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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Monte Carlo simulation of the effect of soil moisture variation on the microwave emission from soils

In this paper, results of a Monte Carlo simulation of the effect of noise on the relationship between the microwave emissivity of soil and its moisture content are presented. It is found that whenever the magnitude of the noise for the independent variable, in this case the soil moisture, is increased, both the slope of the regression and the correlation coefficient decrease. In particular, when the noise has magnitude equivalent to a coefficient of variation of 0.25, the slope and correlation coefficient are in good agreement with those obtained from the data of a 21-cm airborne microwave radiometer which was flown over a test site in hand county, South Dakota. The comparison was made using a linear relationship to determine the estimated emissivity from the ground measurements of soil moisture. The linear relationship was derived from a radiative transfer model calculation of the microwave emissivities using realistic soil-moisture profiles. The effect of surface roughness was included in the relationship, and the variability of the surface roughness was also simulated by a Monte Carlo technique.

Mo, T.↗
NASA NTRS1985

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Pelletier, R. E.↗
NASA NTRS1991

A case study demonstration of the soil temperature extrema recovery rates after precipitation cooling at 10-cm soil depth

Since the invention of maximum and minimum thermometers in the 18th century, diurnal temperature extrema have been taken for air worldwide. At some stations, these extrema temperatures were collected at various soil depths also, and the behavior of these temperatures at a 10-cm depth at the Tifton Experimental Station in Georgia is presented. After a precipitation cooling event, the diurnal temperature maxima drop to a minimum value and then start a recovery to higher values (similar to thermal inertia). This recovery represents a measure of response to heating as a function of soil moisture and soil property. Eight different curves were fitted to a wide variety of data sets for different stations and years, and both power and exponential curves were fitted to a wide variety of data sets for different stations and years. Both power and exponential curve fits were consistently found to be statistically accurate least-square fit representations of the raw data recovery values. The predictive procedures used here were multivariate regression analyses, which are applicable to soils at a variety of depths besides the 10-cm depth presented.

Welker, Jean Edward↗
NASA NTRS1992

Determination of Martian soil mineralogy and water content using the Thermal Analyzer for Planetary Soils (TAPS)

Physical and chemical interactions between the surface and atmosphere of Mars can be expected to embody a strong cause-and-effect relationship with the minerals comprising the martian regolith. Many of the minerals in soils and sediments are probably products of chemical weathering (involving surface/atmosphere or surface/hydrosphere reactions) that could be expected to subsequently influence the sorption of atmospheric gases and water vapor. Therefore, identification of the minerals in martian surface soils and sediments is essential for understanding both past and present interactions between the Mars surface and atmosphere. Clearly, the most definitive mineral analyses would be achieved with well-preserved samples returned to Earth-based laboratories. In advance of a Mars sample return mission, however, significant progress could be made with in situ experiments that fill current voids in knowledge about the presence or abundance of key soil minerals such as clays (layered-structured silicates), zeolites, and various salts, including carbonates. TAPS is intended to answer that challenge by providing first-order identification of soil and sediment minerals.

Gooding, James L.↗
NASA NTRS2010

Biotoxicity of Mars Analog Soils: Microbial, Dispersal into Desiccated Soils Versus Emplacement in Salt or Ice Inclusions Fluids

Recent evidence from the Opportunity and Spirit rovers and the Mars Express mission suggests that the soils on Mars might be very high in biotoxic materials including sulfate salts, chlorides, and acidifying agents. Yet, very little is known about how the chemistries of Mars soils might affect the survival and growth of terrestrial microorganisms. The primary objectives of the research included: (1) prepare and characterize Mars analog soils amended with potential biotoxic levels of sulfates, chlorides, and acidifying minerals; and (2) use the simulants to conduct a series of toxicology assays to determine if terrestrial microorganisms from spacecraft can survive direct exposure to the biotoxic soils.

