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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Blanchard, M. B.↗
NASA NTRS1974

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

Two methods are used to estimate soil moisture remotely using the 0.4- to 14.0-micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Blanchard, M. B.↗
NASA NTRS1975

Microwave remote sensing of soil water content

Microwave remote sensing of soils to determine water content was considered. A layered water balance model was developed for determining soil water content in the upper zone (top 30 cm), while soil moisture at greater depths and near the surface during the diurnal cycle was studied using experimental measurements. Soil temperature was investigated by means of a simulation model. Based on both models, moisture and temperature profiles of a hypothetical soil were generated and used to compute microwave soil parameters for a clear summer day. The results suggest that, (1) soil moisture in the upper zone can be predicted on a daily basis for 1 cm depth increments, (2) soil temperature presents no problem if surface temperature can be measured with infrared radiometers, and (3) the microwave response of a bare soil is determined primarily by the moisture at and near the surface. An algorithm is proposed for monitoring large areas which combines the water balance and microwave methods.

Cihlar, J.↗
NASA NTRS1975

The utility of surface temperature measurements for the remote sensing of surface soil water status

Experiments carried out on an Avondale loam soil indicated that the thermal inertia concept of soil water content detection is reasonably sound. The volumetric water contents of surface soil layers between 2 and 4 cm thick were found to be linear functions of the amplitude of the diurnal surface soil temperature wave for clear day-night periods. They were also found to be linear functions of the daily maximum value of the surface soil-air-temperature differential. Tests on three additional soils ranging from sandy loam to clay indicated that the relations determined for Avondale loam could not be accurately applied to these other soil types. When the moisture characteristic curves of each soil were used to transform water contents into pressure potentials, however, it was found that soil water pressure potential could be determined without prior knowledge of soil type, and thus its value as a potential soil water status survey tool was significantly enhanced.

Idso, S. B.↗
DOE OSTI2020

The effects of different types of mulch on soil properties and tea production and quality

Abstract BACKGROUND Tea is an important economic crop in China. Mulching, a modern agricultural practice, can modify the soil microenvironment and maintain the crop yield. RESULTS To investigate the effect of different mulching modes on tea plant growth, filed experiments were conducted in a Shizipu tea plantation located in Langxi Country (Xuanchen City, Anhui Province, China). Five treatments were carried out in a randomized complete block arrangement: (i) clean tillage (control); (ii) black plastic film; (iii) weed barrier fabric; (iv) rice straw mulch; and (v) intercropping with Vulpia myuros . The effects of different mulch modes on soil temperature, water moisture, soil compactness, root activity, soil enzyme activity and nutrition status on tea yield, quality and economic benefits were compared at the harvest stage. In the present study, compared with other mulch treatments, intercropping with V. myuros significantly reduced the topsoil temperature (to an optimum temperature) and soil compactness, and increased the water holding capacity in the deep soil layer, which contributed to increased tea root activity and respiration. Furthermore, intercropping with V. myuros significantly increased soil enzymes activity, soil organic matter, and the available nitrogen and phosphorus concentrations in the main root zone. Therefore, the stronger tea root activity accelerated nutrition uptake and increased the tea yield and quality‐related components of the tea, thus resulting in a larger average net income. CONCLUSION Intercropping with V. myuros could serve as a profitable agricultural method for tea production. © 2020 Society of Chemical Industry

Xianchen, Zhang↗
NASA NTRS1990

Documentation for Program SOILSIM: A computer program for the simulation of heat and moisture flow in soils and between soils, canopy and atmosphere

SOILSIM, a digital model of energy and moisture fluxes in the soil and above the soil surface, is presented. It simulates the time evolution of soil temperature and moisture, temperature of the soil surface and plant canopy the above surface, and the fluxes of sensible and latent heat into the atmosphere in response to surface weather conditions. The model is driven by simple weather observations including wind speed, air temperature, air humidity, and incident radiation. The model intended to be useful in conjunction with remotely sensed information of the land surface state, such as surface brightness temperature and soil moisture, for computing wide area evapotranspiration.

