Abstract

We address the modeling of spatial distribution of coseismic landslides, based on an empirical approach applied to both recent and historical well-documented events. We analyze a dataset of 11 historical and recent normal faulting earthquakes in the Italian Central Apennines. Firstly, making use of a kernel density estimator approach, we calculated the regression between the extent of the maximum area affected by landslides (A; km2) and Mw, on the combined dataset of recent and historic earthquakes: Log A = (1.0397 Mw)–3.9288. Then, for recent earthquakes only, we analyzed the attenuation regression of landslide density (Dens; no. of landslides/km2) with distance from surface fault trace (Dfault; meters): Dens = 0.3661 × exp (− 5.053 Dfault). Historical events, still presenting systematically lower values of landslide densities, can be regressed on the same functional form resulting in a similar factor of attenuation with distance but with a different scaling factor. We thus argue that empirical regressions on historical earthquake-triggered landslides can be successfully exported elsewhere if a well-documented catalog is present and a calibration with several recent events can be done.

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