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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advancing stream temperature prediction with a generalizable large-sample framework across CONUS river reaches

Accurately predicting stream temperature in ungauged basins remains a critical challenge for water resource management, thermoelectric power plant cooling, and ecosystem conservation. Large-sample machine learning models trained on hundreds of well-monitored river basins have shown remarkable performance; however, such models have yet to be developed solely using forcing data that can be readily extracted to simulate stream temperatures anywhere in the contiguous United States (CONUS). In this study, we present a scalable, large-sample deep learning framework using Long Short-Term Memory (LSTM) networks to simulate daily stream temperatures in ungauged basins across the CONUS. The framework leverages both modeled reanalysis of meteorological and streamflow inputs as well as static attributes available for all 2.7 million CONUS river reaches in the National Hydrography Dataset Plus (NHDPlusV2). By generating dynamical inputs from predefined thermally relevant upstream contributing areas, rather than the entire upstream basin, the model also offers improvements in very large basins where full-basin averaging can dilute the most important influences on stream temperature. Evaluated across 300 basins, the model achieves a median Mean Absolute Error (MAE) of 1.1 °C and a Nash-Sutcliffe Efficiency (NSE) of 0.95 on temporally and spatially distinct test folds—comparable to models trained exclusively using meteorological and streamflow observational data. The flexible, high-performing framework generalizes to any unmonitored river reach without significant regulation or unnatural thermal input immediately upstream, substantially expanding predictive capabilities in data-scarce regions.

Hydrology↗
DOE OSTI2024

Efficient species identification for Pacific salmon genetic monitoring programs

Abstract Genetic monitoring of Pacific salmon in the Columbia River basin provides crucial information to fisheries managers that is otherwise challenging to obtain using traditional methods. Monitoring programs such as genetic stock identification (GSI) and parentage‐based tagging (PBT) involve genotyping tens of thousands of individuals annually. Although rare, these large sample collections inevitably include misidentified species, which exhibit low genotyping success on species‐specific Genotyping‐in‐Thousands by sequencing (GT‐seq) panels. For laboratories involved in large‐scale genotyping efforts, diagnosing non‐target species and reassigning them to the appropriate monitoring program can be costly and time‐consuming. To address this problem, we identified 19 primer pairs that exhibit consistent cross‐species amplification among salmonids and contain 51 species informative variants. These genetic markers reliably discriminate among 11 salmonid species and two subspecies of Cutthroat Trout and have been included in species‐specific GT‐seq panels for Chinook Salmon, Coho Salmon, Sockeye Salmon, and Rainbow Trout commonly used for Pacific salmon genetic monitoring. The majority of species‐informative amplicons (16) were newly identified from the four existing GT‐seq panels, thus demonstrating a low‐cost approach to species identification when using targeted sequencing methods. A species‐calling script was developed that is tailored for routine GT‐seq genotyping pipelines and automates the identification of non‐target species. Following extensive testing with empirical and simulated data, we demonstrated that the genetic markers and accompanying script accurately identified species and are robust to missing genotypic data and low‐frequency, shared polymorphisms among species. Finally, we used these tools to identify Coho Salmon incidentally caught in the Columbia River Chinook Salmon sport fishery and used PBT to determine their hatchery of origin. These molecular and computing resources provide a valuable tool for Pacific salmon conservation in the Columbia River basin and demonstrate a cost‐effective approach to species identification for genetic monitoring programs.

Robinson, Zachary L.↗
DOE OSTI2023

Fulfilling global climate pledges can lead to major increase in forest land on Tibetan Plateau

The UN Climate Change Conference in Glasgow spawned the enhancement and updating of many nations’ climate pledges. Previous research has investigated the effects of these pledges on limiting planetary warming, but their spatially explicit effects on land use/cover are unknown. Here, we linked the Glasgow pledges and the spatially explicit responses of the Tibetan Plateau’s land systems. We found that while fulfilling global climate pledges may not significantly affect the global shares of forestland, grassland/pasture, shrubland, and cropland, it needs a 9.4% increase in the forest area of the Tibetan Plateau. This need is an area 11.4 times the increase of the plateau’s forest in the 2010s, or greater than the size of Belgium. The new forest comes mainly from the medium-density grassland in the Yangtze River basin, calling for more proactive environmental management for the headwaters area of this longest river in Asia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Uranyl oxalate species in high ionic strength environments: stability constants for aqueous and solid uranyl oxalate complexes

