Department of GIS/RS, Faculty of Natural resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Department of Irrigation and Drainage, Abouraihan Campus, University of Tehran, Tehran, Iran.
Environ Sci Pollut Res Int. 2019 Jul;26(21):21808-21827. doi: 10.1007/s11356-019-04853-4. Epub 2019 May 27.
Effects of pollution caused by seawater intrusion into groundwater in coastal aquifers cannot be ignored. Identification of areas exposed to this pollution by preparing vulnerability maps is one way of preventing aquifer pollution. In its primary section, the present study compared three different index ranking methods of DRASTIC, GALDIT, and SINTACS to select an optimal model for determining vulnerability of the Gharesoo-Gorgan Rood coastal aquifer. Initial results led to selection of the GALDIT model for vulnerability assessment of the selected coastal aquifer. Since this type of models use a rating system, the model must be modified and optimized in various regions to show the vulnerable areas more accurately. In the next step, and for the first time, the ratings in this index were modified using the Wilcoxon nonparametric statistical method and its weights were optimized employing particle swarm optimization (PSO) and single-parameter sensitivity analysis (SPSA) methods. Finally, in order to select the best hybrid model, the total dissolved solids (TDS) parameter was used to determine correlation coefficients. Results indicated that the GALDT model modified by the Wilcoxon-PSO method has the strongest correlation (0.77) with the TDS parameter. Moreover, the correlations of the Wilcoxon-GALDIT and Wilcoxon-SPSA models were 0.66 and 0.73, respectively. Final results of the Wilcoxon-PSO model revealed that the northwestern and western areas of the study region needed considerable protection against pollution. In general, we can conclude that by combining statistical, mathematical, and metaheuristic methods, we can obtain more accurate results for preparing vulnerability maps.
海水入侵地下水造成的污染影响不容忽视。通过编制脆弱性图来识别易受这种污染的区域，是防止含水层污染的一种方法。本研究在初步部分比较了 DRASTIC、GALDIT 和 SINTACS 三种不同的指数排名方法，以选择一种确定 Gharesoo-Gorgan Rood 沿海含水层脆弱性的最优模型。初步结果导致选择 GALDIT 模型来评估选定的沿海含水层的脆弱性。由于这类模型使用评级系统，因此必须在不同地区对模型进行修改和优化，以更准确地显示脆弱区域。在下一步中，首次使用 Wilcoxon 非参数统计方法修改了该指数中的评级，并使用粒子群优化 (PSO) 和单参数敏感性分析 (SPSA) 方法对其权重进行了优化。最后，为了选择最佳的混合模型，使用总溶解固体 (TDS) 参数来确定相关系数。结果表明，经过 Wilcoxon-PSO 方法修正的 GALDT 模型与 TDS 参数具有最强的相关性 (0.77)。此外，Wilcoxon-GALDIT 和 Wilcoxon-SPSA 模型的相关性分别为 0.66 和 0.73。Wilcoxon-PSO 模型的最终结果表明，研究区域的西北部和西部需要对污染进行相当大的保护。总的来说，我们可以得出结论，通过结合统计、数学和元启发式方法，可以为编制脆弱性图获得更准确的结果。