Schuerger, A. C.↗
NASA NTRS2009

A Model of Thermal Conductivity for Planetary Soils: Theory for Cemented Soils - 2

A numerical model of heat conduction through particulate media made of spherical grains cemented by various bonding agents is presented. The pore-filling gas conductivity, volume fraction, and thermal conductivity of the cementing phase are tunable parameters. Cement fractions <0.001-0.01% in volume have small effects on the soil bulk thermal conductivity. A significant conductivity increase (factor 3-8) is observed for bond fractions of 0.01 to 1% in volume. In the 1 to 15% bond fraction domain, the conductivity increases continuously but less intensely (25-100% conductivity increase compared to a 1% bond system). Beyond 15% of cements, the conductivity increases vigorously and the bulk conductivity rapidly approaches that of bedrock. The composition of the cements (i.e. conductivity) has little influence on the bulk thermal inertia of the soil, especially if the volume of bond <10%. These results indicate that temperature measurements are sufficient to detect cemented soils and quantify the amount of cementing phase, but the mineralogical nature of the bonds and the typical grain size are unlikely to be determined from orbit. On Mars, a widespread surface unit characterized by a medium albedo (0.19-0.26) and medium/high thermal inertia (200-600 J s(0.5)/sq m/K) has long been hypothesized to be associated with a duricrust. The fraction of cement required to fit the thermal data is less than approx.1-5% by volume. This small amount of material is consistent with orbital observations, confirming that soil cementation is an important factor controlling the thermal inertia of the Martian surface

Piqueux, S.↗
NASA NTRS2012

ISRU Soil Mechanics Vacuum Facility: Soil Bin Preparation and Simulant Strength Characterization

Testing in relevant environments is key to exploration mission hardware development. This is true on both the component level (in early development) and system level (in late development stages). During ISRU missions the hardware will interface with the soil (digging, roving, etc) in a vacuum environment. A relevant test environment will therefore involve a vacuum chamber with a controlled, conditioned simulant bed. However, in earth-based granular media, such as lunar soil simulant, gases trapped within the material pore structures and water adsorbed to all particle surfaces will release when exposed to vacuum. Early vacuum testing has shown that this gas release can occur violently, which loosens and weakens the simulant, altering the consolidation state. The Vacuum Facility #13, a mid-size chamber (3.66m tall, 1.5m inner diameter) at the NASA Glenn Research Center has been modified to create a soil mechanics test facility. A 0.64m deep by 0.914m square metric ton bed of lunar simulant was placed under vacuum using a variety of pumping techniques. Both GRC-3 and LHT-3M simulant types have been used. An electric cone penetrometer was used to measure simulant strength properties at vacuum including: cohesion, friction angle, bulk density and shear modulus. Simulant disruptions, caused by off gassing, affected the strength properties, but could be mitigated by reducing pump rate. No disruptions were observed at pressures below 2.5Torr, regardless of the pump rate. However, slow off gassing of the soil lead to long test times, a full week, to reach 10-5Torr. This work highlights the need for robotic machine-simulant hardware and operations in vacuum to expeditiously perform (sub-)systems tests.

Kleinhenz, Julie↗
NASA NTRS2015

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. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.

L4-SM↗
NASA NTRS2019

Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16)

