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This content will become publicly available on December 20, 2023

Title: Real‐Time Prediction of Alongshore Near‐Field Tsunami Runup Distribution From Heterogeneous Earthquake Slip Distribution

Real‐time tsunami prediction is necessary for tsunami forecasting. Although tsunami forecasting based on a precomputed tsunami simulation database is fast, it is difficult to respond to earthquakes that are not in the database. As the computation speed increases, various alternatives based on physics‐based models have been proposed. However, physics‐based models still require several minutes to simulate tsunamis and can have numerical stability issues that potentially make them unreliable for use in forecasting—particularly in the case of near‐field tsunamis. This paper presents a data‐driven model called the tsunami runup response function for finite faults (TRRF‐FF) model that can predict alongshore near‐field tsunami runup distribution from heterogeneous earthquake slip distribution in less than a second. Once the TRRF‐FF model is trained and calibrated based on a discrete set of tsunami simulations, the TRRF‐FF model can predict alongshore tsunami runup distribution from any combination of finite fault parameters. The TRRF‐FF model treats the leading‐order contribution and the residual part of the alongshore tsunami runup distribution separately. The interaction between finite faults is modeled based on the leading‐order alongshore tsunami runup distribution. We validated the TRRF‐FF modeling approach with more than 200 synthetic tsunami scenarios in eastern Japan. We further explored the performance more » of the TRRF‐FF model by applying it to the 2011 Tohoku (Japan) tsunami event. The results show that the TRRF‐FF model is more flexible, occupies much less storage space than a precomputed tsunami simulation database, and is more rapid and reliable than real‐time physics‐based numerical simulation.

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Award ID(s):
1630099 1735139
Publication Date:
Journal Name:
Journal of Geophysical Research: Oceans
DOI PREFIX: 10.1029
Sponsoring Org:
National Science Foundation
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