Field, Richard T.↗
DOE OSTI2022

Development of New g-function Data for Simulating a Novel Shallow Bore Ground Heat Exchanger

Geothermal heat pump (GHP), which is also referred as ground source heat pump, is the most energy-efficient technology for space heating and cooling. However, the application of GHP is hindered by its high initial cost, of which approximately 30% is for the ground heat exchanger (GHE). In recent years, researchers have developed different types of shallow bore ground heat exchangers (SBGHE) intending to reduce the cost of drilling. The ability to predict the thermal response of an SBGHE is critical for sizing SBGHE. While g-functions have been commonly used for predicting the thermal response of conventional vertical bore ground heat exchangers (VBGHE), they cannot be directly used for predicting the performance of SBGHE because they did not account for the impacts of the seasonal variation of the soil temperature along with the depth of an SBGHE. In addition, an SBGHE has a larger thermal mass within the borehole than the VBGHE due to the larger borehole diameter of SBGHE. This study develops new g-function data pairs for a new design of SBGHE, which is named Underground Thermal Battery (UTB). Impacts of the seasonal variation of soil temperature on the thermal response of UTB were accounted for by superposing a time-dependent soil temperature onto the g-functions calculated with a numerical model that assumes constant undisturbed soil temperature. The TOUGH program was used to predict the thermal response of several configurations involving multiple UTBs. The results indicate that the proposed methodology is appropriate to generate g-functions for the UTB, and the g-function value of UTB is much lower than that of VBGHE in the time range of 15 min to 1 year due to the large thermal mass and convection heat transfer within the UTB.

Shi, Liang↗
DOE OSTI2021

Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models

Microbially-explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (RH), a stringent test for soil biogeochemical models, has never been evaluated. We used statistical global RH products, as well as 7,821 daily site-scale RH measurements, to evaluate the spatio-temporal performance of one first-order decay model (CASA-CNP) and two microbially-explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different climate datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the meteorological input data used to drive them. Spatial RH variability was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of RH well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise, but also needs to be improved for realistic spatio-temporal variability of RH. Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models.

Jian, Jinshi↗
NASA NTRS1981

Numerical simulation of soil brightness temperatures at wavelength of 21 cm

A simulation model is applied to reproduce some observed brightness temperatures at a wavelength of 21 cm. The simulated results calculated with two different soil textures are compared directly with observations measured over fields in Arizona and South Dakota. It is found that good agreement is possible by properly adjusting the surface roughness parameter. Correlation analysis and linear regression of the brightness temperatures versus soil moistures are also carried out.

Mo, T.↗
NASA NTRS1994

Using optical-microwave synergy for estimating surface energy fluxes over semi-arid rangeland

First results of the Walnut Gulch '92 (Arizona, U.S.) experiment concerning the combined use of radar backscattering (ERS-1) and thermal infrared (LANDSAT TM (Thematic Mapper)) data to estimate surface sensible heat flux are reported. The first step investigates the potential use of ERS-1 SAR (Synthetic Aperture Radar) images for surface soil moisture monitoring of the watershed using five calibrated images acquired during the year 1992 (dry to wet conditions). Results show that despite the typical low level of biomass of semi arid rangeland, an attenuation of the soil backscatter (up to 2 dB) can occur during the rainy season mainly due to the vegetation characteristics. A statistical relationship is then used to retrieve the volumetric surface soil moisture from ERS-1 backscattering (sensitivity of 0.23 dB/% moisture) with a resulting root mean square error of 1.3% of soil moisture. In a second step a semi empirical approach based on energy balance relates soil temperatures to this estimated surface soil moisture. Vegetation temperature is then deduced from soil temperatures and LANDSAT TM composite temperature in order to estimate sensible heat flux according to a two layer type model providing an RMSE of 29 W/sq m.

Troufleau, D.↗
NASA NTRS1997

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Potter, C. S.↗
NASA NTRS2011

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Ballard, Jerrell R., Jr.↗
DOE OSTI2022

A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature

Abstract. Measuring soil and snow temperature with high vertical and lateral resolution is critical for advancing the predictive understanding of thermal and hydro-biogeochemical processes that govern the behavior of environmental systems. Vertically resolved soil temperature measurements enable the estimation of soil thermal regimes, frozen-/thawed-layer thickness, thermal parameters, and heat and/or water fluxes. Similarly, they can be used to capture the snow depth and the snowpack thermal parameters and fluxes. However, these measurements are challenging to acquire using conventional approaches due to their total cost, their limited vertical resolution, and their large installation footprint. This study presents the development and validation of a novel distributed temperature profiling (DTP) system that addresses these challenges. The system leverages digital temperature sensors to provide unprecedented, finely resolved depth profiles of temperature measurements with flexibility in system geometry and vertical resolution. The integrated miniaturized logger enables automated data acquisition, management, and wireless transfer. A novel calibration approach adapted to the DTP system confirms the factory-assured sensor accuracy of ±0.1 ∘C and enables improving it to ±0.015 ∘C. Numerical experiments indicate that, under normal environmental conditions, an additional error of 0.01 % in amplitude and 70 s time delay in amplitude for a diurnal period can be expected, owing to the DTP housing. We demonstrate the DTP systems capability at two field sites, one focused on understanding how snow dynamics influence mountainous water resources and the other focused on understanding how soil properties influence carbon cycling. Results indicate that the DTP system reliably captures the dynamics in snow depth and soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes. Overall, the DTP system fulfills the needs for data accuracy, minimal power consumption, and low total cost, enabling advances in the multiscale understanding of various cryospheric and hydro-biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Effect of surface roughness on the microwave brightness temperature of soils

