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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
DOE OSTI2023

Development of a molecularly informed biogeochemical framework for reactive transport modeling of subsurface carbon inventories, transformations and fluxes (Final Report)

The overall objective of the project was to combine new molecular-level characterization strategies with soil carbon flux measurements to develop and evaluate model representations of subsurface carbon cycling. We expanded on existing studies in the East River watershed, Colorado, in collaboration with the Berkeley Lab Watershed Function Scientific Focus Area (SFA), SLAC Groundwater Quality SFA, and Rocky Mountain Biological Laboratory (RMBL) to develop an elevation and vegetation gradient that is now the subject of long-term monitoring by the USGS. To achieve the overall objective, we combined field studies of soil respiration with laboratory analyses, ranging from spectroscopy to incubation studies. This combination of techniques enabled us to develop a new understanding of the drivers of high-elevation soil respiration. In the process, we developed three new modeling approaches that improve our ability to conceptualize and ultimately to represent soil respiration in numerical models. The first approach is a plot-scale transient inverse model that can be used to determine in situ CO 2 production rates from measured concentration profiles and surface fluxes. Application of this method revealed the importance of plant phenology and deep CO 2 production in moderating CO 2 fluxes to the atmosphere. The second modeling approach is a molecular-scale tool that enables spectroscopic and elemental data for carbon speciation to be transformed into functional group abundances, or the ‘SOC-fga model’. This method uniquely enables carbon speciation to be tracked within a reactive transport framework to partition carbon among different pathways and storage zones within the soil. The third modeling tool builds strongly on the previous approaches and captures the microbial processes driving heterotrophic respiration. This ‘dormancy model’ allows the native soil microbial population to respond transiently to the presence or absence of water in order to catalyze carbon respiration. This approach was also compared to the simpler and more widely used first-order model using two experimental datasets with different temporal and spatial resolutions. Our results illustrate that the simpler first order model provides a robust and efficient representation of deep (>1 meter) soil respiration, but that shallow soils, where most respiration occurs, require explicit representation of moisture-dependent activation and dormancy rates. By assessing soil organic carbon turnover at multiple scales, we see a complex array of controls emerge. Atte scale of a hillslope, spatial heterogeneity in soil respiration rates dominates and is uncorrelated with instantaneous soil moisture and plant community. At the profile scale, the balance between plant inputs and water availability is the dominant control. At the microbial to molecular scale, physiological processes associated with carbon use and carbon speciation are important controls. These scale-dependent controls emphasize the need for new modeling approaches that examine their interactions and hierarchies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Physicochemical Gas–Solid Sorption Properties of Geologic Materials Using Inverse Gas Chromatography

The goal of this study was to determine the physicochemical properties of a variety of geologic materials using inverse gas chromatography (IGC) by varying probe gas selection, temperature, carrier gas flow rate, and humidity. This is accomplished by measuring the level of interaction between the materials of interest and known probe gases. Identifying a material’s physicochemical characteristics can help provide a better understanding of the transport of gaseous compounds in different geologic materials or between different geological layers under various conditions. Our research in this study focused on measuring the enthalpy (heat) of adsorption, Henry’s constant, and diffusion coefficients of a suite of geologic materials, including two soil types (sandy clay-loam and loam), quartz sand, salt, and bentonite clay, with various particle sizes. The reproducibility of IGC measurements for geologic materials, which are inherently heterogeneous, was also assessed in comparison to the reproducibility for more homogeneous synthetic materials. This involved determining the variability of physicochemical measurements obtained from different IGC approaches, instruments, and researchers. For the investigated IGC-determined parameters, the need for standardization became apparent, including the need for application-relevant reference materials. The inherent physical and chemical heterogeneities of soil and many geologic materials can make the prediction of sorption properties difficult. Characterizing the properties of individual organic and inorganic components can help elucidate the primary factors influencing sorption interactions in more complex mixtures. This research examined the capabilities and potential challenges of characterizing the gas sorption properties of geologic materials using IGC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
DOE OSTI2024

Continuous soil temperature measurements from 2019-10-4 to 2020-10-4, Teller road Mile 27, Seward Peninsula, Alaska

