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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Properties of Subsurface Soil Cores from Four Geologic Provinces Surrounding Mars Desert Research Station, Utah: Characterizing Analog Martian Soil in a Human Exploration Scenario

The DOMEX program is a NASA-MMAMA funded project featuring simulations of human crews on Mars focused on science activities that involve collecting samples from the subsurface using both manual and robotic equipment methods and analyzing them in the field and post mission. A crew simulating a human mission to Mars performed activities focused on subsurface science for 2 weeks in November 2009 at Mars Desert Research Station near Hanksville, Utah --an important chemical and morphological Mars analog site. Activities performed included 1) survey of the area to identify geologic provinces, 2) obtaining soil and rock samples from each province and characterizing their mineralogy, chemistry, and biology; 3) site selection and reconnaissance for a future drilling mission; 4) deployment and testing of Mars Underground Mole, a percussive robotic soil sampling device; and 5) recording and analyzing how crew time was used to accomplish these tasks. This paper summarizes results from analysis of soil cores

Stoker, C. R.↗
NASA NTRS2014

Global-Scale Comparison of Passive (SMOS) and Active (ASCAT) Satellite Based Microwave Soil Moisture Retrievals with Soil Moisture Simulations (MERRA-Land)

Global surface soil moisture (SSM) datasets are being produced based on active and passive microwave satellite observations and simulations from land surface models (LSM). This study investigates the consistency of two global satellite-based SSM datasets based on microwave remote sensing observations from the passive Soil Moisture and Ocean Salinity (SMOS;SMOSL3 version 2.5) and the active Advanced Scatterometer (ASCAT; version TUWien- WARP 5.5) with respect to LSM SSM from the MERRA-Land data product. The relationship between the global-scale SSM products was studied during the 2010-2012 period using (1) a time series statistics (considering both original SSM data and anomalies), (2) a space-time analysis using Hovmoller diagrams, and (3) a triple collocation error model. The SMOSL3 and ASCAT retrievals are consistent with the temporal dynamics of modeled SSM (correlation R (is) greater than 0.70 for original SSM) in the transition zones between wet and dry climates, including the Sahel, the Indian subcontinent, the Great Plains of North America, eastern Australia, and southeastern Brazil. Over relatively dense vegetation covers, a better consistency with MERRA-Land was obtained with ASCAT than with SMOSL3. However, it was found that ASCAT retrievals exhibit negative correlation versus MERRA-Land in some arid regions (e.g., the Sahara and the Arabian Peninsula). In terms of anomalies, SMOSL3 better captures the short term SSM variability of the reference dataset (MERRA-Land) than ASCAT over regions with limited radio frequency interference (RFI) effects (e.g., North America, South America, and Australia). The seasonal and latitudinal variations of SSM are relatively similar for the three products, although the MERRALand SSM values are generally higher and their seasonal amplitude is much lower than for SMOSL3 and ASCAT. Both SMOSL3 and ASCAT have relatively comparable triple collocation errors with similar spatial error patterns: (i) lowest errors in arid regions (e.g., Sahara and Arabian Peninsula), due to the very low natural variability of soil moisture in these areas, and Central America, and (ii) highest errors over most of the vegetated regions (e.g., northern Australia, India, central Asia, and South America). However, the ASCAT SSM product is prone to larger random errors in some regions (e.g., north-western Africa, Iran, and southern South Africa). Vegetation density was found to be a key factor to interpret the consistency with MERRA-Land between the two remotely sensed products (SMOSL3 and ASCAT) which provides complementary information on SSM. This study shows that both SMOS and ASCAT have thus a potential for data fusion into long-term data records.

