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

Author:

Fukutani YoORCID,Yasuda TomohiroORCID,Yamanaka RyoichiORCID

Abstract

AbstractProbabilistic 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, the number of random tsunami sources was reduced to 20% of the original number by applying proper orthogonal decomposition (POD) to tsunami inundation depth distributions obtained from random tsunami sources. Additionally, the failure degree of seawalls was stochastically assessed, and its impact was incorporated into the evaluation model for tsunami inundation hazards because this factor 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 a novel feature of this study. Finally, tsunami inundation distribution maps were developed to represent the probability of occurrence of different inundation depths 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.

Funder

JSPS KAKENHI

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine learning emulation of high resolution inundation maps;Geophysical Journal International;2024-04-24

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