Quantification of soil textural and hydraulic properties in a complex conductivity imaging framework: Results from the Wolfsegg slope

Abstract

We present an approach that permits to predict hydraulic conductivity from extensive, multi-methodical geophysical data collected on a hillslope affected by landslides in Austria. The objective of the investigation is the spatial characterization of a slope affected by mass movements to derive hydrogeological structures and preferential flow paths. The geophysical data sets presented in this study consists of 24 densely distributed complex conductivity (CC) imaging profiles, collocated to these profiles we also collected 517 transient electromagnetic (TEM) soundings and 10 refraction seismic tomography (RST) profiles. Additionally, we also present well-logging data (namely electrical resistivity, natural gamma logs) collected in five boreholes. Cores recovered during the drilling of the boreholes are used to aid in the interpretation of the geophysical units, while analysis of the sediments was conducted to obtain grain size distributions, cation exchange capacity and mineralogy of the subsurface materials. While all geophysical data was processed initially independently, the final complex conductivity imaging results are based on the incorporation of structural constraints about the electrical units obtained from the TEM soundings. The interpretation of the resolved CC units is then sustained by the RST images and the lithological information from the boreholes. We estimate then the hydraulic conductivity of the subsurface derived from the CC images using a two-step approach. In a first step, we investigated the link between the complex conductivity and the different soil volume fractions of gravel, sand, silt and clay. In a second step, we applied a pedo-transfer function, namely the well-known Rosetta model, that permits to predict the hydraulic conductivity from the estimated grain size volumes. This approach allowed a quantitative interpretation of the geophysical data and thus a 3-dimensional (3D) representation of the grain size distribution and hydraulic conductivity in the investigated slope section. Thereby, we observed well-determined site-specific relationships (R2 > 0.7) from the comparison of the complex resistivity images and grain size analysis. The obtained hydrogeophysical 3D model permits to delineate the geometry of an aquiclude, and, thus, the analysis of preferential water-flow paths. In particular, we can identify a spatial correlation between the aquiclude interface and morphological features.