Hydropower Infrastructure – LAkes, Reservoirs, and RIvers (HILARRI), Version 4

Overview

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include:

1. Dams from the National Inventory of Dams (version published on August 18, 2025) and the Global Reservoir and Dam Database (GRanD v1.3)
2. Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025)

These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from:

• Products from the National Hydrography Dataset (NHD)
  • NHDPlusV2 Medium Resolution river network flowlines,
  • NHD waterbodies (limited to lakes and reservoirs),
  • NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS))
  • NHD High Resolution waterbodies
• HydroLAKES water bodies (lakes and reservoirs)
• LAGOS-US lakes and reservoirs
• EPA National Lakes Assessment (2007, 2012, 2017, and 2022)
• The Reservoir Sedimentation Database (RESSED)
• Sampling locations from the EPA SURGE project (2016-2023)

Unique identifiers are used to facilitate joining with the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites.

This dataset was developed to support research funded by the Water Power Technologies Office including the Greenhouse Gas Emissions at Hydropower Reservoirs project.

Methodology

The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in the data that are joined through the identifiers listed in HILARRI.

HILARRI was created by using spatial joins and fuzzy matching techniques to determine matches between power plants and dams. Additional spatial joins and tabular joins based on common identifiers have been used to link other datasets. Cross-references between datasets describing removal, operational, or development status are also used to categorize the infrastructure into different types. Improvement to coordinates have been made based on OpenStreetMaps or satellite imagery.