This dataset includes modeled velocity and discharge at five communities in the middle Kuskokwim River region: Aniak, Chuathbaluk, Crooked Creek, Red Devil and Stony River. Modeled velocities and discharge represent daily averages calculated for the openwater season (OWS) from June 1 - October 18 over the 20 year period 2000-2019 using the raw data described below and included in this archive; full details of methodology are described in (Brown et al. submitted to Renewable Energy). Raw data inputs to inform the modeling process include in-situ measurements of 1) discharge with an acoustic Doppler current meter (ADCP, 600kHz Workhorse Rio Grande by Teledyne RD Instruments) and a global positioning receiver (GPS, Trimble 5700, 5800 and R8) utilizing Real Time Kinematic (RTK) GPS mode over 1-2 days at each site in 2009 or 2010 (Ravens 2014), and 2) river stage with a water level logger (HOBO U20-001-01 by Onset) over 2-9 weeks at each site (Ravens 2014), 3) in addition to a 20 year long-term discharge record collected at the USGS stream gage site in Crooked Creek (USGS 2016). Raw data (discharge and stage) are included in this archive for two additional communities: Lower Kalskag and Sleetmute, where modeled velocities were not calculated due to equipment failure or loss. The USGS stream gage data at Crooked Creek (USGS 2016) and stream gage methodology (Turnipseed and Sauer 2010) are publicly available online, so the data are not duplicated here.

These datasets are from tidal resource characterization measurements collected on the Terrasond High Energy Oceanographic Mooring (THEOM) from 1 July 2021 to 30 August 2021 (60 days) in Cook Inlet, Alaska. The lander was deployed at 60.7207031 N, 151.4294998 W in ~50 m of water. The dataset contains raw and processed data from the following two instruments: 1. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 5 minutes bins and converted to the East-North-Up (ENU) coordinate system. 2. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz in the beam coordinate system. Processed data has been averaged into 5 minutes bins and converted to the Streamwise - Cross-stream - Vertical (Principal) coordinate system. Turbulence statistics were calculated from 5-minute bins, with an FFT length equal to the bin length, and saved in the processed dataset. Data was read and analyzed using the DOLfYN (version 1.0.2) python package and saved in MATLAB (.mat) and netCDF (.nc) file formats. Files containing analyzed data (".b1") were standardized using the TSDAT (version 0.4.2) python package. NetCDF files can be opened using DOLfYN (e.g., `dat = dolfyn.load(''*.nc")`) or the xarray python package (e.g. `dat = xarray.open_dataset("*.nc"). All distances are in meters (e.g., depth, range, etc), and all velocities in m/s. See the DOLfYN documentation linked in the submission, and/or the Nortek documentation for additional details.

The 2023 National Offshore Wind data set (NOW-23) is the latest wind resource data set for offshore regions in the United States, which supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published about a decade ago and is currently one of the primary resources for stakeholders conducting wind resource assessments in the continental United States. The NOW-23 data set was produced using the Weather Research and Forecasting Model (WRF) version 4.2.1. A regional approach was used: for each offshore region, the WRF setup was selected based on validation against available observations. The WRF model was initialized with the European Centre for Medium Range Weather Forecasts 5 Reanalysis (ERA-5) data set, using a 6-hour refresh rate. The model is configured with an initial horizontal grid spacing of 6 km and an internal nested domain that refined the spatial resolution to 2 km. The model is run with 61 vertical levels, with 12 levels in the lower 300m of the atmosphere, stretching from 5 m to 45 m in height. The MYNN planetary boundary layer and surface layer schemes were used the North Atlantic, Mid Atlantic, Great Lakes, Hawaii, and North Pacific regions. On the other hand, using the YSU planetary boundary layer and MM5 surface layer schemes resulted in a better skill in the South Atlantic, Gulf of Mexico, and South Pacific regions. A more detailed description of the WRF model setup can be found in the WRF namelist files linked at the bottom of this page. For all regions, the NOW-23 data set coverage starts on January 1, 2020. For Hawaii and the North Pacific regions, NOW-23 goes until December 31, 2019. For the South Pacific region, the model goes until 31 December, 2022. For all other regions, the model covers until December 31, 2020. Outputs are available at 5 minute resolution, and for all regions we have also included output files at hourly resolution. The NOW-23 data are provided here as HDF5 files. Examples of how to use the HSDS Service to Access the NOW-23 files are linked below. A list of the variables included in the NOW-23 files is also linked below.

Raw ADCP (Acoustic Doppler Current Profiler) datasets from acoustic interference surveys with a TRDI Workhorse 300, a Nortek Signature500 and two Signature1000 instruments from August 2020. One Signature 1000 ADCP was deployed for 13 days on a bottom lander in Sequim Bay Inlet, WA. Data from the other three instruments were taken from a survey vessel running transects above the deployed lander.