ASCAT↗
NASA NTRS2019

Diagnosing Bias in Modeled Soil Moisture/runoff Coefficient Correlation Using the SMAP Level 4 Soil Moisture Product

The physical parameterization of key processes in land surface models (LSMs) remains uncertain, and new techniques are required to evaluate LSM accuracy over coarse spatial scales. Given the role of soil moisture in the partitioning of surface water fluxes (between infiltration, runoff and evapotranspiration), surface soil moisture (SSM) estimates represent an important observational benchmark for such evaluations. Here, we apply SSM estimates from the NASA Soil Moisture Active Passive Level 4 product (SMAP_L4) to diagnose bias in the coupling between SSM and surface runoff for multiple Noah-Multiple Physics (Noah-MP) LSM parameterization cases. Results demonstrate that Noah-MP surface runoff parameterizations often underestimate the coupling strength between pre-storm SSM and the event-scale runoff coefficient (RC; defined as the ratio between event-scale streamflow and precipitation volumes). This bias squanders RC information contained in pre-storm SSM and reduces RC estimation skill. Such bias can be quantified against an observational benchmark calculated using streamflow observations and SMAP_L4 SSM and applied to explain a substantial fraction of the observed basin-to-basin (and case-to-case) variability in the skill of event-scale Noah-MP RC estimates. Based on this concept, a novel case selection strategy for ungauged basins is introduced and demonstrated to successfully identify poorly performing Noah-MP parameterization cases.

SSM↗
NASA NTRS2020

Soil Evaporation Stress Determines Soil Moisture‐Evapotranspiration Coupling Strength in Land Surface Modeling

Model‐based estimates of soil moisture (SM)‐evapotranspiration (ET) coupling strength(ρ) vary widely and are prone to bias. Here we apply numerical modeling and remote sensing to identify the process‐level source of modeledρbias with the goal of improving the fidelity of current Earth system models. Results illustrate that modeledρis most strongly determined by soil evaporation (E) stress, and (generally positive)ρmodeling bias is attributable to the oversimplification of soil texture impacts on E stress. Based on new remotely sensed estimates ofρ, we demonstrate that removingρbias via a single optimized E stress parameter leads to improved ET accuracy and resolves a well‐known modeling bias in the partitioning of ET into E and T. As such, we highlight the importance of the stress function relating E and SM and its central role in regulating land‐atmosphere coupling processes impacting local climate.

Jianzhi Dong↗
NASA NTRS2021

Comparison of soil dielectric mixing models for Soil Moisture Retrieval using SMAP Brightness Temperature over croplands in India

The accurate estimation of soil moisture (SM) using microwave remote sensing depends mostly on careful selection of retrieval parameters among which the soil dielectric mixing model is the important one. These models are often categorized into empirical, semi-empirical or volumetric based on their methodologies and input data requirements. To study in detail, the comparative performance of four dielectric mixing models -- Wang & Schmugge model, Hallikainen model, Dobson model and Mironov model were used with Soil Moisture Active Passive (SMAP) L-band brightness temperature and Single Channel Algorithm for SM retrieval over agricultural landscapes in India. The highest performance statistics combination in terms of Root Mean Square Error (RMSE), correlation coefficient (R^(2)) and percentage bias (PBIAS) against the concurrent in-situ SM measurements were calculated at the selected validation sites. The overall results indicate that the best performance was given by the Mironov model (RMSE = 0.07 cu. m/cu. m), followed by Wang & Schmugge model (RMSE = 0.08 cu. m3/cu. m), Hallikainen model (RMSE = 0.09 cu. m/cu. m), Dobson model (RMSE = 0.10 cu. m/cu. m) and original SMAP radiometer SM (RMSE = 0.12 cu. m/cu. m). Findings of this study provides important insights into application and performance of dielectric mixing models in mapping surface SM variations. This study also underlines the pivotal role of local conditions for SM retrieval which should be carefully included in the algorithms.

Swati Suman↗
DOE OSTI2025

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗
DOE OSTI2021

A reporting format for field measurements of soil respiration

Field observations of the soil-to-atmosphere CO2 flux–soil respiration, RS–are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and novel syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the field as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, and optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g. FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. Finally, this proposed RS reporting format is available online, and is intended to be a dynamic document, subject to further community feedback and/or change in the future.

Bond-Lamberty, Benjamin↗
DOE OSTI2023

Continuous soil temperature and soil deformation measurements, Teller road Mile 47, Nome, Alaska.

