Statistical analysis of shallow landslides in the Alpes-Maritimes (France) : predisposing factors, meteorological variables, and extreme events

Shallow landslides, characterized by sudden, superficial movements and the absence of precursors, pose an increasing threat to the population and local authorities, particularly in the context of climate change and rapid urbanization. A good understanding of the triggering mechanisms of these phenomena is essential to predict their occurrence and to design reliable early warning systems. For that purpose, the retrospective analysis of event inventories can provide critical information on predisposing and triggering factors, making it possible to establish, e.g., susceptibility maps and rainfall triggering thresholds.

This study presents the results of a statistical analysis of an inventory of 4786 shallow landslides that occurred in the Alpes Maritimes department (southeastern France). This area, characterized by Mediterranean and mountainous climates, is prone to intense and localized rainfall events. It was severely impacted by the Alex storm in October 2020, an exceptional event that triggered numerous landslides among other consequences. A total of 1656 landslides in our inventory are related to this storm. Our objective is to assess how landslides triggered by this exceptional event can integrated into hazard analyses.

For that purpose, we analyse the relations between two groups of landslides (i.e Alex or non-Alex landslides) and both meteorological variables and predisposing factors. Cumulative rainfall/duration thresholds are computed using the CTRL-T algorithm (Melillo et al., 2018). Results show that rainfall thresholds for landslides triggered by Storm Alex are significantly higher than those for other landslides. In addition, predisposing factors, in particular the geology derived from the harmonized geological map of France, show different distribution The formations corresponding to surface deposits, such as debris material, were more heavily mobilized during storm Alex. The implications of these outcomes for improving the reliability of susceptibility maps and early warning systems are discussed.