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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Historical Contingency in Microbial Resilience to Hydrologic Perturbations

Development of reliable biogeochemical models requires a mechanistic consideration of microbial interactions with hydrology. Microbial response to and its recovery after hydrologic perturbations (i.e., resilience) is a critical component to understand in this regard, but generally difficult to predict because the impacts of future events can be dependent on the history of perturbations (i.e., historical contingency). Fundamental issues underlying this phenomenon include how microbial resilience to hydrologic perturbations is influenced by historical contingency and how their relationships vary depending on the characteristics of microbial functions. To answer these questions, we considered a simple microbial community composed of two species that redundantly consume a common substrate but specialize in producing distinct products and developed a continuous flow reactor model where the two species grow with trade-offs along the flow rate. Simulations of this model revealed that (1) the history of hydrologic perturbations can lead to the shifts in microbial populations, which consequently affect the community's functional dynamics, and (2) while historical contingency in resilience was consistently predicted for all microbial functions, it was more pronounced for specialized functions, compared to the redundant function. As a signature of historical contingency, our model also predicted the emergence of hysteresis in the transitions across conditions, a critical aspect that can affect transient formation of intermediate compounds in biogeochemistry. This work presents microbial growth traits and their functional redundancy or specialization as fundamental factors that control historical contingencies in resilience.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

BOREAS HYD-3 Tree Measurements

The BOREAS HYD-3 team collected several data sets related to the hydrology of forested areas. This data set contains measurements of canopy density (closure), stem density, and DBH from a variety of sites. Canopy density measurements were made during the FFC-W and FFC-T 1994 in both the SSA and the NSA. Stem density measurements were made during FFC-W 1996 in the SSA only. Canopy density measurements were made using a forest densiometer, while measurements of stem density and DBH were made using standard techniques. This study was undertaken to predict spatial distributions of energy transfer, snow properties important to the hydrology, remote sensing signatures, and transmissivity of gases through the snow and their relation to forests in boreal ecosystems. The data are available in tabular ASCII 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).

Hardy, Janet P.↗
NASA NTRS2001

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Johnson, Donald R.↗
NASA NTRS1985

Sensitivity of an energy balance climate model with predicted snowfall rates

A snowfall parameterization and a polar-ice-sheet model are developed and applied to the two-level zonally averaged seasonal energy-balance climate model of Held and Suarez (1979), and sensitivity experiments involving changes in insolation are performed both with and without ice sheets. The results are presented in tables and graphs, and the hydrological-cycle response to insolation changes is found to be similar to that predicted by global-circulation models employing prescribed precipitation levels, with a somewhat higher sensitivity in the snow line. The area covered by ice sheets in the ice-sheet models is shown to be greater than that covered by permanent snow in the models without ice sheets, an effect attributed to lower surface temperatures over the ice. It is inferred that an increase in the solar constant can cause increased high-latitude precipitation but not an ice age.

Bowman, K. P.↗
DOE OSTI2022

Watershed Workflow: A toolset for parameterizing data-intensive, integrated hydrologic models

Integrated, distributed hydrologic models leverage advances in computational power and data accessibility to improve predictive understanding of the water cycle. While impressive advances in this area of environmental modeling have been accomplished, such models are still rarely used, partially because of difficulty integrating model and data. This research describes the release of Watershed Workflow version 1.2, a new library aiming to automate and enable complex workflows defining inputs to high resolution, integrated, distributed hydrologic models. Watershed Workflow provides tools enabling the discovery, acquisition, mapping, and coordination of watershed geometry, land cover, soil properties, and meteorological data. It enables the construction of unstructured meshes that incorporate this data, and provides tools for automating a “first” simulation on any watershed in the United States. We present the design of the workflow tool, and describe best practices for its usage, culminating in a final example from watershed specification to simulation at the Coweeta Hydrologic Laboratory.

Integrated hydrologic modeling↗
DOE OSTI2025

Drivers of Historical and Future Coastal Runoff Across the Arctic and Sub‐Arctic Subregions of Alaska, USA

This study investigates historical and future coastal runoff across the Arctic and sub-Arctic subregions of Alaska, USA, emphasising changes in terrestrial hydrology and their implications for coastal discharge. Using the physically based SnowModel-HydroFlow framework, historical (1991–2020) and future (2071–2100) coastal discharge climatologies were simulated, incorporating meteorological, topographic, and land cover inputs. Results reveal distinct seasonal and spatial patterns in temperature, precipitation, and snow dynamics across the Beaufort, Chukchi, Yukon, and Bristol subregions. Future projections suggest significant warming and shifts in hydrological regimes, such as increased annual precipitation and coastal discharge totals. Following a high emissions, business as usual pathway (SSP5-8.5), coastal discharge hydrographs in the Beaufort and Yukon subregions remain snow dominated with increases in discharge in nearly all months, while Chukchi and Bristol subregions shift from snow dominated to rain dominated. These changes are linked to rising temperatures, decreasing snow precipitation fractions, and altered freezing levels, with implications for water storage, timing, and availability. This research provides insights into the drivers and consequences of hydrological changes in a rapidly warming Arctic, supporting efforts to predict and mitigate the impacts on coastal and marine ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics

Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Peatland emissions are projected to increase under climate change, as rising temperatures and shifting precipitation accelerate microbial metabolic pathways favorable for CH 4 production. However, how these changing environmental factors will impact peatland emissions over the long term remains unknown. Here, we investigate a novel data set spanning an exceptionally long 11 years to analyze the influence of soil temperature and water table elevation on peatland CH 4 emissions. We show that higher water tables dampen the springtime increases in CH 4 emissions as well as their subsequent decreases during late summer to fall. These results imply that any hydroclimatological changes in northern peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if temperature remains unchanged. Furthermore, advancing hydrological understanding in peatland watersheds will be crucial for improving predictions of CH 4 emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Understanding the Hydrogeochemical Response of a Mountainous Watershed Using Integrated Surface‐Subsurface Flow and Reactive Transport Modeling

Abstract Climate change and other disturbances significantly impact hydrogeochemical exports from mountainous headwater catchments such as the Upper Colorado River Basin. Developing a mechanistic understanding of how the physical and chemical processes interact in time and space in an integrated manner is key to quantifying the future impacts of such disturbances. The hydrogeochemical response of a mountainous catchment in the 2010–2019 period is evaluated quantitatively using a high‐resolution model that simulates integrated hydrology, and transport and reactions for selected solutes and minerals. The model assumes that pyrite is present only at depth while calcite is distributed uniformly, and captures the observed C‐Q reasonably well. Distinct C‐Q dynamics are observed in an average (WY16), a wet (WY17), and a dry (WY18) water year. The model also quantifies the water fraction from surface, shallow and deep groundwater compartments using tracers, and suggests greater groundwater contributions to peak stream discharge in the dry WY18. Results demonstrate that calcium concentrations do not change significantly from year to year, while sulfate shows significant temporal variability. Pyrite dissolution is affected by the changing hydrological drivers where it is enhanced in the dry WY18; calcite dissolution supplements calcium dilution under high flow conditions. The model simulates the reaction hotspots controlled by hydrological conditions, and the spatially‐resolved results show that higher soil saturation and less snowpack occur earlier on the south‐facing side than on the north‐facing side. This is a first‐of‐its‐kind demonstration of a model that integrates hydrologic processes, including evapotranspiration, and reactive transport to enable a predictive understanding of hydrogeochemical exports.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Transition Zones at the Changing Coastal Terrestrial‐Aquatic Interface

Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience spatial and temporal variability in biogeochemical processes, driven by marsh‐to‐upland gradients and hydrological fluctuations. These fluctuations make it difficult to understand and predict biogeochemical processes in these highly dynamic systems. We studied coastal soil biogeochemistry and its variability (a) at regional scales and (b) across transects from upland forest to marsh, in two contrasting regions—Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity‐related analytes were a key source of variability in soil biogeochemistry, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI—however, contrary to expectations, transition soils were not consistently intermediate between upland and marsh endmembers; the non‐monotonic trends of C, P, Fe along our transects suggest that these do not behave as expected and may be difficult to model and predict—thus these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients (e.g., Ca, K, CEC, and TS) may act as precursors to ecosystem shifts. Our comprehensive soil characterization represents a snapshot of a single timepoint of surface soils and provides essential data for mechanistic modeling of ecosystem dynamics across coastal transects.

Patel, Kaizad F. [Pacific Northwest National Labor↗
DOE OSTI2021

Physics-Informed Machine Learning from Observations for Clouds, Convection, and Precipitation Parameterizations and Analysis

Fusing learning from Earth observations from space and from the ground (e.g., ARM) with newly developed interpretable and generalizable physics-informed model structures to improve the parameterization of clouds and convection and advance the simulation, understanding and analysis of hydrological extreme events. This covers the prescribed foci of (2) predictive modeling using a hierarchy of models and (3) insight gleaned from complex data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Initialization of soil-water content in regional-scale atmospheric prediction models

The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information. A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.

Smith, Christopher B.↗
NASA NTRS1999

Research and Educational Opportunities with NASA GSFC

The research carried out in the Earth sciences at NASA's Goddard Space Flight Center will be the focus of the presentation. These research interests span the full breath of disciplines in Earth System Science. Branches and research groups focus on areas as diverse as planetary geomagnetics and atmospheric chemistry. There are 4 major laboratories in the directorate and 2 organizations that focus on scientific information technology. These laboratories focus on atmospheric sciences (atmospheric chemistry, climate and radiation, regional processes, atmospheric modeling), hydrological sciences (snow, ice, oceans, and seasonal-to-interannual prediction), terrestrial physics (geology, terrestrial biology, land-atmosphere interactions, geophysics), climate modeling (global warming, greenhouse gases, climate change). Two of the labs also have branches that focus on sensor development especially using lidar and microwave technologies. In the information technologies, areas of scientific and technical research, and expertise include massively parallel computers, technologies for high speed electronic networks, scientific visualization, information systems, archive and distribution systems, and information processing. Examples will be presented from each of these research disciplines.

