Research project description

Investigating the potential of seismic monitoring for rock mass movements

Introduction

The retreat caused by the erosion of coastal cliffs poses a risk to people and infrastructure located above. These areas are subject to various weathering and erosion processes such as freeze-thaw cycles and the action of tides and waves during storms. Climate change introduces uncertainty regarding predictions of the retreat rates of these cliffs. For example, the increased frequency and intensity of storms, coupled with the reduced ice cover during winter, may accelerate the retreat of coastal cliffs in northern environments. Methods exist to characterize surface deformation, such as LIDAR, but it is still challenging to understand the link between meteorological variations and the evolution of stresses at depth. Monitoring based on geophysical methods, however, can help understand deformations in depth.

Objectives

Seismic monitoring is a prevalent technique within the mining and oil industries for understanding stress variations within geological formations coming from their exploitation. Recently, methodologies developed in these fields have found application in natural hazard surveillance. The project aims to 1) build artificial intelligence tools for the detection and localization of seismic events, and 2) establish relationships between seismicity and environmental parameters to understand the mechanisms governing the development of rock instability.

Study Sites

Recently, significant rockfalls have been observed on the limestone cliffs of Cap-Bon-Ami in Forillon National Park, located in the Haute-Gaspésie region. These events pose a risk to park users, necessitating thorough monitoring. The rock wall, composed of soft conglomerate rock, is highly susceptible to meteoritic erosion and freeze-thaw cycles. Consequently, it serves as an excellent open-air laboratory for gaining a deeper understanding of the mechanisms associated with instability development.

Material and methods

A network of fifteen geophones, coupled with an extensive array of instruments (weather station, temperature probe within the rock face, piezometer, extensometer, wave height sensor, surveillance camera), has been deployed on the site. The high-density geophone network will enable the triangulation of seismic event locations in space, letting us map the instability development. To achieve this, artificial intelligence tools inspired by transformers will be employed, using their powerful attention module for processing data with a temporal dimension. Ultimately, the seismic activity will be correlated with meteorological conditions to elucidate the mechanisms underlying rock instability within the massif.

References

Birien, T., & Gauthier, F. (2023). Influence of climate dependent variables on deformation and differential erosion of stratified sedimentary rocks. Geomorphology 421 , 108518. D'Amato, J., Hantz, D., Guerin, A., Jaboyedoff, M., Baillet, L.,

Research Site Coordinates