Abstract

This work focuses on the characterization of seismic sources observed in clay–shale landslides. Two landslides are considered: Super-Sauze (France) and Valoria (Italy). The two landslides are developed in reworked clay–shales but differ in terms of dimensions and displacement rates. Thousands of seismic signals have been identified by a small seismic array in spite of the high-seismic attenuation of the material. Several detection methods are tested. A semi-automatic detection method is validated by the comparison with a manual detection. Seismic signals are classified in three groups based on the frequency content, the apparent velocity and the differentiation of P and S waves. It is supposed that the first group of seismic signals is associated to shearing or fracture events within the landslide bodies, while the second group may correspond to rockfalls or debris flows. A last group corresponds to external earthquakes. Seismic sources are located with an automatic beam-forming location method. Sources are clustered in several parts of the landslide in agreement with geomorphological observations. We found that the rate of rockfall and fracture events increases after periods of heavy rainfall or snowmelt. The rate of microseismicity and rockfall activity is also positively correlated with landslide displacement rates. External earthquakes did not influence the microseismic activity or the landslide movement, probably because the earthquake ground motion was too weak to trigger landslide events during the observation periods.

Highlights

  • Landslide failures may seriously damage the human and environmental resources of a region

  • At the Valoria landslide, the seismic array was installed in 2009 November for a short monitoring period in order to compare the seismic signals detected at Valoria with those detected at Super-Sauze

  • We suggest that the seismic signals classified as rockfalls are generated by the propagation of material on the surface, either as falls of blocks or debris from the upper scarp or as small volumes debris flows at the landslide surface

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Summary

Introduction

Landslide failures may seriously damage the human and environmental resources of a region. It is still uneasy to forecast the evolution of a landslide because it depends both on its dynamics and on external triggering events, such as earthquakes and rainfall (Guzzetti et al 2007) To better understand these processes, passive seismic monitoring techniques have been developed since the 1960s, in order to detect possible seismic signals triggered by the slope dynamics (Cadman & Goodman 1967; Novosad et al 1977). It consists generally in identifying seismic sources induced by the slope movement using seismic sensors. Passive seismic monitoring has been carried out on very diverse geological contexts and for very different objectives, and the number of studies has increased in the last decades

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