Flood Exposure Assessment of Electrical Substations in Iowa Using Geospatial Service-Area and Influence-Zone Modeling
Abstract
Flooding poses a growing risk to electric substations, yet statewide assessments often fail to connect facility exposure with the spatial context of service territories, communities, built environments, and grid infrastructure. This study develops a data-driven geospatial framework to assess direct and indirect flood impacts on electrical substations across Iowa under 50-, 100-, and 500-year flood scenarios. The framework combines footprint-level inundation analysis with county aggregation, electric service boundaries (ESB), influence zones, demographic and energy-burden indicators, kernel density mapping, and allocation-sensitivity checks. Results show that exposed substations increase from 108 to 226 across the scenarios, with deeper and broader within-site inundation under larger events. Under the 500-year scenario, direct exposure affects 12.83% of substations, but affected service territories contain 66.27% of Iowa’s population, 68.03% of statewide building footprint area, and 46.59% of grid-line length. Influence zone results show that impacted substation-centered zones contain 20.51% of the statewide population and remain above the statewide energy-burden average. Exposure concentrates along eastern and southeastern Iowa near the Mississippi corridor, extends into western and northwestern border transmission corridors, and appears as a strong urban built-environment hotspot in Polk County. Sensitivity results show that building-area exposure is the most transferable indicator between ESB and influence frameworks, while grid-line exposure is more boundary-dependent. The framework identifies priority substations where flood exposure intersects with broader regional consequence potential.
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BibTeX
@misc{duran2026flood,
title = {{Flood Exposure Assessment of Electrical Substations in Iowa Using Geospatial Service-Area and Influence-Zone Modeling}},
author = {Ege Duran and Omer Mermer and Ibrahim Demir},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x5s23c},
url = {https://eartharxiv.org/repository/view/15731/},
note = {CC BY-NC-SA 4.0},
}
RIS
TY - UNPB
TI - Flood Exposure Assessment of Electrical Substations in Iowa Using Geospatial Service-Area and Influence-Zone Modeling
AU - Ege Duran
AU - Omer Mermer
AU - Ibrahim Demir
PY - 2026
DA - 2026/10/24
PB - EarthArXiv
DO - 10.31223/x5s23c
UR - https://eartharxiv.org/repository/view/15731/
AB - Flooding poses a growing risk to electric substations, yet statewide assessments often fail to connect facility exposure with the spatial context of service territories, communities, built environments, and grid infrastructure. This study develops a data-driven geospatial framework to assess direct and indirect flood impacts on electrical substations across Iowa under 50-, 100-, and 500-year flood scenarios. The framework combines footprint-level inundation analysis with county aggregation, electric service boundaries (ESB), influence zones, demographic and energy-burden indicators, kernel density mapping, and allocation-sensitivity checks. Results show that exposed substations increase from 108 to 226 across the scenarios, with deeper and broader within-site inundation under larger events. Under the 500-year scenario, direct exposure affects 12.83% of substations, but affected service territories contain 66.27% of Iowa’s population, 68.03% of statewide building footprint area, and 46.59% of grid-line length. Influence zone results show that impacted substation-centered zones contain 20.51% of the statewide population and remain above the statewide energy-burden average. Exposure concentrates along eastern and southeastern Iowa near the Mississippi corridor, extends into western and northwestern border transmission corridors, and appears as a strong urban built-environment hotspot in Polk County. Sensitivity results show that building-area exposure is the most transferable indicator between ESB and influence frameworks, while grid-line exposure is more boundary-dependent. The framework identifies priority substations where flood exposure intersects with broader regional consequence potential.
ER -