The dataset comprises Soil Temperature and Deformation monitoring data gathered from a watershed situated along the Nome-Teller road at Mile 47 in Alaska. Its primary objective is to enhance comprehension of deformation mechanisms in permafrost environments by using 51 probes designed following Wielandt et al. (2022). The dataset comprises a description of Probe_ID, Location, start time, end time and probe length in the "ProbesLocations_StartEndDates.csv" file, the 51 data files encapsulated within "Data_files.zip" and the computed deformation for 2023 and 2022 in "Deformation_T47.zip".Each file in Data_files.zip is named as followed "ProbeId_StartMonth_EndMonth.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the sensor’s battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The data collection frequency is set at 30-minute intervals. Each file in Deformation_T47.zip is named as followed "ProbeId_Temp_def_year.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the temperature at each sensor and cumulative deformation from last to first sensor in subsequent columns. The data collection is daily averaged.This dataset forms an integral component of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). 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 NTRS2018

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

This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project.

Soil Moisture↗
DOE OSTI2021

Reactive oxygen species alter chemical composition and adsorptive fractionation of soil organic matter

Reactive oxygen species (ROS), formed during redox fluctuations in iron-rich soils, have been known to stimulate lignin degradation, although not much is known about how they alter soil organic matter (SOM) composition and interaction with mineral surfaces. We conducted a laboratory experiment to see how ROS altered SOM composition and adsorptive fractionation onto Fe-mineral surfaces. We reacted water extracts of SOM with ·OH, produced by the Fenton reaction, and then conducted a sorption experiment of the extracts with goethite to analyze the amount and quality of SOM adsorbed. The Fenton reaction preferentially consumed low-O, mostly aromatic molecules, and new high-O molecules were detected post-Fenton, nearly half of which were carbohydrate-like. Although the amount of C adsorbed did not change after oxidation, the post-Fenton adsorbed molecules were more oxidized. Pre-Fenton adsorption was dominated by aromatic molecules (90%), but post-Fenton, the adsorbed molecules were 75% aromatic and 25% carbohydrate-like. We show that the ·OH radical oxidized SOM and shifted patterns of adsorption to a more oxidized pool. Because adsorption to minerals is thought to stabilize SOM, our results suggest that ROS may alter the availability and stabilization patterns of SOM.

Patel, Kaizad F.↗
DOE OSTI2022

Microbe-iron interactions control lignin decomposition in soil

Lignin decomposition is critically linked to terrestrial carbon (C) cycle due to the enormous C mass of lignin and its importance in controlling overall rates of litter decomposition. Interactions between lignin and iron (Fe) minerals have been increasingly recognized as key mediators of lignin decomposition in experimental studies. However, we still lack a quantitative understanding of how Fe minerals interact with microbes to control lignin decomposition. Here, we leveraged experimental results from an incubation of Fe-rich soil, in which lignin decomposition rates were measured at aerobic conditions after four levels of pre-treated O2 availability, to examine microbe-Fe (MiFe) interactions in lignin decomposition with a MiFe model. We quantified how Fe redox cycling interacted with microbial activities to control lignin decomposition via data-model integration. Our results showed that the MiFe model with time-dependent growth and mortality functions better represented CO2 release from lignin decomposition (R2 ranging from 0.96 to 0.97) than models assuming either first-order or Michaelis-Menten kinetics. Reduction of Fe(III) to Fe(II) after pre-treatments with lower O2 availability stimu-lated the Fenton reaction to break down macro-molecular lignin into small molecules available to microbes. The small molecules of lignin and necromass bounded with oxidized Fe and were protected from decomposition. After 1-year incubation, the model implied that most of C stabilized with Fe minerals was derived from small molecular lignin C. Our quantitative analysis of microbe-Fe interactions sheds new light on lignin decomposition and preservation and helps improve model prediction of soil C persistence under global change.

