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

Author

Listed:
  • Jun-Whan Lee

    (Virginia Tech)

  • Jennifer L. Irish

    (Virginia Tech
    Virginia Tech)

  • Robert Weiss

    (Virginia Tech
    Virginia Tech)

Abstract

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: $$

Suggested Citation

  • Jun-Whan Lee & Jennifer L. Irish & Robert Weiss, 2020. "Rapid prediction of alongshore run-up distribution from near-field tsunamis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1157-1180, November.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:2:d:10.1007_s11069-020-04209-z
    DOI: 10.1007/s11069-020-04209-z
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    References listed on IDEAS

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    1. Hyoungsu Park & Daniel T. Cox & Andre R. Barbosa, 2018. "Probabilistic Tsunami Hazard Assessment (PTHA) for resilience assessment of a coastal community," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(3), pages 1117-1139, December.
    2. Carl Harbitz & Finn Løvholt & Hilmar Bungum, 2014. "Submarine landslide tsunamis: how extreme and how likely?," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(3), pages 1341-1374, July.
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