Uranyl ion, UO 2 2+ , and its aqueous complexes with organic and inorganic ligands can be the dominant species for uranium transport on the Earth surface or in a nuclear waste disposal system if an oxidizing condition is present. As an important biodegradation product, oxalate, C 2 O 4 2– , is ubiquitous in natural environments and is known for its ability to complex with the uranyl ion. Oxalate can also form solid phases with uranyl ion in certain environments thus limiting uranium migration. Therefore, the determination of stability constants for aqueous and solid uranyl oxalate complexes is important not only to the understanding of uranium mobility in natural environments, but also to the performance assessment of nuclear waste disposal. In this work, we developed a thermodynamic model for the UO 2 2+ –Na + –H + –Cl – –ClO 4 – –C 2 O 4 2– –NO 3 – –H 2 O system to ionic strength up to ~11 mol•kg –1 . We constrained the stability constants for UO 2 C 2 O 4 (aq) and UO 2 (C 2 O 4 ) 2 2– at infinite dilution based on our evaluation of the literature data over a wide range of ionic strengths up to ~11 mol•kg –1 . We also obtained the solubility constants at infinite dilution for solid uranyl oxalates, UO 2 C 2 O 4 •3H 2 O, based on the solubility data over a wide range of ionic strengths. The developed model will enable for the accurate stability assessment of oxalate complexes affecting uranium mobility under a wide range of conditions including those in deep geological repositories.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Observationally-based relations among water cycle parameters during snowfall events in the Upper Colorado River Basin

Cold-season precipitation predictability within the complex terrain of the Upper Colorado River Basin is vital for water resource management across many western states, as the Colorado River serves as a primary source of water for over 40 million people in the Western United States and Mexico. This study uses the remote sensing measurements of such water cycle parameters as the liquid equivalent snowfall rate, S, and accumulation, A, vertically integrated amounts of supercooled cloud liquid and ice expressed as liquid water path(LWP) and ice water path (IWP), respectively, and vertically integrated water vapor IWV.

Matrosov, Sergey [CIRES University of Colorado Bou↗
NASA NTRS2019

Reviewing Benefits and Costs of Hydropower Development Evidence From the Lower Mekong River Basin

In this paper, we examine the benefits and costs of hydropower development in the Mekong River Basin. We compare four major reports—the Mekong River Commission's (MRC's) Basin Development Plan Programme, Phase 2 (BDP2), the Strategic Environmental Assessment of Hydropower on the Mekong Mainstream (SEA), the Study on the Impacts of Mainstream Hydropower on the Mekong River (MDS), and the MRC's recent council study (CS)—in order to provide the basis for a comparative analysis of the major impact evaluation literature on mainstream dam construction in the Mekong River Basin for the period of 2010–2018. The primary objective of the review is to identify points of agreement, disagreement, inconsistency, and knowledge gaps. Both Mekong River Commission reports (BDP2 and CS) suggest extensive economic benefits for proposed hydropower development, whereas the SEA and MDS indicate that the net impact would be negative. The projected impacts of hydropower development on fisheries, sediment flows, and ecosystems vary widely both in economic and biophysical terms. However, all four reports point to decreased food security and loss of local livelihoods for millions of people as major concerns related to dam development. While considerable resources have been devoted to producing these important studies, the lack of standardization across reports, especially assumptions and methodologies for economic impacts, frustrates efforts at meaningful comparison of their findings and precludes the prospect of clear analytical outcomes or policy impacts.

Cumulative impact assessment↗
DOE OSTI2024

Hydrologic applicability of satellite-based precipitation estimates for irrigation water management in the data-scarce region

