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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗
DOE OSTI2025

The water use of data center workloads: A review and assessment of key determinants

The global importance of data center water use is increasing with the rapid growth of digitalization and artificial intelligence. This study analyzes the factors influencing workload-level water use, measured in liters consumed per workload, to guide water-saving strategies in data centers. Our findings reveal workload-level water use variations exceeding 10,000-fold, driven by over 1000-fold differences in water consumption per kilowatt hour of server electricity consumed and approximately 10-fold differences in server workload efficiency. Key determinants are ranked as server efficiency, electrical grid water consumption factors, server utilization, cooling system type, infrastructure efficiency, climate zone, inactive server percentage, and server refresh cycle. Notably, there is no single recipe for minimizing water use; instead, optimal outcomes depend on tailored combinations of these factors. This analysis addresses critical knowledge gaps by identifying the determinants of data center water use and exploring their achievable minima under diverse site-specific constraints.

Data centers↗
DOE OSTI2026

Water isotope data for the TEMPEST study site, 2023-2026

This dataset contains water isotope (deuterium (dD) and oxygen (d18O)) data from porewater, experimental source water, and aquifer sources from the Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental field site in Edgewater, MD. Samples were taken from 2023-2026 and included in file "TEMPEST_Water_Isotope_LANL_2023-2026.csv". Porewater samples were taken from 15cm depth at multiple locations in each experimental plot (i.e., control, freshwater, and saltwater). Water samples were stored in 2 ml amber glass vials with septum caps under refrigeration until analysis. A L2140-i Picarro cavity ringdown spectrometer connected to an A0211 Picarro vaporization module was used to run water samples. Standards (United States Geological Survey (USGS) 47 and 48) were used to check instrument accuracy during each run of samples. Post-processing codes were run to calculate isotopic values from raw data. Reported isotope data is post-processed. Raw data CSV files from the Picarro were processed using a Python script and output as excel files containing data calibrated to Vienna Standard Mean Ocean Water (VSMOW). Standardization is based on USGS47 and USGS48 standards that are measured before and after every 5-10 unknowns. Every measurement is comprised of 10 injections. Processing involved discarding the first 4 injections due to a known memory effect. Raw means of the last 6 injections are taken for each measurement and then corrected from the linear calibration relationship of the USGS standards expected vs measured values to obtain corrected compositions relative to VSMOW. Reported isotope data are corrected mean results.

Aquifer↗
DOE OSTI2021

East River Watershed Stable Water Isotope Data in Precipitation, Snowpack and Snowmelt 2016-2020

Stable water isotopes (d18O, d2H and d-excess) are important tracers in hydrologic research to understand water partitioning between vegetation, groundwater, and runoff but are rarely applied to large watersheds with persistent snowpack and complex topopgraphy. Data were collected for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area supported by the U.S Department of Energy in the East River, CO Hydrologic Unit Code (140200010) with limited data also collected in adjacent watersheds Ohio Creek and Taylor River. Data are provided in csv and includes isotopic information for precipitation (years 2014-2016), snowmelt (years 2016-2017) and snowpits (years 2016-2020). Snowpit data contain depth resolved information at 10 cm intervals for density, snow water equivalent (SWE) and stable water isotopes. Bulk isotopic data for 86 snowpits contain depth, SWE, density and SWE-weighted isotope values. Sampling locations and elevations are provided within the data files, while kmz files are provided to view sampling locations using Google Earth software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Geospatial Capabilities to Couple Hazard and Social Vulnerability Data in Water Distribution Criticality Analysis

A resilience analysis of a water distribution system is greatly enhanced by the integration of up-to-date geospatial data describing the water system, hazards, and surrounding community. The Water Network Tool for Resilience (WNTR), an open-source Python package designed to simulate and analyze the resilience of water distribution systems, was recently updated to incorporate geographic information system (GIS) data into the resilience analysis. This paper describes the GIS capabilities and includes a case study using the drinking water distribution system model for a large city in Pennsylvania. The case study focuses on potential pipe damage from landslides and on pipes that are particularly difficult to repair. The analysis couples data on hazards, social vulnerability, and the location of emergency services to identify and prioritize high-impact critical infrastructure for mitigation. Results demonstrate that pipes can be prioritized for mitigation based on water shortage and vulnerable populations that are affected. In conclusion, the methods can be adopted for general use and are available as part of the WNTR software.

