Search NASA⌕ Search

SEARCH · Search NASA

Results for “soil moisture”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Effect of vegetation on soil moisture sensing observed from orbiting microwave radiometers

The microwave radiometric measurements made by the Skylab 1.4 GHz radiometer and by the 6.6 GHz and 10.7 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer were analyzed to study the large-area soil moisture variations of land surfaces. Two regions in Texas, one with sparse and the other with dense vegetation covers, were selected for the study. The results gave a confirmation of the vegetation effect observed by ground-level microwave radiometers. Based on the statistics of the satellite data, it was possible to estimate surface soil moisture in about five different levels from dry to wet conditions with a 1.4 GHz radiometer, provided that the biomass of the vegetation cover could be independently measured. At frequencies greater than about 6.6 GHz, the radiometric measurements showed little sensitivity to moisture variation for vegetation-covered soils. The effects of polarization in microwave emission were studied also.

Wang, J. R.↗
NASA NTRS1981

HCMM detection of high soil moisture areas

It is noted that one objective of NASA's Heat Capacity Mapping Mission (HCMM) is to evaluate the feasibility of using HCMM data to assess soil moisture effects by observing temperatures near the maximum and minimum of the diurnal temperature cycle. The satellite, which carries a two-channel radiometer (0.5-1.1 and 10.5-12.5 microns) gathers data at 1:30 P.M. and 2:30 A.M. local time at midlatitudes, with a repeat cycle of 5 or 16 days depending on latitude. The spatial resolutions are 0.5 x 0.5 km at nadir for the visible channel and 0.6 x 0.6 km at nadir for the thermal infrared channel. An example is presented here of HCMM detection of a region of high soil moisture.

Heilman, J. L.↗
NASA NTRS2022

Flash Drought Onset and Development Mechanisms Captured With Soil Moisture and Vegetation Data Assimilation

Flash droughts evolve and intensify rapidly under the influence of anomalous atmospheric conditions. In this study, we investigate the role of assimilating remotely sensed soil moisture (SM) and vegetation properties in capturing the evolution and impacts of two flash droughts in the Northern Great Plains. We find that during 2016 drought triggered by anomalously high temperatures and excessive evaporative demands, multivariate data assimilation (DA) of MODIS-derived leaf area index (LAI) and Soil Moisture Active Passive SM within Noah-Multiparameterization model helps capture elevated transpiration at onset. Assimilation of LAI particularly helped model the resulting rapid decline in SM during onset with as high as 10.0% steeper rate of decline compared to the simulation without any assimilation. Modeled-SM anomalies exhibit a 7.5% and 11.7% increase in similarity with Evaporative Stress Index (ESI) data and U.S. Drought Monitor (USDM) maps, respectively. In contrast, during 2017 flash drought driven by record-low precipitation during summers, SM assimilation resulted in largest rates of decline in rootzone SM, as large as 48.4% compared to results from no assimilation. Multivariate DA of SM and LAI results in 6.7% and 14.3% higher spatial similarity with ESI and USDM, respectively, and is necessary to model rapid intensification caused by anomalous precipitation deficits. This study elucidates the need to incorporate multiple observational constraints from remote sensing to effectively capture rapid onset rates, intensification, and severity of flash drought following different propagation mechanisms. This is fundamental for drought early detection to provide a wider window of response and implement efficient mitigation strategies.

Shahryar K. Ahmad↗
NASA NTRS1997

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

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

Engman, Edwin T.↗
NASA NTRS1999

Retrieval of Soil Moisture from AMSR Data

In this paper we discuss the potential and problems of soil moisture sensing using AMSR data that will become available in late 2000 or early 2001.

soil moisture rediometry AMSR remote sensing satel↗
NASA NTRS2015

Variability of Phenology and Fluxes of Water and Carbon with Observed and Simulated Soil Moisture in the Ent Terrestrial Biosphere Model (Ent TBM Version 1.0.1.0.0)

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan- Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Soil moisture↗
NASA NTRS1992

Synergistic use of active and passive microwave in soil moisture estimation

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.

O'Neill, P.↗
NASA NTRS2012

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Nearing, Grey S.↗
NASA NTRS2017

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗
NASA NTRS2023

Aconcagua Basin Agriculture: Analyzing Hydrological Norms, Evapotranspiration, and Soil Moisture to Assess Crop Water Demand and Water Usage in Chile’s Aconcagua River Basin

