As the run-of-river (RoR) hydropower projects remain understudied, we conducted this study to understand how these projects affect the hydro-chemical dynamics and water quality index (WQI) of the Sindh River in the Kashmir Himalayas. We used multivariate statistical techniques and WQI to identify the spatiotemporal dynamics of 18 physico-chemical parameters from 11 sampling stations distributed along the length of river Sindh from December 2017 to December 2019. The dataset was classified into three groups using hierarchical cluster analysis based on similarities between hydro-chemical characteristics, and the results were confirmed by discriminant analysis. Wilk's quotient distribution further showed that ions, nutrients, free carbon dioxide, water temperature, and pH contributed to the formation of clusters. Principle component analysis revealed that the chloride (Cl-), total phosphorus (TP), ortho-phosphorus (PO4-P), nitrate-nitrogen (NO3-N), nitrite-nitrogen (NO2-N), and sulfate ion (SO42-) are significant factors that influence the water quality. Furthermore, our results suggest that diverting water for RoR operation did not significantly raise the WQI value to the point where water in the bypassed reaches could be declared unfit for drinking. Our analysis concluded that inclusive assessments are vital for framing policies on expanding RoR hydropower in the region.
Keywords: Multivariate techniques; Pollution; Run-of-river hydropower plants; Water.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.