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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2020

The effects of warming and soil chemistry on bacterial community structure in Arctic tundra soils

Soil microbial communities in the Arctic play a critical role in regulating the global carbon (C) cycle. Vast amounts of C are stored in northern latitude soils, and rising temperatures in the Arctic threaten to thaw permafrost, making relatively inaccessible C sources more available for mineralization by soil microbes. Few studies have characterized how microbial community structure responds to thawing permafrost in the context of varying soil chemistries associated with contrasting tundra landscapes. Here, we subjected active layer and permafrost soils from upland and lowland tundra sites on the North Slope of Alaska to a soil-warming incubation experiment and compared soil bacterial community profiles (obtained by 16S rRNA amplicon sequencing) before and after incubation. The influence of soil composition (characterized by mid-infrared [MIR] spectroscopy) on bacterial community structure and class abundance was analyzed using redundancy and correlation analyses. We found increased abundances of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes [Sphingobacteriia] post incubation, particularly in permafrost soils. The categorical descriptors site and soil layer had the most explanatory power in our predictive models of bacterial community structure, highlighting the close relationship between soil bacteria and the soil environment. Specific soil chemical attributes characterizing the soil environments that were found to be the best predictors include MIR spectral bands associated with inorganic C, silicates, amide II (C=N stretch), and carboxylics (C-O stretch), and MIR peak ratios representing C substrate quality. Overall, these results further characterize soil bacterial community shifts that may occur as a frozen environment with limited access to C sources, such as is found in undisturbed permafrost, transitions to warmer and more C-available environments, such as is predicted in thawing permafrost due to climate change.

16S rRNA sequencing↗
DOE OSTI2022

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances—Part 3: Optical properties of black and brown carbon emissions

Residential biomass combustion is a source of carbonaceous aerosol. Inefficient combustion, particularly of solid fuels produces large quantities of black and brown carbon (BC and BrC). These particle types are important as they have noted effects on climate forcing and human health. One method of measuring these quantities is by measurement of aerosol light-absorption and scattering, which can be performed using an aethalometer and nephelometer, respectively. These instruments are widely deployed in the study of ambient air and are frequently used in air quality modeling and source apportionment studies. In this study, we will describe (1) a method for measuring primary BC and BrC emissions from two residential log-fired wood hydronic heaters and (2) the BC and BrC emission from these devices over a wide range of operating conditions, such as cold-starts, warm-starts, four different levels of output ranging from 15% to 100% maximum rated output, and periods of repeated cycling. The range in flue-gas BC concentrations, measured using an aethalometer at the 880 nanometer (nm) wavelength, were between 5.09 × 10 2 and 2.24 × 10 4 micrograms per cubic meter (µg/m 3 ) while the scattering coefficient of the flue-gas, measured by a nephelometer at 880 nm, ranged between 2.20 × 10 3 and 8.56 × 10 5 inverse megameters (Mm –1 ). The BrC concentrations, measured using the 370 nm wavelength of an aethalometer, were between 9.10 × 10 1 and 3.56 × 10 4 µg/m 3 . The calculated Angstrom Absorption Exponent (AAE) of the flue-gas aerosol ranged between 1.54 and 3.63. Performing a comparison between the measured BC concentration and an external particulate matter (PM) concentration showed that overall BC makes up roughly a quarter of the PM emitted by either of the two appliances. Further for both appliances, the cold-start and the test phase immediately following it had the highest BC and BrC concentrations, the highest measured scattering coefficient, as well as a low AAE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Editorial: Hydrology, ecology, and nutrient biogeochemistry at the terrestrial-aquatic interface

