This paper aims at assessing the feasibility of suspended sediment concentration (SSC) estimation by using predictor variables of heavy metal concentration (HMC, viz., iron, chromium, zinc and nickel) transported in solution and solid. The study was conducted in the Research and Educational Forest Watershed of the Tarbiat Modares University (Kojour) which comprises an area of ca. 50000 ha. For this study, suspended sediment samples were collected from the left bank of the Kojour River twice a week, as well as during runoff events from November 2007 to June 2008. The samples were then prepared through direct digestion and finally analyzed by atomic absorption spectrophotometry (AAS). The relationship between SSC and particle size distribution (PSD) were correlated with HMC by using bivariate and multivariate regression models. Proposed models were then selected based on statistical criteria. The results showed high correlation between dissolved and particulate chromium content with efficiency coefficients beyond 77% (𝑃 > 0.001). However, a lower relationship was found between SSC and nickel content. From these results, it is clearly shown that the HMC can practically be estimated by SSC in watersheds with different accuracy and vice versa. It is also understood that heavy metal pollution can be easily managed by controlling SSC.
Volume 131, 2022
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