1. Probabilistic tsunami hazard assessment with simulation-based response surfaces.
- Author
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Kotani, T., Tozato, K., Takase, S., Moriguchi, S., Terada, K., Fukutani, Y., Otake, Y., Nojima, K., Sakuraba, M., and Choe, Y.
- Subjects
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TSUNAMI warning systems , *TSUNAMIS , *PROBABILITY density function , *MONTE Carlo method - Abstract
This paper proposes a novel response surface-based method for probabilistic tsunami hazard assessment (PTHA). Although recent advancements in numerical simulation have enabled the accurate characterization of tsunami hazards, the high computational cost of numerical simulation often prohibits its broad application to probabilistic hazard analysis. The proposed method addresses this challenge by constructing the response surface (RS) of a target output using the results of high-fidelity tsunami simulations. The proposed method quantifies uncertainties in key simulation variables and propagates those uncertainties to the target output through the RS in a computationally efficient Monte Carlo simulation (MCS). We illustrate and validate the proposed method through a case study of the tsunami induced by the 2011 Great East Japan earthquake. The case study focuses on Sendai, Ishinomaki, and Kamaishi in Japan as the target locations. The proposed method estimates coastal tsunami heights while considering uncertainties in the fault slip and rake as well as the modeling error associated with the numerical simulation. The MCS allows us to estimate the probability density functions of the tsunami height at the target locations. The proposed method quantifies the contribution of each source of uncertainty to the overall uncertainty in the target output and thus facilitates engineering decision-making. • A novel method for probabilistic tsunami hazard assessment (PTHA) is proposed. • The method constructs a response surface using high-fidelity numerical simulations. • The method propagates uncertainties in key simulation variables to a target output. • The method enables a computationally efficient Monte Carlo simulation for PTHA. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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