Data and code that is not already in a public location that is used in Kilcher, Thomson, Harding, and Nylund (2017) "Turbulence Measurements from Compliant Moorings - Part II: Motion Correction" doi: 10.1175/JTECH-D-16-0213.1. The links point to Python source code used in the publication. All other files are source data used in the publication.

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in June of 2014. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on Tidal Turbulence Mooring's (TTMs). The TTM positions the ADV head above the seafloor to make mid-depth turbulence measurements. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity has some 'persistent motion contamination' due to mooring sway. Each ttm was deployed with two ADVs. The 'top' ADV head was positioned 0.5m above the 'bottom' ADV head. The TTMs were placed in 58m of water. The position of the TTMs were: ttm01 : (48.1525, -122.6867) ttm01b : (48.15256666, -122.68678333) ttm02b : (48.152783333, -122.686316666) Deployments TTM01b and TTM02b occurred simultaneously and were spaced approximately 50m apart in the cross-stream direction. Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. Additional details on TTM measurements at this site can be found in the included Marine Energy Technology Symposium paper.

The TidGen Power System generates emission-free electricity from tidal currents and connects directly into existing grids using smart grid technology. The power system consists of three major subsystems: shore-side power electronics, mooring system, and turbine generator unit (TGU) device. This submission includes the Advanced TidGen cost and cost of energy metrics after critical design review for BP1, and a complete LCOE content model and LCOE reporting according to DOE guidance for the baseline system and the system with advanced technology integrated. A revised LCOE content model is also included, with more relevant market array assumptions. Additionally, this submission includes a complete system overview and component overview content models. The LCOE Content Model provides data submitters with an easy and consistent means of uploading data that can be used to calculate the levelized cost of energy for MHK devices. Data represents the design completed for the Critical Design Review conducted at ORPC in December, 2017. All values are for a single device. Note that with substantial fixed costs, larger arrays will greatly reduce LCOE. For an array in Admiralty Inlet producing 136,000 MWh, 270 devices with an array CAPEX of $540,260,052 and an array OPEX of $39,959,207 would result in an LCOE of $722/MWh.

The TidGen Power System generates emission-free electricity from tidal currents and connects directly into existing grids using smart grid technology. The power system consists of three major subsystems: shore-side power electronics, mooring system, and turbine generator unit (TGU) device. This submission includes the system fabrication plan for Advanced TidGen project.

Downloadable GIS data about various basin fields. Website states: " This website report brings together abundant current and existing datasets and concepts in a common and integrated format to advance our understanding of the distribution, geologic framework, burial history, and geochemical character of the basin's oil, gas, and coal resources. Among the anticipated benefits of these digital data layers are improvements in: 1) resource assessment estimates and methodology, 2) exploration strategy, 3) basin models, and 4) energy use policies."

Listing of Bell Creek Seismic Publications and Reports

This dataset includes chemistry of geothermal water samples of the Camas Prairie area in Idaho. The samples included in this dataset were collected over the period of 2016-2019. Collection/analysis of new water samples and compilation of existing water chemistry database were conducted for Snake River Play Fairway Project. All chemical analysis of the samples were conducted in the Analytical Laboratory at the Center of Advanced Energy Studies (unless otherwise indicated) in Idaho Falls, Idaho. Isotope analysis were conducted in analytical/isotope measurement labs at Lawrence Berkeley National Laboratory, Utah State University, and University of Utah.

Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Admiralty Inlet (connecting Puget Sound to the Strait of San Juan de Fuca) in July 2022. Tests focused on occurrences of flow noise for three hydrophone package variants and on the potential for alternative tether materials.

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--based on the Excel data files--some of which were described in the reports. The scripts depend on the 'score_site' package, and the score site package depends on a number of standard Python libraries (see the score_site install instructions).

This data set is associated with the Nevada Play Fairway project. Excel file 5-Area Chem contains all the major chemistry for the areas sampled in the project. New analyses are in lines 2-30, while older analyses appear below that. Field Data excel file contains both field notes and data with ninety entries showing sixty areas not sampled either because they were to dry, cold, or unable to locate. Thirty sites were sampled and their sample numbers appear in this file corresponding to those in the 5-Area Chemistry file. Excel file 5-Area Geothermometer contains a summary of geothermometers calculated for the new and historical data sets. Scanned field sheets are attached as a pdf.

Version 2 of the GeoRePORT protocols and excel-based reporting tools. Software allows users to grade the geologic, technical, and socio-economic conditions at a geothermal resource location for both electricity generation and direct-use. Includes tool and protocols for: * Geologic Assessment Tool * Technical Assessment Tool * Socio-Economic Assessment Tool * International Socio-Economic Assessment Tool In addition, GeoRePORT now includes a Resource Size Assessment tool and protocol.

