Login

Proceedings

Find matching any: Reset
Add filter to result:
Development of a Soil ECa Inversion Algorithm for Topsoil Depth Characterization
1E. Leksono, 1V. Adamchuk, 2W. Ji, 1M. Leclerc
1. Bioresource Engineering Dept., McGill University, Ste-Anne-de-Bellevue, QC, Canada
2. Soil and Environment Dept., Swedish University of Agricultural Sciences, Skara, Sweden

Electromagnetic induction (EMI) proximal soil sensor systems can deliver rapid information about soil. One such example is the DUALEM-21S (Dualem, Inc. Milton, Ontario, Canada). EMI sensors measure soil apparent electrical conductivity (ECa) corresponding to different depth of investigation depending on the instrument configuration. The interpretation of the ECa measurements is not straightforward and it is often site-specific. Inversion is required to explore specific depths. This inversion process is an “ill-posed” problem which might lead to non-existing, or non-unique solutions. Commonly, a complicated regularization method is chosen to tackle this problem. In this paper, a simple exhaustive “brute-force” method was developed to characterize soil layering depths and their corresponding ECa values. A two-layer soil ECamodel was used to depict the depth of the topsoil layer and its corresponding ECa value. The two-layer model represents a shallow (topsoil) and deeper subsoil depths. From the high density DUALEM-21S input data, the “brute-force” algorithm was successfully converged to the minimum mean squared error (MSE) for each depth increment. The software’s GUI was intuitive and provided an up to date progress of the calculations. This algorithm has been tested successfully to determine the topsoil and subsoil ECa values together with muck soil layer depth on the 25-ha field near Naperville, Quebec, Canada. 

Keyword: electromagnetic induction, soil ECa, inversion, topsoil depth