{7717f3ed-6ab2-4465-b36b-03040c1f2eaf} eng; USA utf8 dataset EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact 2025-07-23 ISO 19115 Geographic Information - Metadata ISO 19115:2003/Cor.1:2006(E) EnviroAtlas - Annual average potential wind energy resource by 12-digit HUC for the Conterminous United States 2016-06-13 publication U.S. EPA Office of Research & Development (ORD) - National Exposure Research Laboratory (NERL) Research Triangle Park NC publisher US Environmental Protection Agency (US EPA) originator This EnviroAtlas dataset shows the annual average potential wind energy resource in kilowatt hours per square meter per day for each 12-digit Hydrologic Unit (HUC). It was produced using data from the National Renewable Energy Laboratory (NREL). These estimates represent wind resources at a 10 meter height above surface. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). This EnviroAtlas dataset can be used to analyze the potential wind energy that could be produced across the conterminous United States. It can be used by planners and the public to estimate potential renewable energy resources. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. completed EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact asNeeded Ecosystem Environment theme EPA GIS Keyword Thesaurus 12-digit HUCs Ecosystem Services Energy EnviroAtlas Environment Environmental Atlas Natural Resources theme EnviroAtlas Alabama Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas United States Utah Vermont Virginia Washington Washington DC West Virginia Wisconsin Wyoming place None https://edg.epa.gov/EPA_Data_License.html otherRestrictions Use Constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated. otherRestrictions Access Constraints: None. PUBLIC https://project-open-data.github.io/schema/#accessLevel Standard Technical Controls eng; USA environment -128.02839229 -65.20336449 22.7348894 51.6773602 2001-01-01 2002-01-01 2003-01-01 2004-01-01 2005-01-01 2012-01-01 This data is based on datasets produced by NREL and AWS TrueWind in cooperation with the U.S. Department of Energy's WINDExchange program; the same methodologies were not used for all states, resulting in values that sometimes vary along state lines. The 50-meter resolution data for many states were produced as part of the Wind Powering America Program. The 50m datasets that were produced by AWS TrueWind account for surface roughness; however, the 50m datasets produced by NREL (IL, ND, and SD) do not. NREL used publicly available datasets for the remaining states where data were available; these data might have been developed using different methodologies than those used by Wind Powering America. For several states (Louisiana, Mississippi, Alabama, and Florida), NREL only offers data at 25-kilometer resolution. Therefore, the data sources and methodologies used to produce the wind power estimates may not have been consistent across all states. These data represent potential wind energy; the actual wind energy produced in a location might be lower. These estimates only apply to areas of low surface roughness, such as grassy plains. In areas with greater surface roughness, such as forests, wind power will be reduced. Many, but not all, of the NREL datasets used to produce this dataset account for surface roughness. This data is not suitable for micro-siting wind development projects. true Entity and Attribute Information Entity and Attribute Overview: For more information about EnviroAtlas data, go to https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets. NREL's wind datasets can be found on http://www.nrel.gov/gis/data_wind.html. An explanation of the wind power classes that NREL uses can be found on http://www.nrel.gov/gis/wind_detail.html. The following list shows the relationship between wind power classes and their corresponding wind power densities in watts per square meter at 10-meter height: WPC 1 = 0-100 W/m2, WPC 2 = 100-150 W/m2, WPC 3 = 150-200 W/m2, WPC 4 = 200-250 W/m2, WPC 5 = 250-300 W/m2, WPC 6 = 300-400 W/m2, WPC 7 = 400-1000 W/m2. Because each wind power class represents a range of wind power densities, the minimum and maximum wind power densities were averaged, and the following values were used to develop this EnviroAtlas dataset: WPC 1 = 50 W/m2, WPC 2 = 125 W/m2, WPC 3 = 175 W/m2, WPC 4 = 225 W/m2, WPC 5 = 275 W/m2, WPC 6 = 350 W/m2, WPC 7 = 700 W/m2. 