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. GeoRePORT provides scientists and nonscientists a comprehensive and quantitative means of reporting: (1) features intrinsic to geothermal sites (project grade) and (2) maturity of the development (project readiness). Because geothermal feasibility is not determined by any single factor (e.g., temperature, permeability, permitting), a site?s project grade and readiness are evaluated on 12 attributes pertaining to geological, technical, or socio-economic feasibility. In this paper, we present case studies showing how GeoRePORT can be used to compare geological, technical, and socio-economic attributes between geothermal systems. The consistent and objective assessment protocols used in GeoRePORT allow for comparison of project attributes across unique locations and geological settings. GeoRePORT case studies presented here outline the geological, socio-economic, and technical features of four individual geothermal sites: Coso, Chena, Dixie Valley, and White Sands Missile Range. The case studies illustrate the usefulness of GeoRePORT in evaluating project risk and return, identifying gaps in reported data, evaluating R&D impact, and gathering insights on successes and failures as applicable to future projects.

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. GeoRePORT provides scientists and nonscientists a comprehensive and quantitative means of reporting: (1) features intrinsic to geothermal sites (project grade) and (2) maturity of the development (project readiness). Because geothermal feasibility is not determined by any single factor (e.g., temperature, permeability, permitting), a site?s project grade and readiness are evaluated on 12 attributes pertaining to geological, technical, or socio-economic feasibility. In this submission, we present the geological, socio-economic, and technical protocols as well as the spreadsheet template for easy data entry and reporting of the GeoRePORT protocol.

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources.

This spreadsheet identifies various flexibility characteristics for flash and binary geothermal power plants which could potentially facilitate provision of grid services beyond bulk power generation. Characteristics are differentiated between resource characteristics such as metal concentration and plant characteristics such as flow rates of pumps used in flash vs. binary plants.

Paper and metadata for studies regarding geothermal information and data in West Virginia. Includes location coordinates, chemical analyses, and other factors/measurements. From the site: "Preliminary study of the potential geothermal resources and analysis of the subsurface temperatures and heat flows of West Virginia. Geothermal resources in eastern United States include (1) warm-spring systems, (2) radioactive granite plutons beneath thick sedimentary cover, and (3) deep sedimentary basins having normal temperature gradients. The Appalachian basin in West Virginia contains sedimentary rocks that are greater than 20000 ft deep; thick sections of shale and sandstone occur in these regions. These deep basins are potentially attractive geothermal resources if higher-than-normal temperature gradients are identified. Numerous warm springs in eastern West Virginia suggest that deep circulation of ground waters along faults may locally elevate wall rock temperatures in the Appalachian basin. This is a preliminary study of the potential geothermal resources and provides an analysis of the subsurface temperatures and heat flow of West Virginia."

To prepare for its third phase, the Hawaii Play Fairway project conducted groundwater sampling and analyses in ten locations in the Hawaiian islands, magnetotelluric (MT) and gravity surveys, as well as calculations of 3D subsurface stress due to the weight of the rock underlying the topography of the volcano. The subsurface stresses were used to evaluate the potential for fracture-induced permeability. Inversions of the MT and gravity data produce 3D models of resistivity and density, respectively, on Lanai, across Haleakala's SW rift (Maui), and surrounding Mauna Kea (Hawaii Island). The project developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The project then incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. These results were used to identify target sites for exploratory drilling. Spreadsheet information: Each sheet contains data for a particular depth in kilometers. Positive depths are above sea level, and negative below. For more information, go to the Hawaii Groundwater and Geothermal Resources Center website linked in the resources.

This submission includes all the data to support an LCOE baseline assessment for the Resolute Marine Energy (RME) Surge WEC device.

Useful information and tools for calculating the Levelized Cost of Energy (LCOE) and MHK Cost Breakdown Structure. Includes a structure for calculating the capital expenditures and operating costs of a marine energy technology or device, reference resource data for both wave and tidal, and LCOE reporting guidance. These tools are meant to be used to help calculate the Levelized Cost of Energy (LCOE) for an MHK or MRE technology or device.

The volume of methane released through the Arctic Ocean to the atmosphere and its potential role in the global climate cycle has increasingly become the focus of studies seeking to understand the source and origin of this methane. In 2009, an international, multi-disciplinary science party aboard the U.S. Coast Guard icebreaker Polar Sea successfully completed a trans-U.S. Beaufort shelf expedition aimed at understanding the sources and volumes of methane across this region. Following more than a year of preliminary cruise planning and a thorough site evaluation, the Methane in the Arctic Shelf/Slope (MITAS) expedition departed from the waters off the coast of Barrow, Alaska in September 2009. The expedition, led by researchers with the U.S. Naval Research Laboratory (NRL), the Royal Netherlands Institute for Sea Research (NIOZ), and the U.S. Department of Energy's National Energy Technology Laboratory (NETL), was organized with an international shipboard science team consisting of 33 scientists with the breadth of expertise necessary to meet the expedition goals. NETL researchers led the expeditions initial core processing and lithostratigraphic evaluations, which are the focus of this report. A full expedition summary is available at in First Trans-Shelf-Slope Climate Study in the U.S. Beaufort Sea Completed by Coffin et al.,( 2010).

