Complex-conductivity imaging for the understanding of landslide architecture

Abstract

Geophysical methods are widely used for landslide investigation to delineate depth and geometry of the sliding plane. In particular, electrical resistivity tomography (ERT) is often used because both porosity and water saturation control the electrical resistivity of the subsurface materials and are critical for slope stability. Moreover, ERT can be employed to monitor changes in pore-fluid pressure which is an important factor triggering landslides. However, the interpretation of ERT results in clay-rich landslides can be challenging considering that high electrical conductivity values may not only be related to an increase in saturation but also to the surface conduction mechanism, which becomes dominant in the presence of clays. Recently, environmental investigations have demonstrated an improved subsurface characterization through induced polarization (IP) imaging, an extension of the ERT method, which permits to gain information about electrical conductive and capacitive (i.e., polarization effect) properties of the subsurface. As the polarization effect is mainly controlled by surface charge, which is large in clays, IP images are expected to improve the lithological interpretation and overcome the limitations of the ERT method. Additionally, measurements collected over a broad frequency bandwidth, the so-called spectral IP (SIP), have been successfully used in laboratory experiments to quantify textural and hydrogeological parameters. However, the application of SIP field measurements for the delineation of hydrogeological structures in landslides has not been addressed to date. To fill this gap, in this study we present SIP imaging results for data collected at the La Valette landslide (South East French Alps), where an existing geotechnical model of the landslide is available for evaluation. Moreover, our study provides a detailed revision on the collection and processing of SIP datasets, as well as a description of the diverse sources of error in IP surveys, to stress the importance of data-error quantification for a quantitative application of the SIP method. Our results demonstrate that adequate data processing allows obtaining consistent results at different frequencies and independently of the measuring protocol. Furthermore, the frequency dependence of the complex conductivity obtained in the field-scale SIP survey is consistent with earlier laboratory experiments. In conclusion, our study shows the potential of the SIP method to improve our understanding of subsurface properties, and an improved delineation of the contact between the mobilized material and the bedrock as well as variations in the clay content within the landslide and the bedrock.