Modeling the Sources of the 2018 Palu, Indonesia, Tsunami Using Videos From Social Media
Abstract
The 2018 Palu tsunami contributed significantly to the devastation caused by the associated MW 7.5 earthquake. This began a debate about how the moderate size earthquake triggered such a large tsunami within Palu Bay, with runups of more than 10Â m. The possibility of a large component of vertical coseismic deformation and submarine landslides have been considered as potential explanations. However, scarce instrumental data have made it difficult to resolve the potential contributions from either type of source. We use tsunami waveforms derived from social media videos in Palu Bay to model the possible sources of the tsunami. We invert InSAR data with different fault geometries and use the resulting seafloor displacements to simulate tsunamis. The coseismic sources alone cannot match both the video-derived time histories and surveyed runups. Then we conduct a tsunami source inversion using the video-derived time histories and a tide gauge record as inputs. We specify hypothetical landslide locations and solve for initial tsunami elevation. Our results, validated with surveyed runups, show that a limited number of landslides in southern Palu Bay are sufficient to explain the tsunami data. The Palu tsunami highlights the difficulty in accurately capturing with tide gauges the amplitude and timing of short period waves that can have large impacts at the coast. The proximity of landslides to locations of high fault slip also suggests that tsunami hazard assessment in strike-slip environments should include triggered landslides, especially for locations where the coastline morphology is strongly linked to fault geometry.
Más información
| Título según SCOPUS: | Modeling the Sources of the 2018 Palu, Indonesia, Tsunami Using Videos From Social Media |
| Título de la Revista: | Journal of Geophysical Research: Solid Earth |
| Volumen: | 125 |
| Número: | 3 |
| Editorial: | John Wiley and Sons Inc. |
| Fecha de publicación: | 2020 |
| Idioma: | English |
| DOI: |
10.1029/2019JB018675 |
| Notas: | SCOPUS |