Mean average *offshore* wind speeds in metres per second (m/s) at 100m above sea level. The wind speed data, modelled in 2003, covers the Irish Internal Waters and the Irish Territorial Sea up to 12 nautical miles from the baseline. The Sustainable Energy Authority of Ireland (SEAI) offers the same data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind speed datasets assist wind energy planners, developers and policy makers. __Background on 2003 wind maps__ The 2003 wind-mapping project was completed by ESB International and TrueWind Solutions for SEAI (then SEI). It predicted wind characteristics, at heights of 50m, 75m and 100m, spanning onshore and offshore. (Larger heights of 125m and 150m were later covered in SEAI’s 2013 wind-mapping project.) The resulting GIS maps cover onshore in 200m grids, and offshore in 400m grids. Generally, wind maps extend to 15km offshore, or occasionally 20km. About the 2003 methodology, it iterated a MesoMap system and a faster WindMap model through reducing grid sizes. MesoMap is built on MASS (Mesoscale Atmospheric Simulation System), a numerical weather model that embodied the fundamental physics of the atmosphere. Iterations through the nested grids accounted for local land elevation, land cover and roughness. Final iterations accounted for increased wind shear and reduced near-surface wind speed at less windy sites. The 2003 Wind-mapping Project Report is available [here](https://seaiopendata.blob.core.windows.net/wind/Report_2003_Wind_Atlas.pdf).

Information about mineral resources, including the number of mines and types of mines in New York.

This dataset includes modeled tidal current velocities, direction and depth at two locations in East and North Forelands (60.716, -151.434 and 61.024, -151.157) near Nikiski and Tyonek, respectively, in Cook Inlet, Alaska. Data from two grid cells were provided by the Pacific Northwest National Laboratory based on a tidal hydrodynamic model that characterized the tidal stream resources in Cook Inlet for a period from May 1 to September 1, 2005 (Wang and Yang 2020). The model grid size had a horizontal spatial resolution of 100 m at East Forelands and 200 m at Tyonek; mean sea level (MSL) depth was 47.9 m and 23.7 m at each respective site, and there were 10 depth bins that ranged in size with the tide from 4.3-5.2 m and 1.9-2.8 m, respectively (Wang and Yang 2020).

Field measurements of mean flow and turbulence parameters at the Kvichak river prior to and after the deployment of ORPC's RivGen hydrokinetic turbine. Data description and turbine wake analysis are presented in the attached manuscript "Wake measurements from a hydrokinetic river turbine" by Guerra and Thomson (recently submitted to Renewable Energy). There are three data sets: NoTurbine (prior to deployment), Not_Operational_Turbine (turbine underwater, but not operational), and Operational_Turbine. The data has been quality controlled and organized into a three-dimensional grid using a local coordinate system described in the paper. All data sets are in Matlab format (.mat). Variables available in the data sets are: qx: X coordinate matrix (m) qy: Y coordinate matrix (m) z : z coordinate vector (m) lat : grid cell latitude (degrees) lon: grid cell longitude (degrees) U : velocity magnitude (m/s) Ux: x velocity (m/s) Vy: y velocity (m/s) W: vertical velocity (m/s) Pseudo_beam.b_i: pseudo-along beam velocities (i = 1 to 4) (m/s) (structure with raw data within each grid cell) beam5.b5: 5th-beam velocity (m/s) (structure with raw data within each grid cell) tke: turbulent kinetic energy (m2/s2) epsilon: TKE dissipation rate (m2/s3) Reynolds stresses: uu, vv, ww, uw, vw (m2/s2) Variables from the Not Operational Turbine data set are identified with _T Variables from the Operational Turbine data set are identified with _TO

The RETScreen SoftwareHeat Pump Modelcan be used worldwide to evaluate the energy production and savings, costs, emission reductions, financial viability and risk for heat pump projects, ranging in size from air-source heat pump (ASHP) networks in commercial and institutional buildings, to horizontal ground-coupled heat pumps (GCHP) to heat and/or cool space and/or processes in institutional buildings and industrial facilities, to combined heating and cooling using vertical boreholes for residential, commercial and institutional buildings and industrial facilities, to open loop or standing well groundwater heat pumps (GWHP) for residential systems. In addition, both the size and cost of the ground heat exchanger can be calculated using a convenientGround heat exchanger tool. The software (available in mu

