Quantitative soil characterization using frequency domain electromagnetic induction method in heterogeneous fields

Abstract. The frequency domain electromagnetic induction (FDEM) method is a widely used tool for geophysical soil exploration. Field surveys using FDEM provide apparent electrical conductivity (ECa), which is typically used for qualitative interpretations. Quantitative estimations of soil properties remain challenging, especially in heterogeneous fields. Quantitative approaches are either based on deterministic or stochastic modeling. While the deterministic approach faces limitations related to instrumental drift, data calibration, inversion, and pedophysical modeling, the stochastic approach requires developing a local model, which involves extensive field sampling.

This study aims to evaluate the effectiveness of the FDEM modelling based on either a deterministic or stochastic approach, identify its limitations, and search for optimal field protocols. We provide practical guidelines for end-users to quantitatively predict soil water content, bulk density, clay content, cation exchange capacity, and water EC in heterogeneous fields.

Two field surveys were conducted in Belgium, where FDEM data was collected using Dualem-421S and Dualem-21HS sensors, along with data taken from electrical resistivity tomography (ERT) measurements and an impedance moisture probe, and soil sampling.

A comprehensive sensitivity analysis revealed that deterministic modeling procedures could not predict water content more accurately than a mean value approximation (negative R²). This analysis also highlighted the sensitivity of the minimization method used in FDEM data inversion and the applied pedophysical model. Stochastic modeling, which does not require FDEM data calibration or inversion, outperformed the deterministic approach. However, its prediction accuracy is limited, particularly if soil sample depth is not considered.