Terrestrial-aquatic interfaces (TAI) play important roles in mediating the exchange of water and chemicals between land, surface and subsurface water systems, which is tightly coupled with biogeochemical transformations that influence water quality and ecosystem health (Harvey and Gooseff, 2015; Harvey et al., 2019). Understanding and predicting the interactions between the hydrologic, ecologic, and biogeochemical processes at those interfaces is crucial for the sustainable management of water resources and promotion of healthy ecosystems under different environmental stresses and disturbances, including climate change, human activities, and more frequent occurrence of extreme events. Both process-based and data-driven approaches have emerged to address critical challenges at TAIs as integral parts of the Earth system (e.g., Ward and Packman, 2019; Chen et al., 2021; Dwivedi et al., 2022). In this Research Topic, we sought research that advances the understanding of coupled hydrologic, ecologic, and biogeochemical processes along various TAIs from the summit to sea, e.g., river corridors and coastal TAI systems. We invited observational, experimental, theoretical, analytical, numerical, and data-driven research that aims to understand hydro-biogeochemical processes such as the redox dynamics and biogeochemical transformations of carbon, nutrients, and metals occurring at the TAIs and address their heterogeneity and scaling challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Diel cycle impacts on the chemical and light absorption properties of organic carbon aerosol from wildfires in the western United States

Abstract. Organic aerosol (OA) emissions from biomass burning have been the subject of intense research in recent years, involving a combination of field campaigns and laboratory studies. These efforts have aimed at improving our limited understanding of the diverse processes and pathways involved in the atmospheric processing and evolution of OA properties, culminating in their accurate parameterizations in climate and chemical transport models. To bring closure between laboratory and field studies, wildfire plumes in the western United States were sampled and characterized for their chemical and optical properties during the ground-based segment of the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Using a custom-developed multiwavelength integrated photoacoustic-nephelometer spectrometer in conjunction with a suite of instruments, including an oxidation flow reactor equipped to generate hydroxyl (OH⚫) or nitrate (NO3⚫) radicals to mimic daytime or nighttime oxidative aging processes, we investigated the effects of multiple equivalent hours of OH⚫ or NO3⚫ exposure on the chemical composition and mass absorption cross-sections (MAC(λ)) at 488 and 561 nm of OA emitted from wildfires in Arizona and Oregon. We found that OH⚫ exposure induced a slight initial increase in absorption corresponding to short timescales; however, at longer timescales, the wavelength-dependent MAC(λ) decreased by a factor of 0.72 ± 0.08, consistent with previous laboratory studies and reports of photobleaching. On the other hand, NO3⚫ exposure increased MAC(λ) by a factor of up to 1.69 ± 0.38. We also noted some sensitivity of aerosol aging to different fire conditions between Arizona and Oregon. The MAC(λ) enhancement following NO3⚫ exposure was found to correlate with an enhancement in CHO1N and CHOgt1N ion families measured by an Aerodyne aerosol mass spectrometer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Quantitative Phase Analysis by Neutron Diffraction of Conventional and Advanced Aluminum Alloys Thermally Conditioned for Elevated-Temperature Applications

As the issue of climate change becomes more prevalent, engineers have focused on developing lightweight Al alloys capable of increasing the power density of powertrains. The characterization of these alloys has been focused on mechanical properties and less on the fundamental response of microstructures to achieve these properties. Therefore, this study assesses the quality of the microstructure of two high-temperature Al alloys (A356 + 3.5RE and Al-8Ce-10Mg), comparing them to T6 A356. These alloys underwent thermal conditioning at 250 and 300 °C for 200 h. Time-of-flight neutron diffraction experiments were performed before and after conditioning. The phase evolution was quantified using Rietveld refinement. It was found that the Si phase grows significantly (13–24%) in T6 A356, A356 + 3.5RE, and T6 A356 + 3.5RE alloys, which is typically correlated with a reduction in mechanical properties. Subjecting the A356 3.5RE alloy to a T6 heat treatment stabilizes the orthorhombic Al4Ce3Si6 and monoclinic β-Al5FeSi phases, making them resistant to thermal conditioning. These two phases are known for enhancing mechanical properties. Additionally, the T6 treatment reduced the vol.% of the cubic Al20CeTi2 and hexagonal ᴨ-Al9FeSi3Mg5 phases by 13% and 23%, respectively. These phases have detrimental mechanical properties. The Al-8Ce-10Mg alloy cubic β-Al3Mg2 phase showed significant growth (82–101%) in response to conditioning, while the orthorhombic Al11Ce3 phase remained stable. The growth of the beta phase is known to decrease the mechanical properties of this alloy. These efforts give valuable insight into how these alloys will perform and evolve in demanding high-temperature environments.

