Structure-based geoelectrical models derived from genetic algorithms: A case study for hydrogeological investigations along Elbe River coastal area, Germany

Abstract

Abstract Vertical electrical sounding (VES) and electrical resistivity tomography (ERT) surveys are performed to assess the hydrogeological conditions along Elbe River coastal area, Germany. Because the interpretation of actual resistivity data still has a degree of non-uniqueness and ill-conditioning, linear and non-linear inversion methods have been applied in this paper for optimal interpretation of the measured data. The 1D model generation using hybrid genetic algorithms (GA) represents an accurate and quick solution to image the subsurface resistivity distributions; freshwater aquifer and two highly conductive zones of perched saltwater and seawater intrusion. The longitudinal conductance of the interpreted layers above the water table is calculated to explain why the vulnerable zone to the perched saltwater concentrates at the central and southern parts of the area investigated. Two-dimensional layered-earth models consisting of undulating interfaces are generated by the 2D hybrid GA. These structure-based models are then compared to the cell-models derived from the conventional smoothness-constrained inversion in view of available borehole data. A finite element forward 2D modeling scheme is used for the calculation of theoretical data. This survey example demonstrates that the combined use of the GA with structure-based model and conventional derivative-based inversion with cell-model provides valuable information to constrain the number of interfaces to interpret the DC resistivity measurements for hydrogeological investigations. The limitations of conventional inversion methods under the presence of conductive layers can be overcome by the use of GA with a structure-based model. However, the structure-based parameterization is not practical in the case of significant and sudden discontinuities along the lateral direction.