This study proposes the evaluation of GIS-based groundwater quality index (GQI) and spatial variability with a hybrid system that combines Fuzzy Logic with GIS-based GQI. A case study in the semi-arid area of Punjab, namely Rupnagar, illustrates the proposed hybrid outline. Two GIS-based GQI models GQI-10 (using ten water quality parameters (WQPs)) and GQI-6 (using six “apprehensive/crucial” WQPs), as well as hybrid Fuzzy Logic GIS-based GQI (FGQI) (using six crucial WQPs) models, were developed using trapezoidal membership functions and rule sets based on expert's knowledge. Performance comparison of GQI models showed that the FGQI model predicts improved groundwater quality than the GQI-10 and GQI-6. FGQI model variance, RMSE, and R² values are 84.25, 6.49, 0.89, respectively. Results have shown that the developed FGQI model is successful and GQI modelling suggests the use of northern and central groundwater without treatment to be unsafe for drinking purposes.

中文翻译：

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使用 GQI 和模糊逻辑方法的基于 GIS 的地下水质量评估

本研究提出了使用模糊逻辑与基于 GIS 的 GQI 相结合的混合系统来评估基于 GIS 的地下水质量指数 (GQI) 和空间变异性。旁遮普半干旱地区 Rupnagar 的案例研究说明了拟议的混合轮廓。两个基于 GIS 的 GQI 模型 GQI-10（使用十个水质参数 (WQP)）和 GQI-6（使用六个“忧虑/关键”WQP），以及基于混合模糊逻辑 GIS 的 GQI (FGQI)（使用六个关键 WQPs) 模型是使用梯形隶属函数和基于专家知识的规则集开发的。GQI 模型的性能比较表明，FGQI 模型预测的地下水质量优于 GQI-10 和 GQI-6。FGQI 模型方差、RMSE 和R ² 值分别为 84.25、6.49、0.89。结果表明，开发的 FGQI 模型是成功的，而 GQI 模型表明，未经处理就使用北部和中部地下水不安全用于饮用目的。