Chemistry↗
DOE OSTI2022

Tracking the environmental impacts of ecological engineering on coastal wetlands with numerical modeling and remote sensing

Coastal wetlands are the most valuable ecosystems on the earth but facing severe degradation and losses owing to climate change and anthropogenic activities. Many ecological engineering projects (EEP) have been conducted to mitigate the degradation of coastal wetlands. However, the geomorphological impacts of EEP on coastal wetlands have not been well documented. In this study, a method employed a process-based hydrodynamic model and remote sensing (RS) was developed to evaluate the impacts of EEP on the geomorphological change of a prototype Ramsar site. Results demonstrated that RS has great potential in improving the quality of bathymetry data for the numerical model with a decrease of RMSE from 0.52 m to 0.3 m. It also showed good capacity in trend detection of geomorphological change spatially. Results showed the Chongming Dongtan wetland experienced erosion with an annual rate of -0.035 m/yr from 2013 to 2016 after the implementation of EEP. The deposition rate changed significantly in the area within 200 m of the EEP. It is found that the EEP modified the composition of vegetation, sediment transportation, as well as substrate stability, affecting the geomorphological change of coastal wetlands. It is suggested that the EEP with moderate anthropogenic disturbance is a direct and effective way to recover the coastal habitats for waterbirds. However, the modification of the coastal wetland ecosystem by EEP will lead to the potential vulnerability to global climate change. Therefore, how to mitigate the advantages and disadvantages of the EEP is needed to be further studied to find a more sustainable way for coastal management.

geomorphological change, coastal wetlands, Ecologi↗
DOE OSTI2024

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Plant organic matter inputs exert a strong control on soil organic matter decomposition in a thawing permafrost peatland

Peatlands are climate critical carbon (C) reservoirs that could become a C source under continued warming. A strong relationship between plant tissue chemistry and the soil organic matter (SOM) that fuels C gas emissions is inferred, but rarely examined at the molecular level. Here we compared Fourier transform infrared (FT-IR) spectroscopy measurements of solid phase functionalities in plants and SOM to ultra-high-resolution mass spectrometric analyses of plant and SOM water extracts across a palsa-bog-fen thaw and moisture gradient in an Arctic peatland. From these analyses we calculated the C oxidation state (NOSC), a measure which can be used to assess organic matter quality. Palsa plant extracts had the highest NOSC, indicating high quality, whereas extracts of Sphagnum, which dominated the bog, had the lowest NOSC. The percentage of plant compounds that are less bioavailable and accumulate in the peat, increases from palsa (25%) to fen (41%) to bog (47%), reflecting the pattern of percent Sphagnum cover. The pattern of NOSC in the plant extracts was consistent with the high number of consumed compounds in the palsa and low number of consumed compounds in the bog. However, in the FT-IR analysis of the solid phase bog peat, carbohydrate content was high implying high quality SOM. Here, we explain this discrepancy as the result of low solubilization of bog SOM facilitated by the low pH in the bog which makes the solid phase carbohydrates less available to microbial decomposition. Plant-associated condensed aromatics, tannins, and lignin-like compounds declined in the unsaturated palsa peat indicating decomposition, but lignin-like compounds accumulated in the bog and fen peat where decomposition was presumably inhibited by the anaerobic conditions. A molecular-level comparison of the aboveground C sources and peat SOM demonstrates that climate-associated vegetation shifts in peatlands are important controls on the mechanisms underlying changing C gas emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Flexible, Multipurpose Laboratory Advances Building and Thermal Energy Systems: Expanding Evaluation and Development of Grid-Interactive Buildings

Robust hardware and controls are necessary to ensure results match their intent before they can be used broadly. However, this often requires multiple field experiments in a variety of climate zones. In the field, it is more difficult to obtain information on other important factors, such as thermal, grid, and occupant interaction. Gaps also exist in understanding the performance degradation and life cycle of thermal energy systems as they relate to buildings. There is a lack of robust, high-quality performance data for projects at scale; this data can be expensive to produce and often remain proprietary.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Ventilation and Indoor Air Quality in Recently Constructed U.S. Homes: Measured Data From Select Southeastern States

