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Parameters Impacting Columnated Granular Soil Pneumatic Seal Performance

The ability of a column of loose granular soil to form a pneumatic seal was investigated by varying the diameter of the soil column, the effective column height, and the level of compaction in the soil. The soil column diameter was tested at three levels using pipes with inner diameters measuring 5.08, 10.16, and 15.24 centimeters (2, 4, and 6 inches). Soil was filled in each pipe to form 15, 30, and 45 centimeter (6, 12, and 18 inch) tall soil columns. Each diameter/height configuration was also tested at three levels of soil compaction, compared by calculating the bulk density of the soil with mass and volume measurements. GRC-1a simulant was used, with approximate low/medium/high bulk densities of 1.6, 1.75, and 1.9 g/cc achieved with a combination of vibration and tamping. The order of tests for a given column diameter was randomized and repeated three times. With the top of the soil open to atmosphere at room temperature, compressed air was injected through a small diffuser at the column base with several small downward-facing holes. The number and size of these holes was scaled such that a constant total inlet orifice area to column cross sectional area ratio was maintained for each column diameter. Inlet air pressure was slowly increased via a precision regulator to preserve quasi-static equilibrium in the soil column to minimize the impact of dynamics. Air pressure was increased all the way through the static and bubbling regimes until slugging or turbulent behavior was observed in the soil to ensure that the entire static regime had been captured during data collection. A three-factor, three-level analysis of variance (ANOVA) statistical analysis was performed on the resulting data to determine the extent to which each physical parameter impacted the soil column seal performance. It was concluded that there is statistically significant evidence that column height, and the interaction between column height and diameter impact soil seal performance. In all other cases there was insufficient data to identify a statistically significant causal relationship. Additionally, plots were generated comparing experimental data to the predictive formula developed by Ogino et al. for fluidized beds in 1993. Because this model was developed for industrial spouted fluidized beds, the accuracy of its output prior to fluidization in the static seal ‘edge case’ is unknown, especially considering in this application the working gas was diffused across the column base rather than being injected through a spout. Further, the fidelity of the model had not yet been tested with lunar soil simulants. Plotting the Ogino et al. model alongside test data allows for a more intuitive sense of the impact of test parameters on soil seal performance, as well as providing a quick means to further tune this predictive model for more accurate use with static seals across granular lunar soil simulants. The model provided by Ogino et al. was further tuned using test data to determine the degree to which a spouted bed model could be applied to a slightly modified set of testing conditions: lunar soil simulants and a more diffuse, homogeneous application of pneumatic pressure. A Matlab script was created to test different values for the leading coefficient and exponents in Ogino’s formula. The script swept preset ranges, then iterated with higher resolutions across narrower ranges to converge on the optimal value for each parameter. The resulting adjusted model was compared to the original, as well as test data with noticeable improvements across the entire test domain.

Jack Stewart↗

NASA NTRS1984

Aggregating available soil water holding capacity data for crop yield models

The total amount of water available to plants that is held against gravity in a soil is usually estimated as the amount present at -0.03 MPa average water potential minus the amount present at -1.5 MPa water potential. This value, designated available water-holding capacity (AWHC), is a very important soil characteristic that is strongly and positively correlated to the inherent productivity of soils. In various applications, including assessing soil moisture status over large areas, it is necessary to group soil types or series as to their productivity. Current methods to classify AWHC of soils consider only total capacity of soil profiles and thus may group together soils which differ greatly in AWHC as a function of depth in the profile. A general approach for evaluating quantitatively the multidimensional nature of AWHC in soils is described. Data for 902 soil profiles, representing 184 soil series, in Indiana were obtained from the Soil Characterization Laboratory at Purdue University. The AWHC for each of ten 150-mm layers in each soil was established, based on soil texture and parent material. A multivariate clustering procedure was used to classify each soil profile into one of 4, 8, or 12 classes based upon ten-dimensional AWHC values. The optimum number of classes depends on the range of AWHC in the population of oil profiles analyzed and on the sensitivity of a crop to differences in distribution of water within the soil profile.

