High-resolution fingerprints of past landsliding and spatially explicit, probabilistic assessment of future reactivations: Aiguettes landslide, Southeastern French Alps

The purpose of this study was to reconstruct spatio-temporal patterns of past landslide reactivation and the possible occurrence of future events in a forested area of the Barcelonnette basin (Southeastern French Alps). Analysis of past events on the Aiguettes landslide was based on growth-ring series from 223 heavily affected Mountain pine (Pinus uncinata Mill. ex Mirb.) trees growing on the landslide body. A total of 355 growth disturbances were identified in the samples indicating 14 reactivation phases of the landslide body since AD 1898. Accuracy of the spatio-temporal reconstruction is confirmed by historical records and aerial photographs. Logistic regressions using monthly rainfall data from the HISTALP database indicated that landslide reactivations occurred due to above-average precipitation anomalies in winter. They point to the important role of snow in the triggering of reactivations at the Aiguettes landslide body. In a subsequent step, spatially explicit probabilities of landslide reactivation were computed based on the extensive dendrogeomorphic dataset using a Poisson distribution model for an event to occur in 5, 20, 50, and 100 yr. High-resolution maps indicate highest probabilities of reactivation in the lower part of the landslide body and increase from 0.28 for a 5-yr period to 0.99 for a 100-yr period. In the upper part of the landslide body, probabilities do not exceed 0.57 for a 100-yr period and somehow confirm the more stable character of this segment of the Aiguettes landslide. The approach presented in this paper is considered a valuable tool for land-use planners and emergency cells in charge of forecasting future events and in protecting people and their assets from the negative effects of landslides.

► Probability maps of landslide reactivation are derived from tree-ring analysis.
► Role of snow in the triggering of reactivations demonstrated by logistic regression.
► It demonstrates the reliability of dendrogeomorphic mapping in shallow landslides.
► This approach is a valuable tool for land managers in charge of protecting people.