Multivariate Approach to Understanding Ganga River Water Quality in Varanasi: A Case Study

Abstract

To establish a foundation for mitigation of river water pollution and ensuring long-term water quality management, this investigation explored the spatial and temporal variability of water quality parameters of the river Ganga at Varanasi. Present study explored the monthly data collected from 14 sampling sites located along the river Ganga at Varanasi between 2017 and 2023. One-way analysis of variance (ANOVA) was used to assess the significance of spatiotemporal variations in river water quality. Additionally, cluster analysis (CA) was utilized to identify spatial groupings (clusters) within the river segment that exhibit similar water quality characteristics. A qualitative assessment of the possible causes of river water contamination and their respective contributions was conducted using principal component analysis (PCA). The two principal components (PCs) that explained the most variance in the water quality data were PC1 (46.546%) and PC2 (24.644%). While there has been a general enhancement in water quality parameters, spatial analysis revealed consistently lower water quality upstream compared to downstream locations. The study offers a comprehensive analysis to identify the precise reasons behind water contamination of river Ganga at Varanasi. © 2025 Informa UK Limited, trading as Taylor & Francis Group.