Reliable precipitation estimates are crucial for planning and managing water resources, monitoring hydrologic extremes, and fulfilling irrigation water requirements. Accurate precipitation estimates are particularly challenging in complex mountain terrains, where monitoring gauges are often sparsely distributed due to their remote locations, and high installation and long-term operation costs. Recent advances in satellite-based precipitation estimates offer promising opportunities to improve our understanding of hydrologic processes and their applications for irrigation water management. Several datasets are available varying considerably in terms of their data sources, quality control methods, estimation procedure, and spatiotemporal resolutions. Choosing the most suitable dataset for a particular application is a complex task. In this study, we (1) evaluate the performance of six satellite-based precipitation estimates (SPEs): i) CHIRPS v2.0, ii) CMORPH v1.0, iii) ERA5, iv) IMERG v6, v) MSWEP v2.8, and vi) PERSIANN-CDR against the gauge precipitation using continuous statistical and categorical indices, (2) integrate SPEs with a calibrated semi-distributed hydrologic model to predict streamflow, and (3) demonstrate practical implications of improved streamflow prediction for irrigation water management in the central Himalayan region, Nepal. Our results illustrate that satellite-based precipitation estimates have competitive performance in capturing a wide range of rainfall characteristics, with demonstrated variability across river basins and time scales. Further, there are no significant discrepancies observed in satellite-based precipitation estimates for estimating irrigation water requirements for the three major crops (maize, wheat, and paddy) during the cropping period across the selected river basins, showing a greater promise for irrigation water management planning and decision making.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Evaluating the Performance of GPM IMERG Products for Extreme Precipitation Estimation in Volta River Basin of Ghana

The Volta River basin in West Africa, covering a substantial area of Ghana, faces significant water management challenges due to highly variable rainfall and limited availability of high temporal resolution rain gauges. This study, developed under the 2024 Global Precipitation Measurement (GPM) Mission mentorship program, evaluates precipitation in the Volta River basin using high-resolution satellite-derived data from the Integrated Multi-satellite Retrievals for GPM (IMERG). In the absence of sub-daily rainfall data, comparisons were made between daily, monthly, and seasonal precipitation from local gauges and IMERG V06 and V07 (early and final) runs. Results indicated a very weak correlation between daily precipitation estimates from IMERG and gauge data, but a significantly improved correlation for monthly and seasonal estimates. Additionally, IMERG data were used to identify heavy rainfall events and drought periods, which were compared to known occurrences in the region. By addressing these objectives, this study contributes to more accurate extreme precipitation estimation in the Volta River basin, thereby enhancing disaster risk management and climate resilience in Ghana.

Jessica Sutton↗
DOE OSTI2025

Machine Learning Prediction of Tritium‐Helium Groundwater Ages in the Central Valley, California, USA

Abstract Groundwater ages provides insight into recharge rates, flow velocities, and vulnerability to contaminants. The ability to predict groundwater ages based on more accessible parameters via Machine Learning (ML) would advance our ability to guide sustainable management of groundwater resources. In this study, ML models were trained and tested on a large data set of tritium concentrations and tritium‐helium groundwater ages from the California Central Valley, a large groundwater basin with complex land use, irrigation, and water management practices. The ML models were trained on 63 features, including location, well construction information, landscape characteristics, and climate variables, water chemistry, and stable isotopes. The Bagging regressor method can accurately classify (F1‐score = 0.91) groundwater samples as either modern or pre‐modern whereas the accuracy of the ML prediction of continuous tritium‐helium groundwater ages is limited and explains only of the variability in this data set. In general, ML groundwater age prediction relies mostly on features related to (a) the source of groundwater recharge, (b) contaminant history, (c) aquifer materials, (d) well construction, and (e) geochemical reactions along flow paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins

Droughts across the U.S. have imposed substantial challenges to the management of water resources. Reservoir drought, one type of hydrological drought, is characterized by abnormally low reservoir storage levels, reflecting combined impacts of natural water shortages and water management practices. We investigate how reservoir drought signatures, particularly onset, severity, duration, recovery and frequency, may shift under rising temperatures, and how these shifts vary by reservoir typology and degree of regulation. By coupling atmosphere-land-river models with reservoir operations at ~12-km resolution, we simulated reservoir storage and characterized reservoir droughts across five heavily regulated U.S. basins. Our findings reveal significant regional and functional disparities in reservoir drought resilience under the scenario of rising temperatures. Reservoirs in the Texas-Gulf region are projected to become more resilient, while systems in the Upper Colorado and South Atlantic-Gulf regions face increased risk due to prolonged drought durations and slower recovery. With respect to primary function, reservoirs used for irrigation and hydropower, particularly those with smaller storage capacity and lower degrees of regulation, are most susceptible to future drought stress. These results are valuable in understanding water availability in highly regulated environments, and the influence of hydrometeorological conditions on storage dynamics. Overall, this study provides the first of its kind benchmark for reservoir droughts at a continental scale to support evolving multi-sectoral drought mitigation efforts. Future research is needed to link reservoir drought conditions to actual supply shortages across competing water uses, while leveraging existing adaptive management strategies and coordinated reservoir operations.

