Rheology and bathymetry effects captured by a multilayer landslide-tsunami model
Résumé
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 4 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.
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