Hurricane Scenario Generation for Uncertainty Modeling of Coastal and Inland Flooding - Kim, Kyoung Yoon; Wu, Wen-Ying; Kutanoglu, Erhan; Hasenbein, John J.; Yang, Zong-Liang (Frontiers in Climate, 2021)
Hurricanes that bring heavy rain and storm surge particularly may lead catastrophic flooding to both inland and coastal regions. In an effort to contribute to uncertainty quantification of impending flood events, we propose a probabilistic scenario generation scheme for hurricane flooding using state-of-art hydrological models to forecast both inland and coastal flooding. The hurricane scenario generation scheme incorporates locational uncertainty in hurricane landfall locations. Using a stratified sampling method, we generate multiple landfall locations for a forecasted hurricane and create flooding scenarios by shifting meteorological inputs such as precipitation. By combining inland and coastal flooding models, we seek to provide a comprehensive understanding of potential flood scenarios from an impending hurricane. To demonstrate the modeling approach, we use real-world data from the Southeast Texas region in our case study.