Articles | Volume 24, issue 8
https://doi.org/10.5194/nhess-24-2689-2024
https://doi.org/10.5194/nhess-24-2689-2024
Research article
 | 
09 Aug 2024
Research article |  | 09 Aug 2024

Temporal clustering of precipitation for detection of potential landslides

Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele

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Short summary
Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
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