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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mobilization of mercury from contaminated creekbank soils

The industrial use of mercury (Hg) led to the contamination of numerous watersheds worldwide, including the East Fork Poplar Creek (EFPC) in Tennessee, USA. Mercury can accumulate in creek banks and floodplain soils and is mobilized into downstream environments due to erosion from precipitation and flooding. Here, this study aimed to evaluate the geochemical conditions contributing to the release of Hg from contaminated soils in this watershed. Bank soil samples from the EFPC watershed with total Hg concentrations ranging from 27.2 to 1,425 mg·kg −1 were used in a series of batch experiments with artificial creek water at a solid-to-solution ratio of 1:30 to assess Hg release. Additional experiments examined Hg release across different soil size fractions and solid-to-solution ratios, as well as the effect of dissolved organic matter and time on Hg mobilization. Mercury release ranged from 0.011 to 0.17% of the total soil Hg and is correlated with total Hg concentrations. Variations in release among size fractions suggested heterogeneous distribution of labile Hg species. Results indicated two distinct solubility regimes depending on solid-to-solution ratios. Dissolved organic matter enhanced Hg release, and time-dependent experiments showed that changes in mercury speciation could decrease dissolved Hg concentrations over time. Identifying conditions that promote Hg mobilization from contaminated soils improves our understanding of Hg fluxes into downstream environments. Key factors influencing mercury release include soil characteristics, water chemistry, and temporal changes in mercury speciation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Modeling and Simulation of Vehicle Dynamics on the Surface of Phobos

In this paper we analyze the dynamics of a spacecraft in proximity of Phobos by developing the equations of motion of a test mass in the Phobos rotating frame using a model based on circularly-restricted three body problem, and by analyzing the dynamics of a ATHLETE hopper vehicle interacting with the soil under different soil-interaction conditions. The main conclusion of the numerical studies is that the system response is dominated by the stiffness and damping parameters of the leg springs, with the soil characteristics having a much smaller effect. The system simulations identify ranges of parameters for which the vehicle emerges stably (relying only on the passive viscoelastic damper at each leg) or unstably (needing active attitude control) from the hop. The implication is that further experimental and possibly computational modeling work, as well as site characterization (from precursor missions) will be necessary to obtain validated performance models.

soil-structure interaction↗
DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

Switchgrass ( Panicum virgatum L.) is a native North American grass currently considered a high-potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30-year history of contrasting tillage and N-fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no-till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no-till. Fertilized no-till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect.

bioenergy crop production system↗
DOE OSTI2026

Dataset about Warming Effects on Carbon Cycling and Greenhouse Gas Fluxes in Permafrost Ecosystems

Field observations provide direct evidence of how does carbon cycling in permafrost ecosystems respond to climate change. This study provides a comprehensive dataset on the impact of warming on carbon cycling and greenhouse gas (GHG) fluxes in permafrost ecosystems. The dataset is extracted and integrated from 132 peer-reviewed studies with 1430 paired observations across eight major permafrost ecosystems, including Arctic and subarctic tundra and wetland, and alpine meadow, steppe, tundra and wetland. This dataset includes 17 variables from experiments conducted during the growing season, covering the plant and soil carbon pools, soil nitrogen pool, and GHG (i.e., CO 2 , CH 4 , and N 2 O) fluxes, among others. Background information on site climate conditions, vegetation and soil characteristics, and details of the warming experiments, including timing, methods, and warming magnitude, are also contained in the dataset. This dataset facilitates a comprehensive understanding of the impact of warming on carbon cycling and GHG fluxes in permafrost ecosystems, and provides supports for meta-analyses and literature reviews, remote sensing data validation, and land model development and parameterization.

Bao, Tao [Chinese Academy of Sciences (CAS), Beiji↗
DOE OSTI2025

NitroNet: Smart System to Quantify Nitrous Oxide Emissions

Agricultural croplands are the largest anthropogenic source of nitrous oxide (N 2 O), the third most important greenhouse gas. Emissions are characterized by “hot spots” and “hot moments”, meaning emissions are highly heterogeneous in space and time. Emissions are driven by nitrification and denitrification processes which depend upon complex factors such as soil characteristics (type, compaction, pH, moisture, topography), management practices (fertilizer type and application, tillage, crop type, field history, irrigation), biogeochemistry (organic carbon, microbial composition), and meteorology (precipitation, temperature, and wind). For these reasons, quantifying cropland emissions by either measurements or modeling is extremely challenging with large uncertainties.