Seubert, C. E.↗

NASA NTRS1998

Teaching Soil Science in Primary and Secondary Schools

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Levine, Elissa R.↗

NASA NTRS2000

BOREAS TE-2 NSA Soil Lab Data

This data set contains the major soil properties of soil samples collected in 1994 at the tower flux sites in the Northern Study Area (NSA). The soil samples were collected by Hugo Veldhuis and his staff from the University of Manitoba. The mineral soil samples were largely analyzed by Barry Goetz, under the supervision of Dr. Harold Rostad at the University of Saskatchewan. The organic soil samples were largely analyzed by Peter Haluschak, under the supervision of Hugo Veldhuis at the Centre for Land and Biological Resources Research in Winnipeg, Manitoba. During the course of field investigation and mapping, selected surface and subsurface soil samples were collected for laboratory analysis. These samples were used as benchmark references for specific soil attributes in general soil characterization. Detailed soil sampling, description, and laboratory analysis were performed on selected modal soils to provide examples of common soil physical and chemical characteristics in the study area. The soil properties that were determined include soil horizon; dry soil color; pH; bulk density; total, organic, and inorganic carbon; electric conductivity; cation exchange capacity; exchangeable sodium, potassium, calcium, magnesium, and hydrogen; water content at 0.01, 0.033, and 1.5 MPascals; nitrogen; phosphorus: particle size distribution; texture; pH of the mineral soil and of the organic soil; extractable acid; and sulfur. These data are stored in ASCII text files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Veldhuis, Hugo↗

NASA NTRS1982

Characteristic variations in reflectance of surface soils

Surface soil samples from a wide range of naturally occurring soils were obtained for the purpose of studying the characteristic variations in soil reflectance as these variations relate to other soil properties and soil classification. A total 485 soil samples from the U.S. and Brazil representing 30 suborders of the 10 orders of 'Soil Taxonomy' was examined. The spectral bidirectional reflectance factor was measured on uniformly moist soils over the 0.52 to 2.32 micron wavelength range with a spectroradiometer adapted for indoor use. Five distinct soil spectral reflectance curve forms were identified according to curve shape, the presence or absence of absorption bands, and the predominance of soil organic matter and iron oxide composition. These curve forms were further characterized according to generically homogeneous soil properties in a manner similar to the subdivisions at the suborder level of 'Soil Taxonomy'. Results indicate that spectroradiometric measurements of soil spectral bidirectional reflectance factor can be used to characterize soil reflectance in terms that are meaningful to soil classification, genesis, and survey.

Stoner, E. R.↗

NASA NTRS2001

Unexprected Changes in Soil Phosphorus Dynamics Following Tropical Deforestation to Cattle Pasture

Phosphorus (P) is widely believed to limit plant growth and organic matter storage in a large fraction of the world's lowland tropical rainforests. We investigated how the most common land use change in such forests, conversion to cattle pasture, affects soil P fractions along forest to pasture chronosequences in the central Brazilian Amazon and in southwestern Costa Rica. Our sites represent a broad range in rainfall, soil type, management strategies, and total soil P (45.2 - 1228.0 microng P / g soil), yet we found some unexpected and at times strikingly similar changes in soil P in all sites. In the Brazilian sites, where rainfall is relatively low and pasture management is more intense than in the Costa Rican sites, significant losses in total soil P and soil organic carbon (SOC) were seen with pasture age on both fine-textured oxisol and highly sandy entisol soils. However, P losses were largely from occluded, inorganic soil P fractions, while organic forms of soil P remained constant or increased with pasture age, despite the declines in SOC. In Costa Rica, SOC remained constant across the oxisol sites and increased from forest to pasture on the mollisols, while total soil P increased with pasture age in both sequences. The increases in total soil P were largely due to changes in organic P; occluded soil P increased only slightly in the mollisols, and remained unchanged in the older oxisols. We suggest that changes in the composition and/or the primary limiting resources of the soil microbial community may drive the changes in organic P. We also present a new conceptual model for changes in soil P following deforestation to cattle pasture.

Townsend, Alan R.↗

NASA NTRS2004

Evidence for Differential Comminution/Aeolian Sorting and Chemical Weathering of Martian Soils Preserved in Mars Meteorite EET79001

