Digital mapping of buried soil horizons using 2D and pseudo-3D geoelectrical measurements in a ground moraine landscape

  • The identification of buried soil horizons in agricultural landscapes helps to quantify sediment budgets and erosion-related carbon dynamics. High-resolution mapping of buried horizons using conventional soil surveys is destructive and time consuming. Geoelectrical sensors can offer a fast and non-destructive alternative for determining horizon positions and properties. In this paper, we compare the suitability of several geoelectrical methods for measuring the depth to buried horizons (Apb, Ahb and Hab) in the hummocky ground moraine landscape of northeastern Germany. Soil profile descriptions were developed for 269 locations within a 6-ha experimental field "CarboZALF-D". A stepwise linear discriminant analysis (LDA) estimated the lateral position of the buried horizons using electromagnetic induction data and terrain attributes. To predict the depth of a buried horizon, multiple linear regression (MLR) was used for both a 120-m transect and a 0.2-ha pseudo-three-dimensional (3D) area. At these scales, apparent electricalThe identification of buried soil horizons in agricultural landscapes helps to quantify sediment budgets and erosion-related carbon dynamics. High-resolution mapping of buried horizons using conventional soil surveys is destructive and time consuming. Geoelectrical sensors can offer a fast and non-destructive alternative for determining horizon positions and properties. In this paper, we compare the suitability of several geoelectrical methods for measuring the depth to buried horizons (Apb, Ahb and Hab) in the hummocky ground moraine landscape of northeastern Germany. Soil profile descriptions were developed for 269 locations within a 6-ha experimental field "CarboZALF-D". A stepwise linear discriminant analysis (LDA) estimated the lateral position of the buried horizons using electromagnetic induction data and terrain attributes. To predict the depth of a buried horizon, multiple linear regression (MLR) was used for both a 120-m transect and a 0.2-ha pseudo-three-dimensional (3D) area. At these scales, apparent electrical conductivity (ECa), electrical resistivity (ER) and terrain attributes were used as independent variables. The LDA accurately predicted Apb- and Ahb-horizons (a correct classification of 93%). The LDA of the Hab-horizon had a misclassification of 24%, which was probably related to the smaller test set and the higher depth of this horizon. The MLR predicted the depth of the Apb-, Ahb- and Hab-horizons with relative root mean square errors (RMSEs) of 7, 3 and 13%, respectively, in the pseudo-3D area. MLR had a lower accuracy for the 2D transect compared to the pseudo-3D area. Overall, the use of LDA and MLR has been an efficient methodological approach for predicting buried horizon positions. Highlights The suitability of geoelectrical measurements for digital modelling of diagnostic buried soil horizons was determined. LDA and MLR were used to detect multiple horizons with geoelectrical devices and terrain attributes. Geoelectrical variables were significant predictors of the position of the target soil horizons. The use of these tested digital technologies gives an opportunity to develop high-resolution soil mapping procedures.show moreshow less

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Author details:Ilona van der KroefORCiD, Sylvia KoszinskiORCiD, Michael GrinatGND, Marijn van der MeijORCiD, Wilfried Hierold, Wolfgang SüdekumGND, Michael SommerGND
ISSN:1351-0754
ISSN:1365-2389
Title of parent work (English):European journal of soil science : EJSS
Publisher:Wiley
Place of publishing:Hoboken
Publication type:Review
Language:English
Date of first publication:2019/05/17
Completion year:2020
Release date:2021/06/03
Tag:EM38DD; colluvium depth modelling; electrical conductivity; electrical resistivity tomography; electromagnetic induction; linear discriminant analysis; linear regression; moraine soil landscape
Volume:71
Issue:1
Page number:17
First page:10
Last Page:26
Funding institution:Federal Ministry of Food and Agriculture (BMEL) Germany; Ministry of Science; Research and Culture (MWFK), State of Brandenburg, Germany
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie
Peer review:Referiert