Little data is available that quantifies IAQ or associates contaminant levels with air exchange in U.S. homes. To address this gap, the U.S. Department of Energy (DOE) Building America Program conducted a study to characterize IAQ in U.S. homes constructed since 2013, along with presence, functionality, and occupant use of control measures. Specific objectives of this study effort included: Measuring time-integrated concentrations and temporal profiles of established contaminants of concern; monitoring the use of ventilation equipment; and tracking activities that impact air pollutant emissions and removal processes in typical homes in various climate zones; Characterizing the prevalence, type, and installed performance of mechanical ventilation equipment in new homes; exploring regional variations in system designs and performance; Investigating associations between contaminant levels and the presence of control measures including whole-house mechanical ventilation (WHMV). The study engaged research teams to collect data at a regional level. This report introduces the study protocol and presents and discusses high-level results obtained from Florida Solar Energy Center (FSEC) data collection efforts in the southeastern U.S. states of Florida, Georgia, and South Carolina.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"

This data package contains the associated data and scripts for Nagamoto, E., Ombadi, M., Ciulla, F. et al. Widespread drought-driven declines in streamflows and water quality in the Upper Colorado River Basin during 1998-2022. Commun Earth Environ 7, 734 (2026). https://doi.org/10.1038/s43247-026-03890-5. This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, we modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows: - INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb - OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI) - climatic_variables: The code used to collect meteorologic data from Google Earth Engine - feature_importance: The code used for the catchment attributes analysis - preprocessing: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - pyeto: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - calculations: Code used in UCRB_Drought_Workflow_Impacts.ipynb - plotting: Code used in UCRB_Drought_Workflow_Impacts.ipynb - README.md - UCRB_Drought_Workflow_Preprocessing.ipynb: The code used to prep raw data for the analysis - UCRB_Drought_Workflow_Impact.ipynb: The code which uses the prepped raw data for analysis, and plots all figures - requirements_ucrb-drought_v2.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the code The INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb. The "RESERVOIRS_RAW" folder contains ".csv" files for each reservoir in the UCRB with daily reservoir storage. There are also two files in the INPUTS folder that have combined reservoir storage data and reservoir metadata. The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "Peak95_Min5_Relchange" that has ".csv" files for the relative change in peak (95th %) and minimum (5th %) variables. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries. Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought]. UPDATE 1: Title and code file updated to match submitted manuscript 10-15-2025. UPDATE 2: Code and data files updated to match revised manuscript 3-4-2026. UPDATE 3: Code and data files updated to match revised manuscript 6-7-2026. ** NOTE: DD and FLMD have not been updated yet. UPDATE 4: Added associated Manuscript information and DD and FLMD have been updated. To cite this code, please use the following BibTeX: @misc{nagamoto2025drought, author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan}, title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"}, year = {2025}, doi = {10.15485/2551894}, publisher = {ESS-DIVE Repository}, url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894} }

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗
DOE OSTI2021

Rapid retreat of the southwestern Laurentide Ice Sheet during the Bølling-Allerød interval

The timing of Laurentide Ice Sheet deglaciation along its southwestern margin controlled the evolution of large glacial lakes and has implications for human migration into the Americas. Accurate reconstruction of the ice sheet’s retreat also constrains glacial isostatic adjustment models and is important for understanding ice-sheet sensitivity to climate forcing. Despite its significance, retreat of the southwestern Laurentide Ice Sheet (SWLIS) is poorly constrained by minimum-limiting 14 C data. We present 26 new cosmogenic 10 Be exposure ages spanning the western Interior Plains, Canada. Using a Bayesian framework, we combine these data with geomorphic mapping, 10 Be, and high-quality minimum-limiting 14 C ages to provide an updated chronology. This dataset presents an internally consistent retreat record and indicates that the initial detachment of the SWLIS from its convergence with the Cordilleran Ice Sheet began by ca. 15.0 ka, concurrent with or slightly prior to the onset of the Bølling-Allerød interval (14.7–12.9 ka) and retreated >1200 km to its Younger Dryas (YD) position in ~2500 yr. Ice-sheet stabilization at the Cree Lake Moraine facilitated a meltwater drainage route to the Arctic from glacial Lake Agassiz within the YD, but not necessarily at the beginning. Our record of deglaciation and new YD constraints demonstrate deglaciation of the Interior Plains was ~60% faster than suggested by minimum 14 C constraints alone. In conclusion, numerical modeling of this rapid retreat estimates a loss of ~3.7 m of sea-level equivalent from the SWLIS during the Bølling-Allerød interval.

