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Probabilistic Landslide Tsunami Estimation in the Makassar Strait, Indonesia, Using Statistical Emulation

Dignan, Jack; Hayward, Matthew W; Salmanidou, Dimitra; Heidarzadeh, Mohammad; Guillas, Serge; (2023) Probabilistic Landslide Tsunami Estimation in the Makassar Strait, Indonesia, Using Statistical Emulation. Earth and Space Science , 10 (8) , Article e2023EA002951. 10.1029/2023ea002951. Green open access

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Abstract

This paper presents a significant advancement in the understanding of tsunamigenic landslide hazard across the length of the Makassar Strait in Indonesia. We use statistical emulation across the length of the continental slope to conduct a probabilistic assessment of tsunami hazard on a regional scale, across 14 virtual coastal gauges. Focusing on the potential maximum wave amplitudes (distance between the wave crest and the still‐water level) from possible tsunamigenic landslide events, we generate predictions from Gaussian Process emulators fitted to input‐outputs from 50 training scenarios. We show that the most probable maximum wave amplitudes in the majority of gauges are between 1 and 5 m, with the maximum predicted amplitudes reaching values of up to 10 m on the eastern coast, and up to 50 m on the western coast. We also explore the potential use of Gaussian multivariate copulas to sample emulator prediction input values to create a more realistic distribution of volumes along the continental slope. The novel use of statistical emulation across a whole slope enables the probabilistic assessment of tsunami hazard due to landslides on a regional scale. This area is of key interest to Indonesia since the new capital will be established in the East Kalimantan region on the western side of the Makassar Strait.

Type: Article
Title: Probabilistic Landslide Tsunami Estimation in the Makassar Strait, Indonesia, Using Statistical Emulation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1029/2023ea002951
Publisher version: https://doi.org/10.1029/2023EA002951
Language: English
Additional information: © 2023 The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10174929
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