The dataset contains depth-resolved soil temperature measured at 45 discrete locations in a watershed located along the Nome-Teller road at Mile 27 in Seward Peninsula, Alaska. The dataset was generated to understand the local heterogeneity of soil thermal dynamics and their controls in a discontinuous permafrost region. At each location, temperatures were measured by a distributed temperature profiling probe designed based on Dafflon et al (2022). The dataset includes a description of the probe locations in the "Probe_locations.csv" file and the 45 data files (Soil_temperatures_*.csv). Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in NGA513_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A hybrid data–model approach to map soil thickness in mountain hillslopes

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

58 GEOSCIENCES↗
DOE OSTI2026

A Comprehensive Greenhouse Gas Assessment of Biomass-Based Carbon Dioxide Removal and Storage

Biomass-based Carbon Removal and Storage (BiCRS) is a suite of technological pathways that provide a relatively affordable and high-potential way to remove carbon dioxide from the atmosphere and simultaneously re-purpose residual biomass. BiCRS technologies are individually optimized to different biomass feedstocks, temperatures and oxygen, with the primary goal of capturing a high percentage of biomass-derived carbon dioxide and storing it in permanent below-ground storage (i.e. geologic storage), and a secondary goal of producing renewable energy. The current standard for BiCRS life cycle assessments does not account for greenhouse gas (carbon dioxide, methane and nitrous oxide) fluxes from surface soil amendment of BiCRS byproducts (e.g. char, ash) and their alternate fates. This is partly due to a paucity of empirical data due to the novelty of BiCRS conversion technologies, the range in feedstocks, and the heterogeneity of soils to which they might be amended. To fill this gap in in the life-cycle assessment and provide a realistic range of parameters for a soil amendment component of the BiCRS life cycle assessment, we conducted an incubation experiment to measure soil carbon changes, microbial respiration, methane fluxes, and nitrous oxide fluxes from two different soils amended with char- and ash- byproducts from biomass after gasification to hydrogen, fast pyrolysis to bio-oil, and torrefaction. Our results suggest that nitrous oxide and methane emission or consumption from BiCRS char amendments to soil are context dependent. Nitrous oxide emissions from amendments are higher in soils with higher pH, whereas some char amendments to low pH soil can reduce N 2 O emissions relative to control. In contrast, methane is emitted from BiCRS char amended to low pH soil, but consumed or neutral relative to control when amended to high pH soil. We present carbon and nitrogen mass balance throughout the experiment to help understand short-term durability of BiCRS chars and their counterfactuals, and preliminary suggestions for revisions to the broader BiCRS Measurement, Reporting, and Verification framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Comprehensive Greenhouse Gas Assessment of Biomass-Based Carbon Dioxide Removal and Storage

Biomass with Carbon Removal and Sequestration (BiCRS) is a suite of technological pathways that provide a relatively affordable and high-potential way to remove carbon dioxide from the atmosphere and simultaneously re-purpose residual biomass. BiCRS technologies are individually optimized to different biomass feedstocks, temperatures and oxygen, with the goal of capturing a high percentage of biomass-derived carbon dioxide and storing it in permanent below-ground storage (i.e. geologic storage). The current standard for BiCRS life cycle assessments does not account for carbon dioxide, methane and nitrous oxide (CO 2 , CH 4 , and N 2 O) fluxes from surface soil amendment of BiCRS byproducts (e.g. char, ash) and their alternate fates. This is partly due to a paucity of empirical data due to the novelty of BiCRS conversion technologies, the range in feedstocks, and the heterogeneity of soils to which they might be amended. To fill this gap in in the life-cycle assessment (LCA) and provide a realistic range of parameters for a soil amendment component of the BiCRS LCA, we conducted an incubation experiment to measure soil carbon changes, microbial respiration, methane fluxes, and nitrous oxide fluxes from two different soils amended with char- and ash- byproducts from biomass after gasification to hydrogen, fast pyrolysis to bio-oil, and torrefaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

Land–atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture–precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture–precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. Furthermore, we find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture–precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Colloidal metal transport in soils developing on historic coal mine spoil

