A new generation of tsunami inundation maps of Chilean cities: tsunami source database and probabilistic hazard analysis

Abstract

ABSTRACT Tsunami inundation maps are crucial for understanding the impact of tsunamis and planning mitigation measures. Our research focuses on creating a database of stochastic tsunami scenarios along the Chilean subduction zone and probabilistic inundation maps for 11 coastal cities. We divided the Chile-Perú subduction zone into four seismic segments based on historical seismicity. Stochastic rupture scenarios, ranging from 8.0 to 9.6 magnitudes, were generated using the Karhunen-Loeve expansion. The Stochastic Reduced Order Model (SROM) helped select representative tsunami scenarios for each segment and magnitude bin. We then used the NEOWAVE model to simulate these scenarios to an inundation level, creating probabilistic tsunami maps for various return periods. Our findings reveal that local geography significantly influences tsunami inundation, with some areas facing high inundation risks while others experience minimal impacts. As a result, a uniform planning and design criterion across the entire country is not advisable; site-specific studies are necessary. These probabilistic scenarios can provide tailored solutions for different Chilean coastal cities, enhancing their resilience. Additionally, this research marks the first comprehensive probabilistic tsunami hazard analysis for the Chilean coast, considering multiple seismic sources, marking a crucial step toward full tsunami risk assessment for coastal communities.