The application of an innovative inverse model for understanding and predicting landslide movements (Salazie cirque landslides, Reunion Island)

Abstract

International audienceThe prediction of landslide movement acceleration is a complex problem, among others identified for deep-seated landslides, and represents a crucial step for risk assessment. Within the scope of this problem, the objective of this paper is to explore a modelling method that enables the study of landslide function and facilitates displacement predictions based on a limited data set. An inverse modelling approach is proposed for predicting the temporal evolution of landslide movement based on rainfall and displacement velocities. Initially, the hydrogeology of the studied landslides was conceptualised based on correlative analyses. Subsequently, we applied an inverse model with a Gaussian-exponential transfer function to reproduce the displacements. This method was tested on the Grand Ilet (GI) and Mare-à-Poule-d'Eau (HB) landslides on Reunion Island in the Indian Ocean. We show that the behaviour of landslides can be modelled by inverse models with a bimodal transfer function using a Gaussian-exponential impulse response. The cumulative displacements over 7 years of modelling (2 years of calibration period for GI, and 4 years for HB) were reproduced with an RMSE above 0.9. The characteristics of the bimodal transfer function are directly related to the hydrogeological functioning demonstrated by the correlative analyses: the rapid reaction of a landslide can be associated with the effect of a preferential flow path on groundwater level variations. Thus, this study shows that the inverse model using a Gaussian-exponential transfer function is a powerful tool for predicting deep-seated landslide movements and for studying how they function. Beyond modelling displacements, our approach effectively demonstrates its ability to contribute relevant data for conceptualising the sliding mechanisms and hydrogeology of landslides

Potential and Limitation of SPOT-5 Ortho-Image Correlation to Investigate the Cinematics of Landslides: The Example of “Mare à Poule d’Eau” (Réunion, France)

“…The quality of point matching is evaluated from the quality of geometric transformation between of the point clouds identified on both images. showed that a displacement of at least 5 m towards the north occurred during the year that followed this extreme event [30]. Figure 2) showed that a displacement of at least 5 m towards the north occurred during the year that followed this extreme event [30].…”

“…showed that a displacement of at least 5 m towards the north occurred during the year that followed this extreme event [30]. Figure 2) showed that a displacement of at least 5 m towards the north occurred during the year that followed this extreme event [30]. Only the south-north component of the displacement measured by DGPS is available.…”

“…The landslide covers an area of 2.5 km 2 for an estimated volume of approximately 400 × 10 6 m 3 [30].…”

“…The landslide topography ( Figure 1B) suggests that the landslide displacement has both translational and rotational components [31,33]. The landslide can be divided into four or five compartments delimited by scarps visible on the DEM [30]. The displacement of the landslide has been partly monitored since 2002, using GNSS data from permanent DGPS receivers located on the slipping area.…”

“…The displacement of the landslide has been partly monitored since 2002, using GNSS data from permanent DGPS receivers located on the slipping area. The displacement has a strong component to the north, with an average velocity increasing northward from 0.8 to 1.33 m/year over the period 2005-2011 [30].…”