ORNL_US_Hydropower_DevelopmentPipeline_Data_2024.xlsx

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1	Dataset Title	U.S. Hydropower Development Pipeline Database 2024
2	Keywords	hydropower, water power, hydroelectricity, hydropower market, hydropower plants, Oak Ridge National Laboratory, Department of Energy, Water Power Technologies Office, ORNL, DOE
3	Originator	Oak Ridge National Laboratory
4	Creator	Megan Johnson (johnsonmm@ornl.gov) and Rocio Uria Martinez (uriamartiner@ornl.gov)
5	Publication Date	4/9/2024
6	Updated
7	Online Linkage	U.S. Hydropower Development Pipeline Data, 2024 \| Hydrosource (ornl.gov)
8	Dataset ID	ORNL_US_Hydropower_DevelopmentPipeline_2024
9	DOI	10.21951/HMR_PipelineFY24/2338143
10	Description	U.S. Hydropower Development Pipeline database is a snapshot (as of December 31, 2023) of locations and key characteristics of U.S. hydropower projects that are in the permitting/licensing/exemption phase and yet to be operational.
11	Purpose	For use within geographic informatin system (GIS), databases, statistical software, or applications.
12	Coverage	Conterminous United States, Alaska, and Hawaii.
13	Coordinate System	GCS_North_American_1983 (WKID: 4269 Authority: EPSG)
14	Exclusions	May lack some hydropower projects that are not required to go through standard permitting processes.
15	Maintenance_and_Update_Frequency	Once per year
16	Type	Spreadsheet
17	Format	Microsoft Excel
18	Version	2024
19	Contact Instructions	Megan Johnson: johnsonmm@ornl.gov
20	Citation	Johnson, M.M., and Uría-Martínez, R., (2024). U.S. Hydropower Development Pipeline Database 2024. April 2024 [Excel Data].
21	Use Constraints	The distributor shall not be held liable for improper or incorrect use of this data, based on the description of appropriate/inappropriate uses described in this metadata document. It is strongly recommended that this data is directly acquired from the distributor and not indirectly through other sources which may have changed the data in some way. ORNL should be acknowledged using the citation above as the data source in products derived from these data.
22	Dataset Credit	Funding and support were provided by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy, Water Power Technologies Office through Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-00OR22725.
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