Articles | Volume 26, issue 8
https://doi.org/10.5194/nhess-26-3987-2026
https://doi.org/10.5194/nhess-26-3987-2026
Research article
 | 
21 Aug 2026
Research article |  | 21 Aug 2026

Impact of extreme rainfall on triggering conditions and susceptibility for shallow landslides: a case study in the Alpes-Maritimes region (France)

Lucie Armand, Guillaume Chambon, Olivier Cerdan, Yannick Thiery, Nathalie Marçot, Louis Ferradou, Nicolas Saby, and Séverine Bernardie

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Cited articles

Achu, A. L., Thomas, J., Aju, C. D., Vijith, H., and Gopinath, G.: Redefining landslide susceptibility under extreme rainfall events using deep learning, Geomorphology, 448, 109033, https://doi.org/10.1016/j.geomorph.2023.109033, 2024. 
Altmann, A., Toloşi, L., Sander, O., and Lengauer, T.: Permutation importance: a corrected feature importance measure, Bioinformatics, 26, 1340–1347, https://doi.org/10.1093/bioinformatics/btq134, 2010. 
Arbizzi, S., Cinotti, B., Desbouis, J.-F., Moreau, L., Sauzey, P., and Vilmus, F.: Retour d'expérience des intempéries des 2 et 3 octobre 2020 dans les Alpes-Maritimes, https://www.igedd.developpement-durable.gouv.fr/IMG/pdf/013618-01_rapport-publie_cle57ddc8.pdf (last access: 27 July 2026), 2021. 
Armaş, I., Vartolomei, F., Stroia, F., and Braşoveanu, L.: Landslide susceptibility deterministic approach using geographic information systems: application to Breaza town, Romania, Nat. Hazards, 70, 995–1017, https://doi.org/10.1007/s11069-013-0857-x, 2014. 
Barthélemy, S., Bernardie, S., and Grandjean, G.: Assessing rainfall threshold for shallow landslides triggering: a case study in the Alpes Maritimes region, France, Nat. Hazards, https://doi.org/10.1007/s11069-024-06941-2, 2024. 
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This research examines how extreme-rainfall-induced landslides affect predictive tools for shallow landslides. Focusing on Storm Alex (France), we compared predictions with and without Alex-induced landslides. Results show that Alex-induced landslides do not follow the same triggering conditions as those observed during more frequent rainfalls, leading to different rainfall thresholds and susceptibility maps. This highlights the importance of accounting for rare events when predicting landslide.
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