58 GEOSCIENCES↗
DOE OSTI2020

Assessment of peak power demand reduction available via modulation of building ventilation systems.

Peak power demand strains electrical grids and increases cost of electricity generation, transmission and distribution infrastructure. Many studies have examined ways of reducing peak power demand, including modification of room air temperature setpoints or reduction of lighting levels. However, very few or no studies have examined the peak power reduction resource offered by temporary curtailment of building ventilation systems. For this reason, we conducted a simulation campaign in which we examined the resource offered by temporary ventilation curtailment in commercial buildings of different use types across the United States and in residences in the state of California, with the essential constraint that any changes resulted in air quality acceptable to occupants through additional ventilation to compensate for the curtailment. To do this, we employed previously validated building models implemented in the airflow and contaminant transport tool CONTAM and building thermal and systems modeling tool EnergyPlus, in some cases co-simulated. Overall, results show savings are highly dependent on building type and climate but range from 0–2 W/ft 2 and up to 40% of total peak building power demand. Depending on building type, this power shed can be conducted for 1.5–8 h before acute exposure or odor concerns are expected, assuming a safety factor of 2. This reduction is of the same magnitude as that offered by thermal control strategies such as setpoint increase, or from lighting reduction strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

ARM Radiosondes for SNPP/JPSS Validation Field Campaign Report

This field campaign extension has been a coordinated effort involving the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility, the University of Wisconsin at Madison, and the Joint Polar Satellite System (JPSS) project to validate NOAA Unique Combined Atmospheric Processing System (NUCAPS) temperature and moisture sounding products from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments on board the NOAA-20 and NOAA-21 satellite platforms. In this arrangement, funding for radiosondes and balloons was provided by the JPSS project to ARM. These radiosondes were launched coincident with NOAA-20 and NOAA-21 satellite overpasses at the ARM field sites at Eastern North Atlantic (ENA), North Slope Alaska (NSA), and Southern Great Plains (SGP). Combined with other ARM data, an assessment of the radiosonde data quality was performed and post-processing corrections applied. The dedicated radiosondes were integrated into the NOAA Products Validation System (NPROVS+), which collocated the radiosondes with satellite products (NOAA, National Aeronautics and Space Administration [NASA], European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], Geostationary Operational Environmental Satellite [GOES], Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) and numerical weather prediction (NWP) forecasts for use in product assessment and algorithm development. This work is a part of the NOAA-20 and NOAA-21 satellite retrieval validation efforts and provides critical accuracy assessments of the temperature and water vapor soundings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Nuclear-Driven Integrated Energy Systems: A State-of-the-Art Review

Because of the growing concerns regarding climate change and energy sustainability, a transition toward a modern energy sector that reduces environmental effects while promoting social and economic growth has gained traction in recent years. Sustainable energy solutions, which include renewable and low-carbon sources such as nuclear energy and natural gas, could minimize emissions of greenhouse gases, enhance air and water quality, and encourage energy independence. Yet, the shift to a sustainable energy industry is fraught with difficulties, including governmental and regulatory obstacles, technological and economic limits, and societal acceptability hurdles. Addressing these issues would necessitate the development of long-term, durable, and cost-effective energy systems containing nuclear energy and associated with the generation of both electricity and other by-products required by industry. Integrated energy systems (IES) are a novel way to maximize the use of various energy resources and technologies in order to deliver dependable, efficient, and sustainable energy services. IES entail the integration of various energy systems, such as electricity, heating, cooling, and transportation, in respect to energy sustainability and a system’s resilience and flexibility. Their development and implementation require the cooperation of several parties, including energy providers and policymakers. This study provides a state-of-the-art literature review of the most creative nuclear-driven hybrid energy system applications and methodologies, from which the research challenges and prospects for effective IES implementation emerge.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