Assessment of attenuation regressions for earthquake-triggered landslides in the Italian Apennines: insights from recent
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Franz Livio I Maria Francesca Ferrario
Assessment of attenuation regressions for earthquake-triggered landslides in the Italian Apennines: insights from recent and historical events
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. Keywords Earthquake-triggered landslide . Apennine . Kernel estimator . Landslide inventory Introduction In the past few years, the availability of high-resolution images taken before and immediately after an earthquake prompted to a sensible increase in the quality and completeness of coseismic landslide inventories, which are timely compiled and may help civil protection and local authorities (e.g., Robinson et al. 2017; Xu 2015). These inventories can be used for analyzing the spatial distribution of landslides (Harp et al. 2011) and for compiling attenuation regressions based on the correlation of landslide density (or probability of occurrence) with seismological (i.e., PGA and Arias Intensity; e.g., Carro et al. 2003; Meunier et al. 2007; Marc et al. 2017) and morphological-geological variables (i.e., slope, lithology, topographic roughness etc.; e.g., Lee et al. 2010; Yuan et al. 2013). Such an approach can be successfully used for predicting future seismic landslide occurrence, given the input earthquake parameters. Landslides triggered by historical earthquakes, as well (e.g., Keefer 1984; Bommer and Rodrı́guez 2002; Malamud et al. 2004a, b; Rodríguez et al. 1999; Chen et al. 2012; Tanyaş et al. 2017; Huayong et al. 2019), can potentially be used for calculating an attenuation equation allowing to significantly expand the timewindow covered by the data and to compare data on successive events striking the same area. In territorial settings characterized by extensive historical documentation, detailed inventories of earthquake-induced landslides are in fact available for a number of events encompassing several centuries. A simple approa
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