Using multivariate statistical analysis in assessment of surface water quality and identification of heavy metal pollution sources in Sarough watershed, NW of Iran.

Abstract

The Sarough watershed in NW Iran hosts a large amount of mineral occurrences and ore deposits which may be considered as the source of heavy metals in the region. The area has been studied previously; however, the methodology of this paper was less focused on previous studies. This study aimed to assess water quality, determine the spatial distribution pattern, and identify the sources of heavy metals in the main tributaries of Sarough watershed using pollution indexes, multivariate statistical methods, and processing data by geographic information system. Totally, 51 water samples were collected along the main rivers to determine the concentrations of heavy metals by ICP-MS. Regarding the drinking water, agriculture, and freshwater aquatic life guidelines, the rivers were assumed unsafe considering most of toxic elements' content, especially As. The mean values for heavy metal pollution indexes (HPI: 237.32) and metal indexes (MI: 25.37) indicated the intensive heavy metal pollution. The cluster analysis categorized the 51 sampling sites into four clusters with respect to pollution level. The results obtained from the Kruskal-Wallis and multiple comparison tests had the harmony with the results of CA in introducing the most impacted sampling sites and the parameters responsible for water quality degradation. The results of PCA showed the maximum similarity between As, Sb, Se, Fe, and Mn as well as base metals which was attributed to anthropogenic input from mining and mineral processing wastes. Association of Cr and Ni may suggest a lithology source (weathering of metamorphosed ultramafic outcrops). The maps prepared in the GIS system showed the spatial distribution pattern of toxic elements with maximum values nearby mining sites which decreases gradually toward downstream areas. Finally, the results showed that the Sarough River and its tributaries are influenced by high concentrations of heavy metals from the drainages of mining and ore processing sites and naturally occurring metal loadings as well as the geogenic sources such as weathering of geologic formations and hot springs.