Prediction of the Rainfall-Induced Landslides: Applications of FLAME in the French Alps

Abstract

This work presents an innovative approach to predict changes in landslide displacement rates for early warning purposes. The forecasting tool associates a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the input signal (e.g. rainfall) and the output signal (e.g. displacements) and a simple 1D mechanical (MA) model (e.g. visco-plastic rheology) to take into account changes in pore water pressures. The models have been applied to forecast the displacement rates at three landslide sites (South East France), among the most active and instrumented landslides in the European Alps. Results indicate that the three models are able to reproduce the displacement pattern in the general kinematic regime with very good accuracy (succession of acceleration and deceleration phases); at the contrary, extreme kinematic regimes such as fluidization of part of the landslide mass are not being reproduced. This statement, quantitatively characterised by the Root Mean Square Error between the model and the observations, constitutes however a robust approach to predict changes in displacement rates from rainfall or groundwater time series, several days before it happens. The variability of the results, depending in particular on the fluidization events and on the location of displacement data, is discussed.