On the use of statistical analysis to understand submarine landslide processes and assess their hazard

Because of their inaccessibility, submarine landslides are typically studied individually and at great effort and expense to provide knowledge of the specific site conditions where these landslides occur. Statistical analysis of submarine landslide scars can offer generalized perspectives on the processes that initiate submarine landslides and can help toward hazard assessment in areas that have not been studied in detail. The following review discusses more than a decade of development of statistical approaches to studying submarine landslides. Landslides were previously viewed together with other natural hazards, such as earthquakes and fires, as a phenomenon whose size distribution obeys an inverse power law. Inverse power law distributions are the result of self-organized avalanche processes, in which the final hazard size cannot be predicted at the onset of the disturbance. We find that volume and area distributions of submarine landslides along the U.S. Atlantic continental slope and along nine other margins worldwide do not follow an inverse power law. Rigorous statistical tests of several different probability distribution models indicate that the lognormal model is most appropriate for these siliciclastic environments. Lognormal distributions can be simulated by assuming that the area of slope failure depends on earthquake magnitude, in other words, failure occurs simultaneously over the area affected by horizontal ground shaking and does not cascade from nucleating sources. Therefore, the maximum landslide size can be predicted from the earthquake magnitude and the distance from the rupturing fault. Moreover, earthquakes