Integration of controlled-source and radio-magnetotellurics, electrical resistivity tomography and reflection seismics to delineate 3D structures of a quick-clay landslide site in southwest Sweden

Three-dimensional radio magnetotelluric (RMT), controlled-source radio magnetotelluric (CSRMT), electrical resistivity tomography (ERT), and high-resolution reflection seismic data were acquired at a quick-clay landslide site close to the Göta River in southwest Sweden. These data were collected with the main objectives of evaluating the performance of each method and delineating different subsurface materials down to the bedrock, which in turn control a peculiar and hazardous retrogressive-type landslide. These materials consist of mainly marine clays, quick clays, sand to gravel and the crystalline bedrock. The RMT, CSRMT and ERT data were inverted separately using 3D inversion schemes and the independent results from 3D processing of reflection seismic data together with the existing geotechnical data were used for their interpretations. The 3D CSRMT resistivity model shows the highest depth penetration and well resolves the geometry of the bedrock. The RMT and ERT models, however, show better resolution closer to the surface because of their denser data coverage compared with the CSRMT data. Considerable correlations in resolving a coarse-grained layer and the bedrock were observed between the CSRMT model and the 3D reflection seismic data. Because an Occam-type regularization was used in the inversion, the lateral and depth extent of the quick clays cannot accurately be determined just by using the resistivity models. The depth to the top of the resistive crystalline bedrock is to some extent uncertain. Comparisons with the borehole data suggest that the resistivity models are poor in resolving the sharp boundary between the quick clays and their underlying more resistive coarse-grained materials. The upper boundary of the more conductive marine clays underlain by the coarse-grain materials was well modeled by the CSRMT data. This study illustrates the potentials of 3D geophysical data especially when different types are collected and particularly for better si