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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.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Controlled evolution of rare earth phosphate in coal ash slag

Coal ash slag as a waste by-product, is generated from commercial processes that include gasification facilities, power plants, and steelmaking industries. Some is recycled into construction materials, insulation fibers, and used as a soil neutralizer, but the majority is still discarded. Coal ash slag exhibit trace amounts of critical materials including rare earth elements (REEs). An economically viable extraction of REEs from the coal ash would lower the production costs, addressing the availability and environmental concerns. In nature, most REEs exist as phosphate such as monazite but its synthetic evolution in coal ash slag has never been reported. In industrial processes, P may originate from coal, additives, and/or refractory liners. REEs may be extracted by first concentrating REEs into phosphates, sulphide, or fluorides [1], or carbonates [2]. In this work, P-enriched coal ash slag bearing REEs was first melted above 1600 °C, then crystallization behaviors in the melt during controlled cooling was studied. REE phosphate coprecipitated with mullite and hematite with mullite being the first crystal to form on cooling. The REEs were rejected from the molten slag, mullite, and hematite, and tended to segregate only to the phosphate phase with REE concentration as high as 58 wt.% in the structure.

Nakano, Jinichiro↗
DOE OSTI2020

Depth-resolved soil data from DOE-LM Riverton Wyoming site, April-September 2017

Averaged (from 3 to 5 replicates) and QA/QC:d data for soil cores taken roughly every month in the period April 5 to September 13 in 2017 at a location close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site. The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were separated into 5-20 cm segments based on soil horizonation and each segment was subsampled for microbial analyses (data available at the NCBI Single Read Archive (SRA) Database, https://www.ncbi.nlm.nih.gov/sra/, BioProject ID# PRJNA626616) in addition to the soil analyses included in this dataset. The soil analyses dataset includes aerobic and anaerobic respiration rate estimates (MicroResp method), water content estimates (on collected samples, not in situ), total C, N, S, Ca, K, Mg, Na, Fe, As, Mo, U, and organic-C concentrations, water extractable concentrations of the same elements, and HCl-extractable Fe(II) concentrations.There are four files included in this data package: metadataFile.csv, avgDataFile.csv, methodFile.csv, and RVT2017soilData.xlsx. The excel file contains the same information as the individual csv-files (in separate tabs).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Lunar Soil Enrichment for Plant Production: WILD (Waste Improved Lunar Dirt)

To identify a process to generate a fertile soil for plant growth using lunar regolith and waste compost, several qualitative and quantitative investigations were performed. The primary focus of this project was to demonstrate the feasibility of microbe bioleaching to extract inorganic plant nutrients (P and K) from lunar regolith simulant. This was achieved by developing a screening test method to identify microbial candidates that would effectively bioleach P and K from JSC-1A. Quantitative bioleaching test using the downselected microbes (Pantoea Agglomerans (P. agglo) and a plant-relevant consortium) were then performed. The second focus of the project was to validate the approach of waste compost utilization to improve water retention and fertility of lunar regolith for food production. This was achieved by measuring the water retention property of the mixture of compost and regolith at different ratio and conducting microgreen growth experiments with compost/regolith mixtures. The team also discovered from this study that some native microbes associated with JSC-1A can form biofilm containing JSC-1A particles (a type of soil crust), which showed potential as an ISRU geomicrobiological dust mitigation method for Lunar or Martian applications.

Ray Pitts↗
DOE OSTI2022

Characterizing Bioavailable Soil Nutrients Across Coastal Systems: Western Lake Erie and Chesapeake Bay

Terrestrial Aquatic Interfaces (TAIs), defined as where land meets water, exhibit important hydrological, biological, and biogeochemical dynamics and play a critical role in the Earth’s carbon cycle. Current Earth System Models improperly represent this role due to the complexity of these systems and the disproportionally large impact TAIs have relative to their area. To improve our predictive capacity of coastal system dynamics, a better understanding of carbon and nutrient cycling across TAI’s is needed. Coastal Observations, Mechanisms, and Predictions Across Systems and Scales (COMPASS) aims to achieve this through field observations and laboratory incubations throughout the Western Lake Erie and Chesapeake Bay regions. Here, we report on preliminary results from a soil characterization experiment across the WLE and CB regions. This experiment was conducted as part of the 2-year field, measurements, and experiments (FME) pilot study portion of COMPASS to provide initial baseline data for the sites and to characterize the spatial variability of our analytes. Soil samples were collected from three locations along the TAI transect (upland forest, transitional forest, and wetland) and analyzed for bioavailable nutrients using three types of extractions: (a) water extractions, (b) 2M KCl extractions, and (c) 1M NH4Cl extractions to analyze (a) water soluble organic carbon (WSOC), (b) ammonium and nitrate, and (c) base cations, including Ca, Mg, Na, K, and Fe. These analyses, in conjunction with other bulk physicochemical analyses, will help establish baseline understanding of these sites to drive future research and design focused experiments that will ultimately improve our predictive understanding of these freshwater and marine coastal TAIs and their response to short and long-term changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Molecular and morphological characterization of Tylenchus zeae n. sp. (Nematoda: Tylenchida) from Corn ( Zea mays ) in South Carolina

