Groundwater quality assessment for drinking purpose using traditional and fuzzy-GIS-based water quality index in Gurugram District of Haryana, India

Primarily groundwater is consumed for the drinking and irrigation purpose. However, due to increasing anthropogenic activities, its quality and quantity have substantially declined over time. The focus of this study is to evaluate the pre-monsoonal groundwater quality and its spatial variability for drinking purposes in the Gurugram, Haryana, India. Ground Water quality index (GWQI) developed on the basis of the Geographical Information System is effective in the assessment of groundwater quality and its spatial variability, but it is unable to account for uncertainties related to environmental problems. Thus, a Hybrid Fuzzy-GIS-based Water Quality Index (FGQI) has been proposed for the assessment of groundwater quality. The study conducted factor analysis to identify the prime factors responsible for groundwater contamination and collected pre-monsoonal groundwater samples through primary sampling. The groundwater quality was assessed based on eight hydro geochemical parameters (pH, TDS, Calcium, Chloride, Sulfate, Fluoride, Potassium, and Sodium). The spatial interpolation of each parameter was performed using appropriate techniques, selected based on a normality test. The guidelines of the World Health Organization and Bureau of Indian Standard were incorporated in the development of GWQI and FGQI, respectively. Correlation analysis was performed to determine the best fuzzy overlay technique for FGQI, and the Fuzzy GAMMA technique with gamma equal to 0.9 was selected. Finally, the GWQI and FGQI were classified into three classes: unsuitable, moderate suitable, and suitable using “natural break”. A higher index indicates a higher water quality. The results show that the groundwater in the central part of Gurugram is suitable for drinking, while it is not suitable in the extreme north, south-east, and western regions. In conclusion, this study finds that FGQI effectively assesses the groundwater quality in the region better than GWQI.