GIS, landslide↗
DOE OSTI2026

SPRUCE Whole Ecosystem Warming (WEW) Environmental Data and Water Table Summaries, Marcell Experimental Forest, Minnesota, 2015-2024

This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.

air temperature↗
DOE OSTI2022

Editorial: Themed issue on data-intensive water systems management and operation

The water sector increasingly looks at intensified instrumentation, data collection and automation as tools for daily use. Still, a massive opportunity remains to fully embrace emerging methods and technologies, such as artificial intelligence, data analytics, low-cost sensor hardware, and cloud computing. Indeed, sensing and automation technology has already infiltrated many facets of society. As such, the time is ripe to evaluate the role of novel technologies for systems monitoring, diagnostics, and automation of aquatic processes and large-scale water systems. When leveraged, the water sector will do more with less.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Riverbed and Near-Surface Water Quality Data, Hanford Reach, Columbia River, February 2021 - April 2022

This dataset contains longitudinal profiles of natural groundwater tracers (temperature, electrical conductivity (EC), and Radon-222 (Rn)) collected to identify locations of hydrologic exchange flows along a 75-km reach of the Columbia River near Richland, Washington.A jetboat was used to tow a 30 foot long, weighted tether that had one set of temperature and EC sensors just below the water surface and one set of temperature and EC sensors on the end (just above the river bed). The dataset contains profiles of temperature/EC data (resolution: 1 second) collected along the left and right banks during three different sampling events. During the final sampling event, we revisited some "deep holes" where the river was more than 30 feet deep with a weighted tether that was 75 feet long. The dataset has been processed to remove data collected when the sensors were not in the water, or when the water was too deep to keep the tether on the riverbed. We collected grab samples of water for analysis of dissolved Rn in places where the temperature/EC was different from the background river water. The Rn data was joined to the temperature/EC profiles based on the sample times.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) installation methods; (4) February 2021 data; (5) July 2021 data; (6) April 2022 data; and (7) April 2022 deep hole data. All files are .csv format and can be opened with a spreadsheet program (such as Microsoft Excel or OpenOffice).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Water quality data collected from the Muskegon River (MI, USA) using AquaBOT June-July 2024.

This dataset contains processed output from AquaBOT, which combines 30-second interval measurements of GPS location and YSI water quality parameters (temperature (degrees Celsius), dissolved oxygen (mg/l), specific conductance(microSiemens/cm at 25 degrees Celsius), and turbidity (NTU)), for 3 sections of the Muskegon River in Michigan, USA. The file aquabot2024_MuskegonRiver.csv has information on locations, dates and times, and observations. The data were processed by removing observations recorded before and after AquaBOT was in the water and observations where no data values were recorded. No other QA/QC was done. This research was performed as part of the DOE Research Development and Partnership Pilot award “Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region”, which aims to expand collaborations between researchers at Central Michigan University and U.S. Department of Energy labs and projects focused on enhancing climate resilience in Great Lakes communities and ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

In-situ electrochemical and water quality data; Slate River and East River floodplains, Crested Butte, CO; May 2022-September 2022

This data package includes a time-series of field measurements from May to September 2022 in groundwater and surface water from the Slate River and East River floodplains in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data package includes 5 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature and alkalinity. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

RiverPIXELS: paired Landsat images and expert-labeled sediment and water pixels for a selection of rivers v1.0

RiverPIXELS contains GeoTIFFs of hand-labeled water and sediment pixels from Landsat images containing rivers. Each of the 104 labeled patches contains 256 x 256 Landsat pixels (30 meter resolution). Our aim in releasing RiverPIXELS is to provide an "off-the-shelf" training and testing dataset for building machine-learned models to automatically identify rivers from multispectral imagery. While a number of trained models and/or surface water products already exist, RiverPIXELS aims for pixel-level accuracy in order to precisely identify river boundaries in particular. Our selection of rivers is heavily Arctic, but we include tropical and temperate rivers as well. Patches are provided for the Colville (7), Indigirka (6), Kolyma (4), Ucayali (54), Waitaki (21), and Yana (12) Rivers. For each patch, all surface water pixels are labeled (1) and all in-channel sediment pixels are labeled (2). Sediments not in-channel are considered part of the land (0) class. RiverPIXELS also includes paired surface water data from the Global Surface Water dataset that may be useful as additional features in machine learning models. Each patch therefore contains four aligned GeoTIFFs: labeled, landsat, gswmo, and gswocc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Nanoporous Tio2 Water Training Data

