Rainfall thresholds for possible landslide occurrence in Italy

Peruccacci, Silvia; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Melillo, Massimo; Rossi, Mauro; Guzzetti, Fausto, 2017, Rainfall thresholds for possible landslide occurrence in Italy, Geomorphology (Amst.) 290 (2017): 39–57. doi_10.1016/j.geomorph.2017.03.031,
URL: http://www.cnr.it/prodotto/i/377707

The large physiographic variability and the abundance of landslide and rainfall data make Italy an ideal site to investigate variations in the rainfall conditions that can result in rainfall-induced landslides. We used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with mostly shallow landslides in Italy between January 1996 and February 2014. For each rainfall event with landslides, we reconstructed the rainfall history that presumably caused the slope failure, and we determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm). Adopting a power law threshold model, we determined cumulated event rainfall rainfall duration (ED) thresholds, at 5% exceedance probability, and their uncertainty. We defined a new national threshold for Italy, and 26 regional thresholds for environmental subdivisions based on topography, lithology, land-use, land cover, climate, and meteorology, and we used the thresholds to study the variations of the rainfall conditions that can result in landslides in different environments, in Italy. We found that the national and the environmental thresholds cover a small part of the possible DE domain. The finding supports the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining thresholds for small geographical areas. We observed differences between some of the thresholds. With increasing mean annual precipitation (MAP), the thresholds become higher and steeper, indicating that more rainfall is needed to trigger landslides where the MAP is high than where it is low. This suggests that the landscape adjusts to the regional meteorological conditions. We also observed that the thresholds are higher for stronger rocks, and that forested areas require more rainfall than agricultural areas to initiate landslides. Finally, we observed that a 20% exceedance probability national threshold was capable of predicting all the rainfall induced landslides with casualties between 1996 and 2014, and we suggest that this threshold can be used to forecast fatal rainfall-induced landslides in Italy. We expect the method proposed in this work to define and compare the thresholds to have an impact on the definition of new rainfall thresholds for possible landslide occurrence in Italy, and elsewhere.

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