Abstract

In order to better understand the mechanics and dynamic of landslides, it is of primary interest to image correctly their internal structure and their slip surface. Several active geophysical methods are able to provide the geometry of a given landslide, but were rarely applied in 3 dimensions in the past. The main disadvantages of methods like seismic reflection and electrical tomography are that there are heavy to set up and/or to process, and they consequently are expensive and time consuming. Moreover, in the particular case of soft-rock landslides, their respective sensitivity and resolution are not always adequate to locate the potential slip surfaces. Passive methods may represent an interesting alternative particularly for landslides difficult to access, as they require lighter instrumentation and easier processing tools. Among them, the seismic noise based methods have shown increasing applications and developments, in particular for seismic hazard mapping in urban environment. In this paper, we present seismic noise investigations carried out on two different sites, the “Super Sauze” mudslide and the “Saint Guillaume” translational clayey landslide (France), where independent measurements (geotechnical and geophysical tests) were performed earlier. Our investigations were composed of electrical tomography profiles, seismic profiles for surface-wave inversions, H/V measurements, which are fast and easy to perform in the field, in order to image shear wave contrasts (slip surfaces), and seismic noise array method, which is heavier to apply and interpret, but provides (S)-waves velocity profile versus depth. For both sites, landslide bodies are characterized by lower S wave velocity (Vs < 300 m.s−1) and lower resistivity (ρ < 60 Ohm.m) than in the stable part (Vs > 550 m.s−1; ρ > 150 ohm.m). Their thickness vary from a few m to 50 m. Comparison between geophysical investigations and geotechnical data proved the applicability of such passive methods in 3D complex structures, with however some limitations.

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