To further transparency and openness, DOE established a policy to document and post online all CX determinations involving classes of actions listed in Appendix B to Subpart D of the DOE NEPA regulations (10 CFR Part 1021). This raw data set contains CX determinations required to be posted under the policy, and also some for which documentation and posting are optional, i.e., determinations involving classes of actions listed in Appendix A or made before the policy's effective date of November 2, 2009. The data set includes information by state, CX applied, date range, DOE Program, Field, or Site Office, keyword, and whether the CX determination is for a project related to the American Recovery and Reinvestment Act (Recovery Act or ARRA) of 2009. The web address to the CX determination documents are provided. This data set will be updated approximately monthly. See www.gc.doe.gov/NEPA/categorical_exclusion_determinations.htm for information on DOE CX procedures. For further information on DOE's NEPA compliance program, see www.gc.energy.gov/nepa or email: askNEPA@hq.doe.gov.

This reference database in RIS format contains all of the references that were collected as part of our retrospective analysis of geothermal mineral recovery (REE and Li) activities and domestic resource assessment. The outputs detail the chemistry and molecular processes used in lithium recovery from geothermal brines. The articles included include information about the study including more information on geothermal brines and the technologies used for recovering lithium from geothermal brines.

The report included in this submission details the nontechnical barriers to entry for development of geothermal resources in the Salton Sea. The Salton Sea provides an economically viable opportunity for replacing the energy imported by California which makes up 25 percent of Californias total electricity supply. However, geothermal energy in the Salton Sea has been largely undeveloped since the 1980s. This report preforms a techno-economic analysis of Geothermal Energy in the Salton Sea and develops a model to quantify the nontechnical challenges and opportunities associated with new geothermal development in the Salton Sea. Geothermal energy offers an opportunity to generate baseload, renewable energy that can help support the transition to an energy economy with reduced impacts on climate change and replace older, more expensive, nonrenewable, and more resource-impacting energy-generation facilities. The United States has the largest known geothermal resource in the world, with over 31 GW of conventional geothermal potential. However, due to market conditions, an inability to properly quantify both electrical grid benefits and resource stability, and the difficulty of exploring and developing the geothermal resource, few new geothermal projects have come online over the past three decades. The Salton Sea, in Imperial County, California, provides a prime location and opportunity to develop new geothermal resources. The Salton Sea contains a robust, well-mapped, geothermal resource, with opportunities for concurrent development of lithium and other mineral resources. This report describes the history of geothermal development at the Salton Sea and compares geothermal to other renewable energy sources in the area. The report then uses a techno-economic analysis (TEA) model to analyze the relative benefits and costs of various challenges and opportunities and provides recommendations for streamlining geothermal development at the Salton Sea and elsewhere. The challenges and opportunities analyzed in the TEA model were informed by stakeholder interviews and literature reviews. Based upon the identified challenges and opportunities and the results of the TEA model, primary findings are that certain nontechnical barriers such as permitting costs play only a minor role in determining the viability of development of the geothermal resource at the Salton Sea. Other barriers such as permitting timelines, government/agency coordination, and the potential co-location of lithium extraction with a geothermal plant may result in much larger impacts on project viability.

Seascape effects of wind turbines up to 15km from shoreline are downloadable as GIS shapefiles. SEAI commissioned a Strategic Environmental Assessment (SEA), completed in 2010, to inform policy-making in the Offshore Renewable Energy Development Plan (OREDP). One set of SEA evaluations was seascape assessments. In 2014 the OREDP was published. (References to both reports below).A zipped collection of shapefiles in spatial reference system WGS 84 (EPSG:4326) is downloadable below. The shapefiles assign category values of seascape effects around the Irish coast (excl. N. Ireland). Appendices in SEA Volume 4 describe these category values in detail (reference below). All SEA volumes are accessible by using the search bar in SEAI's website (http://www.seai.ie).The Sustainable Energy Authority of Ireland (SEAI) offers wind-energy data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind-energy datasets assist wind energy planners, developers and policy makers. __References__ SEA Environmental Report Volume 1: Non-Technical Summary. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-1-Non-Technical-Summary.pdfSEA Environmental Report Volume 4: Appendices. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-4-Appendices.pdfOffshore Renewable Energy Development Plan — A Framework for the Sustainable Development of Ireland's Offshore Renewable Energy Resource. February 2014. https://assets.gov.ie/27215/2bc3cb73b6474beebbe810e88f49d1d4.pdf

