Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh.
Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh.
Sci Total Environ. 2023 Dec 15;904:166927. doi: 10.1016/j.scitotenv.2023.166927. Epub 2023 Sep 11.
Water contamination undermines human survival and economic growth. Water resource protection and management require knowledge of water hydrochemistry and drinking water quality characteristics, mechanisms, and factors. Self-organizing maps (SOM) have been developed using quantization and topographic error approaches to cluster hydrochemistry datasets. The Piper diagram, saturation index (SI), and cation exchange method were used to determine the driving mechanism of hydrochemistry in both surface and groundwater, while the Gibbs diagram was used for surface water. In addition, redundancy analysis (RDA) and a generalized linear model (GLM) were used to determine the key drinking water quality parameters in the study area. Additionally, the study aimed to utilize Explainable Artificial Intelligence (XAI) techniques to gain insights into the relative importance and impact of different parameters on the entropy water quality index (EWQI). The SOM results showed that thirty neurons generated the hydrochemical properties of water and were organized into four clusters. The Piper diagram showed that the primary hydrochemical facies were HCO-Ca (cluster 4), Cl---Na (all clusters), and mixed (clusters 1 and 4). Results from SI and cation exchange show that demineralization and ion exchange are the driving mechanisms of water hydrochemistry. About 45 % of the studied samples are classified as "medium quality"," that could be suitable as drinking water with further refinement. Cl may pose increased non-carcinogenic risk to adults, with children at double risk. Cluster 4 water is low-risk, supporting EWQI findings. The RDA and GLM observations agree in that Ca, Mg, Na, Cl and HCO all have a positive and significant effect on EWQI, with the exception of K. TDS, EC, Na+, and Ca have been identified as influencing factors based on bagging-based XAI analysis at global and local levels. The analysis also addressed the importance of SO, HCO, Cl, Mg, K+, and pH at specific locations.
水污染破坏人类生存和经济增长。水资源保护和管理需要了解水地球化学和饮用水质量特性、机制和因素。自组织映射 (SOM) 已使用量化和地形误差方法开发，用于对水地球化学数据集进行聚类。Piper 图、饱和度指数 (SI) 和阳离子交换法用于确定地表水和地下水的水地球化学驱动机制，而 Gibbs 图用于地表水。此外，冗余分析 (RDA) 和广义线性模型 (GLM) 用于确定研究区域内关键饮用水质量参数。此外，该研究旨在利用可解释人工智能 (XAI) 技术深入了解不同参数对熵水质指数 (EWQI) 的相对重要性和影响。SOM 结果表明，三十个神经元生成水的地球化学性质，并组织成四个簇。Piper 图显示主要的水地球化学相是 HCO-Ca（簇 4）、Cl---Na（所有簇）和混合（簇 1 和 4）。SI 和阳离子交换的结果表明，脱矿质和离子交换是水地球化学的驱动机制。约 45%的研究样本被归类为“中等质量”，可能适合进一步精制后作为饮用水。Cl 可能对成人构成增加的非致癌风险，儿童的风险增加一倍。簇 4 的水风险较低，支持 EWQI 的发现。RDA 和 GLM 的观察结果一致，即 Ca、Mg、Na、Cl 和 HCO 对 EWQI 均有正显著影响，除了 K。TDS、EC、Na+和 Ca 已被确定为基于全局和局部袋装 XAI 分析的影响因素。该分析还针对 SO、HCO、Cl、Mg、K+和 pH 在特定位置的重要性进行了讨论。
