Department of GIS/RS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Department of Irrigation and Drainage, Aburaihan Campus, University of Tehran, Tehran, Iran.
Environ Sci Pollut Res Int. 2021 Sep;28(34):46704-46724. doi: 10.1007/s11356-020-11406-7. Epub 2020 Nov 17.
Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment methods. The development of a robust groundwater vulnerability assessment framework for precise identification of susceptible zones may contribute to more efficient policies and plans for sustainable managements. To achieve an overall view of the groundwater pollution potential, the DRASTIC framework (Depth to the water table, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and hydraulic Conductivity) can be used for intrinsic vulnerability assessment. However, the unreliability of this index is because of its inherent drawbacks, including the weight and rating assignment subjectivity. To modify the rating range, this study recommended a new DRASTIC modification using a recently introduced Multi-Criteria Decision-Making (MCDM) method, namely the Stepwise Weight Assessment Ratio Analysis (SWARA); in addition, the Entropy and Genetic Algorithm (GA) methods were employed to alter the relative weights of DRASTIC parameters. To improve the DRASTIC index, nitrate concentration data from 50 observation wells in the study site were used. To assess the models' overall performance, the datasets obtained from new observation wells, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were studied. The experiments were carried out in the aquifer of the Qazvin Plain in Iran. The results indicated the higher performance of the modified DRASTIC framework, manifested as an increase in the AUC value from 0.58 for generic DRASTIC to 0.68 for the SWARA-Ent framework and 0.74 for the SWARA-GA framework. The application of the SWARA technique, as an effective MCDM method, resulted in the DRASTIC rating system enhancement. The generic DRASTIC optimization by integrating SWARA and GA provided an effective framework to assess groundwater vulnerability to nitrate contamination in the Qazvin Plain.
混合和集成技术可用于研究覆盖层和指数地下水脆弱性评估方法的固有不确定性。为精确识别易感区开发稳健的地下水脆弱性评估框架，可能有助于为可持续管理制定更有效的政策和计划。为了全面了解地下水污染潜力，可以使用 DRASTIC 框架（地下水位深度、净补给、含水层介质、土壤介质、地形、包气带影响和水力传导率）进行内在脆弱性评估。然而，由于其固有缺陷，包括权重和评分赋值的主观性，该指数不可靠。为了修改评分范围，本研究建议使用新的多准则决策（MCDM）方法，即逐步权重评估比率分析（SWARA），对 DRASTIC 进行修正；此外，还采用了熵和遗传算法（GA）来改变 DRASTIC 参数的相对权重。为了改进 DRASTIC 指数，使用研究区域 50 个观测井的硝酸盐浓度数据。为了评估模型的整体性能，研究了来自新观测井的数据、接收器操作特性（ROC）曲线和 ROC 曲线下的面积（AUC）。实验在伊朗卡兹温平原的含水层中进行。结果表明，修正后的 DRASTIC 框架性能更高，表现在 AUC 值从通用 DRASTIC 的 0.58 增加到 SWARA-Ent 框架的 0.68 和 SWARA-GA 框架的 0.74。SWARA 技术作为一种有效的 MCDM 方法的应用，导致 DRASTIC 评级系统得到增强。通过将 SWARA 和 GA 集成到通用 DRASTIC 中进行优化，为评估卡兹温平原硝酸盐污染地下水脆弱性提供了一个有效的框架。
