Heavy Metal and Agricultural Toxics Monitoring in Garasou River in Iran for Water Quality Assessment

Abstract

In this study water quality in Garasou river, which is located in north west of Iran in Ardabil province was assessed through multivariate statistical techniques including cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA). During a year toxic and heavy metals were sampled in 11 stations. Based on the findings from cluster analysis, principle component analysis and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP) and less polluted (LP) stations. Station 10 fell in HP group. Station 11, 8, 7, 4 and 2 fell in MP group. The rest of the stations fell in LP group. Stations that were at the same or similar level of pollution were put in the same group. The amount of pollutants resulting from the analysis of principal components showed that the three first components accounted for 81 % of differences altogether, the first component accounting for 41.6, the second for 22.5 and the third for 16.9 % of differences, respectively. The value of KMO coefficient confirms the classification. This, in addition, confirmed that the model resulting from multi-linear regression analysis of the main component is a good indicator of each source or factor's loading in the distribution of pollution in the river.