Ferdinand Diermanse, Kathryn Roscoe, Maarten van Ormondt, Tim Leijnse, Gundula Winter, and Panagiotis Athanasiou, 2023. “Probabilistic compound flood hazard analysis for coastal risk assessment: A case study in Charleston, South Carolina”, Shore & Beach, 91(2), 9-18.
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Probabilistic compound flood hazard analysis for coastal risk assessment: A case study in Charleston, South Carolina
Ferdinand Diermanse (1), Kathryn Roscoe (1), Maarten van Ormondt (2), Tim Leijnse (1), Gundula Winter (1), and Panagiotis Athanasiou (1)
1) Deltares, Delft, Boussinesqweg 1, The Netherlands
2) Deltares USA, 8601 Georgia Avenue 508, Silver Springs, MD, USA
Coastal communities are susceptible to flooding due to flood drivers such as high tides, surge, waves, rainfall, and river discharges. Recent hurricanes such as Harvey, Florence, and Ian brought devastating impacts from combinations of high rainfall and storm surge, highlighting the need for resilience and adaptation planning to consider compound flood events when evaluating options to reduce future flood risk. Flood risk assessments often focus on a single flood driver (e.g. storm surge) due to the complexity of accounting for compound flood drivers. However, neglecting these compound flood effects can grossly underestimate the total flood risk. A probabilistic compound flood hazard analysis considers all compound events that lead to flooding, estimates their joint probabilities, simulates the flood response, and applies a probabilistic computation technique to translate flood responses and probabilities into probabilistic flood maps (such as the 100-year flood map). Probabilistic flood maps based on compound events can be used to assess risk more accurately for current and future conditions, with and without additional adaptation measures. In this paper we present an example of a probabilistic compound flood hazard analysis for the city of Charleston, South Carolina, considering tide, surge, and rainfall, for both hurricane and non-hurricane events. Charleston is regularly confronted with compound flood events, which are expected to worsen with sea level rise and more frequent tropical storms. Starting with an initial set of over 1,000 synthetic compound events, selection techniques described in the paper led to a final set of 207 compound events. The fast compound flood model SFINCS simulated the flood response for each event and, using numerical integration, compound flood return-period maps were created for Charleston, under current and future sea level rise conditions.