Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269;
The National Socio-Environmental Synthesis Center, Annapolis, MD 21480.
Proc Natl Acad Sci U S A. 2021 Mar 30;118(13). doi: 10.1073/pnas.2016839118.
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.
洪水风险是水文灾害(如暴雨期间的河流泛滥)、暴露度、脆弱性(如结构损坏或生命损失的可能性)和恢复力(我们从过去的洪水事件中恢复、学习和适应的程度)之间复杂相互作用的结果。基于这些复杂相互作用的最新综合概念,我们在比以往更全面的范围内描述了人类与洪水的相互作用(集体记忆和风险承受态度),涉及 50 个美国大都市区统计区,采用与可获取的本地数据(年度峰值流量的历史记录、洪水保险损失索赔、有效保险政策记录和人口密度)相结合的社会水文学(SH)模型进行了分析。对大都市区校准的 SH 模型参数集进行聚类分析,确定了两种主要行为:1)“风险承受”城市,其洪水防御能力较低,对过去洪水损失事件的记忆较长;2)“风险规避”城市,其洪水防御能力较高,对过去洪水的记忆较少。这些不同的行为与当地河流湍急指数(即流量的日变化频率和速度)、最大水坝高度以及美国大都市区的白人和非白人居民比例的差异相关。风险规避型城市往往存在于以湍急河流水文条件、更大的水坝和更多白人居民为特征的地区。我们的研究支持在城市大都市区开发 SH 模型,并设计风险管理策略,既要考虑人口结构多样化的群体,也要考虑不断变化的洪水防御措施,以及社区风险认知和容忍度的时间变化。