Chemical weathering of pyrite via oxidative dissolution is well-known for generating Fe(III)-bearing colloids at acid mine drainage (AMD) sites; however, the potential for physical weathering of pyrite-bearing materials and subsequent release and transport of colloidal pyrite and associated trace metals has not been studied. Here, we monitored the colloidal metal transport in soil developing on abandoned coal mine spoil with a history of AMD generation to systematically study the contribution of colloids to base and trace metal transport and determine the elemental and mineralogical composition of colloids. Additionally, we collected soil pore water using lysimeters with a pore size of approximately 1.3 μm and centrifugation was used to separate the colloids from aqueous fractions. Metal concentrations of Na, Ca, Mg, K, Si, Al, Mn, Fe, Cu, and Zn were analyzed. Our results show only 14% of the total Al and Cu were present in colloidal fractions whereas 23%, 43%, and 54% of Fe, Mn, and Zn were transported in the colloidal phase, respectively. In contrast, all base metals were primarily present in the aqueous concentration with a small fraction (<10%) present in the colloidal phase. The colloidal fractions of the base metals were inferred to be associated with the concentration of clay colloids. The release of colloids exhibited possible sensitivity toward weather conditions such as alternating high temperatures and rainfall during summer (May–July) compared to fall (August–November). The morphology, elemental, and mineral composition of colloids were determined by a scanning electron microscopy equipped with energy dispersive spectroscopy (SEM-EDS) and X-ray diffraction (XRD). Colloids were dominated by phyllosilicates (biotite, muscovite, and kaolinite) with minor quartz and feldspars. Other minerals phases identified in colloidal fractions were hematite, goethite, arsenopyrite, and chalcopyrite. Colloids consisting of Fe, S, and O with structures resembling framboidal pyrite were identified, which is consistent with the non-silicates minerals identified by XRD. Our study suggests that the physical weathering of pyrite in the mine spoil can generate colloidal pyrite, which is mobilized and transported by soil pore water. Our results also indicate that these pyritic colloids are associated with toxic trace metals including Cu, Mn, and Zn. Colloid mobilization is also impacted by changes in temperature and precipitation, where clay mobilization afer rain events is favored. Further, sudden spikes in aqueous and/or colloidal concentrations may be the result of local heterogeneity within soils developing on mine spoil, indicating that further field-based work is necessary to better characterize pore-scale processes that control aqueous and colloid transport at similar sites to have a better understanding of potential contaminant transport from mine spoil systems.

58 GEOSCIENCES↗
DOE OSTI2021

Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

Abstract The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.

Virkkala, Anna‐Maria↗
NASA NTRS1988

Evapotranspiration from nonuniform surfaces - A first approach for short-term numerical weather prediction

Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.

Wetzel, Peter J.↗
NASA NTRS1997

Airborne Microwave Radiometry on a Semi-Arid Area During HAPEX-Sahel

Airborne microwave radiometric measurements in the framework of the HAPEX-Sahel Experiment were performed by the Push Broom Microwave Radiometer (PBMR) and the PORTOS radiometer. The flights of both radiometers produced an original set of data covering the 1.4-90 GHz range of frequency. The East and West Central Super Sites were the areas most intensively observed by the microwave radiometers. Over those sites, several brightness temperature (TB) maps are available at seven dates distributed over a 1 month period in the middle of the rainy season. A comparison of the two radiometers demonstrates their radiometric quality and the precision of the localization of the microwave observations. At 1.4 GHz, the vegetation had very little effect on the soil microwave emission. Maps of soil moisture were developed using a single linear relationship between TB and the surface soil moisture. There is an important spatial heterogeneity in the soil moisture distribution, which is explained by both the soil moisture hydrodynamic properties and the localization of the precipitation fields. At 5.05 GHz, the vegetation must be accounted for to infer soil moisture from the microwave observations. A method based on a simple radiative transfer model and on microwave data has shown encouraging results.

