Combining seismic and electric methods for predicting bedrock depth along a Mediterranean soil toposequence

Bedrock depth provides important information for many environmental and agricultural applications, such as shallow groundwater monitoring, the determination of soil water availability, and the estimation of crop production potential. Direct estimates of bedrock depth from destructive soil observations are discontinuous and too expensive to be used in large areas. Geophysical methods are often cited as possible alternatives. However, their ability to provide reliable estimations of bedrock depth is known to depend greatly on local site characteristics. Therefore, combining geophysical methods based on different physical parameters may help to provide better predictions. This study examines the ability of the Spectral Analysis of Surface Waves (SASW) method combined with the classical high resolution Electrical Resistivity Tomography (ERT) method to predict soil depths in a 500 m ranged Mediterranean hillslope (Southern France) with increasing soil depths along the slope. SASW was performed using the data measured in the field with classical seismic equipment (impulse source and geophones distributed along a line). In the same place, eight transects of ERT (Wenner–Schlumberger array, 1 m electrode spaced) were measured under wet and dry conditions. To calibrate the geophysical measurements, 81 boreholes (from two to 5 m deep) were interpreted to determine the bedrock depth, which was defined as the occurrence in the depth of heterogeneous marine Miocene loose sandstone with centimetric laminations. ERT and SASW were found to have highly variable performances for predicting separately the bedrock depth along the hillslope. SASW correctly predicted the bedrock depth in the lower part of the hillslope, whereas the data from ERT were disrupted by shallow permanent groundwater. Conversely, ERT correctly predicted bedrock depth within the upper part of the hillslope, whereas a high variability of SASW data near the topsoil caused difficulties for bedrock depth prediction. From these results, it was possible to define an estimator of bedrock depth according to the presence of shallow groundwater, which varies along the slope, such that more importance is given to ERT estimates in the upper part of the hillslope and more importance is given to SASW in the lower part. This study shows the usefulness of such a sensor combination to estimate soil properties when the uncertainties of making predictions vary according to the geophysical methods.