Specimens of a tylenchid nematode were recovered in 2019 from soil samples collected from a corn field, located in Pickens County, South Carolina, USA. A moderate number of Tylenchus sp. adults (females and males) were recovered. Extracted nematodes were examined morphologically and molecularly for species identification, which indicated that the specimens of the tylenchid adults were a new species, described herein as Tylenchus zeae n. sp. Morphological examination and the morphometric details of the specimens were very close to the original descriptions of Tylenchus sherianus and T. rex. However, females of the new species can be differentiated from these species by body shape and length, shape of excretory duct, distance between anterior end and esophageal intestinal valve, and a few other characteristics given in the diagnosis. Males of the new species can be differentiated from the two closely related species by tail, spicules, and gubernaculum length. Cryo-scanning electron microscopy confirmed head bearing five or six annules; four to six cephalic sensilla represented by small pits at the rounded corners of the labial plate; a small, round oral plate; and a large, pit-like amphidial opening confined to the labial plate and extending three to four annules beyond it. Phylogenetic analysis of 18S rRNA gene sequences placed Tylenchus zeae n. sp. in a clade with Tylenchus arcuatus and several Filenchus spp., and the mitochondrial cytochrome oxidase c subunit 1 (COI) gene region separated the new species from T. arcuatus and other tylenchid species. In the 28S tree, T. zeae n. sp. showed a high level of sequence divergence and was positioned outside of the main Tylenchus-Filenchus clade.

18S↗
DOE OSTI2024

Linkages Between Mineral Element Composition of Soils and Sediments With Hyporheic Zone Dissolved Organic Matter Chemistry Across the Contiguous United States

The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x-ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo-metal linkages into multi-scale hydrobiogeochemical models.

58 GEOSCIENCES↗
DOE OSTI2020

Iron mineral dissolution releases iron and associated organic carbon during permafrost thaw

It has been shown that reactive soil minerals, specifically iron(III) (oxyhydr)oxides, can trap organic carbon in soils overlying intact permafrost, and may limit carbon mobilization and degradation as it is observed in other environments. However, the use of iron(III)-bearing minerals as terminal electron acceptors in permafrost environments, and thus their stability and capacity to prevent carbon mobilization during permafrost thaw, is poorly understood. We have followed the dynamic interactions between iron and carbon using a space-for-time approach across a thaw gradient in Abisko (Sweden), where wetlands are expanding rapidly due to permafrost thaw. We show through bulk (selective extractions, EXAFS) and nanoscale analysis (correlative SEM and nanoSIMS) that organic carbon is bound to reactive Fe primarily in the transition between organic and mineral horizons in palsa underlain by intact permafrost (41.8 ±10.8 mg carbon per g soil, 9.9 to 14.8% of total soil organic carbon). During permafrost thaw, water-logging and O 2 limitation lead to reducing conditions and an increase in abundance of Fe(III)-reducing bacteria which favor mineral dissolution and drive mobilization of both iron and carbon along the thaw gradient. By providing a terminal electron acceptor, this rusty carbon sink is effectively destroyed along the thaw gradient and cannot prevent carbon release with thaw.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Intensive agricultural management‐induced subsurface accumulation of labile phosphorus in Midwestern agricultural soils dominated by tile lines

