Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran.
Department of Civil and Architectural Engineering, Sultan Qaboos University, Muscat, Oman.
Environ Sci Pollut Res Int. 2022 Aug;29(37):55845-55865. doi: 10.1007/s11356-022-19620-1. Epub 2022 Mar 23.
Groundwater management is essential in water and environmental engineering from both quantity and quality aspects due to the growing urban population. Groundwater vulnerability evaluation models play a prominent role in groundwater resource management, such as the DRASTIC model that has been used successfully in numerous areas. Several studies have focused on improving this model by changing the initial parameters or the rates and weights. The presented study investigated results produced by the DRASTIC model by simultaneously exerting both modifications. For this purpose, two land use-based DRASTIC-derived models, DRASTICA and susceptibility index (SI), were implemented in the Shiraz plain, Iran, a semi-arid region and the primary resource of groundwater currently struggling with groundwater pollution. To develop the novel proposed framework for the progressive improvement of the mentioned rating-based techniques, three main calculation steps for rates and weights are presented: (1) original rates and weights; (2) modified rates by Wilcoxon tests and original weights; and (3) adjusted rates and optimized weights using the genetic algorithm (GA) and particle swarm optimization (PSO) algorithms. To validate the results of this framework applied to the case study, the concentrations of three contamination pollutants, NO, SO, and toxic metals, were considered. The results indicated that the DRASTICA model yielded more accurate contamination concentrations for vulnerability evaluations than the SI model. Moreover, both models initially displayed well-matched results for the SO concentrations, specifically 0.7 for DRASTICA and 0.58 for SI, respectively. Comparatively, the DRASTICA model showed a higher correlation with NO concentrations (0.8) than the SI model (0.6) through improved steps. Furthermore, although both original models demonstrated less correlation with toxic metal concentrations (0.05) compared to SO and NO concentrations, the DRASTICA and SI models with modified rates and optimized weights exhibited enhanced correlation with toxic metals of about 0.7 and 0.2, respectively.
地下水管理在水和环境工程中至关重要，从数量和质量两方面来看，这都是由于城市人口的增长所导致的。地下水脆弱性评估模型在地下水资源管理中起着重要作用，例如 DRASTIC 模型，该模型已在许多地区成功应用。许多研究都集中在通过改变初始参数或速率和权重来改进该模型。本研究通过同时施加这两种修改，对 DRASTIC 模型的结果进行了研究。为此，在伊朗半干旱地区的 Shiraz 平原实施了两种基于土地利用的 DRASTIC 衍生模型，即 DRASTICA 和易感性指数 (SI)，该地区目前正面临地下水污染问题，地下水是其主要的水资源。为了提出一种改进基于评级技术的新框架，本研究提出了用于速率和权重的三个主要计算步骤：（1）原始速率和权重；（2）通过 Wilcoxon 检验和原始权重修改的速率；（3）使用遗传算法 (GA) 和粒子群优化 (PSO) 算法调整速率和优化权重。为了验证该框架应用于案例研究的结果，考虑了三种污染污染物（NO、SO 和有毒金属）的浓度。结果表明，DRASTICA 模型在脆弱性评估方面比 SI 模型产生了更准确的污染浓度。此外，两个模型最初对 SO 浓度的结果都非常匹配，分别为 DRASTICA 的 0.7 和 SI 的 0.58。相比之下，通过改进步骤，DRASTICA 模型与 NO 浓度（0.8）的相关性更高，而 SI 模型为 0.6。此外，尽管原始模型与有毒金属浓度的相关性较低（与 SO 和 NO 浓度相比分别为 0.05），但修改速率和优化权重后的 DRASTICA 和 SI 模型与有毒金属的相关性增强，分别为约 0.7 和 0.2。
