The Al-Borani submarine landslide and associated tsunami. A modelling approach

Abstract

The key goals to studying submarine landslides and associated tsunamis are to better assess the magnitude information of palaeo-tsunamis and to contribute to assessing future tsunami risks. The numerical modelling of submarine landslides and the tsunamis thus generated comprises important interdisciplinary research that requires knowledge of both geology and numerical modelling. Models are capable of delineating the time evolution of tsunami hydrodynamics, sediment transport, and the resulting morphological changes associated with deposition. To advance towards the ultimate goal of improved tsunami risk assessment, modellers and geologists need to develop an in-depth mutual understanding of the advantages, limitations, and uncertainties in both numerical modelling and geological records. In this work, seafloor features related to former submarine landslides in the Alboran Sea basin have been identified through multibeam bathymetry data and high- to very high-resolution seismic profiles. The mathematical modelling and hindcasting have been performed through numerical simulation of a hypothetical submarine landslide and the associated tsunami that could have originated one of the submarine landslides identified. This system, on the southern Alboran Ridge slope, is currently reworked by turbidite processes, forming a submarine canyon-sedimentary fan system known as the Al-Borani System. The HySEA numerical model simulates the submarine landslide triggering the tsunami and the water mass evolution, wave propagation, and the final penetration of the tsunami waves onto the coast, reproducing initial and subsequent tsunami wave impacts by means of a single coupled numerical model. This numerical model allows an analysis of the influence of basin morphology on the tsunami propagation features, such as shape and propagation patterns, speed or wave amplitude and, finally, its impact on the coast (in this case South Iberia and North Africa). This model can also be used as a prediction tool for the simulation of potential landslides, many of which generate tsunamis. Monitoring of critical areas, where landslides are more probable, and modelling their consequences will allow a choice of the appropriate mitigation strategies. Therefore, monitoring and modelling are areas of key scientific and socio-economic interests. © 2015 Elsevier B.V.