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Flooding risk results from complex interactions between hydrological hazards (e.g., riverine inundation during periods of heavy rainfall), exposure, vulnerability (e.g., the potential for structural damage or loss of life), and resilience (how well we recover, learn from, and adapt to past floods). Building on recent coupled conceptualizations of these complex interactions, we characterize human–flood interactions (collective memory and risk-enduring attitude) at a more comprehensive scale than has been attempted to date across 50 US metropolitan statistical areas with a sociohydrologic (SH) model calibrated with accessible local data (historical records of annual peak streamflow, flood insurance loss claims, active insurance policy records, and population density). A cluster analysis on calibrated SH model parameter sets for metropolitan areas identified two dominant behaviors: 1) “risk-enduring” cities with lower flooding defenses and longer memory of past flood loss events and 2) “risk-averse” cities with higher flooding defenses and reduced memory of past flooding. These divergent behaviors correlated with differences in local stream flashiness indices (i.e., the frequency and rapidity of daily changes in streamflow), maximum dam heights, and the proportion of White to non-White residents in US metropolitan areas. Risk-averse cities tended to exist within regions characterized by flashier streamflow conditions, larger dams, and larger proportions of White residents. Our research supports the development of SH models in urban metropolitan areas and the design of risk management strategies that consider both demographically heterogeneous populations, changing flood defenses, and temporal changes in community risk perceptions and tolerance.
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This content will become publicly available on July 4, 2026
Building Flood Resilience in West Virginia through Community-Engaged Research
Riverine flooding events are expected to become increasingly severe in the coming decades due to climate change, resulting in an urgent need to build flood resilience in underserved areas of the country. West Virginia has some of the highest risk of flooding in the United States, which is often compounded by aging infrastructure and high levels of socioeconomic vulnerability. In June 2016, one storm caused flooding that killed twenty-three people, destroyed or damaged thousands of homes and businesses, and caused $1 billion in damages across the state. Some of the most affected towns have yet to fully recover. This mixed-methods community-engaged research project was the first systematic investigation of lessons learned from the 2016 floods in Greenbrier County, West Virginia, a place devastated by this disaster. Using a county-wide survey, focus groups, and participatory GIS (PGIS), this project resulted in the creation of community-informed geospatial products to communicate flood risk, as well as a set of community-identified recommendations for increasing resilience to future flood disasters. Findings offer critical insights for more effective flood response and recovery in West Virginia and other rural areas of the United States with high riverine flood risk.
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- PAR ID:
- 10642767
- Publisher / Repository:
- Routledge
- Date Published:
- Journal Name:
- The Professional Geographer
- Volume:
- 77
- Issue:
- 4
- ISSN:
- 0033-0124
- Page Range / eLocation ID:
- 430 to 444
- Subject(s) / Keyword(s):
- community-engaged research, flood risk, natural hazards, participatory GIS, resilience
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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