Integrated modelling with environmental parameters for aquatic system assessment: a case study on the Ghare-Bagh drainage, Iran
2017
Sheykhi, Vahideh | Moore, Farid | Kavousi-Fard, Abdollah | Keshavarzi, Behnan | Bikineh, Elham
This paper is an attempt to use a combination of geochemical methods, swarm intelligence-based optimization technique, and geographic information system (GIS) processing in order to provide an efficient way for analysing the geochemistry of potentially toxic metals in an aquatic system. Using this combined approach, the contamination characteristics of selected potentially toxic metals (As, Cd, Cr, Cu, Co, Mo, Ni, Pb, and Zn) in the surface water and sediment samples of Ghare-Bagh drainage in SE Shiraz, Iran is evaluated and potential risk is assessed. The results indicated that the maximum content of Ni, Mo, and Cu greatly exceeds the maximum permissible levels, when compared with the maximum value of world rivers. Considering sediment quality guidelines, occurrence of adverse aquatic biological effects due to high Cu, Zn, Ni, and Cr is likely. The more labile fractions of sequential extraction analysis of potentially toxic metals gave the following decreasing risk order: Mo > Pb > As > Zn > Cu > Cd > Co > Ni > Cr. Hence, Mo and Pb are more available, and likely to enter the food chain of the aquatic fauna. The modified krill herd optimization algorithm (MKHOA) was used for automatic clustering purposes in spatial data analysis using 14 variables (pH, CaCO ₃, OM, CEC, electrical conductivity, As, Cd, Cr, Cu, Co, Mo, Ni, Pb, and Zn) measured in drainage sediments. The results of MKHOA demonstrated that the sources of potentially toxic metals are divided into three groups including (i) industrial effluents (Mo), (ii) erosion and leaching of riverside soil(Ni, Co, and As), and (iii) domestic wastewater and/or agricultural run-off (Pb, Zn, Cd, Cr, and Cu).
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