Bertol Victor Flanclin Nouwa Ngouateu, Jean Victor Kenfack, Lucas Kegni, Hallelua De Tambou Tsobmo Baleba Ii
Department of Earth Science, Faculty of Science, University of Dschang, Cameroon.
Heliyon. 2024 Apr 15;10(8):e29589. doi: 10.1016/j.heliyon.2024.e29589. eCollection 2024 Apr 30.
This study aims to predict specific soil parameters based on quantitative and qualitative correlations between electrical and geotechnical data. A total of 21 geotechnical boreholes followed by sampling, 21 light dynamic penetrometer tests, and 76 vertical electrical sounding surveys were carried out in Maroua 1st. The electrical resistivity data of the soil layers were obtained through 1D and 2D inversions of the ERT surveys. The geotechnical data were obtained from field tests and laboratory experiments. The statistical analysis of the entire dataset indicates that most of the samples are clay formations, as demonstrated by the means of variables and low variance coefficients, enabling qualitative identification. The distribution analysis of the parameters confirms the complexity of the physical characteristics of soils and the measurement procedures for each parameter. The Spearman's rank correlation matrix indicates that these observations can be used to propose predictive models for free swelling, allowable stress, natural water content, and electrical resistivity. Correlations between free swelling (εg) and other variables are not significant, as the degree of significance is lower than the fixed limit, except for models εg - W (R = 0.94), εg - ρ (Ώ.m) (R = 0.803), and εg - σ (R = 0.757). Grouping variables in multiple linear regression enables the development of a mathematical model. The predicted values of εg from this model demonstrate good agreement with the measured values for a validity domain of 0-16 %. The soil's natural water content has a strong correlation (R = 0.80 and rs = - 0.87) with electrical resistivity, meaning that an increase in water content results in a decrease in electrical resistivity. The permissible stress σ has a strong correlation (R = 0.89 and rs = 0.85) with electrical resistivity. This indicates that changes in soil electrical resistivity are associated with soil stiffness.
本研究旨在基于电学数据与岩土工程数据之间的定量和定性相关性来预测特定的土壤参数。在马鲁阿一区共进行了21个岩土钻孔并随后取样、21次轻型动力触探试验以及76次垂直电测深调查。通过ERT调查的一维和二维反演获得了土层的电阻率数据。岩土工程数据则来自现场测试和实验室实验。对整个数据集的统计分析表明，如变量均值和低变异系数所示，大多数样本为粘土地层，从而能够进行定性识别。参数的分布分析证实了土壤物理特性以及每个参数测量程序的复杂性。斯皮尔曼等级相关矩阵表明，这些观测结果可用于提出自由膨胀、许用应力、天然含水量和电阻率的预测模型。自由膨胀（εg）与其他变量之间的相关性不显著，因为显著性程度低于固定限值，除了模型εg - W（R = 0.94）、εg - ρ（Ω.m）（R = 0.803）和εg - σ （R = 0.757）。在多元线性回归中对变量进行分组可建立一个数学模型。该模型预测的εg值与测量值在0 - 16%的有效范围内显示出良好的一致性。土壤的天然含水量与电阻率具有很强的相关性（R = 0.80，rs = - 0.87），这意味着含水量增加会导致电阻率降低。许用应力σ与电阻率具有很强的相关性（R = 0.89，rs = 0.85）。这表明土壤电阻率的变化与土壤刚度相关。
