Evaluation of Surface Water Quality through Water Quality Index Model and Multivariate Statistical Techniques

Abstract

Abstract The Betwa River Basin, a subbasin of the Yamuna, is the oldest flowing water system in Central India. Factor analysis and principal component analysis (FA/PCA) were multivariate statistical techniques used to extract three and four varimax factors that explained 96.408 and 100.00 percent of the total variance in water quality, respectively. Cluster analysis (CA) categorizes observed items into distinct quality categories based on correlations between stations and years. Point industrial/sewage effluents, non-point runoff from arable land and erosion, and natural source pollution are all factors that contribute to the pollution of the Betwa River, a mineral component of the water. As a result, water quality is threatened or impaired, and conditions often depart from natural or desirable levels at Rajghat, Garrauli, Mohana, and Shahijina stations. According to the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), the water quality ranking at the Rajghat and Mohana stations corresponds to fair ecological status. However, the Garrauli and Shahijina stations' surface water has marginal water quality status. From 1985 to 2018, the Shahijina had the most considerable load of nutrients and organic matter, as established by the CCME-WQI and by comparing the water quality data. A thorough examination revealed a fluctuating trend in the Betwa River pollution, particularly at all stations. Results indicate that between 1985 and 2018, the only defense mechanism of the river was the auto purification mechanism, which is strongly influenced by the drought, point resource of pollution, and extreme meteorological events that probably cause these fluctuations.