Impact-melt glasses containing Martian atmospheric gases in Mars meteorite EET79001 are formed from Martian soil fines that had undergone meteoroid-comminution and aeolian sorting accompanied by chemical weathering near Mars surface. Using SiO2 and SO3 as proxy for silicates and salts respectively in Mars soils, we find that SiO2 and SO3 correlate negatively with FeO and MgO and positively with Al2O3 and CaO in these glasses, indicating that the mafic and felsic components are depleted and enriched relative to the bulk host (Lith A/B) respectively as in the case of Moon soils. Though the overall pattern of mineral fractionation is similar between the soil fines on Mars and Moon, the magnitudes of the enrichments/depletions differ between these sample-suites because of pervasive aeolian activity on Mars. In addition to this mechanical processing, the Martian soil fines, prior to impact-melting, have undergone acid-sulfate dissolution under oxidizing/reducing conditions. The S03 content in EET79001,507 (Lith B) glass is approx.18% compared to < 2% in EET79001, 506 (Lith A). SiO2 and SO3 negatively correlate with each other in ,507 glasses similar to Pathfinder soils. The positive correlation found between FeO and SO3 in ,507 glasses as well as Pathfinder rocks and soils is consistent with the deposition of ferric-hydroxysulfate on regolith grains in an oxidizing environment. As in the case of Pathfinder soils, the Al 2O3 vs SiO2 positive correlation and FeO VS S102 negative correlation observed in ,507 glasses indicate that SiO2 from the regolith is mobilized as soluble silicic acid at low pH. The large off-set in the end-member FeO abundance ( SO3=0) between Pathfinder soil-free rock and sulfur-free rock in ,507 glass precursors suggests that the soils comprising the ,507 glasses contain much larger proportion of fine-grained Martian soil fraction that registers strong mafic depletion relative to Lith B. This inference is strongly supported by the Al2O3 - SO3 negative correlation observed in both ,507 glasses and pathfinder soils. Furthermore, the flat MgO-SO3 correlation observed in the case of ,507 glasses shows that the solubilized MgSO4 is mobilized by the aqueous solutions leaving behind the rock-residue with approx.2-3% MgO. This value is similar to the approx.2% MgO found for the soil-free rock at the Pathfinder site. The EET79001 ,506 glasses, in contrast, show that Al2O3 and CaO positively correlate with SO3 indicating that Al is precipitated as amorphous hydroxysulfate at relatively high pH. The FeO - SO3 negative correlation observed in ,506 glasses yields an end-member FeO abundance of approx.21% for the sulfur-free rock, which is consistent with the 22% FeO deduced for the Viking soil-free rock. Further, the FeO and MgO negative correlation with S03 observed in ,506 glasses indicates that the divalent Fe and Mg released from ferromagnesian minerals by acid sulfate dissolution are mobilized away from the reaction sites as soluble sulfates under reducing environment. A similar negative correlation between FeO and SO3 and a positive correlation between Al2O3 and SO3 found in Viking soils suggest that they also had undergone acid-sulfate dissolution under relatively reducing conditions.

Rao, M. N.↗

NASA NTRS2021

Leveraging NASA Soil Moisture Active Passive for Assessing Fire Susceptibility and Potential Impacts over Australia and California

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influences wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the Soil Moisture Active Passive (SMAP) sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1-2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

Nazmus Sazib↗

NASA NTRS2022

Soil Moisture Estimation in South Asia via Assimilation of SMAP Retrievals

A soil moisture retrieval assimilation framework is implemented across South Asia in an attempt to improve regional soil moisture estimation as well as to provide a consistent regional soil moisture dataset. This study aims to improve the spatiotemporal variability of soil moisture estimates by assimilating Soil Moisture Active Passive (SMAP) near-surface soil moisture retrievals into a land surface model. The Noah-MP (v4.0.1) land surface model is run within the NASA Land Information System software framework to model regional land surface processes. NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA2) and Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals (IMERG) provide the meteorological boundary conditions to the land surface model. Assimilation is carried out using both cumulative distribution function (CDF)-corrected (DA-CDF) and uncorrected SMAP retrievals (DA-NoCDF). CDF matching is applied to correct the statistical moments of the SMAP soil moisture retrieval relative to the land surface model. Comparison of assimilated and model-only soil moisture estimates with publicly available in situ measurements highlights the relative improvement in soil moisture estimates by assimilating SMAP retrievals. Across the Tibetan Plateau, DA-NoCDF reduced the mean bias and RMSE by 8.4 % and 9.4 %, even though assimilation only occurred during less than 10 % of the study period due to frozen (or partially frozen) soil conditions. The best goodness-of-fit statistics were achieved for the IMERG DA-NoCDF soil moisture experiment. The general lack of publicly available in situ measurements across irrigated areas limited a domain-wide direct model validation. However, comparison with regional irrigation patterns suggested correction of biases associated with an unmodeled hydrologic phenomenon (i.e., anthropogenic influence via irrigation) as a result of SMAP soil moisture retrieval assimilation. The greatest sensitivity to assimilation was observed in cropland areas. Improvements in soil moisture potentially translate into improved spatiotemporal patterns of modeled evapotranspiration, although limited influence from soil moisture assimilation was observed on modeled processes within the carbon cycle such as gross primary production. Improvement in fine-scale modeled estimates by assimilating coarse-scale retrievals highlights the potential of this approach for soil moisture estimation over data-scarce regions.

