Department of Geography, The University of Burdwan, Bardhaman, West Bengal, 713104, India.
Department of Disaster Management, Begum Rokeya University, Rangpur, 5400, Bangladesh.
J Environ Manage. 2022 Sep 15;318:115582. doi: 10.1016/j.jenvman.2022.115582. Epub 2022 Jun 27.
Vulnerability of groundwater is critical for the sustainable development of groundwater resources, especially in freshwater-limited coastal Indo-Gangetic plains. Here, we intend to develop an integrated novel approach for delineating groundwater vulnerability using hydro-chemical analysis and data-mining methods, i.e., Decision Tree (DT) and K-Nearest Neighbor (KNN) via k-fold cross-validation (CV) technique. A total of 110 of groundwater samples were obtained during the dry and wet seasons to generate an inventory map. Four K-fold CV approach was used to delineate the vulnerable region from sixteen vulnerability causal factors. The statistical error metrics i.e., receiver operating characteristic-area under the curve (AUC-ROC) and other advanced metrices were adopted to validate model outcomes. The results demonstrated the excellent ability of the proposed models to recognize the vulnerability of groundwater zones in the Indo-Gangetic plain. The DT model revealed higher performance (AUC = 0.97) followed by KNN model (AUC = 0.95). The north-central and north-eastern parts are more vulnerable due to high salinity, Nitrate (NO), Fluoride (F) and Arsenic (As) concentrations. Policy-makers and groundwater managers can utilize the proposed integrated novel approach and the outcome of groundwater vulnerability maps to attain sustainable groundwater development and safeguard human-induced activities at the regional level.
地下水脆弱性对地下水资源的可持续发展至关重要，特别是在淡水资源有限的印度-恒河平原沿海地区。在这里，我们旨在开发一种综合的新方法，利用水文化学分析和数据挖掘方法（即决策树（DT）和 K-最近邻（KNN）通过 k 折交叉验证（CV）技术）来划定地下水脆弱性。在旱季和雨季共采集了 110 个地下水样本，以生成一个清单图。采用了四种 K 折 CV 方法来根据十六个脆弱性成因因素划定脆弱区域。采用统计误差指标（接收者操作特征曲线下的面积（AUC-ROC）和其他高级指标）来验证模型结果。结果表明，所提出的模型具有识别印度-恒河平原地下水带脆弱性的卓越能力。DT 模型表现出更高的性能（AUC=0.97），其次是 KNN 模型（AUC=0.95）。由于高盐度、硝酸盐（NO）、氟化物（F）和砷（As）浓度，中北部和东北部地区更容易受到影响。政策制定者和地下水管理者可以利用所提出的综合新方法和地下水脆弱性图的结果，在区域层面实现可持续的地下水开发并保护人为活动。
