Abstract. This study explores the relationship between soil magnetic susceptibility (𝜅) and cation exchange capacity (𝐶𝐸𝐶) across diverse European soils, aiming to enhance pedotransfer functions (PTFs) for soil 𝐶𝐸𝐶 using near-surface electromagnetic geophysics. We hypothesize that soil 𝜅, can improve the prediction of 𝐶𝐸𝐶 by reflecting the soil’s mineralogical composition, particularly in sandy soils. We collected data from 49 soil samples in vertical profiles across Belgium, the Netherlands, and Serbia, including 𝜅 in field conditions (𝜅^∗), low and high frequency 𝜅 in the laboratory, in-site electrical conductivity (𝜎), iron content, soil texture, humus content, bulk density, water content, water pH, and 𝐶𝐸𝐶. We used these properties as features to develop univariable and multivariable (in pairs) polynomial regressions to predict 𝐶𝐸𝐶 for sandy and clayey soils. Results indicate that 𝜅^∗ significantly improves 𝐶𝐸𝐶 predictions in sandy soils, independent of clay content, with a combined 𝜅^∗ - 𝜎 model achieving the highest predictive performance (R² = 0.94). In contrast, laboratory-measured 𝜅 was less effective, likely due to sample disturbance. This study presents a novel 𝐶𝐸𝐶 PTF based on 𝜎 and 𝜅^∗, offering a rapid, cost-effective method for estimating 𝐶𝐸𝐶 in field conditions. While our findings underscore the value of integrating geophysical measurements into soil characterization, further research is needed to refine the 𝜅- 𝐶𝐸𝐶 relationship and develop a more widely applicable model.

中文翻译：

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探索阳离子交换容量与磁化率之间的联系


摘要。本研究探讨了不同欧洲土壤的土壤磁化率 （κ） 和阳离子交换能力 （CEC） 之间的关系，旨在使用近地表电磁地球物理学增强土壤 CEC 的土壤转移函数 （PTF）。我们假设土壤 κ 可以通过反映土壤的矿物组成来改善 CEC 的预测，尤其是在沙质土壤中。我们从比利时、荷兰和塞尔维亚的 49 个垂直剖面土壤样本中收集了数据，包括田间条件下的 κ （κ^∗）、实验室中的低频和高频 κ、现场电导率 （σ）、铁含量、土壤质地、腐殖质含量、堆积密度、含水量、水 pH 值和 CEC。我们使用这些属性作为特征来开发单变量和多变量（成对）多项式回归，以预测沙质和粘土质土壤的 CEC。结果表明，κ^∗ 显着改善了沙质土壤中 CEC 的预测，与粘土含量无关，联合 κ^∗ - σ 模型实现了最高的预测性能 （R² = 0.94）。相比之下，实验室测量的 κ 效果较差，可能是由于样品干扰。本研究提出了一种基于 σ 和 κ 的新型 CEC PTF，^∗提供了一种快速、经济高效的方法来估计现场条件下的 CEC。虽然我们的研究结果强调了将地球物理测量整合到土壤表征中的价值，但需要进一步的研究来完善 κ-CEC 关系并开发更广泛适用的模型。