Assessing the vulnerability of U.S. energy infrastructure to dual source flood hazards: A spatial and population...

Flood risk to U.S. energy infrastructure (EI) is shaped by both inland and coastal processes, yet most national assessments rely on a single hazard dataset. To address this limitation, we combine FEMA Special Flood Hazard Areas (SFHA; 1% annual chance) with NOAA's coastal composite (storm surge, high-tide flooding, sea-level rise, and related layers) to develop a unified view of exposure. Using a national EI inventory (n = 21,988), we conduct spatial overlays, county-level Getis-Ord Gi* clustering, subtype analyses, and a 5-mile population proximity assessment. Nationwide, 3174 facilities (14.4%) are classified as flood-exposed in the combined dataset, compared with 9.2% when using FEMA alone and 9.5% when using NOAA alone; 925 facilities (4.2%) are exposed in both, while FEMA-only (1096) and NOAA-only (1153) contribute roughly equally. Exposure varies by sector, with petrochemical and petroleum facilities exhibiting the highest rates. Subtypes such as petroleum ports, LNG terminals, and hydropower plants stand out as particularly exposed. Within NOAA's footprint, agreement between sources is high (87.8%), but NOAA-only facilities far exceed FEMA-only facilities, highlighting additional coastal exposure beyond regulatory SFHAs. Hotspot analysis reveals complementary geographies: NOAA emphasizes a continuous coastal belt (TX-LA Gulf, Florida, Mid-Atlantic, NY-NJ harbor, Puget Sound), while FEMA emphasizes inland regions along the Mississippi and Ohio-Tennessee corridors. Population exposure is substantial, with over 52 million people living within 5 miles of FEMA SFHA electric power facilities and 37 million near petroleum assets, underscoring the societal stakes of infrastructure disruption. To our knowledge, this is the first national-scale study to integrate FEMA and NOAA hazard datasets for EI exposure, providing a more comprehensive basis for resilience planning and focusing attention on the sectors and communities at most significant risk.