASA Technical Reports Server (NTRS)

    Kellogg, Kent; Njoku, Eni; Thurman, Sam; Edelstein, Wendy; Jai, Ben; Spencer, Mike; Chen, Gun-Shing; Entekhabi, Dara; O'Neill, Peggy; Piepmeier, Jeffrey; Brown, Molly; Savinell, Chris; Entin, Jared; Ianson, Eric

    2010-01-01

    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 Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the

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

    PubMed

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

    2014-03-01

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

  17. A physical scaling model for aggregation and disaggregation of field-scale surface soil moisture dynamics.

    PubMed

    Ojha, Richa; Govindaraju, Rao S

    2015-07-01

    Scaling relationships are needed as measurements and desired predictions are often not available at concurrent spatial support volumes or temporal discretizations. Surface soil moisture values of interest to hydrologic studies are estimated using ground based measurement techniques or utilizing remote sensing platforms. Remote sensing based techniques estimate field-scale surface soil moisture values, but are unable to provide the local-scale soil moisture information that is obtained from local measurements. Further, obtaining field-scale surface moisture values using ground-based measurements is exhaustive and time consuming. To bridge this scale mismatch, we develop analytical expressions for surface soil moisture based on sharp-front approximation of the Richards equation and assumed log-normal distribution of the spatial surface saturated hydraulic conductivity field. Analytical expressions for field-scale evolution of surface soil moisture to rainfall events are utilized to obtain aggregated and disaggregated response of surface soil moisture evolution with knowledge of the saturated hydraulic conductivity. The utility of the analytical model is demonstrated through numerical experiments involving 3-D simulations of soil moisture and Monte-Carlo simulations for 1-D renderings-with soil moisture dynamics being represented by the Richards equation in each instance. Results show that the analytical expressions developed here show promise for a principled way of scaling surface soil moisture.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  1. Feedbacks between vegetation and soil moisture in mountain grasslands

    NASA Astrophysics Data System (ADS)

    Castelli, M.; Bertoldi, G.; Notarnicola, C.; Brenner, J.; Greifeneder, F.; Niedrist, G.; Tappeiner, U.

    2015-12-01

    Soil moisture content (SMC) is a key variable for water budget and controls both physical processes, as runoff generation, and biological processes, as vegetation development. On the other hand, vegetation and land management influence soil evolution and therefore SMC dynamic. Moreover, in mountain areas complex topography adds an additional control on water fluxes and climate. For those reasons, understanding the controls on the spatio-temporal variability of SMC is essential to predict how perturbations in vegetation and climate affects mountain hydrology. In this contribution we want to analyze the impact of different land management (meadows versus pastures) on the spatial and temporal dynamic of surface and root-zone SMC, and its relationships with climate and topography. We focus on water-limited alpine grasslands in the LTER area Mazia Valley in the European Alps. The infrastructure includes a dense network of more than 20 stations measuring soil moisture, biomass production observations and two eddy-covariance stations over meadow and pasture. Moreover, more than ten high-resolution SAR (Sentinel1 and RADARSAT2) images were acquired, in combination with ground surveys to monitor SMC spatial distribution. In order to understand the different physical controls, SMC has been also modelled using the GEOtop hydrological model, coupled with a dynamic vegetation model. Results show that meadows and pastures have different behaviors. Meadows are in general wetter and in flatter locations. This leads to higher vegetation productivity, development of soils with higher water holding capacity and to a positive feedback on SMC. In contrast, pastures are drier, in steeper locations with lower vegetation density and more compact soils due animal trampling, with a negative feedback on SMC. This co-evolution of land cover and SMC leads to persistent spatial patterns controlled by both topography and management.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  3. Effect of Soil Moisture on Chlorine Deposition (POSTPRINT)

    DTIC Science & Technology

    2014-01-01

    obtained nd prepared for extraction (10 mL deionized water, 18 M/cm) nd subsequent analysis by ion chromatography [16] to measure l− concentrations. Ion ...Photobiol. A: Chem. 86 (1995) 1–7. 16] Determination of Inorganic Anions by Ion Chromatography , EPA Method 9056A, 2007, http://www.epa.gov/wastes/hazard...examine Cl2 eposition into soils with moisture contents from 0 to 0.2 (w/w) and ith varying organic matter contents. We use the chloride ion (Cl−) s

  4. Observational Evidence that Soil Moisture Variations Affect Precipitation

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Suarez, Max J.; Higgins, R. Wayne; VandenDool, Huug M.

