Fiber-optic high-resolution acoustic emission (AE) monitoring of slope failure
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We measured precursory acoustic emissions (AE) preceding the release of landslides in an inclined chute (3.0 m × 0.5 m × 0.5 m) filled with well-graded sandy soil. To detect elastic waves, we used an intelligent distributed acoustic sensing (DAS) technology. This method is based on fiber-optic technology that provides AE measurements at a high spatial and temporal resolution across large distances. The objective was to investigate acoustic emissions as precursors of slope failure and to assess the potential for landslide early warning based on this technology. We used a micro-sprinkler irrigation system to mimic triggering of landslides by rainfall. Fiber-optical cables were embedded within the soil material at three different depths. Additionally, we monitored occurrence of AE using independent piezoelectric transducers. Hydraulic monitoring of the wetted slope provided information on its hydrologic evolution and an audiovisual inspection system recorded deformations of the surface. Failure of the material was typically preceded by collapse of the slope toe followed by slowly accelerating retrogressive failure. This progressive failure resulted in an unambiguous acoustic signature captured by the DAS. Time-domain processing of waveforms provided insights into the prevailing failure mechanisms. The imminence of global failure was indicated by elevated AE activity. The fiber-optic AE detection using the iDAS™ (intelligent Distribute Acoustic Sensor) allows acquisition of failure-related elastic waves and may provide a valuable warning tool for large scale (km-scale) monitoring of shallow landslides and other rapid mass movements.
KeywordsLandslide early warning Acoustic emissions Fiber-optic technology
The authors thank the SNF and the Swiss Competence Center for Environmental Sustainability (CCES) for their financial support. We are also grateful for the support of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL, particularly through Brian McArdell and Werner Gerber. We thank Daniel Breitenstein, Achille Capelli, Linfeng Fan, Patrick Hagenbucher, Peter Lehmann, and Hans Wunderli for their assistance with the system setup and landslide tests. We further thank the two anonymous reviewers that improved this manuscript with their constructive criticism and valuable comments.
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