EGU24-19801, updated on 11 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Mathieu Le Breton1,2, Eric Larose2, Florent Chatelain3, Laurent Baillet2, Alexandra Royer1, and Antoine Guillemot1
Mathieu Le Breton et al.
  • 1Géolithe, Crolles, France (
  • 2Institut des Sciences de la Terre, CNRS, Université Grenoble Alpes, Grenoble
  • 3Gipsa-lab, Université Grenoble Alpes, Grenoble, France

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).

How to cite: Le Breton, M., Larose, E., Chatelain, F., Baillet, L., Royer, A., and Guillemot, A.: Alternance of two reactivation regimes on Pont-Bourquin earthflow, highlighted by changes in seismic velocity and sensitivity to rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19801,, 2024.