Seascape effects of wind turbines up to 24km from shoreline are downloadable as GIS shapefiles.SEAI commissioned a Strategic Environmental Assessment (SEA), completed in 2010, to inform policy-making in the Offshore Renewable Energy Development Plan (OREDP). One set of SEA evaluations was seascape assessments. In 2014 the OREDP was published. (References to both reports below).A zipped collection of shapefiles in spatial reference system WGS 84 (EPSG:4326) is downloadable below. The shapefiles assign category values of seascape effects around the Irish coast (excl. N. Ireland). Appendices in SEA Volume 4 describe these category values in detail (reference below). All SEA volumes are accessible by using the search bar in SEAI's website (http://www.seai.ie).The Sustainable Energy Authority of Ireland (SEAI) offers wind-energy data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind-energy datasets assist wind energy planners, developers and policy makers. __References__ SEA Environmental Report Volume 1: Non-Technical Summary. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-1-Non-Technical-Summary.pdfSEA Environmental Report Volume 4: Appendices. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-4-Appendices.pdfOffshore Renewable Energy Development Plan — A Framework for the Sustainable Development of Ireland's Offshore Renewable Energy Resource. February 2014. https://assets.gov.ie/27215/2bc3cb73b6474beebbe810e88f49d1d4.pdf

Seascape effects of wind turbines up to 35km from shoreline are downloadable as GIS shapefiles.SEAI commissioned a Strategic Environmental Assessment (SEA), completed in 2010, to inform policy-making in the Offshore Renewable Energy Development Plan (OREDP). One set of SEA evaluations was seascape assessments. In 2014 the OREDP was published. (References to both reports below).A zipped collection of shapefiles in spatial reference system WGS 84 (EPSG:4326) is downloadable below. The shapefiles assign category values of seascape effects around the Irish coast (excl. N. Ireland). Appendices in SEA Volume 4 describe these category values in detail (reference below). All SEA volumes are accessible by using the search bar in SEAI's website (http://www.seai.ie).The Sustainable Energy Authority of Ireland (SEAI) offers wind-energy data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind-energy datasets assist wind energy planners, developers and policy makers. __References__ SEA Environmental Report Volume 1: Non-Technical Summary. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-1-Non-Technical-Summary.pdfSEA Environmental Report Volume 4: Appendices. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-4-Appendices.pdfOffshore Renewable Energy Development Plan — A Framework for the Sustainable Development of Ireland's Offshore Renewable Energy Resource. February 2014. https://assets.gov.ie/27215/2bc3cb73b6474beebbe810e88f49d1d4.pdf

Seascape effects of wind turbines up to 5km from shoreline are downloadable as GIS shapefiles. SEAI commissioned a Strategic Environmental Assessment (SEA), completed in 2010, to inform policy-making in the Offshore Renewable Energy Development Plan (OREDP). One set of SEA evaluations was seascape assessments. In 2014 the OREDP was published. (References to both reports below). A zipped collection of shapefiles in spatial reference system WGS 84 (EPSG:4326) is downloadable below. The shapefiles assign category values of seascape effects around the Irish coast (excl. N. Ireland). Appendices in SEA Volume 4 describe these category values in detail (reference below). All volumes of the SEA are accessible by using the search bar in SEAI's website (http://www.seai.ie). The Sustainable Energy Authority of Ireland (SEAI) offers wind-energy data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind-energy datasets assist wind energy planners, developers and policy makers. __References__ SEA Environmental Report Volume 1: Non-Technical Summary. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-1-Non-Technical-Summary.pdfSEA Environmental Report Volume 4: Appendices. October 2010. https://seaiopendata.blob.core.windows.net/wind/OREDP-SEA-ER-Volume-4-Appendices.pdfOffshore Renewable Energy Development Plan — A Framework for the Sustainable Development of Ireland's Offshore Renewable Energy Resource. February 2014. https://assets.gov.ie/27215/2bc3cb73b6474beebbe810e88f49d1d4.pdf

This submission contains a link to two USGS data publications. Each data release contains all digital geographic data used and produced by the Snake River Plain Play Fairway Analysis for Phase 1 and Phase 2 (ArcGIS shapefiles and raster files) as well as the model processing script, tables, and documentation used to generate data outputs. Brief descriptions of data layers are in the metadata of GIS files. Greater detail is available in the Phase 1 and Phase 2 final reports (linked below). The citations for the favorability model data products are: Phase 1 DeAngelo, J., Shervais, J.W., Glen, J.M., Dobson, P.F., Liberty, L.M., Siler, D.L., Neupane, G., Newell, D.L., Evans, J.P., Gasperikova, E., Peacock, J.R., Sonnenthal, E., Nielson, D.L., Garg, S.K., Schermerhorn, W.D., and Earney, T.E., 2021, Snake River Plain Play Fairway Analysis Phase 1 Favorability Model (DE EE0006733): U.S. Geological Survey data release, https://doi.org/10.5066/P95EULTI. Phase 2 DeAngelo, J., Shervais, J.W., Glen, J.M., Dobson, P.F., Liberty, L.M., Siler, D.L., Neupane, G., Newell, D.L., Evans, J.P., Gasperikova, E., Peacock, J.R., Sonnenthal, E., Nielson, D.L., Garg, S.K., Schermerhorn, W.D., and Earney, T.E., 2021, Snake River Plain Play Fairway Analysis Phase 2 Favorability Model (DE EE0006733): U.S. Geological Survey data release, https://doi.org/10.5066/P9Y8MEZY.