Chanzy, A↗
DOE OSTI2021

Soil gas probes for monitoring trace gas messengers of microbial activity

Abstract Soil microbes vigorously produce and consume gases that reflect active soil biogeochemical processes. Soil gas measurements are therefore a powerful tool to monitor microbial activity. Yet, the majority of soil gases lack non-disruptive subsurface measurement methods at spatiotemporal scales relevant to microbial processes and soil structure. To address this need, we developed a soil gas sampling system that uses novel diffusive soil probes and sample transfer approaches for high-resolution sampling from discrete subsurface regions. Probe sampling requires transferring soil gas samples to above-ground gas analyzers where concentrations and isotopologues are measured. Obtaining representative soil gas samples has historically required balancing disruption to soil gas composition with measurement frequency and analyzer volume demand. These considerations have limited attempts to quantify trace gas spatial concentration gradients and heterogeneity at scales relevant to the soil microbiome. Here, we describe our new flexible diffusive probe sampling system integrated with a modified, reduced volume trace gas analyzer and demonstrate its application for subsurface monitoring of biogeochemical cycling of nitrous oxide (N 2 O) and its site-specific isotopologues, methane, carbon dioxide, and nitric oxide in controlled soil columns. The sampling system observed reproducible responses of soil gas concentrations to manipulations of soil nutrients and redox state, providing a new window into the microbial response to these key environmental forcings. Using site-specific N 2 O isotopologues as indicators of microbial processes, we constrain the dynamics of in situ microbial activity. Unlocking trace gas messengers of microbial activity will complement -omics approaches, challenge subsurface models, and improve understanding of soil heterogeneity to disentangle interactive processes in the subsurface biome.

04 OIL SHALES AND TAR SANDS↗
NASA NTRS1993

Spatial Variations in the Spectral Properties of Bright Regions on Mars

Much of the surface of Mars is covered by material that is bright and reddish at visible wavelengths and which is interpreted as chemically altered soil. High spatial resolution data from the ISM near-infrared imaging spectrometer on the Phobos 2 spacecraft have provided new information about the composition and compositional heterogeneity of this soil. Most bright soil exhibits a weak, narrow absorption feature near 2.2 micron, suggesting the presence of poorly crystalline phyllosilicate. The strength of the 3.0-micron H2O absorption exhibits spatially coherent variations, with stronger absorptions occurring in specific geologic units. These variations may result from differences in the content of molecular water in soils developed on different deposits. Additionally, the position and shape of the 0.9-micron Fe(3+) absorption indicate hematite to be present in bright soils covering many areas, including Tharsis. However, other large areas covered by bright soil, including much of Arabia, exhibit a deeper absorption at a longer wavelength, suggesting occurrence of ferric minerals other than hematite. These spectral heterogeneities indicate that bright martian soil is compositionally diverse and not completely homogenized by eolian activity. The compositional differences may result from different histories of chemical alteration of parent materials and their resulting soils, possibly including local effects of liquid water.

Murchie, Scott↗
NASA NTRS2022

Local Scale (3-M) Soil Moisture Mapping Using SMAP and Planet Superdove

A capability for mapping meter-level resolution soil moisture with frequent temporal sampling over large regions is essential for quantifying local-scale environmental heterogeneity and eco-hydrologic behavior. However, available surface soil moisture (SSM) products generally involve much coarser grain sizes ranging from 30 m to several 10s of kilometers. Hence a new method is proposed to estimate 3-m resolution SSM using a combination of multi-sensor fusion, machine- learning (ML) and Cumulative Distribution Function (CDF) matching approaches. This method established favorable SSM correspondence between 3-m pixels and overlying 9-km grid cells from overlapping Planet SuperDove (PSD) observations and NASA Soil Moisture Active-Passive (SMAP) mission products. The resulting 3-m SSM predictions showed improved accuracy by reducing ab- solute bias and RMSE by ~0.01 cm3/cm3 over the original SMAP data in relation to in-situ soil moisture measurements for the Australian Yanco region, while preserving the high sampling frequency (1-3 day global revisit) and sensitivity to surface wetness (R 0.865) from SMAP. Heterogeneous soil moisture distributions varying with vegetation biomass gradients and irrigation regimes were generally captured within a selected study area. Further algorithm refinement and implementation for regional applications will allow for improvement in water resources management, precision agriculture, and disaster forecasts and responses.

soil moisture↗