Assessing rainfall threshold for shallow landslides triggering: a case study in the Alpes Maritimes region, France

Sophie Barthélemy (), Séverine Bernardie () and Gilles Grandjean
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Sophie Barthélemy: BRGM
Séverine Bernardie: BRGM
Gilles Grandjean: BRGM

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 4, No 13, 4023-4049

Abstract: Abstract In this work, we use a statistical approach for modeling shallow landslide rainfall thresholds (Caine 1980) with a case study for the Alpes-Maritimes region (France). Cumulated rainfall / duration (ED) thresholds are obtained with the CTRL-T algorithm (Melillo and al. 2018) for different non-exceedance probabilities from a landslide and two climatic datasets. This tool allows to automatically define rainfall events that might trigger landslides, ensuring robustness and objectivity in this process. The first climate dataset stores high resolution gridded rainfall data (1km resolution, hourly), which provides rainfall data with high temporal and spatial accuracy. This dataset, coming from radar data, is calibrated with rainfall gauges, ensuring a higher accuracy of the rainfall measurements. It provides the rainfall records directly used in the threshold construction The second dataset contains lower resolution gridded rainfall, snow, temperature, and evapotranspiration data (8km resolution, daily); it enables to assess the region’s climate through parameters imported in CTRL-T. The thresholds are then validated using a method designed by Gariano and et al. (2015). Several improvements are made to the initial method. First, evapotranspiration values approximated in the process are replaced by values from the second climate dataset, the result accounting best for the regional climate. Then, computing duration values used for isolating events and sub-events for each mesh point allows to consider the heterogeneity of the Alpes-Maritimes climate. Rainfall thresholds are eventually obtained, successively from a set of probable conditions (MRC) and a set of highly probable conditions (MPRC). The validation process strengthens the analysis as well as enables to identify best performing thresholds. This work represents novel scientific progress towards landslide reliable warning systems by (a) making a case study of empirical rainfall thresholds for Alpes-Maritimes, (b) using high-resolution rainfall data and (c) adapting the method to climatically heterogeneous zones.

Keywords: Shallow landslides; Rainfall thresholds; French Alpes-Maritimes; CTRL-T; Gridded rainfall data (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-024-06941-2

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