Articles | Volume 11, issue 2
https://doi.org/10.5194/soil-11-629-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/soil-11-629-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the link between cation exchange capacity and magnetic susceptibility
Gaston Matias Mendoza Veirana
CORRESPONDING AUTHOR
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, geb. B, 9000 Ghent, Belgium
Hana Grison
Institute of Geophysics of the Czech Academy of Sciences, Boční II/1401, 14100 Prague 4, Czech Republic
Jeroen Verhegge
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, geb. B, 9000 Ghent, Belgium
Department of Archaeology, Ghent University, Sint-Pietersnieuwstraat 35-UFO, 9000 Ghent, Belgium
Wim Cornelis
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, geb. B, 9000 Ghent, Belgium
Philippe De Smedt
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, geb. B, 9000 Ghent, Belgium
Department of Archaeology, Ghent University, Sint-Pietersnieuwstraat 35-UFO, 9000 Ghent, Belgium
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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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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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To assess the impact of the groundwater table (GWT) depth on soil moisture and C mineralization, we designed a laboratory setup using 200 cm undisturbed soil columns. Surprisingly, the moisture increase induced by a shallower GWT did not result in enhanced C mineralization. We presume this upward capillary moisture effect was offset by increased C mineralization upon rewetting, particularly noticeable in drier soils when capillary rise affected the topsoil to a lesser extent due to a deeper GWT.
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Measurements of soil water retention properties play an important role in a variety of societal issues that depend on soil water conditions. However, there is little concern about the consistency of these measurements between laboratories. We conducted an interlaboratory comparison to assess the reproducibility of the measurement of the soil water retention curve. Results highlight the need to harmonize and standardize procedures to improve the description of unsaturated processes in soils.
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Short summary
This study explores the link between soil magnetic susceptibility and cation exchange capacity (CEC) to improve prediction models for CEC in European soils. The results show that magnetic susceptibility significantly enhances CEC prediction in sandy soils, achieving high accuracy (R2 = 0.94). This offers a rapid, cost-effective way to estimate CEC, emphasizing the value of geophysical data integration in soil assessment.
This study explores the link between soil magnetic susceptibility and cation exchange capacity...
Special issue