%0 Journal article
%A Schmäck, Jessica
%A Weihermüller, Lutz
%A Klotzsche, Anja
%A von Hebel, Christian
%A Pätzold, Stefan
%A Welp, Gerhard
%A Vereecken, Harry
%T Large‐scale detection and quantification of harmful soil compaction in a post‐mining landscape using multi‐configuration electromagnetic induction
%R 10.1111/sum.12763
%J Soil Use and Management
%V 38
%N 1

%I 
%X Fast and accurate large‐scale localization and quantification of harmfully compacted soils in recultivated post‐mining landscapes are of particular importance for mining companies and the following farmers. The use of heavy machinery during recultivation imposes soil stress and can cause irreversible subsoil compaction limiting crop growth in the long term. To overcome or guide classical point‐scale methods to determine compaction, fast methods covering large areas are required. In our study, a recultivated field of the Garzweiler mine in North Rhine‐Westphalia, Germany, with known variability in crop performance was intensively studied using non‐invasive electromagnetic induction (EMI) and electrode‐based electrical resistivity tomography (ERT). Additionally, soil bulk density, volumetric soil water content and soil textures were analysed along two transects covering different compaction levels. The results showed that the measured EMI apparent electrical conductivity (ECa) along the transects was highly correlated (R2 > .7 for different dates and depths below 0.3 m) to subsoil bulk density. Finally, the correlations established along the transects were used to predict harmful subsoil compaction within the field, whereby a spatial probabilistic map of zones of harmful compaction was developed. In general, the results revealed the feasibility of using the EMI derived ECa to predict harmful compaction. They can be the basis for quick monitoring of the recultivation process and implementation of necessary melioration to return a well‐structured soil with good water and nutrient accessibility, and rooting depths for increased crop yields to the farmers.
%U http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/9780
%~  FID GEO-LEO e-docs