Department of Nuclear Chemistry and Environmental Research Centre, Department of Earth Sciences, Ghana Atomic Energy Commission) Ghana, University of Ghana, Legon, Accra, Ghana.
Department of Earth Science, University of Ghana, Legon, Accra, Ghana.
Environ Monit Assess. 2021 Oct 25;193(11):748. doi: 10.1007/s10661-021-09514-z.
In this study, descriptive statistics, correlation matrix, multiple regression model, and geostatistical models were used to assess the contamination of groundwater with respect to trace elements in the Lower Tano river basin, Ghana, West Africa. A total number of 48 boreholes drilled across the basin with depths ranging from 18 to 60 m were used as data sources in this study. The results of the descriptive statistics showed that the average lead, iron, and aluminium concentrations exceeded the WHO permissible limits of 0.3 mg/L, 0.01 mg/L, and 0.2 mg/L respectively. Furthermore, copper, chromium, aluminium, zinc, manganese, nickel, iron, arsenic, electrical conductivity, and total dissolved solids were found to be extreme and highly positively skewed. Even though significant correlations exist among some variables, the statistical results showed that the quality of the boreholes drilled across the basin was mainly originating from geogenic and anthropogenic sources. In addition, each pair of correlated physical parameters and trace elements in the drilled boreholes were predicted using multiple regression models. Likewise, geostatistical modelling was used to assess the spatial analysis of each pair of correlated physical parameters and trace elements in the drilled boreholes. The cross-validation results revealed kriging model, as the most precise model for the spatial distribution maps for the correlated physical parameters, and correlated trace elements concentration in the boreholes drilled across the study region. The semivariogram models showed that most of the correlated physical parameters and correlated trace elements were weak moderately and strongly spatially dependent, suggesting fewer agronomic influences. The results of the spatial analysis were consistent with the multiple regression model and the Pearson correlation matrix.
本研究采用描述性统计、相关矩阵、多元回归模型和地质统计学模型，评估了西非加纳下塔诺河流域地下水微量元素的污染情况。本研究共使用了 48 个钻孔的数据，这些钻孔分布在整个流域，深度从 18 米到 60 米不等。描述性统计结果表明，铅、铁和铝的平均浓度分别超过了世界卫生组织规定的 0.3 毫克/升、0.01 毫克/升和 0.2 毫克/升的允许限值。此外，铜、铬、铝、锌、锰、镍、铁、砷、电导率和总溶解固体含量呈现极端的高度正偏态分布。尽管一些变量之间存在显著相关性，但统计结果表明，整个流域钻孔的水质主要来自地球化学和人为来源。此外，还使用多元回归模型预测了钻孔中每对相关物理参数和微量元素。同样，地质统计学模型也被用于评估钻孔中每对相关物理参数和微量元素的空间分析。交叉验证结果表明，克里金模型是用于绘制钻孔中相关物理参数和相关微量元素空间分布地图的最精确模型。半变异函数模型表明，大多数相关物理参数和相关微量元素具有较弱到中等和较强的空间依赖性，这表明农业影响较小。空间分析的结果与多元回归模型和皮尔逊相关矩阵一致。
