On the Inference of Tsunami Uncertainties From Landslide Run-Out Observations

Probabilistic tsunami hazard analysis (PTHA) due to submarine landslides is much less developed than PTHA for earthquake sources. This is partly because of less constrained data available for quantifying source probability, and partly because of the lack of knowledge related to the tsunami generation process due to landslide dynamics. This study provides a basis for estimating the uncertainty related to landslide dynamics for PTHA from submarine landslides based on a new landslide database in the Gulf of Cadiz. The establishment of this new database is described herein. We use submarine landslide run-out statistics from this database to calibrate landslide parameters and related uncertainties employing the cohesive landslide model BingClaw. In turn, coupling the landslide motion to tsunami genesis is performed in order to characterize the inferred tsunami uncertainties. Important parameters that can explain the large tsunami uncertainties are the initial water depth of the landslide, the slope, the landslide volume, and the initial yield strength of the landslide material. Kinematic properties such as the initial landslide acceleration or the Froude number are found to strongly correlate with the tsunami-genesis. In this study, we show how matching numerical landslide models with observed run-out from past events in the field can give information about the uncertainty in their tsunami-genic strength. This can in turn be applied in future PTHA for spanning uncertainty ranges due to the landslide dynamics on tsunami-genesis, constrained by landslide run-out data.

Automated summary

This study establishes a new database in the Gulf of Cadiz to estimate the uncertainty related to submarine landslide dynamics for Probabilistic Tsunami Hazard Analysis (PTHA). By calibrating landslide parameters and uncertainties using the newly acquired data, the research aims to understand the correlation between landslide motion and tsunami genesis, highlighting key parameters that influence tsunami uncertainties.