Meeson, Blanche W.↗
NASA NTRS2000

Earth System Science at NASA: Teleconnections Between Sea Surface Temperature and Epidemics in Africa

The research carried out in the Earth Sciences in NASA and at NASA's Goddard Space Flight Center will be the focus of the presentations. In addition, one research project that links sea surface temperature to epidemics in Africa will be highlighted. At GSFC research interests span the full breath of disciplines in Earth Science. Branches and research groups focus on areas as diverse as planetary geomagnetics and atmospheric chemistry. These organizations focus on atmospheric sciences (atmospheric chemistry, climate and radiation, regional processes, atmospheric modeling), hydrological sciences (snow, ice, oceans, and seasonal-to-interannual prediction), terrestrial physics (geology, terrestrial biology, land-atmosphere interactions, geophysics), climate modeling (global warming, greenhouse gases, climate change), on sensor development especially using lidar and microwave technologies, and on information technologies, that enable support of scientific and technical research.

Meeson, Blanche W.↗
NASA NTRS2001

An Integrated System for Water Budget Closure Over the Pan-Tropical Land Mass: A TRMM Validation Effort

A concerted effort was undertaken this past year to analyze the National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) Reanalysis II tropical hydrologic cycle. The topics included in this progress report are: (1) analysis of the surface hydrologic cycle; (2) long term CO2 sensitivity simulations with NCAR's CCM3 and global recycling rates; (3) tropical atmospheric hydrologic cycle; (4) GCIP (Global Continental Scale International Project) WEBS (Water and Energy Budget Synthesis); (5) the impact of precipitation uncertainties on global water balance calculations.

Roads, J.↗
NASA NTRS1997

Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.

Hsu, A. Y.↗
DOE OSTI2025

A Scale‐Adaptive Urban Hydrologic Framework: Incorporating Network‐Level Storm Drainage Pipes Representation

Abstract Below‐ground urban stormwater networks (BUSNs) significantly influence urban flood dynamics, yet their representation at the watershed or larger scales remains challenging. We introduce a scalable urban hydrologic framework that centers on a novel network‐level BUSN representation, balancing the needs for physical basis, parameter parsimony, and computational efficiency. Our framework conceptualizes an urban watershed into four interacting zones: hillslopes (natural), storm‐sewersheds (urban), a sub‐network channel (tributaries), and a main channel. We develop an innovative Graph Theory‐based algorithm to derive network‐level BUSN parameters from publicly available datasets, enabling efficient, scalable parameterization. We demonstrate this framework's applicability at nine representative watersheds in the Houston metropolitan region, USA, with urban imperviousness ranging from 0% to 64% and drainage areas ranging from 24 to 302 . Our model achieves satisfying computational efficiency, completing hourly time step simulations for 18 years in less than 5 sec per watershed on a standard PC. Validation against observed daily streamflow confirms that the model can capture small‐to‐large flood peaks and seasonal and annual water balance over these watersheds. Comparisons with the National Water Model show better performance in predicting flood peaks and overall water balance, underscoring the promises of our new framework for urban hydrologic modeling at large scales. Furthermore, analysis reveals nonlinear relationships between BUSNs' designed capacities and flood reduction effects. Our approach bridges the gap between detailed hydraulic and large‐scale hydrologic models, providing a valuable tool for urban flood prediction and management across broader spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hydrological and Thermal Dynamics of a Supra‐Permafrost Subterranean Estuary

Subterranean estuaries (STEs), where groundwater interacts with seawater, influence surface and subsurface coastal ecology and biogeochemistry. In Arctic-STEs overlying permafrost, groundwater flow and heat transport determine the fate of organic matter. Yet, direct observations of groundwater flow and heat and solute transport processes in Arctic STEs remain limited. This study characterized groundwater flow paths and fluxes and heat transport within an Arctic-STE along Alaska's Beaufort Sea coast during thawing, summer, and freeze-up. Intertidal seabed temperature-depth profiles collected along a 10-m transect captured the active groundwater flow period, from thaw and flow onset in mid-June to freeze-up in late-September. During this period, aquifer geometry evolved non-uniformly due to spatially varying thaw rates across the STE (mean (m) thaw depths–beach: 0.25 to 0.55–0.6 m on 20 June, 25 July, 1 October; seabed: 0.6–0.9 m from 25 July to 1 October). Groundwater and surface water levels, salinity, and subsurface temperature profiles measured over tidal time scales were interpreted alongside groundwater flow-heat transport numerical simulations. Fresh groundwater discharge was sporadic during thawing (m: 0.32 m 3 /day/m), abundant in summer (m: 0.45 m 3 /day/m), and was largely absent during freeze-up. During freeze-up, groundwater flow was driven exclusively by seawater recirculation via tidal pumping (from thawing to summer to freeze-up: 0.00025–0.15–0.5 m3/day/m) and convection. Heat advection dominated near aquatic interfaces (shaping intertidal ice), and conduction controlled vertical temperature gradients in low-flow and unsaturated sediments. These findings will help predict how prolonged summers will alter Arctic-STE cryo-hydrology and biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