reservoir↗
NASA NTRSDate not supplied

Openet: Applications of Satellite-Based Evapotranspiration Data for Water Resources Management in the Western United States

Advancing water security in overallocated river basins globally requires consistent and reproducible information on consumptive use of water that can anchor the development of data-driven solutions to the challenge of balancing water supply and demand. OpenET is a fully automated system for field-scale (30 m), satellite-based mapping of evapotranspiration (ET) at daily, monthly and annual timesteps. OpenET currently provides spatially contiguous data throughout the 23 westernmost states in the continental US, and includes both current information as well as multi-year timeseries of ET. The OpenET consortium has implemented an ensemble of satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) on Google Earth Engine, which provides a shared computing platform for collaboration on processing of data from Landsat and other satellites, land cover and meteorological inputs, leading to increased consistency and accuracy across the ensemble of models. Earth Engine also facilitates hosting and distribution of data via open data collections and an application programming interface. We provide updates on the OpenET framework, open data services and data access tools, approach to geographic expansion, recent accuracy assessments, and describe how a user-driven design approach has facilitated successful applications of OpenET data for a wide range of water resource management activities. Applications to date include: use of ET data to improve quantification of ET and consumptive use in Oregon, Utah and the Upper Colorado River Basin; streamlining of water use reporting requirements in the California Delta; support for calculation of water budgets for the implementation of the Sustainable Groundwater Management Act in California; and integration into decision support tools for irrigation management. The use cases demonstrate how satellite-derived ET data that are easily accessed and seen as broadly accepted can accelerate adoption of innovative water management practices at scale, and support advances in the sustainability of water supplies. Uptake and use of data by the OpenET science community has also led to advances in our understanding of the impacts of landcover change, irrigation intensification and wildfire events on hydrology and the water security.

Applications↗
DOE OSTI2026

A dendritic strontium river isoscape for fisheries applications in the Sacramento River basin, California, USA

Objective Understanding the origins and movements of fish is fundamental to effective conservation and fisheries management. Strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths provide a powerful tracer of natal origin and migratory pathways. However, existing 87 Sr/ 86 Sr isoscapes for the Sacramento River basin, an ecosystem that supports ecologically and economically important salmon populations, rely on discrete classification approaches that overlook unsampled habitats and do not incorporate spatial uncertainty. Our objective was to develop a continuous, network-explicit 87 Sr/ 86 Sr isoscape with quantified uncertainty to fill in data gaps and enable probabilistic assignments of fish origin and movement. Methods We used river water 87 Sr/ 86 Sr data from 106 sites (1997–2021) to develop spatial stream network models that use dendritic connectivity and watershed characteristics (lithology, bedrock age, and land cover) to predict river water 87 Sr/ 86 Sr throughout the basin. Models were fitted using maximum and restricted likelihood and were evaluated via Akaike’s information criterion and leave-one-out cross validation. We produced both historical (pre-dam) and present-day (below-dam) isoscapes, delineated uncertainty-informed isotopic ranges using k -means clustering, and applied a proof-of-concept Bayesian assignment to estimate natal origins and early rearing habitats for two endangered winter-run Chinook Salmon Oncorhynchus tshawytscha. Results Cross validation indicated strong performance of the 87 Sr/ 86 Sr model (leave-one-out cross validation: R 2 = 0.91; root mean square error = 0.0005). Uncertainty-informed clustering identified 19 isotopic “suites” (reaches with indistinguishable 87 Sr/ 86 Sr values) in present-day anadromous habitats and 25 suites in the historical network. Example natal and early rearing assignments included predictions that challenged expectations for juvenile salmon migration based on predicted river 87 Sr/ 86 Sr compositions. Conclusions This study developed a continuous, network-explicit 87 Sr/ 86 Sr isoscape that integrates existing river data to predict 87 Sr/ 86 Sr in unsampled reaches and the likely achievable range and resolution of otolith-based origin and life history inference. The resulting river isoscape provides a valuable tool to predict salmon movements and identify habitats supporting their survival and growth that otherwise might remain undetected. Coupling these predictions with complementary approaches that ground-truth juvenile presence (e.g., targeted fish surveys) represents an important step toward science-informed restoration and management of critical habitats throughout the Sacramento River basin.

