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

Viewed

Total article views: 1,020 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
787 176 57 1,020 42 41
  • HTML: 787
  • PDF: 176
  • XML: 57
  • Total: 1,020
  • BibTeX: 42
  • EndNote: 41
Views and downloads (calculated since 12 Dec 2023)
Cumulative views and downloads (calculated since 12 Dec 2023)

Viewed (geographical distribution)

Total article views: 1,020 (including HTML, PDF, and XML) Thereof 974 with geography defined and 46 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2024
Download
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.
Altmetrics
Final-revised paper
Preprint