Efficient probabilistic tsunami inundation prediction considering random tsunami sources and failure probability of seawalls

Abstract Probabilistic tsunami inundation assessment ordinarily requires many inundation simulations that consider various uncertainties; thus, the computational cost is very high. In recent years, active research has been conducted to reduce the computational cost. In this study, we successfully reduced the number of random tsunami sources to 20% of the original numbers by applying proper orthogonal decomposition (POD) to tsunami inundation depth distributions obtained from random tsunami sources. Additionally, we stochastically treated the failure degree of seawalls and incorporated its impact into the evaluation model for tsunami inundation hazard because the failure degree of seawalls has a significant impact on the tsunami inundation depth assessment for land areas. Although the randomness of the slip distribution in tsunami sources has been studied extensively in the past, the idea of simultaneously modelling the failure degree of seawalls is an outstanding feature of this study. Finally, we developed tsunami inundation distribution maps to represent the probability of occurrence of inundation depth for the next 50 years and 10 years by using a number of tsunami inundation distributions that consider the randomness of the tsunami sources and the failure probability of the seawalls.