Environmental sciences↗
DOE OSTI2021

State-Space Model to Estimate Salmon Escapement Using Multiple Data Sources

Abstract Accurate estimates of salmonids passing Lower Granite Dam on the Snake River, by species and origin, are a critical input to assessing the status and trends of various populations as well as successful management of fisheries in the Snake River basin. Here, we describe a state-space model that estimates such escapement past a dam by using window counts, PIT tag observations, and data from an adult fish trap, accounting for issues such as nighttime passage, fallback and reascension, potential observation error at the window, and uncertainty in the adult trap rate. We tested the approach using a simulation framework that mimicked several levels of observation error, differences between nighttime passage and reascension rates, and the possibility of the adult trap being closed for some period of time. Our results demonstrate that the model produced unbiased estimates across all tested scenarios. We also applied this model to empirical data from Lower Granite Dam to produce estimates of wild, clipped hatchery, and unclipped hatchery spring/summer-run Chinook Salmon Oncorhynchus tshawytscha and steelhead O. mykiss from spawn years 2010–2019.

See, Kevin E. (ORCID:0000000297626442)↗
DOE OSTI2024

2023 Central Hanford Ecological Integrity Assessments Monitoring Report

The Hanford Site is comprised of an expanse of shrub-steppe habitats that provides exceptional ecological value to plants and animals located on the site and in the surrounding greater Columbia Basin. The U.S. Department of Energy (DOE)-managed portion of the Hanford Site, referred to from here on as Central Hanford, has been the focus of various ecological monitoring efforts, including vegetation monitoring. The scope and goals of vegetation surveys have varied greatly since the Hanford Site was established, but previous studies have documented a rapidly changing landscape, making it clear that continued vegetation monitoring is integral to preserving the ecological value of Central Hanford. A new vegetation monitoring effort was initiated in 2023 using methods based on ecological integrity assessments (EIA) (Natural Heritage Report [NHR] 2020-05) developed by the Washington Natural Heritage Program (WNHP), a division of the Washington State Department of Natural Resources (DNR) and NatureServe®. The methods were modified and supplemented to meet monitoring goals at the Hanford Site. The 2023 EIA monitoring effort consisted of field surveys to evaluate vegetation and soil condition across Central Hanford. Surveys were focused on upland habitats, and areas under consideration for upcoming projects were prioritized. Vegetation cover estimates were used to score a variety of metrics for vegetation conditions in each area. In 2023, approximately half of the site was surveyed. Monitoring methods and results for the 2023 field season are summarized in this report, and management recommendations are also provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

High-Head Bypass Fish Passage Investigations: Year One (Final Report)

The goal of this first year study is to investigate the effects of downstream passage on fish health by comparing two methods: downstream fish passage at a high head dam through a bypass system, and downstream fish passage at a collection facility with vehicle conveyance to understand which method best supports achieving biological performance metrics, and what structural design or operational changes can be implemented to reduce stress and mortality in juvenile Chinook salmon. This study will occur at Green Peter Dam (or Green Peter). To achieve this goal, we will evaluate stress, injury, and mortality rates of downstream migrating juveniles after passage through a bypass system compared to holding fish in a collection facility and vehicle conveyance (trap and haul). This study will be conducted by researchers from Pacific Northwest National Laboratory (PNNL) in collaboration with researchers from Oregon State University (OSU). Results from this study will be used to inform the U.S. Army Corps of Engineers (USACE) Product Delivery Teams (PDTs) charged with designing improvements for downstream juvenile fish passage at high head dams in the Willamette River basin. The broader intent is to support management decisions on long-term measures and operations to rebuild populations of Upper Willamette River spring Chinook salmon listed as threatened under the Endangered Species Act.

13 HYDRO ENERGY↗
DOE OSTI2022

Numerical Simulation of Commercial-Scale CO2 Storage in a Saline Formation Evaluating Basin-Scale Pressure Interference and CO2 Plume Commingling

Presentation at NETL Carbon Management Project Review Meeting held in Pittsburgh, Pennsylvania, August 15–19, 2022. The presentation provides quantitative evaluation of subsurface pressure interference and emphasizes the importance of interproject coordination among stakeholders associated with multi-project geologic CO2 storage in a shared sedimentary basin.

Wijaya, Nur↗