Evaluation of surface water quality on spatiotemporal gradient using multivariate statistical techniques: A case study of river Chenab, Pakistan

Abstract

The Chenab River is experiencing deteriorating water quality due to ill-planned industrialization, population pressure, extensive agriculture, water diversion and rapid urbanization. Our study was designed to highlight the spatiotemporal variation in the water quality of the Chenab and identify potential pollution sources using multivariate analyses viz cluster analysis, discriminant analysis, principal component analysis and factor analysis. Water samples were collected from nine sampling sites along the Chenab from 2012 to 2014 during dry and wet seasons. Cluster analysis identified three zones, i.e., least stressed zone (LSZ), moderately stressed zone (MSZ) and highly stressed zone (HSZ). The discriminant analysis differentiated seven parameters (COD, Cl, SO 4 , K, Cu, Cd and Pb) and five parameters (TDS, Cl, S, F and Ca) as most significant on spatial and temporal bases, respectively. The untreated industrial and domestic wastewater, atmospheric deposition and surface runoff containing heavy metals and fertilizer along with a decrease in dilution factor due to the diversion of the water through link canals were identified as the major factors causing water quality deterioration. Therefore, the results imply that a comprehensive water management plan and implementation of environmental laws are urgently needed to protect Chenab water quality.