The NASA's Soil Moisture Active Passive (SMAP) mission conducted a field experiment with its partners over two 40-km agricultural domains in Iowa and Manitoba in the summer of 2016 to address concerns observed in SMAP soil moisture (SM) retrievals over agricultural areas. The experiment featured airborne Passive Active L-band System (PALS) flights over each domain with intensive ground measurements and dense networks of SM monitoring stations. With two intensive observation periods separated in time (May 28–June 20 and July 14–August 16), the flights captured both early-season/low vegetation and later-season/high-vegetation conditions. The comparison of the PALS brightness temperature (TB) measurements to the SMAP TB observed over the sites resulted in root mean square difference (RMSD) of 2.8 K and 4.0 K for vertical and horizontal polarizations, respectively. The subsequent SM analysis rescaled the PALS TB with the SMAP TB to allow equitable comparisons between the SM retrievals from the two instruments. The PALS SM retrieval algorithm used the SM sampled by the ground teams during the overpass days for tuning, and was parameterized by a high-resolution vegetation water content product calibrated using vegetation samples collected during the experiment. The tuning process was not able to find a satisfactory result with a temporally constant set of parameters in the single channel algorithm for the two intensive observation periods of the experiment. This result indicated that the rapid change in the vegetation structure during the growth stages and likely variation in the surface roughness conditions were not compatible with rigid parameterization over the entire period. However, using seasonally variable parameters we found that it was possible to retrieve soil moisture with satisfactory accuracy. Comparative analysis with the SMAP SM product included aggregation of the PALS SM to the SMAP pixel-scale. The RMSD between the PALS SM and the aggregated manual field samples was <0.04 m3/m3 with Pearson correlation >0.85 for both sites. The comparison between different in situ sources indicated that the soil moisture network measurements were not the source of the large biases observed for SMAP over the sites reported in earlier studies. Therefore, the results suggested the rapidly growing vegetation and the early-season surface condition changes not captured by the SMAP algorithm caused the SMAP retrieval errors. In addition, the significant deviations of the vegetation water content used by the SMAP product from the calibrated vegetation water content obtained during the experiment compounds the problem.

Andreas Colliander↗
NASA NTRS1971

Performance of Boeing LRV wheels in a lunar soil simulant. Report 1: Effect of wheel design and soil

Six versions of the wire mesh wheel were laboratory tested in a lunar soil simulant, consisting of a crushed basalt with a grainsize distribution similar to that of samples collected during Apollo 11 and 12 flights, to determine their relative performance. The consistency of the soil was varied to cover a range of cohesive and frictional properties to simulate soil conditions assumed to exist on the moon. Programmed-slip and constant-slip tests conducted with the single wheel dynamometer system showed that the performance of the wheel covered with a metal chevron tread over 50 percent of its contact surface was slightly superior to that of other tread designs.

Green, A. J.↗
NASA NTRS1981

Relationships between soil moisture-holding properties and soil texture, organic matter content, and bulk density

Specimens from the surface horizon and the subsoil of 62 soil horizons in Hedmark and Oppland were investigated to study how the mechanical composition of the soil, the organic matter content and the bulk density affect their porosity and air capacity and their total and available water content. Most of the specimens belonged to the loam group, and a smaller number was from sandy and silty types of soil. Equations were established to make it possible to calculate the water retention curves and the amount of available water from the above mentioned parameters. As a rule, errors derived from the equations are no greater than those which are found in similar research in other countries.

Riley, H. C. F.↗
NASA NTRS2004

LSCC Apollo and Luna Soil Analyses: Update of Soil Evolution Model

The Lunar Soil Characterization Consortium (LSCC) has obtained samples of Luna 16, 20 and 24 soils. Although these particular samples encountered contamination during processing, preliminary results are consistent with previous integrated analyses and expand the soil data to three additional sites.

Pieters, C. M.↗
NASA NTRS2005

The Effect of Soil Hydraulic Properties vs. Soil Texture in Land Surface Models

This study focuses on the effect of Soil Hydraulic Property (SHP) selection on modeled surface fluxes following a rain storm in a semi-arid environment. SHPs are often defined based on a Soil Texture Class (STC). To examine the effectiveness of this approach, the Noah land surface model was run with each of 1306 soils in a large SHP database. Within most STCs, the outputs have a range of 350 W/m2 for latent and sensible heat fluxes, and 8K for surface temperature. The average difference between STC median values is only 100 W/m2 for latent and sensible heat. It is concluded that STC explains 5-15% of the variance in model outputs and should not be used to determine SHPs.

Gutmann, E. D.↗
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↗