Department of Agricultural and Bioresources Engineering, Faculty of Engineering, Nnamdi Azikiwe University, Awka, Nigeria.
Research Fellow, Future Africa, University of Pretoria, Pretoria, South Africa.
Environ Sci Pollut Res Int. 2023 Apr;30(17):49856-49874. doi: 10.1007/s11356-023-25447-1. Epub 2023 Feb 14.
This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that net recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98% of the study area falls into a very high vulnerability class, 31.90% falls into a high vulnerability, 23.52% falls into the average vulnerability, 21.75% falls into a low vulnerability, and 9.85% falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution.
本研究采用改进的 DRASTIC 模型评估地下水污染的敏感性。通过一个新的基于 DRASTIC 模型的脆弱性指数,利用结合了区间粗糙数(IRN)、决策试验与评价实验室(DEMATEL)和分析网络过程(ANP)的新型混合多准则决策(MCDM)模型,综合考虑了关键水文地质因素之间的相互关系(并确定其相对权重)。通过使用 GIS 处理空间数据的灵活性,对水文地质因素的专题图层进行了划分,并对 DRASTIC 模型进行了改进。混合 MCDM 模型的结果表明,净补给(一个关键的水文地质因素)具有最高的优先级,权重为 0.1986。相比之下,地形因素的优先级最低,权重为 0.0497。尼日利亚阿南布拉州的案例研究验证了混合模型的有效性。生成的脆弱性图显示,研究区有 12.98%属于极高脆弱性类别,31.90%属于高脆弱性类别,23.52%属于中等脆弱性类别,21.75%属于低脆弱性类别,9.85%属于极低脆弱性类别。此外,硝酸盐浓度被用来评估地下水污染的程度。基于观测到的硝酸盐浓度,对改进的 DRASTIC 模型进行了验证,并与传统的 DRASTIC 模型进行了比较;有趣的是,改进的 DRASTIC 模型的空间模型表现更好。因此,这项研究对于环境监测和实施适当的管理干预措施以保护地下水资源免受各种污染源的污染至关重要。