Multivariate statistical analysis to assess the surface water quality of a snow and glacier-fed river: A case from Alaknanda River basin

The water quality of Himalayan rivers has declined due to human activities, untreated effluent discharge, and poor sewage and drainage systems. The current study aimed to assess the water quality of these rivers using multivariate statistical analysis throughout four seasons. The analyses of 44 surface water samples taken during the monsoon, winter, spring, and summer seasons are well within the ranges acceptable for drinking and domestic use after the sedimentation. The suspended soils and turbidity are highly correlated and affect the water quality index (WQI). The WQI of headwater streams is good during low water flow seasons and poor during high water flow seasons. This is due to the number of melting glaciers and suspended solids/turbidity. Principal component analysis shows that in all the seasons, human activities such as road-cutting projects across the river and natural causes such as intense rainfall and melting of moraine-filled glaciers both impact the WQI. The findings of this study provide important information for future research and policy decisions aimed at improving the water quality of the Himalayan rivers. HIGHLIGHTS Water quality indices were calculated from physicochemical parameters across 15 sampling locations and four seasons (monsoon, winter, spring, and summer).; A strong positive correlation was observed between TSS-Turbidity, TA-TH, TSS-TA, and TSS-TH during different seasons.; Winter and spring showed WQI values ranging from good to poor, with pH, EC, TA, TH, and DO having less impact on WQI compared to turbidity and TSS.; PCA was used to identify latent variables affecting water quality parameters across different seasons.; The findings of this study provide important information for future research and policy decisions aimed at improving the water quality of the Himalayan rivers.;