Data and input files used to train a Deep Potential (DP) model for the nanoporous TiO2-water interface. The DeepMD-kit code was used to train the DP. Information about data format, and how to use DeepMD-kit can be found at https://docs.deepmodeling.com/projects/deepmd/en/master/

08 HYDROGEN↗
DOE OSTI2023

TEAMER: Water Tunnel Data from Testing the Pterofin Skimmer Concept

Pterofin's Skimmer concept relies on a flapping and pitching hydrofoil to extract hydrokinetic energy from water flows. The concept aims to utilize unsteady fluid dynamics phenomena (added mass, shed vorticity, and unsteady boundary layer development) to achieve higher lift coefficients, enabling increased power density of the hydrokinetic device and a fundamental shift in the rpm/torque scaling of the power take off compared with turbines. The Applied Research Laboratory at Penn State, in collaboration with Pterofin, designed and built a proof-of-concept flapping/pitching mechanism which was subsequently tested in ARL's 12-inch water tunnel facility. The mechanical power supplied to or extracted from the mechanism was measured for a range of hydrofoils provided by Pterofin over operating conditions including reduced frequency, Reynolds number, and the ratio between pitching and flapping amplitudes. The power lost to friction in the mechanism was removed from the net power measurement by means of a bare hub tare, with the resultant hydrodynamic power being used to calculate a mechanism-independent and non-dimensional power coefficient. The product of this effort is a dataset describing the power coefficient of a hydrofoil having simultaneous pitching and flapping motions, both of which are approximately sinusoidal. Power coefficients were collected for a range of primary design variables including: - Reduced frequency: 0.01 to 0.95 - Pitching/flapping peak angle ratio: 1.5 to 3.0 - Chord-based Reynolds number: 60,000 to 560,000 Secondary design variables relating to the hydrofoil geometry were explored including: - Aspect ratio - Planform shape - Section thickness distribution - Hydrofoil position relative to the pitching axis - Hydrofoil sweep angle relative to the pitching axis Measured data are provided in mean and time series formats. MATLAB scripts are provided which can be used to generate figures of time-averaged and phase-averaged hydrodynamic power coefficients calculated from the measured data. A complete description of the experiment and data reduction can be found in the Post Access Report for the Pterofin Skimmer test effort which will be available on the TEAMER website. This work was supported by the Pacific Energy Ocean Trust via a TEAMER award.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Time to Use Dendrohydrological Data in Water Resources Management?

Despite a wide consensus on the potential importance of streamflow reconstructions to water resources planning and management activities, applications of dendrohydrology have been piecemeal. This review article describes barriers to widespread use of dendrohydrological data and suggests research needs for operationalizing streamflow records reconstructed from these proxy data.

42 ENGINEERING↗
DOE OSTI2023

NEWTS Well Summary by Hydrologic Regions and Subbasins in the U.S.

Oil and gas well production data (2000-2022), including water production and injection, as well as summary information (e.g., well count by status, total vertical depth statistics, etc.) spatially summarized by Watershed Boundary Dataset's (WBD) region (Hydrologic Unit Code (HUC) 2) and subbasin (HUC8). Energy-related produced waters data were acquired and summarized in support of the development of the National Energy Technology Laboratory's NEWTS (National Energy Water Treatment and Speciation Database). Due to the proprietary nature of the wellbore data, this derived product has been spatially compiled by key areas to support research and stakeholder needs.

Energy Infrastructure↗
DOE OSTI2020

Water chemistry data and calculations for Fracture Sustainability Tests

Measured cation, anion, and silica are presented as well as calculations evaluating mass balance performed for 4 fracture sustainability tests under EGS conditions: Stripa granite, Metamudstone, Rhyolitic Ashflow Tuff, and Silicified Rhyolitic Tuff. Calculations of charge balance are included for water samples in the 4 tests.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Utah FORGE Groundwater Levels: Updated 2021

Contains Utah FORGE ground water data for wells WOW2 and WOW3. The data was updated on October 5th, 2021 and contains legacy data. Groundwater data includes the level, offset, date, and time for each measurement. Temperature, drift, water elevation and other parameters are recorded. Figures in the data include a water elevation over time plot. Legacy data ranges from year 1976 to 2019 and updated data ranges from year 2019 to 2021.

15 GEOTHERMAL ENERGY↗