Extending the Joint Probability Method to Compound Flooding: Statistical Delineation of Transition Zones and Design Event Selection
Mark S. Bartlett, Nathan Geldner, Zach Cobell, Luis Partida, Ovel Diaz, David R. Johnson, Hanbeen Kim, Brett McMann, Gabriele Villarini, Shubra Misra, Hugh J. Roberts, Muthukumar Narayanaswamy

TL;DR
This paper extends the Joint Probability Method to include hydrologic factors, enabling probabilistic assessment of compound flooding from storms and rainfall, with applications to delineating transition zones and selecting design events.
Contribution
The paper introduces a novel extension of the JPM to incorporate hydrologic processes, filling a critical gap in compound flood risk quantification.
Findings
CFTZ area more than doubles previous estimates
Compound interactions increase flood depths by up to 2.25 feet
Method provides a probabilistic basis for flood risk assessment
Abstract
Compound flooding from the combined effects of extreme storm surge, rainfall, and river flows poses significant risks to infrastructure and communities -- as demonstrated by hurricanes Isaac and Harvey. Yet, existing methods to quantify compound flood risk lack a unified probabilistic basis. Copula-based models capture the co-occurrence of flood drivers but not the likelihood of the flood response, while coupled hydrodynamic models simulate interactions but lack a probabilistic characterization of compound flood extremes. The Joint Probability Method (JPM), the foundation of coastal surge risk analysis, has never been formally extended to incorporate hydrologic drivers -- leaving a critical gap in quantifying compound flood risk and the statistical structure of compound flood transition zones (CFTZs). Here, we extend the JPM theory to hydrologic processes for quantifying the likelihood…
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Taxonomy
TopicsTropical and Extratropical Cyclones Research · Flood Risk Assessment and Management · Coastal wetland ecosystem dynamics
