Abstract
Management of surface water resources is directly associated with determining the correlation between physical, chemical and biological variables and also identifying their natural and anthropogenic origin. The present study was conducted to scrutinize the correlation between the major parameters affecting the water quality of Shafarood River (Gilan Province, Northern Iran) and to monitor the water quality in different areas of the river using canonical correlation analysis and cluster analysis models, respectively. The measured parameters were five physical parameters and four chemical parameters at five stations based on Standard Methods for the Examination of Water and Wastewater 2015 over six years. The results showed that there was a significant correlation between two categories of response variables (physical parameters) and predictor variables (chemical parameters), which were mainly caused by anthropogenic pollution sources (effluents from residential and garden areas). According to the results of cluster analysis, the stations were grouped into two clusters based on the level of pollution, and the cluster grouping confirmed the data of the canonical correlation matrix. The research findings revealed the effectiveness of the obtained linear combinations for the physical parameters, including total suspended solids and turbidity, as well as the chemical parameters, including biochemical oxygen demand and nitrate. To conclude, the efficiency of canonical correlation analysis and cluster analysis methods was confirmed in identifying the determinant variables of water quality and in classifying the water quality monitoring stations in the optimal management of rivers.