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Compound flooding ( CF ) events, driven by coincident/concurrent and mutually reinforcing factors such as heavy rainfall, storm surges, and river discharge, pose severe threats to coastal communities around the Globe. Moreover, the exacerbating influence of climate change and sea-level rise further amplifies these risks. This study delves into the complex and multifaceted issue of compound coastal flooding in two freshwater-influenced systems on the Gulf Coast of the United States – Southeast Texas and South Alabama. We first conduct a robust statistical analysis to evaluate the significance of non-stationarity, multi-dimensionality, and non-linearity of interactions among various drivers of CF . Second, to assess the extent to which current flood resilience policies and guidelines account for these characteristics of CF events, we perform a critical review of existing policy documents. The results of the statistical analysis reveal significant compounding and shifts in the statistics of flood drivers that emphasize the pressing need for a multi-mechanism, non-stationary approach to flood hazard assessment. We also found an evident lack of appropriate language/recommendation in policy documents of solid tools that systematically take non-stationarity, multi-dimensionality, and non-linearity of CF into account. By identifying the gaps between current policy measures and the detected complexities of CF , we seek to provide insights that can inform more effective flood resilience policies and design guidelines. Through this robust analysis, we aspire to bridge the divide between research and policy.
Lewis et al. (Thu,) studied this question.