Bayesian optimization of submarine landslide parameters for the 2020 Alaska Sand Point tsunami

In the Alaskan subduction zone, a magnitude 7.6 earthquake in October 2020 generated a tsunami substantially larger than predicted by the earthquake magnitude alone. Here, we hypothesize that this additional source—a submarine landslide—contributed to this discrepancy. We used Bayesian optimization to efficiently estimate landslide parameters that reproduce the observed tsunami. The ensemble of best-fitting solutions yielded a thickness of 9.5–11.5 m, width of 108–140 km, length of 18–33 km, and delay time of 262–319 s. The relatively small thickness suggests a shallow landslide occurring within weak seafloor sediments. These results support the interpretation that a submarine landslide contributed to the non-seismic component of the tsunami.

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Publication Details

Journal
Earth Planets and Space
Published
2026-09-29
DOI
https://doi.org/10.1186/s40623-026-02543-3
Primary Topic
earthquake and tectonic studies
Type
article
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Bayesian optimization of submarine landslide parameters for the 2020 Alaska Sand Point tsunami

Toshitaka Baba, Yasuhiko Igarashi, Akino Naitoh
Earth Planets and Space
earthquake and tectonic studies
article

Bayesian optimization of submarine landslide parameters for the 2020 Alaska Sand Point tsunami

Toshitaka Baba, Yasuhiko Igarashi, Akino Naitoh
article en

Abstract

In the Alaskan subduction zone, a magnitude 7.6 earthquake in October 2020 generated a tsunami substantially larger than predicted by the earthquake magnitude alone. Here, we hypothesize that this additional source—a submarine landslide—contributed to this discrepancy. We used Bayesian optimization to efficiently estimate landslide parameters that reproduce the observed tsunami. The ensemble of best-fitting solutions yielded a thickness of 9.5–11.5 m, width of 108–140 km, length of 18–33 km, and delay time of 262–319 s. The relatively small thickness suggests a shallow landslide occurring within weak seafloor sediments. These results support the interpretation that a submarine landslide contributed to the non-seismic component of the tsunami.

Earth Planets and SpaceVol. 78(1)
University of Tsukuba (JP), Tokushima University (JP)
Life below water
Openalex Percentile: Top 14%
earthquake and tectonic studies
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Bayesian optimization of submarine landslide parameters for the 2020 Alaska Sand Point tsunami — Toshitaka Baba, Yasuhiko Igarashi, et al. · Earth Planets and Space (2026) | TGRS Research Map | TGRS