Alternance of two reactivation regimes on Pont-Bourquin earthflow, highlighted by changes in seismic velocity and sensitivity to rainfall

This study detects the regular alternation of two different reactivation regimes of the Pont-Bourquin Earthflow, occurring from 2010 to 2023, by combining the continuous monitoring of three indicators:
(1) seismic velocity, using ambient noise interferometry ^1,2
(2) displacement rate, using extensometers and RFID tags ^3–5
(3) sensitivity to rainfall and snowmelt, using dynamic impulse response deconvolution ^6,7

The study confirms the hypothesis of a dual mechanism previously suggested on this landslide from the lag of hydrological and displacement response to precipitations ^8,9, and goes further by detecting when these regime changes occur. In an early-warning system, this method might serve to discriminate different regimes during accelerations that are seemingly equivalent.

 

References related to this study:

¹ Mainsant, G. et al. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. Earth Surf. 117, F01030 (2012).
² Le Breton, M., Bontemps, N., Guillemot, A., Baillet, L. & Larose, É. Landslide monitoring using seismic ambient noise correlation: challenges and applications. Earth-Sci. Rev. 103518 (2021) doi:10.1016/j.earscirev.2021.103518.
³ Le Breton, M. et al. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Eng. Geol. 250, 1–10 (2019).
⁴ Le Breton, M. et al. Dense and long-term monitoring of earth surface processes with passive RFID — a review. Earth-Sci. Rev. 234, 104225 (2022).
⁵ Charléty, A., Le Breton, M., Baillet, L. & Larose, E. RFID Landslide Monitoring: Long-Term Outdoor Signal Processing and Phase Unwrapping. IEEE J. Radio Freq. Identif. 7, 319–329 (2023).
⁶ Bernardie, S., Desramaut, N., Malet, J.-P., Gourlay, M. & Grandjean, G. Prediction of changes in landslide rates induced by rainfall. Landslides 12, 481–494 (2015).
⁷ Le Breton, M. Suivi temporel d’un glissement de terrain à l’aide d’étiquettes RFID passives, couplé à l’observation de pluviométrie et de bruit sismique ambiant. (Université Grenoble Alpes, 2019).
⁸ Bronnimann, C. S. Effect of Groundwater on Landslide Triggering. (École Polytechnique Fédérale de Lausanne, 2011).
⁹ Bièvre, G. et al. Influence of environmental parameters on the seismic velocity changes in a clayey mudflow (Pont-Bourquin Landslide, Switzerland). Eng. Geol. 245, 248–257 (2018).