The Aconcagua basin has experienced a prolonged drought since 2010, posing a significant concern to the agricultural sector, which contributes to 12% of the national agriculture output. Reduced precipitation and warmer conditions have led to water constraints for agricultural activities. As the agriculture sector relies more on irrigation, there has been a decline in surface water availability and a shrinking groundwater supply, both primarily sourced from snow and glacial melt. This study focuses on evaluating crop water demand and water usage in the Aconcagua Basin, leveraging in-situ and available satellite data from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), 1-km downscaled Soil Moisture Active Passive (SMAP), Global Precipitation Measurement Mission IMERG (GPM), and Landsat 8 Operational Land Imager (OLI). Remote sensing hydrologic norms from pre- and intra-drought conditions provided a baseline for our water use analysis. We have identified areas of the basin where water usage is exaggerated compared to other regions by analyzing soil moisture, evapotranspiration, and vegetation index trends across agricultural lands. The study highlights the presence of irrigation and exaggerated water usage categorized by crop type while normalizing the data by the quantity of water allocation (m3/s) to each subregion. The findings have the potential to assist our partners, the Centro de Información de Recursos Naturales (CIREN) and the Ministry of Agriculture, in refining water allocation approaches; showcasing the feasibility of leveraging remote sensing and earth observation datasets to monitor agricultural practices within the context of water scarcity.

Remote sensing↗
NASA NTRS1984

Inversion algorithms for the microwave remote sensing of soil moisture. Experiments with swept frequency microwaves

Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.

Hancock, G. D.↗
NASA NTRS2013

The Soil Moisture Active Passive (SMAP): Radar Measurements at High Latitudes and of Freeze/Thaw State

The Soil Moisture Active/Passive (SMAP) mission is scheduled for a late 2014 launch date. The mission will use both active radar and passive radiometer instruments at L-Band. In order to achieve a wide swath at sufficiently high resolution for both active and passive channels, an instrument architecture that uses a large rotating reflector is employed. In this paper, a focus will be places on the radar design and associated data products at high latitudes. The radar will employ synthetic-aperture processing to achieve a "moderate" resolution dual-pol product over a 1000 km swath. Because the radar is operating continuously, very frequent temporal coverage will be achieved at high latitudes. This data will be used, among other things, to produce a surface freeze/thaw state data product.

Earth observing↗
NASA NTRS1976

Remote sensing of soil moisture

The results of thermal and microwave studies of soil moisture are presented, and the relative advantage of each method is discussed.

Schmugge, T.↗
NASA NTRS2003

A dual-low-frequency radar for sub-canopy and deep soil-moisture measurements

Measurements of deep and sub-canopy soil moisture are critical in understanding the global water and carbon energy cycle, but are not presently available on a synoptic basis. In this paper, we discuss a proposed spaceborne dual-frequency (UHF and VHF) radar that can provide global & these key measurements. This system is polarimetric and the low transmit frequencies chosen for their penetration abilities necessitate a large antenna that has an aperture of approximately 30m by 11m at VHF, and 30m by 3m at UHF. We describe the mission concept, overall system design and performance characteristics, and discuss ongoing tasks to prototype key system components, and verify the retrieval algorithms. We are also developing a tower-based prototype radar system. This system will, through field observations, demonstrate the scientific effectiveness of the measurement concept and provide critical data for algorithm development. We provide details of the ground experimentation including issues unique to operating at the low-frequencies chosen for these systems.

radar hazard detection↗
NASA NTRS1972

Soil moisture measurements with microwave, radiometers

One technique of measuring moisture content that appears promising is that of microwave radiometry. In the microwave region of the spectrum, the emissivity of water is approximately 0.4, whereas that of dry soil is approximately 0.9. Therefore, the emissivity of the soil can range from about 0.6 to 0.9 as the soil changes from a wet to a dry condition. Recent ground base measurements have demonstrated emissivity changes of this magnitude. To test the use of this approach for remote sensing of soil moisture, flights were made over agricultural test sites in the vicinity of Phoenix, Ariz., during late February 1971. On the same day, soil moisture measurements were made on the ground for 200 fields. On board the aircraft were six microwave radiometers, ranging in wavelength from 21 cm to 8 mm. The results of one of these radiometers are presented.

Schmugge, T. J.↗
NASA NTRS1975

Remote estimation of soil moisture

Two methods under consideration for making remote estimates of soil moisture involve measurements made in electromagnetic spectral region of 0.4 to 14.0 micrometers: (1) spectral reflectance, (2) soil temperature.

Blanchard, M. B.↗
NASA NTRS1988

Effects of spatial variations of soil moisture and vegetation on the initiation of a local severe storm

The role of evapotranspiration in a prestorm environment and the way in which a local severe storm initiates under the influence of spatial variations of soil moisture and vegetation coverage are examined. The Goddard Mesoscale Atmospheric Simulation System (Kaplan et al., 1982) is used to study the case of an isolated but intense convective storm associated with the Grand Island, Nebraska, tornado on June 3-4, 1980. It is found that spatial variations of vegetation and soil moisture increase the surface temperature gradient, enhance the thermally direct ageostrophic circulation, intensify the surface pressure gradient, and enhance the geostrophic low-level southerly flow.

Chang, Jy-Tai↗