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Assessing groundwater quality for drinking water supply using hybrid fuzzy-GIS-based water quality index

机译：使用混合模糊GIS为基础的水质指数评估饮用水的地下水质量

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摘要

Groundwater is a vital source of freshwater in both urban and rural regions of the world. However, its injudicious abstraction and rapidly increasing contamination are posing a severe threat for sustainable water supply worldwide. Geographical Information System (GIS)-based groundwater quality evaluation using Groundwater Quality Index (GQI) has been proved to be a cost-effective tool for assessing groundwater quality and its variability at a larger scale. However, the conventional GQI approach is unable to deal with uncertainties involved in the assessment of environmental problems. To overcome this limitation, a novel hybrid framework integrating Fuzzy Logic with the GIS-based GQI is proposed in this study for assessing groundwater quality and its spatial variability. The proposed hybrid framework is demonstrated through a case study in a hard-rock terrain of Southern India using ten prominent groundwater-quality parameters measured during pre-monsoon and post-monsoon seasons. Two conventional GIS-based GQI models GQI-10 (using all the ten groundwater-quality parameters) and GQI-7 (using seven concerned/critical groundwater-quality parameters) as well as hybrid Fuzzy-GIS-based GQI (FGQI) models (using seven critical parameters) were developed for the two seasons and the results were compared. The Trapezoidal membership functions classified the model input parameters into desirable, acceptable and unacceptable classes based on the experts knowledge and water quality standards for drinking purposes. The concentrations of Ca2+, Mg2+, and SO42- in groundwater were found within the WHO desirable limits for drinking water throughout the year, while the concentrations of seven parameters (TDS, NO3--N, Na+, Cl-, K+, F- and Hardness) exceed their permissible limits during pre-monsoon and post-monsoon seasons. A comparative evaluation of GQI models revealed that the FGQI model predicts groundwater quality better than the conventional GQI-10 and GQI-7 models. GQI modeling results suggest that the groundwater of most of eastern and southern parts (similar to 60% in pre-monsoon season; similar to 90% in post-monsoon season) of the study area is unsuitable for drinking. Further, the groundwater quality deteriorates during post-monsoon seasons compared to pre-monsoon seasons, which indicates an increased influx of contaminants from different industries, mining areas, waste disposal sites and agricultural fields during monsoon seasons. This finding calls for the strict enforcement of regulations for proper handling of effluents from various contamination sources in the study area. It is concluded that the fuzzy logic-based decision-making approach (FGQI) is more reliable and pragmatic for groundwater-quality assessment and analysis at a larger scale. It can serve as a useful tool for the water planners and decision makers in efficiently monitoring and managing groundwater quality at watershed or basin scales. (C) 2020 The Author(s). Published by Elsevier Ltd.
机译：地下水是世界城乡地区的淡水的重要来源。然而，其纯正的抽象和迅速增加的污染正在为全世界的可持续供水构成严重威胁。基于地下水质量指数（GQI）的地理信息系统（GIS）被证明是一种具有成本效益的工具，用于评估地下水质量及其较大规模的可变性。然而，传统的GQI方法无法应对涉及环境问题评估的不确定性。为了克服这一限制，在本研究中提出了一种与基于GIS的GQI集成模糊逻辑的新型混合框架，用于评估地下水质量及其空间变异性。通过在印度南部的硬岩地形中使用10个突出的地下水 - 质量参数来证明拟议的混合框架，并在季风前和季风季节季节测量。基于传统的GIS基GQI模型GQI-10（使用所有十个地下水 - 质量参数）和GQI-7（使用七个有关/关键地下水 - 质量参数）以及混合模糊GIS的GQI（FGQI）模型（使用七个关键参数）是为两种赛季开发的，结果进行了比较。梯形隶属函数根据专家知识和水质标准进行饮用目的，将模型输入参数分类为可理想的，可接受和不可接受的课程。在全年饮用水的可理想限制中发现了Ca2 +，Mg2 +和SO42-在地下水中的浓度，而七个参数的浓度（TDS，NO3 - N，Na +，Cl-，K +，F-和硬度）超越季风和季风季节期间的允许极限。 GQI模型的比较评估表明，FGQI模型比传统的GQI-10和GQI-7模型更好地预测地下水质量。 GQI建模结果表明，大多数东部和南部的地下水（类似于季风季节的60％;类似于季风季节的90％），研究区域不适合饮酒。此外，与季风季节相比，季风季节后地下水质量恶化，这表明在季风季节期间增加了不同行业，采矿区，废物处理场和农业领域的污染物涌入。这一调查要求严格执行法规，以便正确处理研究区域中各种污染源的污染源。结论是，基于模糊的基于逻辑的决策方法（FGQI）更可靠，更务实地用于地下水质量评估和分析更大的规模。它可以作为水规划人员和决策者有效地监测和管理地下水质量的有用工具，在流域或盆地秤上进行地下水。 （c）2020提交人。 elsevier有限公司出版

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