    2002-01-01

    Land-atmosphere feedback, by which precipitation-induced soil moisture anomalies affect subsequent precipitation, may be an important element of Earth's climate system, but its very existence has never been demonstrated conclusively at regional to continental scales. Evidence for the feedback is sought in a 50-year observational precipitation dataset covering the United States. The precipitation variance and autocorrelation fields are characterized by features that agree (in structure, though not in magnitude) with those produced by an atmospheric general circulation model (AGCM). Because the model-generated features are known to result from land-atmosphere feedback alone, the observed features are highly suggestive of the existence of feedback in nature.

  5. Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

    Parrens, Marie; Wigernon, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yarri, Amen; O'Neill, Peggy; Kerr, Yann

    2016-01-01

    For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from -1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth

  6. Considering combined or separated roughness and vegetation effects in soil moisture retrievals

    NASA Astrophysics Data System (ADS)

    Parrens, Marie; Wigneron, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yaari, Amen; O'Neill, Peggy; Kerr, Yann

    2017-03-01

    For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (τnad) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB), soil roughness is modelled with a semi-empirical equation using four main parameters (Qr, Hr, Nrp, with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of Nrp and Hr on the SM and τnad retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that NrH = NrV. The retrievals were performed by varying Nrp from -1 to 2 by steps of 1 and Hr from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of

  7. Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

    NASA Astrophysics Data System (ADS)

    Orth, René; Seneviratne, Sonia I.

    2014-12-01

    Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  9. 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.

  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. Soil moisture could enhance electrokinetic remediation of arsenic-contaminated soil.

    PubMed

    Shin, Su-Yeon; Park, Sang-Min; Baek, Kitae

    2017-03-07

    Electrokinetic remediation (EKR) is the most efficient technique for remediation of fine-grained soil. The primary removal mechanisms of heavy metal in EKR are the electromigration and electroosmosis flow under appropriate electric gradients. Most EKR studies have researched the variation according to the electrolyte and electric voltage. Also, EKR could be influenced by the migration velocity of ions, while few studies have investigated the effect of moisture content. In this study, soil moisture was controlled by using tap water and NaOH as electrolytes to enhance electromigration and electroosmosis flow. In both electrolytes, the higher moisture content led to the more As removal efficiency, but there were no differences between tap water and NaOH. Therefore, tap water was the most cost-effective electrolyte to remove As from fine-grained soil.

  12. 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...

  13. The SMAP level 4 surface and root zone soil moisture data assimilation product

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The NASA Soil Moisture Active Passive (SMAP) mission is scheduled for launch in January 2015 and will provide L-band radar and radiometer observations that are sensitive to surface soil moisture (in the top few centimeters of the soil column). For several of the key applications targeted by SMAP, ho...

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Coates, Victoria; Pattison, Ian; Sander, Graham

    2016-04-01

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

  16. Experiments using new initial soil moisture conditions and soil map in the Eta model over La Plata Basin

    NASA Astrophysics Data System (ADS)

    Doyle, Moira E.; Tomasella, Javier; Rodriguez, Daniel A.; Chou, Sin Chan

    2013-08-01

    An effort towards a more accurate representation of soil moisture and its impact on the modeling of weather systems is presented. Sensitivity tests of precipitation to soil type and soil moisture changes are carried out using the atmospheric Eta model for the numerical simulation of the development of a mesoscale convective system over northern Argentina. Modified initial soil moisture conditions were obtained from a hydrological balance model developed and running operationally at INPE. A new soil map was elaborated using the available soil profile information from Brazil, Paraguay, Uruguay, and Argentina and depicts 18 different soil types. Results indicate that more accurate initial soil moisture conditions and incorporating a new soil map with hydraulic parameters, more representative of South American soils, improve daily total precipitation forecasts both in quantitative and spatial representations.

  17. The role of tree species and soil moisture in soil organic matter stabilization and destabilization

    NASA Astrophysics Data System (ADS)

    Hatten, J. A.; Dewey, J.; Roberts, S.; McNeal, K.; Shaman, A.

    2014-12-01

    Inputs of labile organic substrates to soils are commonly associated with elevated soil organic carbon mineralization rates; this process is known as the priming effect. Plant presence and soil conditions (i.e. water regime, nutrient status) are known to be interacting factors governing priming. In this study, we examine the role of differing species, loblolly pine (Pinus taeda L.) and nuttall oak (Quercus texana B.), and moisture regimes (low and high) upon the soil priming effect in a fine textured soil. We explore whether there is depletion of original soil carbon and concurrent replacement through addition of fresh organic matter from the planted tree species. By employing a series of planted and plant-free pots in a greenhouse mesocosm study, we were able to characterize the composition of soil organic matter and its carbon with the use of CuO oxidation products (e.g. lignin, cutin/suberin biomarkers). Carbon was elevated on the low moisture samples relative to all other treatments, and the C:N ratio suggests that newly produced plant carbon replaced original soil carbon. The soil lignin content of the planted treatments was lower than the plant-free treatments suggesting that lignin present in the original soil may have been preferentially degraded by priming and not replaced. We will discuss the utility of CuO oxidation products to explore soil organic carbon dynamics and the implications of understanding the role of species and soil moisture in predicting the response of soil carbon to land use and climate change.

