Multivariate statistical analysis of surface water chemistry: A case study of Gharasoo River, Iran

摘要

Regional water quality is a hot spot in the environmental sciences for inconsistency of pollutants. In this paper,the surface water quality of the Gharasoo River in western Iran is assessed incorporating multivariate statisticaltechniques. Parameters like EC, TDS, pH, HCO3-, Cl-, SO42-, Ca2+, Mg2+ and Na+ were analyzed. Principalcomponent and factor analysis is showed the parameters generated 3 significant factors, which explained73.06℅ of the variance in data sets. Factor 1 may be derived from agricultural activities and subsequent releaseof EC, TDS, SO42- and Na+ to the water. Factor 2 could be influenced by domestic pollution and explained thedeliverance of HCO3-, Cl- and Mg2+ into the water. Factor 3 contains hydro-geochemical variable Ca2+ and pH,originating from mineralization of the geological components of bed sediments and soils of watershed area.Likewise, the clustering analysis generated 3 groups of the stations as the groups had similar characteristicfeatures. Pearson correlation analysis showed significant correlations between HCO3- and Mg2+ (0.775), Ca2+(0.552) as well as TDS and Na+ (0.726). With reference to multivariate statistical analyses it can be concludedthat the agricultural, domestic and hydro-geochemical sources are releasing the pollutants into the GharasooRiver water.