Articles | Volume 29, issue 13
https://doi.org/10.5194/hess-29-2837-2025
https://doi.org/10.5194/hess-29-2837-2025
Research article
 | 
07 Jul 2025
Research article |  | 07 Jul 2025

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

Gaston Mendoza, Guillaume Blanchy, Ellen Van De Vijver, Jeroen Verhegge, Wim Cornelis, and Philippe De Smedt

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Cited articles

Altdorff, D., von Hebel, C., Borchard, N., van der Kruk, J., Bogena, H. R., Vereecken, H., and Huisman, J. A.: Potential of catchment-wide soil water content prediction using electromagnetic induction in a forest ecosystem, Environ. Earth Sci., 76, 111, https://doi.org/10.1007/s12665-016-6361-3, 2017. 
Bárdossy, A. and Singh, S. K.: Robust estimation of hydrological model parameters, Hydrol. Earth Syst. Sci., 12, 1273–1283, https://doi.org/10.5194/hess-12-1273-2008, 2008. 
Binley, A.: Tools and Techniques: Electrical Methods, in: Treatise on Geophysics, 233–259, Elsevier, https://doi.org/10.1016/B978-0-444-53802-4.00192-5, 2015. 
Binley, A. and Kemna, A.: DC Resistivity and Induced Polarization Methods, edited by: Rubin, Y. and Hubbard, S. S., Hydrogeop., 50, 129–156, Springer Netherlands, https://doi.org/10.1007/1-4020-3102-5_5, 2005 
Blanchy, G., Saneiyan, S., Boyd, J., McLachlan, P., and Binley, A.: ResIPy, an intuitive open source software for complex geoelectrical inversion/modeling, Comput. Geosci., 137, 104423, https://doi.org/10.1016/j.cageo.2020.104423, 2020. 
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Short summary
This study explores two methods for predicting soil properties using the frequency domain electromagnetic induction technique in Belgium. We compared deterministic models, which often require extensive data adjustments, to empirical models. Our findings suggest that empirical models are generally more effective for soil analysis, although each method has its limitations. This research helps improve soil property prediction, crucial for agriculture and environmental management.
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