  18. Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.

    PubMed

    Jarvi, Mickey P; Burton, Andrew J

    2013-09-01

    The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (<1 mm) respiration in a sugar maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.

  19. Developing a dual assimilation approach for thermal infrared and passive microwave soil moisture retrievals

    NASA Astrophysics Data System (ADS)

    Hain, Christopher Ryan

    Soil moisture plays a vital role in the partitioning of sensible and latent heat fluxes in the surface energy budget and the lack of a dense spatial and temporal network of ground-based observations provides a challenge to the initialization of the true soil moisture state in numerical weather prediction simulations. The retrieval of soil moisture using observations from both satellite-based thermal-infrared (TIR) and passive microwave (PM) sensors has been developed (Anderson et al., 2007; Hain et al., 2009; Jackson, 1993; Njoku et al., 2003). The ability of the TIR and microwave observations to diagnose soil moisture conditions within different layers of the soil profile provides an opportunity to use each in a synergistic data assimilation approach towards the goal of diagnosing the true soil moisture state from surface to root-zone. TIR and PM retrievals of soil moisture are compared to soil moisture estimates provided by a retrospective Land Information System (LIS) simulation using the NOAH LSM during the time period of 2003--2008. The TIR-based soil moisture product is provided by a retrieval of soil moisture associated with surface flux estimates from the Atmosphere-Land-Exchange-Inversion (ALEXI) model (Anderson et al., 1997; Mecikalski et al., 1999; Hain et al., 2009). The PM soil moisture retrieval is provided by the Vrijie Universiteit Amsterdam (VUA)-NASA surface soil moisture product. The VUA retrieval is based on the findings of Owe et al. (2001; 2008) using the Land Surface Parameter model (LPRM), which uses one dual polarized channel (6.925 or 10.65 GHz) for a dual-retrieval of surface soil moisture and vegetation water content. In addition, retrievals of ALEXI (TIR) and AMSR-E (PM) soil moisture are assimilated within the Land Information System using the NOAH LSM. A series of data assimilation experiments is completed with the following configuration: (a) no assimilation, (b) only ALEXI soil moisture, (c) only AMSR-E soil moisture, and (d) ALEXI

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. Correlation of spacecraft passive microwave system data with soil moisture indices (API). [great plains corridor

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.; Mcfarland, M. J.; Theis, S.; Richter, J. G.

    1981-01-01

    Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil moisture is most important to winter wheat yield. Other significant results are reported.

  3. Evaluating Remotely-Sensed Soil Moisture with Data Synthesis for Ecological Applications (Invited)

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Evaluation of remotely-sensed soil moisture products for ecological applications remains a challenge, despite an increasing abundance of soil-moisture related data. Available data vary by spatial representation, temporal fidelity and sensitivity, while some data, such as precipitation or evapotranspiration, indirectly relate to soil moisture. Soil moisture cross-correlates with potential confounding factors including vegetation biomass, surface temperature and flooding, further complicating positive attribution of the remotely-sensed signal. The quality of remotely-sensed soil moisture is spatially and temporally heterogeneous and often contains significant retrieval gaps limiting utility for many applications. To address these challenges, we developed a system for simultaneous satellite microwave retrieval of multiple land surface parameters from AMSR-E multi-frequency brightness temperatures. Rather than evaluate soil moisture in isolation, we evaluate consistency of all retrieved parameters in relation to each other and independent datasets. We also develop a data-assimilation-inspired time series merging method for exploiting soil-moisture related data from multiple independent sources to improve soil moisture accuracy and provide detailed uncertainty information. The merging method improves correlations with in situ soil moisture measurements from regional monitoring networks, while estimated RMS errors correlate closely with RMS error calculated directly from the in situ data. The resulting integrated soil moisture dataset serves as a primary driver for remote-sensing-based carbon model simulations of soil respiration and net ecosystem CO2 exchange (NEE). Model fit relative to tower observed NEE improves over model estimates derived using individual unmerged soil