1887
Volume 10 Number 6
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

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.

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2012-07-01
2024-04-20
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