Faculty of Natural Resources, Sari Agricultural Science and Natural Resources University, Sari, Iran.
Civil Engineering Department, University of Ottawa, Ottawa, Ontario K1N6N5, Canada.
Sci Total Environ. 2018 Nov 15;642:1032-1049. doi: 10.1016/j.scitotenv.2018.06.130. Epub 2018 Jun 19.
Groundwater vulnerability assessment is a measure of potential groundwater contamination for areas of interest. The main objective of this study is to modify original DRASTIC model using four objective methods, Weights-of-Evidence (WOE), Shannon Entropy (SE), Logistic Model Tree (LMT), and Bootstrap Aggregating (BA) to create a map of groundwater vulnerability for the Sari-Behshahr plain, Iran. The study also investigated impact of addition of eight additional factors (distance to fault, fault density, distance to river, river density, land-use, soil order, geological time scale, and altitude) to improve groundwater vulnerability assessment. A total of 109 nitrate concentration data points were used for modeling and validation purposes. The efficacy of the four methods was evaluated quantitatively using the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC). AUC value for original DRASTIC model without any modification of weights and rates was 0.50. Modification of weights and rates resulted in better performance with AUC values of 0.64, 0.65, 0.75, and 0.81 for BA, SE, LMT, and WOE methods, respectively. This indicates that performance of WOE is the best in assessing groundwater vulnerability for DRASTIC model with 7 factors. The results also show more improvement in predictability of the WOE model by introducing 8 additional factors to the DRASTIC as AUC value increased to 0.91. The most effective contributing factor for ground water vulnerability in the study area is the net recharge. The least effective factors are the impact of vadose zone and hydraulic conductivity.
地下水脆弱性评估是衡量感兴趣区域地下水潜在污染的一种方法。本研究的主要目的是使用四种客观方法（证据权重法、香农熵法、逻辑模型树法和自助聚合法）对原始 DRASTIC 模型进行修正，为伊朗萨里-贝赫沙赫尔平原创建地下水脆弱性图。该研究还调查了添加八个附加因素（断层距离、断层密度、河流距离、河流密度、土地利用、土壤顺序、地质时间尺度和海拔）对地下水脆弱性评估的影响。共使用了 109 个硝酸盐浓度数据点进行建模和验证。使用接收者操作特征（ROC）曲线下的面积（AUC）定量评估了四种方法的功效。未对权重和速率进行任何修正的原始 DRASTIC 模型的 AUC 值为 0.50。修正权重和速率后，AUC 值分别为 0.64、0.65、0.75 和 0.81，BA、SE、LMT 和 WOE 方法的性能更好。这表明在评估具有 7 个因素的 DRASTIC 模型的地下水脆弱性方面，证据权重法的性能最佳。结果还表明，通过向 DRASTIC 引入 8 个附加因素，WOE 模型的可预测性得到了更大的提高，AUC 值增加到 0.91。在研究区域，对地下水脆弱性影响最大的因素是净补给。影响最小的因素是包气带和水力传导性的影响。