09 BIOMASS FUELS↗
DOE OSTI2025

CO2 Profiling System for CO2 Storage (a1-level)

The Southern Great Plains (SGP) carbon dioxide flux (CO2FLUX) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), sensible heat, and momentum. The systems use the eddy covariance technique, which computes the fluxes from the vertical wind speed in combination with the concentrations of CO2 and H2O, temperature, and horizontal wind speed, respectively. A 3D sonic anemometer obtains the wind components and the temperature, while an infrared gas analyzer measures CO2 and H2O. A sub-system also measures half-hour averages of radiation, meteorological, and soil measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NGEE Arctic Tram: Periodic Soil Moisture, Temperature, and Thaw Depth Measurements across Polygonal Tundra, Utqiagvik (Barrow), Alaska, 2014-2015

Manual measurements of soil moisture, temperature, and thaw depth were collected in the footprint of the NGEE Arctic Tram starting 2014-07-20 and continuing through 2015-07-16. There were 10 periodic sampling events with measurements in one *.csv file. These measurements were collected under the Tram observational platform. Probes were inserted into ground beneath the track closest to Tram sensors measurement locations at each Tram measurement position (Position # marked on the tracks). A MiniTrase Time Domain Reflectometry (TDR) instrument was used to measure volumetric water content (VWC; units = m3/m3). Soil temperature was measured with a thermocouple probe. Depth of thawed soil was measured from the top of the moss layer or top of soil. See user guide for more information *.pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Mapping of soil banks using ERTS-1 pictures

Earth Resources Technology Satellite (ERTS-1) pictures of different wavelengths (MSS 4,5,6,7) were used in the study of two strip mine areas in southeastern Ohio. The first area was near Piedmont Lake and the second area was near New Lexington. Prints were examined under a binocular microscope and the gray tone was correlated with the actual ground conditions at several sites. For the New Lexington area, color infrared pictures taken at an elevation of 18,000 feet were also used for correlation with the ERTS-1 imagery. The results indicate that MSS 5 and 7 are most useful in defining the stripped land and show that the hydrological and soil characteristics are remarkably different than the surrounding lands.

Ahmad, M. U.↗
NASA NTRS1979

Natural sampling strategy

A natural stratum-based sampling scheme and the aggregation procedures for estimating wheat area, yield, and production and their associated prediction error estimates are described. The methodology utilizes LANDSAT imagery and agrophysical data to permit an improved stratification in foreign areas by ignoring political boundaries and restratifying along boundaries that are more homogeneous with respect to the distribution of agricultural density, soil characteristics, and average climatic conditions. A summary of test results is given including a discussion of the various problems encountered.

Hallum, C. R.↗
NASA NTRS1980

Development of a digital data base for reflectance-related soil information

A digital soils data base established for inclusion of soil reflectance data, physical, chemical, and engineering measurements, and site information is discussed. Initial data are taken from 500 soil samples covering the spectral range of 0.5 to 2.3 microns. Information obtained from each observation includes spectral data, and identification records with the soil and spectral observation parameters. The LARSPEC software system is available to retrieve and manipulate information, and scattergrams of identification and spectral data allow the initiation of statistical analyses of soil data. In addition, soil characteristics, graphical displays of reflectance spectra, and identification information examples are given.

Stoner, E. R.↗
NASA NTRS1981

Active microwave investigation of snowpacks: Experimental documentation, Colorado 1979-1980

During the winter of 1979-1980, the University of Kansas Microwave Active Spectrometer systems measured the backscattering properties of snowpacks under varying conditions at four test sites in Colorado. In addition to the radar data over 1-35 GHz, ground-truth measurements of the atmospheric, snow, and soil characteristics were obtained for each radar data set. The test sites, data acquisition procedures, and data that were acquired in this experiment are presented and described.

