Rapid prediction of alongshore run-up distribution from near-field tsunamis

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1007/s11069-020-04209-z. This is version 1 of this Preprint.

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Jun-Whan Lee , Jennifer Irish, Robert Weiss 


Rapid prediction of the spatial distribution of the run-up from near- field tsunamis is critically important for tsunami hazard characterization. Even though significant advances have been made over the last decade, physics- based numerical models are still computationally intensive. Here, we present a response surface methodology (RSM)-based model called the tsunami run-up response function (TRRF). Derived from a discrete set of tsunami simulations, TRRF can produce a rapid prediction of a near-field tsunami run-up distribution that takes into account the influence of variable local topographic and bathymetric characteristics in a given region. This new method reduces the number of simulations required to build an RSM model by separately modeling the leading order contribution and the residual part of the tsunami run-up distribution. Using the northern region of Puerto Rico as a case study, we investigated the performance (accuracy, computational time) of the TRRF. The results reveal that the TRRF achieves reliable prediction while reducing the prediction time by six orders of magnitude (computational time: < 1 second per earthquake).




Engineering, Physical Sciences and Mathematics


Puerto Rico, Run-up, Response surface methodology


Published: 2021-07-28 02:52

Last Updated: 2021-07-28 06:52


CC BY Attribution 4.0 International