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.
Read the full article in Proceedings of the National Academy of Sciences of the United States of America.