Water Quality Assessment of River Soan (Pakistan) and Source Apportionment of Pollution Sources Through Receptor Modeling.

The present study was designed to determine the spatiotemporal patterns in water quality of River Soan using multivariate statistics. A total of 26 sites were surveyed along River Soan and its associated tributaries during pre- and post-monsoon seasons in 2008. Hierarchical agglomerative cluster analysis (HACA) classified sampling sites into three groups according to their degree of pollution, which ranged from least to high degradation of water quality. Discriminant function analysis (DFA) revealed that alkalinity, orthophosphates, nitrates, ammonia, salinity, and Cd were variables that significantly discriminate among three groups identified by HACA. Temporal trends as identified through DFA revealed that COD, DO, pH, Cu, Cd, and Cr could be attributed for major seasonal variations in water quality. PCA/FA identified six factors as potential sources of pollution of River Soan. Absolute principal component scores using multiple regression method (APCS-MLR) further explained the percent contribution from each source. Heavy metals were largely added through industrial activities (28 %) and sewage waste (28 %), nutrients through agriculture runoff (35 %) and sewage waste (28 %), organic pollution through sewage waste (27 %) and urban runoff (17 %) and macroelements through urban runoff (39 %), and mineralization and sewage waste (30 %). The present study showed that anthropogenic activities are the major source of variations in River Soan. In order to address the water quality issues, implementation of effective waste management measures are needed.