Jawairia Ahmad↗

NASA NTRS2024

Shallow Soil Polychlorinated Biphenyl Site Assessment Report: General Services Administration Reclamation Yard Solid Waste Management Unit 010

This report presents a summary of the shallow soil polychlorinated biphenyl (PCB) site assessment activities that occurred from December 2020 through July 2022 at General Services Administration Reclamation Yard, Solid Waste Management Unit (SWMU) 010, located at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program, which also meets the requirements of Chapter 62-780, Florida Administrative Code. For the purposes of this report, three separate shallow soil plumes, known as the Northeast Shallow Soil PCB Plume, Southeast Shallow Soil PCB Plume, and West Shallow Soil PCB Plume, were identified for this site. The activities presented in this report include seven field events conducted between December 2020 and July 2022, which include shallow soil sample collection in the Northeast, Southeast, and West Shallow Soil PCB Plumes. AECOM Technical Services, Inc., personnel collected 330 soil samples from 118 boring locations. The samples were collected at 0.5-foot depth intervals to various depths based on analytical results and depth to groundwater. The soil samples were submitted to a fixed-based laboratory for analysis by United States Environmental Protection Agency Method 8082A for total PCBs. Several soil samples had PCB concentrations above the State of Florida Direct Exposure Residential and Industrial Soil Cleanup Target Levels (SCTLs), and two soil samples had PCB concentrations above the State of Florida Leachability for Groundwater. No soil borings were located beneath impervious surfaces, such as concrete or asphalt. The current Land Use Control Implementation Plan (LUCIP) covers PCBs in soils above the residential SCTL, which includes the paved areas.

soil assessment↗

NASA NTRS2019

Passive/active Microwave Soil Moisture Change Disaggregation Using Smapvex12 Data

The SMAPVEX12 (Soil Moisture Active Passive (SMAP) Validation Experiment 2012) experiment was conducted during June-July 2012 in Manitoba, Canada with the goal of collecting remote sensing data and ground measurements for the development and testing of soil moisture retrieval algorithms under varying vegetation and soil conditions for the SMAP satellite. The aircraft based soil moisture data provided by the passive/active microwave sensor PALS (Passive and Active L-band System) has a nominal spatial resolution of 1600 m. However, this resolution is not compatible with agricultural, meteorological and hydrological studies that require high spatial resolutions and this issue can be solved by soil moisture disaggregation. The soil moisture disaggregation algorithm integrates radiometer soil moisture retrievals and high-resolution radar observations and it can provide soil moisture estimates at a finer scale than the radiometer data alone. In this study, a change detection algorithm was used for disaggregation of coarse resolution passive microwave soil moisture retrievals with radar backscatter coefficients obtained from the higher spatial resolution UAVSAR (Unmanned Air Vehicle Synthetic Aperture Radar) at crop field scale. The accuracy of the disaggregated change in soil moisture was evaluated using ground based soil moisture measurements collected during SMAPVEX12 campaign. The results showed that soil moisture spatial variabilities were better characterized by the disaggregated change in soil moisture estimates at 5 m / 800 m resolution as well as good agreement with in situ measurements. It also showed that VWC (Vegetation Water Content) did not have a big impact on disaggregation algorithm performance, with R2 of the disaggregated results ranging 0.628-0.794. The 5 m and 800m resolution disaggregated soil moisture did no show significant difference in statistical performance variables.

