Abstract
This study presents a rigorous computational framework for visualizing uncertainty of tsunami hazard and risk assessment. The methodology consists of three modules: (i) earthquake source characterization and stochastic simulation of slip distribution, (ii) tsunami propagation and inundation, and (iii) tsunami damage assessment and loss estimation. It takes into account numerous stochastic tsunami scenarios to evaluate the uncertainty propagation of earthquake source characteristics in probabilistic tsunami risk analysis. An extensive Monte Carlo tsunami inundation simulation is implemented for the 2011 Tohoku tsunami (focusing upon on Rikuzentakata along the Tohoku coast of Japan) using 726 stochastic slip models derived from eleven inverted source models. By integrating the tsunami hazard results with empirical tsunami fragility functions, probabilistic tsunami risk analysis and loss estimation are carried out; outputs from the analyses are displayed using various visualization methods. The developed framework is comprehensive, and can provide valuable insights in promoting proactive tsunami risk management and in improving emergency response capability.
Highlights
An extremely large subduction earthquake triggers massive tsunamis, which can destroy coastal cities and towns completely
This paper proposed a computational framework of tsunami hazard and risk assessments for coastal areas by emphasizing the importance of uncertainty modeling and visualization
The improved method for tsunami source characterization generated hundreds of stochastic random-field slip distributions to quantify the uncertainty of tsunami hazard parameters
Summary
An extremely large subduction earthquake triggers massive tsunamis, which can destroy coastal cities and towns completely. This study presents a rigorous approach for visualizing uncertain tsunami hazard/risk analysis outputs that are obtained from extensive Monte Carlo tsunami simulations by taking into account a wide range of earthquake source characteristics. A computational framework of tsunami hazard and risk assessments for coastal cities and towns is presented based on Monte Carlo tsunami inundation simulations (Goda et al 2015) and empirical tsunami fragility models (Suppasri et al 2013). A novel aspect of this study is that quantitative tsunami hazard and risk assessments are carried out by accounting for stochastic earthquake source properties and are presented with various visualization methods for improved tsunami risk mitigation actions and risk communications. A typical IM is the inundation depth, which is often used as an input parameter for tsunami fragility modeling (i.e. fDS|IM). fIM|EQS is evaluated through numerical evaluations of governing equations for tsunami waves and inundation/run-up
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