24,000 was used as a conversion factor to convert the wind power factor from watts per square meter to kilowatt hours per square kilometer per day. The metric was later converted to kilowatt hours per square kilometer per day to match other EnviroAtlas energy potential metrics. A comprehensive list of metric creation steps is included in the Processing Steps. Entity and Attribute Detail Citation: https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas distributor https://enviroatlas.epa.gov/download/CONUS_metrics_FGDB.zip download Download The URL providing direct access to the downloadable dataset. download https://enviroatlas.epa.gov/download/CONUS_metrics_CSV.zip ESRI:ArcGIS API The endpoint of a web service to access the dataset (REST endpoint, WMS GetCapabilities URL, or a SOAP WSDL endpoint). webMapService https://www.epa.gov/enviroatlas/enviroatlas-data information Documentation URL for accessing related documents such as data dictionary, technical information about a dataset, developer documentation, etc. information https://www.epa.gov/enviroatlas information Home Page Alternative landing page used to redirect user to a contextual, Agency-hosted "homepage" for the Dataset or API information dataset Horizontal Positional Accuracy Report Data were collected using methods that have unknown accuracy (EPA National Geospatial Data Policy [NGDP] Accuracy Tier 10). For more information, please see EPA's NGDP at https://epa.gov/geospatial/policies.html Features represented have not been tested for completeness Features represented have not been tested for completeness Tests for integrity have not been performed. This lineage was generated by the FGDC CSDGM to 19139 transformation 1. Obtained wind data from NREL (http://www.nrel.gov/gis/data_wind.html). The data used includes shapefiles showing an estimate of annual wind resources for states and regions at 50-meter resolution. Because this data was not available for all states, a different NREL dataset, showing wind resources at a 25-km resolution for the conterminous U.S., was obtained to use where 50-meter resolution data was not available. 2013-11-01T00:00:00 2. Projected all shapefiles into Albers. 2014-08-01T00:00:00 3. The shapefiles for some states and regions overlapped with each other. In cases of overlap, used the ArcGIS erase tool to erase the overlapping area from the shapefile that showed wind resources at a lower resolution, or that matched the state border less accurately. Retained the overlapping areas from the shapefiles that showed more detail or had more accurate boundaries. 2014-08-01T00:00:00 4. The shapefile for Minnesota contained overlapping features in the interior of the state. Removed one large feature that covered most of the state and obscured many more complex polygons. For smaller polygons, kept the polygon whose wind power class most closely matched the wind power class of its neighbors. 2014-08-01T00:00:00 5. Merged all 50-meter shapefiles into a single shapefile covering most of the conterminous United States. This shapefile does not include Louisiana, Mississippi, Alabama, or Florida, because data for these states was not available at 50-meter resolution. 2014-08-01T00:00:00 6. For both the lower-48 50-meter shapefile and the lower-48 25km shapefile, converted the wind power class attribute to energy in kWh/km2/day. 2014-08-01T00:00:00 6. a. Took the average of the maximum and minimum wind power density values (W/m2) at 10-meter height for each wind power class (see Overview section for details on wind power classes). 2014-08-01T00:00:00 6. b. Multiplied wind power densities in W/m2 by 24,000 to find kWh/km2/day (divide by 1000 to convert W/m2 to kW/m2, multiply by 24 to get kWh/m2/day, multiply by 1,000,000 to get kWh/km2/day). 2014-08-01T00:00:00 7. Converted the two shapefiles from polygon to raster, using the wind energy density in kWh/km2/day as the raster value. 2014-08-01T00:00:00 8. Combined the two rasters using map algebra. Where the 50m raster was null (LA, MI, AL, FL, gaps between states that did not align perfectly, and holes within some states), incorporated values from the 25km raster. 2014-08-01T00:00:00 9. Ran zonal statistics as table to find the mean potential wind energy per km2 for each 12-digit HUC, using a rasterized version of the NHDPlusV2 WBD Snapshot - EnviroAtlas Version. 2016-03-23T00:00:00 10. Converted units from kWh/km2/day to kWh/m2/day to match units in the EnviroAtlas solar energy potential dataset. Divided kWh/km2/day by 1,000,000. 2017-10-16T00:00:00 unknown 2029-07-23 This metadata was automatically generated from the FGDC Content Standard for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2024-02-09T11:11:00 version of the FGDC CSDGM to ISO 19139 transform. EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact