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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

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

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

Soman, Vishwas V.↗
NASA NTRS1997

A Comparison of Soil Moisture Retrieval Models Using SIR-C Measurements over the Little Washita River Watershed

Six SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahoma during 11-17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05-0.06 cu cm/cu cm, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.

Wang, J. R.↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS2000

The Influence of Soil Moisture, Coastline Curvature, and Land-Breeze Circulations on Sea-Breeze Initiated Precipitation

Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.

Baker, David R.↗
NASA NTRS2000

Soil, Groundwater, Surface Water, and Sediments of Kennedy Space Center, Florida: Background Chemical and Physical Characteristics

This study documented background chemical composition of soils, groundwater, surface; water, and sediments of Kennedy Space Center. Two hundred soil samples were collected, 20 each in 10 soil classes. Fifty-one groundwater wells were installed in 4 subaquifers of the Surficial Aquifer and sampled; there were 24 shallow, 16 intermediate, and 11 deep wells. Forty surface water and sediment samples were collected in major watershed basins. All samples were away from sites of known contamination. Samples were analyzed for organochlorine pesticides, aroclors, chlorinated herbicides, polycyclic aromatic hydrocarbons (PAH), total metals, and other parameters. All aroclors (6) were below detection in all media. Some organochlorine pesticides were detected at very low frequencies in soil, sediment, and surface water. Chlorinated herbicides were detected at very low frequencies in soil and sediments. PAH occurred in low frequencies in soiL, shallow groundwater, surface water, and sediments. Concentrations of some metals differed among soil classes, with subaquifers and depths, and among watershed basins for surface water but not sediments. Most of the variation in metal concentrations was natural, but agriculture had increased Cr, Cu, Mn, and Zn.

Shmalzer, Paul A.↗
NASA NTRS2000

Soil Moisture Memory in Climate Models

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.

Koster, Randal D.↗
NASA NTRS2001

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Oglesby, Robert J.↗
NASA NTRS2002

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger.

Oglesby, Robert J.↗
NASA NTRS2004

Vapor Deposition and Solar Wind Implantation on Lunar Soil-Grain Surfaces as Comparable Processes

Vapor deposited patinas (VDP) on lunar soil grains consist of a thin (less than 1 micron) layer of amorphous silicate (glass) embedded with nanoscale Fe(sup 0) globules as seen in many TEM images. VDPs are also present on larger space-weathered lunar rocks; these larger samples will not be discussed here although the process of vapor deposition is common to exposed grains of all sizes. Whether or not the majority of the Fe(sup 0) globules present in lunar soils reside in vapor deposited patina is a matter of some concern. Some Fe(sup 0) globules are clearly seen to reside within the glass of agglutinates and might represent remobilized Fe(sup 0) in agglutinitic melts. remobilized Fe(sup 0) in agglutinitic melts. We argue that because VDP coatings are present only on the surfaces of lunar soil grains, their distribution as a surface correlated component (SCC) of lunar soils should parallel those of Solar Wind Elements (SWE) implanted in the outermost rinds of lunar soil grains. SWE residing in the interior of soils grains make up the volume correlated component (VCC). Relative to Fe(sup 0) in VDP, the distribution of various SWE have been studied well. The reason is understandable because instrumentation for nanoscale imaging is not ubiquitous. In this study we use the distribution of SWE in lunar soils as a guide to understanding the fate of Fe(sup 0) in VDP.

Basu, A.↗
NASA NTRS1993

Reflectance and Mossbauer spectroscopy of ferrihydrite-montmorillonite assemblages as Mars soil analog materials

Spectroscopic analyses show that Fe(3+)-doped smectites prepared in the laboratory exhibit important similarities to the soils on Mars. Ferrihydrite has been identified as the interlayer ferric component in Fe(3+)-doped smectites by a low quadrupole splitting and magnetic field strength of approximately 48 tesla in Mossbauer spectra measured at 4.2 K, as well as a crystal field transition at 0.92 micrometer. Ferrihydrite in these smectites explains features in the visible-near infrared region that resemble the energies and band strengths of features in reflectance spectra observed for several bright regions on Mars. Clay silicates have met resistance in the past as Mars soil analogs because terrestrial clay silicates exhibit prominent hydrous spectral features at 1.4, 1.9, and 2.2 micrometers; and these are observed weakly, if at all, in reflectance spectra of Mars. However, several mechanisms can weaken or compress these features, including desiccation under low-humidity conditions. The hydration properties of the interlayer cations also effect band strengths, such that a ferrihydrite-bearing smectite in the Martian environment would exhibit a 1.9 micrometers H2O absorption that is even weaker than the 2.2 micrometers structural OH absorption. Mixing experiments demonstrate that infrared spectral features of clays can be significantly suppressed and that the reflectance can be significantly darkened by mixing with only a few percent of a strongly absorbing opaque material. Therefore, the absolute reflectance of a soil on Mars may be disproportionately sensitive to a minor component. For this reason, the shape and position of spectral features and the chemical composition of potential analogs are of utmost importance in assessing the composition of the soil on Mars. Given the remarkable similarity between visible-infrared reflectance spectra of soils in bright regions on Mars and Fe(3+)-doped montmorillonites, coupled with recent observations of smectites in SNC meteorites and a weak 2.2 micrometers absorption in some Mars soils, ferrihydrite-bearing smectites warrant serious consideration as a Mars soil analog.

