Landslide dynamics inferred from in-situ measurements and time series of terrestrial imagery: the Cliets rockslide (Savoie, French Alps)

Several geodetic methods can be combined to better understand landslide dynamics and behavior. The obtained deformation/displacement fields can be analyzed to inverse the geometry of the moving mass and the mechanical behavior of the slope (kinematic regime, rheological properties of the media), and sometimes anticipate the time of failure. Among them, dense in-situ measurements (total station measurements, extensometer data and GNSS surveys) allow reaching accuracy close to the centimeter. These techniques can be combined to dense time series of passive terrestrial imagery in order to obtain distributed information. Actually, more and more passive optical sensors are used to provide both qualitative information (detection of surface change) and quantitative information using either a single camera (quantification of displacement by correlation techniques) or stereo-views (creation of Digital Surface Models, DSM).

 

In this study, we analyze a unique dataset of the Cliets rockslide event that occurred on 9 February 2019. The pre-failure and failure stages were documented using the above mentioned methods. The performance of the methods are evaluated in terms of their possible contribution to a monitoring survey.

 

The Cliets landslide is located in the French Alps (Savoie) and is affecting the high traffic road of Gorges de l’Arly. Located upstream of a tunnel, the unstable slope was instrumented by the SAGE Society during the crisis in the period July–February 2019. About 8000 m³ collapsed closing the tunnel access for one year. Topographic measurements of a series of 41 benchmarks by automated total station were used to determined the time of rupture and the landslide mechanical behavior (tertiary creep vs stable regime). Additionally, a fixed CANON EOS 2000D with a lens with a focal length of 24 mm, was installed in front of the landslide. Images were acquired hourly and the time series was processed using the TSM processing toolbox (Desrues et al., 2019). Displacement fields were generated over time and compared to the topographic measurements. Photogrammetric surveys were carried out to generate several DSMs before and after the crisis. It allowed to estimate the volume of the collapsed masses. Finally, geophysical surveys were included in the study to determine the thickness of the potential unstable layer.

The results allow highlighting (1) different kind of behaviors which are identified and explained by a simple physical models, (2) the volumes of the displaced masses, and (3) the absence of a direct relation of the failure with the meterological forcing factors.

 

Acknowledgments: These works are part of a CIFRE / ANRT agreement between IPGS/CNRS UMR7516 and the SAGE Society.