Liao, Cuijuan↗
DOE OSTI2022

Effects of fine-root senescence upon soil communities and nutrient flux into soil pools (Final Report)

Fine roots represent an important flux of carbon into terrestrial soils. Much of this flux occurs through the exudation of polysaccharides and other carbon compounds during the lifetime of fine-roots, but little is known about their contributions to flux as roots senesce, die and decompose. This project was designed 1) to test approaches for inducing senescence in fine roots and 2) assess the effects of the treatments on fine roots and the associated rhizosphere community. We implemented two fine-root treatments, a steam girdling approach and full severing of fine root modules from the tree, and we contrasted them with a control where roots were handled but not girdled. Fine roots and their associated community subjected to each of these three treatments were subsequently analyzed for changes in physical structure, nutrient content, community structure and gene function. Both girdling manipulations resulted in tissue disruption in fine roots and changes in the soil community relative to controls. In particular, microbial diversity for most taxa declined in girdled treatments whereas fungal diversity increased. We also observed changes in overall plant and fungal gene expression associated with treatment with plant gene expression declining over time in girdled roots with a simultaneous increase in fungal gene expression in these same treatments. Finally, in girdled fine root modules, we observed changes in gene function associated with senescence and plant stress in pine-associated genes while at the same time observing upregulation of genes associated with growth and proliferation in fungi. In conclusion, we were able to successfully girdle fine-roots in a field setting and resolve plant-level and community level changes in response to these girdling treatments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1969

Desert soil collection at the JPL soil science laboratory

Collection contains desert soils and other geologic materials collected from sites in the United States and foreign countries. Soils are useful for test purposes in research related to extraterrestrial life detection, sampling, harsh environmental studies, and determining suitable areas for training astronauts for lunar exploration.

Blank, G. B.↗
NASA NTRS1974

Utilizing ERTS imagery to detect plant diseases and nutrient deficiencies, soil types and soil moisture levels

The author has identified the following significant results. ERTS-1 imagery may be used to delineate soil associations. It does have the capacity to divide soils into groups such that their land use and management would be similar. It offers definite potential for making grass flood-plain, wetland, river shoreline, and land use change surveys. Production of volume strata and forest type from the two usable bands of ERTS-1 imagery were of questionable value. No imagery was received for evaluation during the time of year when maine dwarf mosaic virus and southern corn leaf blight were active.

Parks, W. L.↗
NASA NTRS1974

Surface history of lunar soil and soil columns

Measurements of cosmic ray track densities are presented for soil samples from Apollo 15, 16, and 17. Median track densities are used to infer total effective exposure times within about 15 cm of the lunar surface. Minimum track densities are used to derive the time of the last impact-produced rearrangement of soil grains. For samples from near various craters ages are derived of 40 m.y. for St. George, 6 (plus or minus 3) m.y. for S. Ray, 25 to 90 m.y. for Plum, and 20 to 35 m.y. for Shorty. The material of 15003, the Apollo 15 deep core at depths of 120 to 160 cm, is inferred to have been deposited at an average rate greather than or equal to 0.35 cm/m.y. The Apollo 16 core at 41 to 47 cm depths, 60007, appears to be well mixed and was covered up by deposition at greater than 0.3 cm/m.y. for the next few m.y. after its deposition.

Fleischer, R. L.↗
NASA NTRS1978

Soils from Mare Crisium - Agglutinitic glass chemistry and soil development

Agglutinates were studied in 29 polished thin sections of grain mounts from various size fractions of six Luna 24 soil horizons. Three populations of agglutinitic glass compositions were found: a high-MgO, high-FeO group identified as a coarse-grained basaltic component; a low-MgO, low-FeO group from a highland source; and a low-MgO, high-FeO group probably from the subophitic basalt component. The presence of a significant amount of admixed highland component probably accounts for an enrichment in plagioclase and a depletion in ferromagnesian elements displayed by the agglutinitic glass compositions relative to the bulk soil.

Hu, H.-N.↗
NASA NTRS1984

Utilization of active microwave roughness measurements to improve passive microwave soil moisture estimates over bare soils

Multisensor aircraft data were used to establish the potential of the active microwave sensor response to be used to compensate for roughness in the passive microwave sensor's response to soil moisture. Only bare fields were used. It is found that the L-band radiometer's capability to estimate soil moisture significantly improves when surface roughness is accounted for with the scatterometers.

Theis, S. W.↗