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Hourly flow data from hydropower facilities in CONUS

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Type: Resource
Storage: The size of this resource is 565.5 MB
Created: Jun 22, 2021 at 10:05 p.m.
Last updated: Jul 28, 2022 at 10:24 p.m.
DOI: 10.4211/hs.aadf2681d15f48748d49c1533d117e9e
Citation: See how to cite this resource
Sharing Status: Published
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This data resource supports Marshall & Grubert (2021). The study presents operational hydropower parameters calculated based on six years of hourly data from 158 dams, and estimates power generation in these hours based on monthly hydropower generation data reported to the Energy Information Administration (EIA). More details on calculated parameters are available in the associated manuscript. The data are distributed as a Shiny application. The application can be run locally by downloading the data package, accessed at:, or users can use the data included for their own analyses (further documentation in the further down this page).

Marshall, A. M., & Grubert, E. (2022). Hydroelectricity modeling for low-carbon and no-carbon grids: Empirical operational parameters for optimization and dispatch models. Earth’s Future, n/a(n/a), e2021EF002503.

Subject Keywords



Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
United States
North Latitude
East Longitude
South Latitude
West Longitude


Hydropower operational parameters data resource

This resource is structured as a Shiny application that can be run on a user's personal computer. The application can also be accessed in a browser (without downloading this data) at: For users wishing to use the data without using the accompanying application, data are available in the "data" subdirectory as well as in the root directory for users who prefer not to download the .zip file that contains the full shiny application.

Shiny application use

To run the Shiny application locally, please ensure you have the R programming language and RStudio installed on your computer. Install the libraries required in the app.R script with the R command, install.packages("packagename"). In RStudio, open the "app.R" script and click the "Run App" button in order to run the app locally.

Data included

Data used to run the Shiny application are available in the "data" subdirectory. For new analyses, the most relevant data files will be "hourly_flow.csv" and "hourly_flow_metadata.csv". These files are described in detail below.


This dataframe contains quality-controlled hourly data for all the dams included in our sample. Column headers are:

  • date_time: local date and time, formatted as YYYY-MM-DD HH:MM:SS
  • dam_name: Name of dam
  • power: Estimated power generation in MWh - see manuscript for details of calculation.
  • discharge: Reported discharge in m3/sec.


This dataframe contains metadata describing dam characteristics for the dams included in hourly_flow.csv. Columns included are:

  • dam_name: Name of dam; this is the key variable to use if joining to hourly flow data.
  • dam_code: Dam code in the National Inventory of Dams (NID) database.
  • eia_plant_id: Plant ID in the Energy Information Administration (EIA) databases.
  • latitude: degrees
  • longitude: degrees
  • river: Name of river, determined manually
  • system: Name of relevant river system if applicable, determined manually
  • nameplate_power_mw: Nameplate power based on EIA 860 database in 2016.
  • data_type: Identifies whether data was obtained from flow through turbines, flow downstream of the dam, or total flow through the dam.
  • state_name: Name of state in which dam is located
  • nerc_region: NERC region in which dam is located
  • nerc_subregion: NERC subregion in which dam is located interconnect: Interconnect in which dam is located

Related Resources

This resource is referenced by Marshall, A.M., Grubert, E. Hydroelectricity modeling for low-carbon and no-carbon grids: Empirical operational parameters for optimization and dispatch models. In press at Earth's Future.


Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
Carnegie Institution of Washington

How to Cite

Marshall, A. M., E. Grubert (2022). Hourly flow data from hydropower facilities in CONUS, HydroShare,

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