A multi‐method geophysical approach based on fuzzy logic for an integrated interpretation of landslides: application to the French Alps

Abstract

Physics‐based, such as seismic surveying or electrical resistivity imaging, appear to be efficient in investigating landslide structures and, consequently, for understanding related mechanisms of deformation. They are non‐intrusive probing methods that allow the direct measurement of compressional (P), shear (S) wave velocities and also electrical resistivity, three geophysical parameters that are considered as determinants in defining ground properties and identifying anomalies related to structural (faults, fissures), lithological (sand to clay, or calcareous variations) and hydrological (moisture, water flow) conditions. Both the seismic and resistivity methods are commonly used for landslide investigations, having been tested over the last decade or more on various types of landslides, including mudslides, debris flows, unstable slopes, etc. The common approach in these earlier experiments has been to invert the P‐ and S‐wave velocity fields, plus the electrical resistivity field, using suitable algorithms to produce two‐dimensional P‐ and S‐wave velocities and resistivity tomograms. A coherent and integrated interpretation of the resulting information is, however, not straightforward because each geophysical method is sensitive to different soil properties. An innovative approach has thus been developed to combine the geophysical parameters imaged on tomograms and convert them into different geological or geomechanical cross‐sections. Knowing that seismic data provide information on variations in fissure density and the presence of sheared materials and that electrical resistivity data provide information on variations in water content, the final cross‐sections are computed by combining different transformation functions able to model the conversion from geophysical parameters to ground properties. The computations are realized in a framework of the fuzzy‐set mathematical theory that maintains a certain level of objectivity and is able to manage uncertainties. The basics of this approach are explained through a brief presentation of the theory of data fusion with emphasis on how uncertainties are taken into account. The results obtained from case studies in the French Alps are then discussed in terms of reliability and compared with available ground reality obtained from surface observations and borehole descriptions.

Internal Structure and Reactivations of a Mass Movement: The Case Study of the Jacotines Landslide (Champagne Vineyards, France)

“…Data fusion based on fuzzy subsets theory was realized to interpret jointly seismic (Vp) and electrical (ρ) tomograms in regard to physical behaviors and physical properties of the materials [39]. In the fusion process, the definition of belonging functions is determinant because they link the values of the geophysical parameters (Vp, rho) to the possibility that a specific geotechnical behavior occurs.…”

“…Geophysical profiles were exploited separately to understand the internal structure of the slope. We assume here that Vp parameter provides information on the variation of fissure density and on the presence of weathered material whereas the ρ parameter provides information on the variation of water content within and next to the landslide [39]. Along profile 2 (longitudinal, Figure 5), which extends between the foot of the main scarp and the external edge of the reverse slope, the Vp are greater than 2100 m/s at a depth of 40 or 50 m (i.e., 150 m a.s.l.).…”

“…To invert apparent resistivities, we used the Res2dinv software (version 3.59) [38] based on a least squares/quasi-Newton inversion approach also able to damp the convergence process in order to avoid local minimum solutions. Data fusion based on fuzzy subsets theory was realized to interpret jointly seismic (Vp) and electrical (ρ) tomograms in regard to physical behaviors and physical properties of the materials [39]. In the fusion process, the definition of belonging functions is determinant because they link the values of the geophysical parameters (Vp, rho) to the possibility that a specific geotechnical behavior occurs.…”

A Review of the Advantages and Limitations of Geophysical Investigations in Landslide Studies

“…Authors agree that seismic wave velocities and soil ER could be useful in identifying anomalies related to structural (faults, fissures, and stability), lithological (sand to clay or calcareous variations) and hydrological (moisture, water flow) conditions [42,123,143]. However, drillings and inclinometer measurements are still crucial to providing a reliable idea of landslide structures and slip surfaces and to validate any geophysical measurements.…”

“…important to point out that in our analysis, we do not consider papers focused on the geophysical characterization of quickclay that could evolve into a sensitive clay flowslide but only papers focused on those that already occurred [35,51,52,72]. In only 8 works (12.1% of the analysed "soil" landslide works), it is possible to find a detailed discussion of the theory applied to landslides, concerning either how to formulate the inversion problem [41,46,52,55,68,83] or how to combine data from different surveys [7,42]. All the other papers deal with the discussion of a case study.…”