Stiles, W. H.↗
NASA NTRS1982

Geographic Information System in Bolivia: a Case Study for Latin America

Bolivia's Geological Service is concluding a successful project designed to give the Department of Oruro the capability to evaluate its natural resources using data generated by three United States satellites. A permanent integrated geographic information system was created for preparing base maps of soil characteristics, land use, geomorphology, geology, water resources and hydrology. The information compiled through the project was stored on magnetic disks and tapes to permit periodic updating, retrieval of data on specific aspects of development projects, and obtaining various data mixes to analyze aspects of prospective development projects. This is the first digital information system developed in Latin America.

Adrien, P. M.↗
NASA NTRS1984

Investigations of vegetation and soils information contained in LANDSAT Thematic Mapper and Multispectral Scanner data

An extension of the TM tasseled cap transformation to reflectance factor data is presented, and the basic concepts underlying the tasseled cap transformations are described. The ratio of TM bands 5 and 7, and TM tasseled cap wetness, are both shown to offer promise of direct detection of available soil moisture. Some effects of organic matter and other soil characteristics or constituents on TM tasseled cap spectral response are also considered.

Crist, E. P.↗
NASA NTRS1986

Analysis of substrate and plant spectral features of semi-arid shrub communities in the Owens Valley, California

Airborne Imaging Spectrometer (AIS) data were analyzed to deduce plant density and species composition in three semi-arid shrub-dominated communities of Owens Valley, CA, occurring on either a sand, granite alluvium, or basalt substrate. The high-spectral resolution AIS data were related to spectra obtained with field portable spectrometers, which in turn were related to plant and soil characteristics of the communities. Many of the dominant species have unique spectral features which permit their identification in AIS pixel images. The canopy-induced shadow may be a major factor influencing substrate spectral properties during fall and winter, because of low sun angles. Moreover, changes in spectral signatures following dormancy and leaf senescence tend to decrease contrasts between the plant community and the geologic substrate, also suggesting that fall and winter are a difficult time of year for spectral analyses.

Ustin, S. L.↗
NASA NTRS1987

Science synergism study for EOS on evolution of desert surfaces

The effectiveness of EOS data as a basis for the study of desert surfaces' evolution is presently evaluated for both long and short term geomorphic evolution. Attention is given to the usefulness of such sensor systems planned for EOS as MODIS for regional vegetation distribution/variability monitoring, HIRIS for visible-near IR observations, TIMS for lithological identification, HMMR and SSMI for soil characteristics, LASA for atmospheric profiles, SAR for surface roughness, ALT for two-dimensional topography, ACR for the calibration of imaging sensors, and ERBE for climate modeling and regional surface albedo variation determinations.

Farr, Tom G.↗
NASA NTRS1987

Discriminating semiarid vegetation using airborne imaging spectrometer data - A preliminary assessment

A preliminary assessment was made of Airborne Imaging Spectrometer (AIS) data for discriminating and characterizing vegetation in a semiarid environment. May and October AIS data sets were acquired over a large alluvial fan in eastern California, on which were found Great Basin desert shrub communities. Maximum likelihood classification of a principal components representation of the May AIS data enabled discrimination of subtle spatial detail in images relating to vegetation and soil characteristics. The spatial patterns in the May AIS classification were, however, too detailed for complete interpretation with existing ground data. A similar analysis of the October AIS data yielded poor results. Comparison of AIS results with a similar analysis of May Landsat Thematic Mapper data showed that the May AIS data contained approximately three to four times as much spectrally coherent information. When only two shortwave infrared TM bands were used, results were similar to those from AIS data acquired in October.

Thomas, Randall W.↗
NASA NTRS1991

Salinity and spectral reflectance of soils

The basic spectral response related to the salt content of soils in the visible and reflective IR wavelengths is analyzed in order to explore remote sensing applications for monitoring processes of the earth system. The bidirectional reflectance factor (BRF) was determined at 10 nm of increments over the 520-2320-nm spectral range. The effect of salts on reflectance was analyzed on the basis of 162 spectral measurements. MSS and TM bands were simulated within the measured spectral region. A strong relationship was found in variations of reflectance and soil characteristics pertaining to salinization and desalinization. Although the individual MSS bands had high R-squared values and 75-79 percent of soil/treatment combinations were separable, there was a large number of soil/treatment combinations not distinguished by any of the four highly correlated MSS bands under consideration.

Szilagyi, A.↗