Reports of environmental problems occasioned from gold mining activities had prompted the groundwater vulnerability prediction/assessment of the study area. This was with a view to identifying factors responsible for the probability of groundwater contamination as well as developing empirical (LR) model and map that predict the probability of occurrence of contaminant(s) with respect to threshold level in the groundwater resources in the study area. In order to achieve the objectives of the study, logistic regression was applied to independent variables obtained from results of the analysis of remote sensing and geophysical data on one hand and dependent variables obtained from analysis of water samples on the other hand. The results of the analysis obtained from water chemistry established that all the physio-chemical parameters and major metallic ions are within the permissible limit. However, zinc concentration (Zn), being the only dependent variable that had two categorical outcomes, was the contaminant utilized for the study. Similarly, only five (5) independent (predictive) variables, which are percent clay in soil, drainage, slope, unsaturated zone thickness, and total longitudinal conductance, were established to have good correlation and statistically significant with the dependent variable, the contaminant, and thus utilized in logistic regression model development. The quantitative assessment of the developed model established that the overall model prediction accuracy was 85.7% suggesting that the model had a very good fit. The probability prediction model was also accurate and reliable with percentage reliability established to be 90%. In conclusion, it is evident from the results obtained from the study that since the model developed was assessed to be accurate and reliable, the model, and hence the technique, can be replicated in another area of similar geologic condition.

中文翻译：

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逻辑回归分析在金矿开采环境地下水脆弱性预测中的应用：以尼日利亚西南部伊莱莎金矿开采区为例。

金矿开采活动引起的环境问题报告促使研究区的地下水脆弱性预测/评估。目的是找出造成地下水污染可能性的因素，并开发经验模型（LR）和地图，以预测研究区域地下水资源中阈值水平的污染物发生概率。为了实现研究目的，将逻辑回归一方面应用于从遥感和地球物理数据的分析结果获得的自变量，另一方面对从水样分析获得的因变量进行了逻辑回归。从水化学获得的分析结果表明，所有理化参数和主要金属离子均在允许的范围内。然而，锌浓度（Zn）是唯一有两个分类结果的因变量，是用于研究的污染物。同样，只有五（5）个独立的（预测性）变量，即土壤，排水，坡度，非饱和带厚度和总纵向电导率中的粘土百分比，与因变量，污染物，因此可以用于逻辑回归模型开发。对已开发模型的定量评估表明，总体模型预测准确性为85.7％，表明该模型非常适合。概率预测模型也是准确可靠的，可靠性百分比确定为90％。总而言之，从该研究获得的结果中可以明显看出，由于所开发的模型被评估为准确可靠，因此该模型及其技术可以在具有相似地质条件的另一个区域进行复制。