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

Abstract

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.

Translational momentum of deformable submarine landslides off a slope

“…For real landslides composed of visco-plastic soils, the initial yield strength and remoulding rate of the landslide material are dominating parameters and the involved dynamics can be quite different from that in granular landslides (Kim et al. 2019; Zengaffinen-Morris, Urgeles & Løvholt 2022). Besides, it is also remarked that the initial compaction state of real landslides may be significantly different from that of the artificially prepared landslides in laboratory experiments.…”

“…It has been reported that the soil initial yield strength and remoulding rate dominate the genesis of tsunami (Kim et al. 2019; Zengaffinen-Morris et al 2022). Nevertheless, the yielding and remoulding processes of visco-plastic soils are excluded in the present two-phase model.…”

Coastal Environmental Impact of Geohazards in the Area of the Habibas Islands (Western Algeria, Alboran): Insights from GIS-Analysis and Remote Sensing

“…While the potential of mass movements can cause tsunami waves, not all subaqueous landslides generate tsunami waves as the energy transfer into wave energy is determined by multiple factors such as the water depth of the landslide, its volume, and the slope gradient which directly influence the initial acceleration and maximum velocity [43]- [45]. Depending on the volume of deposits mobilized by the failure event, the depth at which failure occurs, and the acceleration history of the failed mass, submarine landslides can generate tsunami waves at the sea surface that are known to have a local and damaging effect along the coastline, a few tens of kilometers around the location of the source of the landslide by comparison with earthquake-induced tsunamis that can affect a whole basin [46], [47].…”

On the inference of tsunami uncertainties from landslide run-out observations

“…The following key data set are used and made available in this paper: The new landslide database covering the Gulf of Cadiz is available through the following repository (Urgeles et al, 2021). The main outputs from the simulation, that is, those displayed in in Figures 9-12 and 14-19 are available through (Zengaffinen-Morris, 2022). The landslide model BingClaw has been published previously in the AGU journal Geophysical Research Letters, with the availability statement given in (Løvholt et al, 2017).…”