The use of electrical resistivity tomography (ERT; non-intrusive geophysical technique) was assessed to identify the hydrogeological conditions at a surface water/groundwater test site in the southern Black Forest, Germany. A total of 111 ERT transects were measured, which adopted electrode spacings from 0·5 to 5 m as well as using either Wenner or dipole-dipole electrode arrays. The resulting two-dimensional (2D) electrical resistivity distributions are related to the structure and water content of the subsurface. The images were interpreted with respect to previous classical hillslope hydrological investigations within the same research basin using both tracer methods and groundwater level observations. A raster-grid survey provided a quasi 3D resistivity pattern of the floodplain. Strong structural heterogeneity of the subsurface could be demonstrated, and (non)connectivities between surface and subsurface bodies were mapped. Through the spatial identification of likely flow pathways and source areas of runoff, the deep groundwater within the steeper valley slope seems to be much more connected to runoff generation processes within the valley floodplain than commonly credited in such environmental circumstances. Further, there appears to be no direct link between subsurface water-bodies adjacent to the stream channel. Deep groundwater sources are also able to contribute towards streamflow from exfiltration at the edge of the floodplain as well as through the saturated areas overlying the floodplain itself. Such exfiltrated water then moves towards the stream as channelized surface flow. These findings support previous tracer investigations which showed that groundwater largely dominates the storm hydrograph of the stream, but the source areas of this component were unclear without geophysical measurements. The work highlighted the importance of using information from previous, complementary hydrochemical and hydrometric research campaigns to better interpret the ERT measurements. On the other hand, the ERT can provide a better spatial understanding of existing hydrochemical and hydrometric data. Copyright © 2009 John Wiley & Sons, Ltd.