Assessing two methods to define rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains

Roberto J. Marin(a,b), María Fernanda Velásquez (a,b), Edwin F. García (b), Massimiliano Alvioli (c), Edier Aristizábal (d), 2021, Assessing two methods to define rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains, Catena (Cremling.) 206 (2021): 105563. doi_10.1016/j.catena.2021.105563,
URL: http://www.cnr.it/prodotto/i/454840

Rainfall thresholds are intensity-duration relations supposedly able to distinguish precipitation events that may or may not trigger landslides. The most common method for defining rainfall thresholds relies on observed landslides and the corresponding values of rainfall intensity and duration that caused each failure. Alternative methods to define rainfall thresholds, using physically-based models, recently gained importance, as they may provide complementary information to other methods. Still, their applicability in most of the world's regions, including the Colombian Andes' mountainous basins, has not been demonstrated or validated. In this study, we evaluated the applicability of the physically-based model TRIGRS to define rainfall intensity and duration thresholds in individual basins from the Colombian Andes. We obtained rainfall thresholds using two different methods and compared them with landslide-triggering rainfall events in two distinct basins, namely La Arenosa and La Liboriana. Furthermore, we used a (presumably incomplete) landslide database from Medellín to rebuild the rainfall events associated with individual landslides and compared them with the physically-based thresholds. The rainfall thresholds calculated in the three study areas and the applicability of the methods in data-scarce environments were assessed. Results showed that both methods for defining rainfall intensity and duration thresholds have merits and represent potential tools to improve or complement landslide early warning systems, especially in data-scarce regions.

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