Abstract In addition to surface runoff, subsurface P loss through tile lines in agricultural lands has received attention over the last decade. It is not clearly understood how this strong ligand, phosphate, is distributed in subsoils (≤180 cm), contributing to subsurface P loss. We hypothesized that subsurface accumulation of labile P as a result of long‐term intensive agricultural management contributes to subsurface P loss. The depth sequence distribution of P and its speciation and reactivity were investigated in tile‐line‐dominated Midwestern agricultural fields via chemical extraction and digestion, batch desorption experiments, and X‐ray absorption near‐edge structure spectroscopy. The results suggest that labile P in subsoils exceeds the eutrophication‐inducing level (>0.01 mg L –1 ). Because of intensive agricultural management, total P was ∼400 mg kg –1 in surface soils and ∼200‐300 mg kg –1 in subsoils. The depth sequence distribution of P indicated the translocation of P to subsoils. Although phosphate and phytic acid adsorbed by Al or Fe (oxyhydro)oxides and calcite were found in surface soils, phosphate adsorbed to calcite, hydroxyapatite, or both were the dominant P species in subsoils. Phosphate was highest in surface soils and decreased sharply with increasing depth. Slightly alkaline soil in subsoils suppressed the release of P but the process was continuous after 30 d. Subsurface P loss was influenced by the dissolution and desorption process of inorganic P phases and preferentially transported P from surface soils. Subsurface P loss should be considered in strategies to reduce agricultural P loss in the Gulf of Mexico.

Xu, Suwei↗
NASA NTRS1975

Separation of man-made and natural patterns in high-altitude imagery of agricultural areas

A nonstationary linear digital filter is designed and implemented which extracts the natural features from high-altitude imagery of agricultural areas. Essentially, from an original image a new image is created which displays information related to soil properties, drainage patterns, crop disease, and other natural phenomena, and contains no information about crop type or row spacing. A model is developed to express the recorded brightness in a narrow-band image in terms of man-made and natural contributions and which describes statistically the spatial properties of each. The form of the minimum mean-square error linear filter for estimation of the natural component of the scene is derived and a suboptimal filter is implemented. Nonstationarity of the two-dimensional random processes contained in the model requires a unique technique for deriving the optimum filter. Finally, the filter depends on knowledge of field boundaries. An algorithm for boundary location is proposed, discussed, and implemented.

Samulon, A. S.↗
NASA NTRS2004

Detecting Organic Compounds in Martian Soil Analogues Using Gas Chromatography Mass Spectrometry

One of the primary objectives of the 1976 Viking missions was to determine whether organic compounds, possibly of biological origin, were present in the Martian surface soils. The Viking gas chromatography mass spectrometry (GCMS) instruments found no evidence for any organic compounds of Martian origin above a few parts per billion in the upper 10 cm of surface soil [l], suggesting the absence of a widely distributed Martian biota. However, Benner et d. have suggested that significant amounts of non-volatile organic compounds, possibly including oxidation products of bioorganic molecules (e.g. carboxylic acids) would not have been detected by the Viking GCMS [2]. Moreover, other key organic compounds important to biology, such as amino acids and nucleobases, would also likely have been missed by the Viking GCMS as these compounds require chemical derivatization to be stable in a GC column [3]. Recent pyrolysis experiments with a Mars soil analogue that had been innoculated with Escherichia coli bacteria have shown that amino acid decomposition products (amines) and nucleobases are among the most abundant products generated after pyrolysis of the bacterial cells [4,5]. At the part per billion level (Viking GCMS detection limit), these pyrolysis products generated from several million bacterial cells per gram of Martian soil would not have been detected by the Viking GCMS instruments [4]. Analytical protocols are under development for upcoming in situ lander opportunities to target several important biological compounds including amino acids and nucleobases. For example, extraction and chemical derivatization techniques [3] are being adapted for space flight use to transform reactive or fragile molecules that would not have been detected by the Viking GCMS instruments, into species that are sufficiently volatile to be detected by GCMS. Recent experiments carried out at NASA Goddard have shown that using this derivatization technique all of the targeted compounds mentioned above can be separated on a GC column and detected by MS at sub-picomole (< 10(exp -l2 mole) levels. With these methods, the detection limit for amino acids, carboxylic acids and nucleobases is several orders of magnitude more sensitive than the Viking GCMS instruments for these compounds. Preliminary results using this analytical technique on a variety of Martian soil analogues will be presented.

Glavin, D. P.↗
DOE OSTI2022

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
DOE OSTI2026

Synchrotron resolved microscale mineralogy and elemental composition of individual plinthic and manganiferous nodules from agricultural soils

