Rheology and bathymetry effects captured by a multilayer landslide-tsunami model

SUMMARY Numerical models are a powerful tool for understanding and predicting the impact of landslide-generated tsunamis. We use here the HySEA code which incorporates a multilayer structure and non-hydrostatic pressure to simulate the tsunami generated by a potential submarine landslide located offshore of the Mayotte island. The island is surrounded by a lagoon and steep slopes weakened by the 2018 seismo-volcanic crisis. The influence of the input parameters and of the model assumptions is shown to change by a factor 2 the predicted maximum water free surface elevation, velocity and maximum inundation depth. This demonstrates the need of using numerical models for building local scaling laws to relate tsunami and landslide properties. Our results highlight the necessity of incorporating high-resolution bathymetry, in-depth variations through multilayer modeling and relevant landslide rheology to accurately predict tsunami impact. In case of strong topography variations as in Mayotte, using four layers seems to be a good compromise between accuracy and computational cost. Accounting for these effects would enable to refine hazard maps by identifying safe and high-risk coastal zones and to improve wave arrival time estimates, thus reducing tsunami-related risks in regions like Mayotte.

Authors

Institutions

Publication Details

Journal
Geophysical Journal International
Published
2025-06-27
DOI
https://doi.org/10.1093/gji/ggaf232
Citations
3
Primary Topic
Geological formations and processes
Type
article
Field-Weighted Citation Impact
5.01

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rheology and bathymetry effects captured by a multilayer landslide-tsunami model

Manuel J. Castro, Annabelle Moatty, David M. Silver, A. Mangeney et al.
3 citations
Geophysical Journal International
Geological formations and processes
5.01
article

Rheology and bathymetry effects captured by a multilayer landslide-tsunami model

Manuel J. Castro, Annabelle Moatty, David M. Silver, A. Mangeney, Pablo Poulain, Rodrigo Pedreros, Finn Løvholt, Alexis Marbœuf, Enrique D. Fernández-Nieto, Anne Le Friant, Anne Lemoine, Albert Lucas
article en
3 citations

Abstract

SUMMARY Numerical models are a powerful tool for understanding and predicting the impact of landslide-generated tsunamis. We use here the HySEA code which incorporates a multilayer structure and non-hydrostatic pressure to simulate the tsunami generated by a potential submarine landslide located offshore of the Mayotte island. The island is surrounded by a lagoon and steep slopes weakened by the 2018 seismo-volcanic crisis. The influence of the input parameters and of the model assumptions is shown to change by a factor 2 the predicted maximum water free surface elevation, velocity and maximum inundation depth. This demonstrates the need of using numerical models for building local scaling laws to relate tsunami and landslide properties. Our results highlight the necessity of incorporating high-resolution bathymetry, in-depth variations through multilayer modeling and relevant landslide rheology to accurately predict tsunami impact. In case of strong topography variations as in Mayotte, using four layers seems to be a good compromise between accuracy and computational cost. Accounting for these effects would enable to refine hazard maps by identifying safe and high-risk coastal zones and to improve wave arrival time estimates, thus reducing tsunami-related risks in regions like Mayotte.

Geophysical Journal InternationalVol. 242(3)
Norwegian Geotechnical Institute (NO), Natural Resources Conservation Service (US), Centre National de la Recherche Scientifique (FR), Institut de physique du globe de Paris (FR), Université Paris-Est Créteil (FR), Université Paris Cité (FR), Laboratoire de Géographie Physique (FR), Bureau de Recherches Géologiques et Minières (FR), Université Paris 1 Panthéon-Sorbonne (FR), Universidad de Sevilla (ES), Universidad de Málaga (ES)
European Commission, Agence Nationale de la Recherche, Bureau de Recherches Géologiques et Minières, Junta de Andalucía, HORIZON EUROPE Framework Programme, European Regional Development Fund, Agencia Estatal de Investigación, Labex UnivEarthS
Life below water
Openalex Percentile: Top 5%
Geological formations and processes
5.01
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.