This title appears in the Scientific Report : 2014 

Three-dimensional imaging of subsurface structural patterns using quantitative large-scale multiconfiguration electromagnetic induction data
von Hebel, Christian (Corresponding Author)
Rudolph, Sebastian / Mester, Achim / Huisman, Johan A. / Kumbhar, Pramod / Vereecken, Harry / van der Kruk, Jan
Agrosphäre; IBG-3
Water resources research, 50 (2014) 3, S. 2732 - 2748
Washington, DC AGU 2014
10.1002/2013WR014864
Journal Article
Terrestrial Systems: From Observation to Prediction
Modelling and Monitoring Terrestrial Systems: Methods and Technologies
OpenAccess
Please use the identifier: http://dx.doi.org/10.1002/2013WR014864 in citations.
Please use the identifier: http://hdl.handle.net/2128/19831 in citations.
Electromagnetic induction (EMI) systems measure the soil apparent electrical conductivity (ECa), which is related to the soil water content, texture, and salinity changes. Large-scale EMI measurements often show relevant areal ECa patterns, but only few researchers have attempted to resolve vertical changes in electrical conductivity that in principle can be obtained using multiconfiguration EMI devices. In this work, we show that EMI measurements can be used to determine the lateral and vertical distribution of the electrical conductivity at the field scale and beyond. Processed ECa data for six coil configurations measured at the Selhausen (Germany) test site were calibrated using inverted electrical resistivity tomography (ERT) data from a short transect with a high ECa range, and regridded using a nearest neighbor interpolation. The quantitative ECa data at each grid node were inverted using a novel three-layer inversion that uses the shuffled complex evolution (SCE) optimization and a Maxwell-based electromagnetic forward model. The obtained 1-D results were stitched together to form a 3-D subsurface electrical conductivity model that showed smoothly varying electrical conductivities and layer thicknesses, indicating the stability of the inversion. The obtained electrical conductivity distributions were validated with low-resolution grain size distribution maps and two 120 m long ERT transects that confirmed the obtained lateral and vertical large-scale electrical conductivity patterns. Observed differences in the EMI and ERT inversion results were attributed to differences in soil water content between acquisition days. These findings indicate that EMI inversions can be used to infer hydrologically active layers.