A hurricane surge risk assessment framework using the joint probability method and surge response functions

Hurricane surge events have caused devastating damage in active-hurricane areas all over the world. The ability to predict surge elevations and to use this information for damage estimation is fundamental for saving lives and protecting property. In this study, we developed a framework for evaluating hurricane flood risk and identifying areas that are more prone to them. The approach is based on the joint probability method with optimal sampling (JPM-OS) using surge response functions (SRFs) (JPM-OS-SRF). Derived from a discrete set of high-fidelity storm surge simulations, SRFs are non-dimensional, physics-based empirical equations with an algebraic form, used to rapidly estimate surge as a function of hurricane parameters (i.e., central pressure, radius, forward speed, approach angle and landfall location). The advantage of an SRF-based approach is that a continuum of storm scenarios can be efficiently evaluated and used to estimate continuous probability density functions for surge extremes, producing more statistically stable surge hazard assessments without adding measurably to epistemic uncertainty. SRFs were developed along the coastline and then used to estimate maximum surge elevations with respect to a set of hurricane parameters. Integrating information such as ground elevation, property value and population with the JPM-OS-SRF allows quantification of storm surge-induced hazard impacts over the continuum of storm possibilities, yielding a framework to create the following risk-based products, which can be used to assist in hurricane hazard management and decision making: (1) expected annual loss maps; (2) flood damage versus return period relationships; and (3) affected business (e.g., number of business, number of employees) versus return period relationships. By employing several simplifying assumptions, the framework is demonstrated at three northern Gulf of Mexico study sites exhibiting similar surge hazard exposure. The framework results reveal Gulfport, MS, USA is at relatively more risk of economic loss than Corpus Christi, TX, USA, and Panama City, FL, USA. Note that economic processes are complex and very interrelated to most other human activities. Our intention here is to present a methodology to quantify the flood damage (i.e., infrastructure economic loss, number of businesses affected, number of employees in these affected businesses and sales volume in these affected businesses) but not to discuss the complex interactions of these damages with other economic activities and recovery plans.