The effect of surface roughness on the brightness temperature of a moist terrain was studied through the modification of Fresnel reflection coefficient and using the radiative transfer equation. Model calculations are in good qualitative agreement with the observed dependence of the brightness temperature on the moisture content in the surface layer.

Choudhury, B. J.↗
DOE OSTI2021

The temperature sensitivity of soil: microbial biodiversity, growth, and carbon mineralization

Abstract Microorganisms drive soil carbon mineralization and changes in their activity with increased temperature could feedback to climate change. Variation in microbial biodiversity and the temperature sensitivities (Q10) of individual taxa may explain differences in the Q10 of soil respiration, a possibility not previously examined due to methodological limitations. Here, we show phylogenetic and taxonomic variation in the Q10 of growth (5–35 °C) among soil bacteria from four sites, one from each of Arctic, boreal, temperate, and tropical biomes. Differences in the temperature sensitivities of taxa and the taxonomic composition of communities determined community-assembled bacterial growth Q10, which was strongly predictive of soil respiration Q10 within and across biomes. Our results suggest community-assembled traits of microbial taxa may enable enhanced prediction of carbon cycling feedbacks to climate change in ecosystems across the globe.

Wang, Chao (ORCID:0000000257567505)↗
DOE OSTI2025

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Prediction of annual soil respiration from its flux at mean annual temperature

Accurately scaling soil respiration (SR, the soil-to-atmosphere flow of CO2) across time and space is important to constrain and understand ecosystem to global scale SR, a major terrestrial carbon flux to the atmosphere. Year-round SR measurements are however expensive and sometimes impossible to perform. Bahn et al. (2010) developed an approach to estimate annual SR (SRannual) from the flux measured at mean soil temperature (SRMAST), but the robustness of this approach needs to be evaluated in diverse ecosystem types and climatic conditions globally. We used a global soil respiration database (SRDB-V4, with 823 SR observations worldwide) to test the capability of SRMAST to predict SRannual. SRMAST estimated using a variety of methods all showed clear relationships with annual SRannual. Two single-rate methods (i.e., using the single SR rate most close to mean annual soil temperature, or the single SR rate most close to mean annual air temperature) showed the most pronounced divergence from the true SRannual, but errors significantly decreased when using multiple SR rates within 1 ? of the mean annual soil temperature to estimate SRMAST. SRannual was most closely correlated with SRMAST estimated via a Q10 relationship, but this method has a potential autocorrelation issue that we explore and discuss. Air temperature data are much more widely available than is soil temperature, and we found that SR at mean annual air temperature (SRMAAT) can be used to predict SRannual as well. This study builds on Bahn et al. (2010) to demonstrate that SR measured at both annual mean soil and air temperature can be used to predict annual SR, with well-quantified errors. This capability could be used to reduce SR measurement frequency required for estimating SRannual and greatly decrease cost, factors that are generally important but especially in lower-income countries and cold, inaccessible regions.

Soil respiration, temperature, modeling↗
DOE OSTI2023

A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature: Supporting Data

This dataset was used to assess the potential of a Distributed Temperature Profiling System developed and presented in the article named "A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature" and submitted to Cryosphere. There are three comma-delimited data files (.csv). Each of them contains snow or soil temperature with times (UTC) in the first column and temperature at various vertical distance from the ground surface (positive means in air/snow) or below the ground surface (negative means in soil). The measurements were acquired every 15 minutes. Data collected at the East River, Colorado site with two probes: 1) measuring air/snow temperature from 1.1 m above the ground surface to the ground surface (with 5 or 10 cm spacing between sensors) and 2) measuring soil temperature from the ground surface to 0.7 m depth (with 5 or 10 cm spacing between sensors). Data collected at the Teller road (mile 27) site near Nome, Alaska with one probe: measuring soil temperature from 5 cm above the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors). Additional metadata included in *.csv and *.pdf files. NGEE Arctic Project Summary: 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↗