This presents the results of Phase 1 of the Snake River Plain Play Fairway Analysis project, along with a proposed work for Phase 2. No new data were collected, but we list data sources for our compilation. The Snake River volcanic province (SRP) overlies a thermal anomaly that extends deep into the mantle; it represents one of the highest heat flow provinces in North America. The Yellowstone hotspot continues to feed a magma system that underlies southern Idaho and has produced basaltic volcanism as young as 2000 years old. It has been estimated to host up to 855 MW of potential geothermal power production, most of which is associated with the Snake River Plain volcanic province. Our goals for this Phase 1 study were to: (1) adapt the methodology of Play Fairway Analysis for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal play fairway model for the SRP and identify the most promising plays, using software tools that are standard in the petroleum industry. Our ultimate goals are to lower the risk and cost of geothermal exploration throughout geothermal industry, and to stimulate the development of new geothermal power resources in Idaho.

Data from a Nortek Signature1000 deployed on a lander for 14 days in Aug 2020 in the entrance to Sequim Bay, WA. Raw data were processed using the DOLfYN python package and standardized using the ME Data Pipeline python package, tsdat version 0.2.12. Processed data were partitioned into 24 hour increments and saved in the NETCDF file format.

To further transparency and openness, DOE established a policy to document and post online all CX determinations involving classes of actions listed in Appendix B to Subpart D of the DOE NEPA regulations (10 CFR Part 1021). The database contains CX determinations required to be posted under the policy, and also some for which documentation and posting are optional, i.e., determinations involving classes of actions listed in Appendix A or made before the policy's effective date of November 2, 2009. The database may be searched by state, CX applied, date range, DOE Program, Field, or Site Office, keyword, and whether the CX determination is for a project related to the American Recovery and Reinvestment Act (Recovery Act or ARRA) of 2009. Links to CX determination documents are provided. The database will be updated approximately monthly. See http://www.gc.doe.gov/NEPA/categorical_exclusion_determinations.htm for information on DOE CX procedures. For further information on DOE's NEPA compliance program, see http://www.gc.energy.gov/nepa or email: askNEPA@hq.doe.gov.

Paper discussing research into Devonian shale gas reserves as a viable energy pursuit. From the paper: "To help meet the increasing demand for natural gas, the U.S. Department of Energy (DOE) is supporting research and development activities to recover gas from unconventional sources. The Eastern Gas Shales Project (EGSP) is an integral part of DOE's Unconventional Gas Recovery Program. Other projects under the DOE program include producing gas from the tight sandstones of the western and southwestern states. methane contained within coal seams and associated strata, and methane from the geopressured aquifers of the Gulf Coast. The EGSP was initiated in 1976 and is designed to promote further commercial development of natural gas supplies from the unconventional gas-bearing Devonian Shales. Methods which have been or are presently being studied to recover and produce the gas include exploration techniques specific to the shale resource, advanced drilling technology such as directional drilling, and advanced stimulation technology including explosives and energy-assisted hydraulic fracturing techniques."

Paper discussing new technologies - both made and being made - that are intended to assist in extracting natural gasses from eastern gas shales. It also discusses the new potentials provided by technological advances. From the paper: "Research in fracturing technology for the ERDA organization is structured on (1) the development of new concepts for increasing the deliverability of natural gas from resources that are classified as marginal by present day practices and (2) the testing and transfer of new technology to the private sector. The program at the Morgantown Energy Research Center is centered about their foremost expertise in delineating and utilizing natural and induced fracture systems for enhancement of resource recovery. More recently, the research program has been expanded to include studies of foam fracturing, production history from fractured wells, cost/effectiveness of stimulation treatments and fracture mechanics as support activities for field demonstration projects. The program at the Bartlesville Energy Research Center evolves about their broad experience in stimulation technology in the marginal gas resources of the western U.S. This experience includes nuclear, explosive and more recently, massive hydraulic fracturing stimulation technology."

This submission contains documents that describe the USU Camas-1 test well, drilled in Camas Prairie, Idaho, in Fall 2018 and Fall 2019. The purpose of this well is to validate exploration methodologies of the Snake River Plain (SRP) Play Fairway Analysis (PFA) project.

