Assessing rainfall triggering of shallow landslides with an automatic tool generating thresholds: a case study for the Alpes-Maritimes region, France

In this work, we use a probabilistic approach for modelling rainfall thresholds (Caine 1980) triggering shallow landslides with a case study for the Alpes-Maritimes region (France).

In particular, the CTRL-T algorithm (Melillo and al. 2018) is tested to output critical rainfall thresholds, based on the accumulated rainfall – duration parameters (E-D), for different exceedance probabilities from respectively a landslide and two climate datasets. The first climate dataset stores high resolution gridded rainfall data (1km resolution, hourly) and the second climate dataset contains lower resolution gridded rainfall, snow, temperature and evapotranspiration data (8km resolution, daily); the first dataset provides the rainfall records directly used for defining the rainfall events and then for the threshold construction; the second one enables to assess the region’s climate via parameters imported in CTRL-T. The thresholds are then validated using a method designed by Gariano and al. (2015).

Several improvements are made to the method. First, potential evapotranspiration values approximated from temperatures and latitudes in one of the process’ steps are replaced by values from the second climate dataset, the result accounting best for the regional climate. Then, climate-specific duration values, used to split the raw rainfall records in events and sub-events, are computed for each mesh point. This second modification enables considering the heterogeneity of the Alpes-Maritimes climate.

Rainfall thresholds are eventually obtained for different exceedance probabilities, first from a set of probable conditions (MRC), then from 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 probabilistic rainfall thresholds for Alpes-Maritimes, (b) using for the first time high-resolution rainfall data and (c) adapting the method to climatically heterogeneous zones.