地下水脆弱性评估如今已发展成为适当保护和管理地下水的重要工具,而DRASTIC方法是应用最广泛的漏洞评估方法之一。然而,DRASTIC方法的高度不确定性主要与分配参数评级和权重的主观性有关,这促使许多研究人员应用各种方法来提高效率。在这种情况下,在本研究中,实施了不同的技术,目的是修改DRASTIC框架,从而提高其在Bouficha含水层中地下水脆弱性评估的性能,突尼斯。在第一阶段,土地利用类型(L)作为典型DRASTIC框架中的附加参数,因此考虑到人为活动对地下水脆弱性的影响。随后,通过应用统计方法(DRASTIC-L-SA)和遗传算法(GA)(DRASTIC-L-GA)对已开发的DRASTIC-L框架的评级和加权系统进行了修改,试图研究和比较线性和非线性修改.为了评估各种漏洞框架,脆弱性值与硝酸盐浓度之间的相关性,表示为斯皮尔曼等级相关系数(ρ)和相关指数(CI),被检查过。结果表明,通过应用完全基于GA的优化程序开发的DRASTIC-L-GA框架在使用的性能指标方面提供了最高值,使其最适合研究区域。此外,当采用典型的DRASTIC框架而不是经过修改的框架时,发现所研究的含水层不太容易受到污染,得出的结论是,前者大大低估了研究区域的污染潜力。
Groundwater vulnerability assessment has nowadays evolved into an essential tool towards proper groundwater protection and management, while the DRASTIC method is included among the most widely applied vulnerability assessment methods. However, the high uncertainty of the DRASTIC method mainly associated with the subjectivity in assigning parameters ratings and weights has driven many researchers to apply various methods for improving its efficiency. In this context, in the present study, different techniques were implemented with the aim of modifying the DRASTIC framework and thus enhancing its performance for groundwater vulnerability assessment in the Bouficha aquifer, Tunisia. In a first stage, the land use type (L) was incorporated as an additional parameter in the typical DRASTIC framework, thus taking into consideration the impact of anthropogenic activities on groundwater vulnerability. Subsequently, the rating and weighting systems of the developed DRASTIC-L framework were modified through the application of statistical methods (DRASTIC-L-SA) and genetic algorithms (GA) (DRASTIC-L-GA) in an attempt to investigate and compare both linear and nonlinear modifications. To evaluate the various vulnerability frameworks, correlation between vulnerability values and nitrate concentrations, expressed as Spearman\'s rank correlation coefficient (ρ) and Correlation Index (CI), was examined. The results revealed that the DRASTIC-L-GA framework developed by applying a fully GA-based optimization procedure provided the highest values in terms of the performance metrics used, making it the most suitable for the study area. In addition, the aquifer under study was found to be less vulnerable to pollution when employing the typical DRASTIC framework instead of the modified ones, leading to the conclusion that the former substantially underestimates pollution potential in the study area.