Prediction of changes in landslide rates induced by rainfall

Abstract

International audienceThis work focuses on the development of a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in rainfall amounts. The forecasting tool FLAME (Forecasting Landslides Accelerations induced by Meteorological Events) associates (1) 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. displacement) and (2) a simple 1D mechanical (MA) model (e.g. viscoplastic rheology) to take into account changes in pore water pressure. The models have been applied to forecast the displacement rates at the Super-Sauze landslide (South East France). The performance of different combinations of models (IR model alone, MA model alone and a combination of the IR and MA models) is evaluated against observed changes in pore water pressures and displacement rates at the study site. Results indicate that the three models are able to reproduce the displacement pattern in the general kinematic regime (succession of acceleration and deceleration phases); conversely, extreme kinematic regimes such as fluidization of part of the landslide mass are not being reproduced. The approach constitutes however a robust tool to predict changes in displacement rates from rainfall or groundwater time series

Contribution of time-related environmental tracing combined with tracer tests for characterization of a groundwater conceptual model: a case study at the Séchilienne landslide, western Alps (France)

“…Groundwater-level rise plays an important role in the (re)activation of deep-seated slope movements (Van Asch et al 1999;Iverson 2000;Rutqvist and Stephansson 2003). Many studies have attempted to characterize the relationships between water infiltration and landslide destabilization (Alfonsi 1997;Hong et al 2005;Helmstetter and Garambois 2010;Abellán et al 2015;Belle et al 2014;Bernardie et al 2014) or to couple hydromechanical models (Cappa et al 2004(Cappa et al , 2006Corominas et al 2005;Guglielmi et al 2005;Bonzanigo et al 2007;Sun et al 2009). However, to be accurate and to reflect field conditions, such approaches must be based on relevant and realistic groundwater conceptual models.…”

Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys

“…The kinematics of the landslide phenomena has been analyzed in a large number of scientific studies; the approaches range from the analytical one-dimensional (1D) infinite slope models, suitable for landslides bodies with sliding surface depth about constant and significantly lower than the landslide length [1][2][3][4][5], to more sophisticated two-(2D) and three-dimensional (3D) Finite Element (FE) models aimed at detecting the different kinematical sectors along the slope area [6][7][8][9]. In particular, the recent development of three-dimensional numerical codes allows us to carry out simulations of the displacement rate field of a landslide process in a more realistic and accurate way.…”

State fusion entropy for real-time and site-specific analysis of landslide stability changing regularities

“…Secondly, external factors such as rainfall (Priest et al, 2011;Bernardie et al, 2015;Liu et al, 2016) and fluctuation of water level (Ashland et al, 2006;Huang et al, 2017) will also change landslide stability. But for now only a few literatures mentioned real-time landslide stability (Montrasio et al, 2011;Chen et al, 2014).…”