The compressed (.zip) file contains Datawell MK-III Directional Waverider binary and unpacked data files as well as a description of the data and manuals for the instrumentation. The data files are contained in the two directories within the zip file, "Apr_July_2012" and "Jun_Sept_2013". Time series and summary data were recorded in the buoy to binary files with extensions '.RDT' and '.SDT', respectively. These are located in the subdirectories 'Data_Raw' in each of the top-level deployment directories. '.RDT' files contain 3 days of time series (at 1.28 Hz) in 30 minute "bursts". Each '.SDT' file contains summary statistics for the month indicated computed at half-hour intervals for each burst. Each deployment directory also contains a description (in 'File.list') of the Datawell binary data files, and a figure ('Hs_vs_yearday') showing the significant wave height associated with each .RDT file (decoded from the filename). The corresponding unpacked Matlab .mat files are contained in the subdirectories 'Data_Mat'. These files have the extension '.mat' but use the root filename of the source .RDT and .SDT files.

This is the Utah FORGE annual report for Phase 3A year 1, which was completed on December 28th, 2020. This report includes site infrastructure, site operations, seismic monitoring, a conceptual geological model, outreach, and communications for the Utah FORGE project during Phase 3A in 2020. Utah FORGE projects showcase the role of geothermal energy and Enhanced Geothermal Systems (EGS) as a renewable source of power for the United States. The geoscientific investigations done in the Utah FORGE projects demonstrate the surrounding region holds significant potential for future EGS development.

This is a GIS point feature shapefile representing wells, and their temperatures, that are located in the general Utah FORGE area near Milford, Utah. There are also fields that represent interpolated temperature values at depths of 200 m, 1000 m, 2000 m, 3000 m, and 4000 m. in degrees Fahrenheit. The temperature values at specific depths as mentioned above were derived as follows. In cases where the well reached a given depth (200 m and 1, 2, 3, or 4 km), the temperature is the measured temperature. For the shallower wells (and at deeper depths in the wells reaching one or more of the target depths), temperatures were extrapolated from the temperature-depth profiles that appeared to have stable (re-equilibrated after drilling) and linear profiles within the conductive regime (i.e. below the water table or other convective influences such as shallow hydrothermal outflow from the Roosevelt Hydrothermal System). Measured temperatures/gradients from deeper wells (when available and reasonably close to a given well) were used to help constrain the extrapolation to greater depths. Most of the field names in the attribute table are intuitive, however HF = heat flow, intercept = the temperature at the surface (x-axis of the temperature-depth plots) based on the linear segment of the plot that was used to extrapolate the temperature profiles to greater depths, and depth_m is the total well depth. This information is also present in the shapefile metadata.

This dataset contains groundwater geochemistry from several wells in North Milford Valley, Utah, in the region of the Utah FORGE project (Phase 2c). Readme file that discusses the data contained in the Excel spreadsheet. Data include GPS coordinates (UTM, Lat-Long), sampling temperature, pH, Li, Na, K, Ca, Mg, SiO2, B, Cl, F, SO4, HCO3, oxygen, and hydrogen isotopes. Analyses were performed at the Utah State Laboratory and the University of Minnesota. The zipped archive includes Excel and csv format spreadsheets, a shapefile map with well locations, and a readme text file with additional information. The zip is updated data from October 2021.

Well 58-32 (previously labeled MU-ESW1) was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. Well Accord-1 was drilled decades ago for geothermal exploration purposes. While the conditions encountered in the well were not suitable for developing a conventional hydrothermal system, the information obtained suggested the region may be suitable for an enhanced geothermal system. Geophysical well logs were collected in both wells to obtain useful information regarding there nature of the subsurface materials. For the recent testing of 58-32, the Utah FORGE Project contracted with the well services company Schlumberger to collect the well logs.

The stream listing was prepared by district fisheries biologists with the WVDNR's Wildlife Resources Section in cooperation with the Natural Resources Conservation Service and other state and federal agencies. Criteria for selection are (1) streams with native or stocked populations of trout and (2) warm water streams five or more miles in length with desirable fish populations that are utilized by the public. This information is made available to agencies involved in projects that may cause stream disturbances in order to highlight the importance of avoiding activities that impact fish populations, especially trout. The high quality streams dataset is a subset of the National Hydrography Dataset (NHD) for West Virginia. WVDNR provided these data in the form of event tables in an ESRI personal geodatabase. WV GIS Technical Center personnel converted the event tables to feature classes, which were then exported as shapefiles. Separate watershed shapefiles and a single merged file are available for download.

From the site: "Abandoned mine features compiled by the Office of Abandoned Mine Lands and Reclamation (AMLR) of the West Virginia Department of Environmental Protection. The AMLR eliminates damage that occurred from mining operations prior to August 3, 1977 and is funded by the AML fund. It corrects hazardous conditions and reclaims abandoned and forfeited mine sites. Typical AML features include highwalls, portals, refuse piles, and mining structures such as tipples. AML features were digitized from AMLR source materials by the WVU Department of Geology and Geography and the WVU Natural Resource Analysis Center. Published in 1996."