The 2018 Anak Krakatoa volcano flank collapse generated a tsunami that impacted the Sunda Strait coastlines. In the absence of a tsunami early warning system, it caused several hundred fatalities. There are ongoing discussions to understand how the failure mechanism of this event affected landslide dynamics and tsunami generation. In this paper, the sensitivity to different failure scenarios on the tsunami generation is investigated through numerical modelling. To this end, the rate of mass release, the landslide volume, the material yield strength, and orientation of the landslide failure plane are varied to shed light on the failure mechanism, landslide evolution, and tsunami generation. We model the landslide dynamics using the depth-averaged viscoplastic flow model BingClaw, coupled with depth-averaged long wave and shallow water type models to simulated tsunami propagation. We are able to match fairly well the observed tsunami surface elevation amplitudes and inundation heights in selected area with the numerical simulations. However, as observed by other authors, discrepancies in simulated and observed arrival times for some of the offshore gauges are found, which raises questions related to the accuracy of the available bathymetry. For this purpose, further sensitivity studies changing the bathymetric depth near the source area are carried out. With this alteration we are also able to match better the arrival times of the waves.

Sediment slumps are known to have generated important tsunamis such as the 1998 Papua New Guinea (PNG) and the 1929 Grand Banks events. Tsunami modellers commonly use solid blocks with short run-out distances to simulate these slumps. While such methods have the obvious advantage of being simple to use, they offer little or no insight into physical processes that drive the events. The importance of rotational slump motion to tsunamigenic potential is demonstrated in this study by employing a viscoplastic landslide model with Herschel–Bulkley rheology. A large number of simulations for different material properties and landslide configurations are carried out to link the slump's deformation, rheology, its translational and rotational kinematics, to its tsunami genesis. The yield strength of the slump is shown to be the primary material property that determines the tsunami genesis. This viscoplastic model is further employed to simulate the 1929 Grand Banks tsunami using updated geological source information. The results of this case study suggest that the viscoplastic model can be used to simulate complex slump-induced tsunami. The simulations of the 1929 Grand Banks event also indicate that a pure slump mechanism is more tsunamigenic than a corresponding translational landslide mechanism.

<p>The 2018 Anak Krakatoa volcano flank collapse and tsunami caused several hundred fatalities. There was no early warning system in place for the landslide triggered tsunami, and there is a lack in understanding on how the failure mechanism affected landslide dynamics and tsunami generation, which we focus on in this study. While researchers previously have modelled the collapse as an instantaneous release, we here illuminate how different landslide failure scenarios, including a gradually released flank failure, influence the tsunami generation. We simulate the material movement by using a viscoplastic flow model with Herschel-Bulkley rheology and we employ a depth-averaged model to both the landslide and the tsunami propagation. A sensitivity study to the gradual mass release, total release volume, the material yield strength, the remoulding coefficient, and landslide directivity is used to shed light on the tsunami generation. Our analysis indicates that an instantaneous mass release in 125 degree SW direction fits the observed waveforms at coastal gauge stations best. In our simulations, we observe, as many other authors, discrepancies between simulated and observed arrival times and wave periods offshore Sumatra. Hence, we have also investigated sensitivity to the bathymetric depth by varying the water depth in areas near the source. Finally, we simulate the tsunami inundation at two coastal sites in southwestern Java using open-source topographic data. Given the limitations in the topographic data, a reasonably good agreement between the simulations and observations are obtained.</p>