Radar Backscatter↗

NASA NTRS2020

Variation of Florida scrub vegetation along gradients of soil pH and landscape age on a barrier island complex

Florida scrub is a fire-maintained shrub vegetation of well-drained, sandy soils associated with ridge systems that originated as coastal dunes. It is unique to Florida and supports many rare plants and animals. Between 1992 and 2005, we sampled 30 stands of long-unburned scrub with 196 line-intercept transects (15 m length) across the Merritt Island-Cape Canaveral barrier island complex where dune ridges range from relatively recent to > 30,000 years old with a range of soil leaching and reaction. These data allow us to determine the relationships of landscape age and soil reaction on community composition. We recorded community composition in < 0.5 m and > 0.5 m height strata. We determined mapped soil type for all transects; for 151 transects we determined soil pH of the 0–15 cm and 15–30 cm layers. Hierarchical cluster analysis of stands (N=30) and transects (N=196) using 41 species (of 53) present in > 2 transects gave two groups: coastal scrub with Quercus virginiana (shrub form) and Serenoa repens as dominant species on the most alkaline soils, and oak-saw palmetto scrub with Quercus chapmanii, Quercus geminata, Quercus myrtifolia, and S. repens on the strongly to somewhat acidic soils. Direct gradient analysis indicated that dominant species except S. repens varied from acidic to alkaline soils. Indicator species analysis identified seven species that indicated acidic soils and five that indicated alkaline soils (P < 0.01). Nonmetric multidimensional scaling (NMS) ordination at the stand level separated the two groups along the first axis, and NMS ordination of the transect data showed the gradient of coastal to oak-saw palmetto scrub. Position of transects on the first axis was related to soil pH class, and to measured pH of the 0–15 cm and 15–30 cm layers. Soils show a progressive leaching of shell material from the surface horizons followed by podsolization; this process takes > 4,000 years. Our results indicate substantial differences between the community composition of scrub vegetation on recent alkaline soils compared to leached acidic soils.

Barrier island↗

NASA NTRS2024

Shallow Soil Polychlorinated Biphenyl Site Assessment Report

PCBs↗

NASA NTRS1997

Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response

The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.

Sarabandi, Kamal↗

NASA NTRS2003

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗

NASA NTRS2005

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Sullivan, Dana↗

NASA NTRS2012

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Reichle, Rolf H.↗

NASA NTRS2024

The Spectral Characteristics of Lunar Agglutinates: Visible-Near-Infrared Spectroscopy of Apollo Soil Separates

The lunar surface evolves over time due to space weathering, and the visible–near-infrared spectra of more mature (i.e., heavily weathered) soils are lower in reflectance and steeper in spectral slope (i.e., darker and redder) than their immature counterparts. These spectral changes have traditionally been attributed to the space-weathered rims of soil grains (and particularly nanophase iron therein). However, understudied thus far is the spectral role of agglutinates—the agglomerates of mineral and lithic fragments, nanophase iron, and glass that are formed by micrometeoroid impacts and are ubiquitous in mature lunar soils. We separated agglutinates and non-agglutinates from six lunar soils of varying maturity and composition, primarily from the 125–250 μm size fraction, and measured their visible–near-infrared reflectance spectra. For each soil, the agglutinate spectra are darker, redder, and have weaker absorption bands than the corresponding non-agglutinate and unsorted soil spectra. Moreover, greater soil maturity corresponds to darker agglutinate spectra with weaker absorption bands. These findings suggest that agglutinates (rather than solely the space-weathered rims) play an important role in both the darkening and reddening of mature soils—at least for the size fractions examined here. Comparisons with analog soils suggest that high nanophase iron abundance in agglutinates is likely responsible for their low reflectance and spectrally red slope. Additional studies of agglutinates are needed both to more comprehensively characterize their spectral properties (across size fractions and in mixing with non-agglutinates) and to assess the relative roles of agglutinates and rims in weathering-associated spectral changes. Plain Language Summary - In scientific study of the Moon, one key focus is surface processes: how do physical and chemical properties of the Moon’s surface change over time due to weathering (e.g., bombardment by micrometeoroids and by particles from the Sun)? Such investigations provide valuable insights into the Moon’s history (such as the ages of impact craters) that are often deduced from measurements of reflected light; as a soil is weathered it reflects light differently, which manifests visually as a progressive darkening of the soil. This phenomenon had primarily been attributed to weathering-associated development of rims on individual soil grains, but in this work we explored an alternative cause: soil particles known as agglutinates (misshapen, vesicular agglomerates of mineral fragments, iron, and glass that form due to weathering processes). We isolated agglutinates of six soil samples from the Moon and measured how they reflect light. We find that they reflect light in patterns reminiscent of how the Moon’s surface does when weathered. These findings suggest that agglutinates play a more important role than previously thought in determining the light-reflecting properties of the Moon’s surface, thus warranting greater and more nuanced consideration in future studies of how the Moon’s surface changes over time.

spectroscopy↗