NASA Discipline Exobiology↗
NASA NTRS2005

Extracting Quantitative Data from Lunar Soil Spectra

Using the modified Gaussian model (MGM) developed by Sunshine et al. [1] we compared the spectral properties of the Lunar Soil Characterization Consortium (LSCC) suite of lunar soils [2,3] with their petrologic and chemical compositions to obtain quantitative data. Our initial work on Apollo 17 soils [4] suggested that useful compositional data could be elicited from high quality soil spectra. We are now able to expand upon those results with the full suite of LSCC soils that allows us to explore a much wider range of compositions and maturity states. The model is shown to be sensitive to pyroxene abundance and can evaluate the relative portion of high-Ca and low-Ca pyroxenes in the soils. In addition, the dataset has provided unexpected insights into the nature and causes of absorption bands in lunar soils. For example, it was found that two distinct absorption bands are required in the 1.2 m region of the spectrum. Neither of these bands can be attributed to plagioclase or agglutinates, but both appear to be largely due to pyroxene.

Noble, S. K.↗
NASA NTRS2005

NASA Soil Moisture Data Products and Their Incorporation in DREAM

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.

Blonski, Slawomir↗
NASA NTRS1982

Method for evaluating moisture tensions of soils using spectral data

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

Peterson, John B.↗
NASA NTRS2009

Improved Instrument for Detecting Water and Ice in Soil

An instrument measures electrical properties of relatively dry soils to determine their liquid water and/or ice contents. Designed as a prototype of instruments for measuring the liquid-water and ice contents of lunar and planetary soils, the apparatus could also be utilized for similar purposes in research and agriculture involving terrestrial desert soils and sands, and perhaps for measuring ice buildup on aircraft surfaces. This instrument is an improved version of the apparatus described in Measuring Low Concentrations of Liquid Water and Ice in Soil (NPO-41822), NASA Tech Briefs, Vol. 33, No. 2 (February 2009), page 22. The designs of both versions are based on the fact that the electrical behavior of a typical soil sample is well approximated by a network of resistors and capacitors in which resistances decrease and capacitances increase (and the magnitude and phase angle of impedance changes accordingly) with increasing water content. The previous version included an impedance spectrometer and a jar into which a sample of soil was placed. Four stainless-steel screws at the bottom of the jar were used as electrodes of a fourpoint impedance probe connected to the spectrometer. The present instrument does not include a sample jar and can be operated without acquiring or handling samples. Its impedance probe consists of a compact assembly of electrodes housed near the tip of a cylinder. The electrodes protrude slightly from the cylinder (see Figure 1). In preparation for measurements, the cylinder is simply pushed into the ground to bring the soil into contact with the electrodes.

Buehler, Martin↗
NASA NTRS2009

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

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

Reichle, Rolf↗
NASA NTRS2011

NASA Soil Moisture Active Passive (SMAP) Mission Formulation

The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and ground processing designs.

Entekhabi, Dara↗
NASA NTRS2011

Analysis of Mars Analogue Soil Samples Using Solid-Phase Microextraction, Organic Solvent Extraction and Gas Chromatography/Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) are robust and abundant molecules in extraterrestrial environments. They are found ubiquitously in the interstellar medium and have been identified in extracts of meteorites collected on Earth. PAHs are important target molecules for planetary exploration missions that investigate the organic inventory of planets, moons and small bodies. This study is part of an interdisciplinary preparation phase to search for organic molecules and life on Mars. We have investigated PAH compounds in desert soils to determine their composition, distribution and stability. Soil samples (Mars analogue soils) were collected at desert areas of Utah in the vicinity of the Mars Desert Research Station (MDRS), in the Arequipa region in Peru and from the Jutland region of Denmark. The aim of this study was to optimize the solid-phase microextraction (SPME) method for fast screening and determination of PAHs in soil samples. This method minimizes sample handling and preserves the chemical integrity of the sample. Complementary liquid extraction was used to obtain information on five- and six-ring PAH compounds. The measured concentrations of PAHs are, in general, very low, ranging from 1 to 60 ng g(sup -1). The texture of soils is mostly sandy loam with few samples being 100% silt. Collected soils are moderately basic with pH values of 8-9 except for the Salten Skov soil, which is slightly acidic. Although the diverse and variable microbial populations of the samples at the sample sites might have affected the levels and variety of PAHs detected, SPME appears to be a rapid, viable field sampling technique with implications for use on planetary missions.

Orzechowska, G. E.↗
NASA NTRS2011

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

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

Kumar, Sujay V.↗