Iron and manganese oxides are strong sorbents and elemental scavengers in the environment that can form macroscopic nodules in soils. Despite their importance in the geochemical cycling of nutrients and contaminants, nodules are rarely characterized. When analyzed, they are often combined into bulk samples, obscuring individual characteristics. This study investigates the composition and mineralogy of individual plinthic and manganiferous nodules in soil from cropping systems in the Farming Systems Project in Beltsville, Maryland. Elemental composition indicates the accumulation of contaminants and nutrients, including copper in all nodules and high levels of phosphorus in select nodules. Sequential extractions determine that highly crystalline minerals comprise the nodules, locking away these nutrients and contaminants. Bulk X-ray diffraction (XRD) demonstrated distinct mineralogies in the plinthic and manganiferous nodules, with the former comprised of quartz, goethite, and kaolinite, and the latter consisting of quartz, Mn 2 O 3 , and hematite. Synchrotron and laboratory-based X-ray fluorescence (XRF) mapping gives critical insight into the elemental distribution within the nodules and elucidates spatial elemental associations, including the coupling of manganese and iron in the manganiferous nodules. XRF maps paired with µXRD provide microscale spatial resolution in mineralogy, which resolved several phases not apparent in bulk XRD, manganese’s association with goethite, and minerals indicative of redox transformations, including magnetite and maghemite. These novel results provide critical insight into the microscale mineralogy and individual elemental composition of plinthic and manganiferous nodules, as well as how they alter bulk soil geochemistry in ways largely unaccounted for in research on soil systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Pigmenting agents in Martian soils: inferences from spectral, Mossbauer, and magnetic properties of nanophase and other iron oxides in Hawaiian palagonitic soil PN-9

We have examined a Hawaiian palagonitic tephra sample (PN-9) that has spectroscopic similarities to Martian bright regions using a number of analytical techniques, including Mossbauer and reflectance spectroscopy, X-ray diffraction, instrumental neutron activation analysis, electron probe microanalysis, transmission electron microscopy, and dithionite-citrate-bicarbonate extraction. Chemically, PN-9 has a Hawaiitic composition with alkali (and presumably silica) loss resulting from leaching by meteoric water during palagonitization; no Ce anomaly is present in the REE pattern. Mineralogically, our results show that nanophase ferric oxide (np-Ox) particles (either nanophase hematite (np-Hm) or a mixture of ferrihydrite and np-Hm) are responsible for the distinctive ferric doublet and visible-wavelength ferric absorption edge observed in Mossbauer and reflectivity spectra, respectively, for this and other spectrally similar palagonitic samples. The np-Ox particles appear to be imbedded in a hydrated aluminosilicate matrix material; no evidence was found for phyllosilicates. Other iron-bearing phases observed are titanomagnetite, which accounts for the magnetic nature of the sample; olivine; pyroxene; and glass. By analogy, np-Ox is likely the primary pigmenting agent of the bright soils and dust of Mars.

Minerals/analysis↗
NASA NTRS1996

On the Capabilities of Using AIRSAR Data in Surface Energy/Water Balance Studies

The capabilities of using remote sensing data, and in particular multifrequency/multipolarization SAR data, like AIRSAR, for the retrieval of surface parameters, depend considerably on the specificity of each application. The potentials, and limitations, of SAR data in ecological investigations are well known. Because the chemistry is a major component in such studies and because of the almost lacking chemical information at the wavelengths of SAR data, the capabilities of using SAR-derived information in such studies are considerably limited. However, in the case of surface energy/water balance studies, the determination of the amount of water content, both in the soil and in the plants, is a major component in all modeling approaches. As the information about water content is present in the SAR signal, then the role of SAR data in studies where water content is to be determined becomes clearly predominant. Another situation where the role of SAR data becomes dominant over other remote sensing systems is the case of dense canopies. Because of the penetration capabilities of microwave data, which is especially superior as compared to optical data, information about the canopy as a whole and even the underlying soil is contained in the SAR data, while only the top canopy provides the information content in the case of optical data. In the case of relatively dense canopies, as has been demonstrated in this study, such different penetration capabilities provide very different results in terms of the derived total canopy water content, for instance. However, although all such capabilities are well known, unfortunately there are also well known limitations. Apart from calibration-related aspects (that we will not consider in this study), and apart from other intrinsic problems (like image noise, topographic corrections, etc.) which also significantly affect the derived results, we will concentrate on the problem of extracting information from the data. Even at this level, methods are still not fully well established, especially over vegetation-covered areas. In this paper, an algorithm is described which allows derivation of three fundamental parameters from SAR data: soil moisture, soil roughness and canopy water content, accounting for the effects of vegetation cover by using optical (Landsat) data as auxiliary. Capabilities and limitations of the data and algorithms are discussed, as well as possibilities to use these data in energy/water balance modeling studies. All the data used in this study were acquired as part of the Intensive Observation Period in June-July 1991 (European Multisensor Aircraft Campaign-91), as part of the European Field Experiment in a Desertification- threatened Area (EFEDA), a European contribution to the global-change research sponsored by the IGBP program (Bolle et al., 1993).

Moreno, Jose F.↗