Water and Wastewater Consulting Engineers Journal of Water and Wastewater; Ab va Fazilab (in persian) 1024-5936 18 4 2007 12 01 Simulation and Prediction of Some Water Quality Parameters in the Zayanderoud River Using Artificial Neural Networks Simulation and Prediction of Some Water Quality Parameters in the Zayanderoud River Using Artificial Neural Networks 49 65 2159 FA Masoud Noushadi Assistant Professor, Depatement of Water Engineering, College of Agriculture, Shiraz University Hamid Reza Salemi Academic Member, Isfahan Agricultural and Natural Resources Research Center Mohsen Ahmadzadeh M.Sc. Student in Desert Region Management, College of Agriculture, Shiraz University Journal Article 2006 07 23 The Zayanderoud River stretches over 350 Km along a roughly west-east direction, originates in the Zagros Mountains on the west of Isfahan, and discharges into the Gavkhoni Swamp on the east of Isfahan. The Zayanderoud River supplies for the irrigation, domestic, and industrial water demands in Isfahan Province. In this paper, some water quality parameters of this river including EC, TDS, pH, HCO₃, and Cl were simulated at different stations using artificial neural networks. The results showed an ascending trend for EC and TDS along the river. The trend in simulated HCO₃ was found to be similar to that over the past few years and was equal to the long-term average. The trend for Cl was ascending at upstream stations and also similar to the long-term average at downstream stations. In general, the simulations of water quality parameters EC, TDS, pH, and HCO₃ were evaluated to be highly satisfactory and the one for Cl satisfactory. The Zayanderoud River stretches over 350 Km along a roughly west-east direction, originates in the Zagros Mountains on the west of Isfahan, and discharges into the Gavkhoni Swamp on the east of Isfahan. The Zayanderoud River supplies for the irrigation, domestic, and industrial water demands in Isfahan Province. In this paper, some water quality parameters of this river including EC, TDS, pH, HCO₃, and Cl were simulated at different stations using artificial neural networks. The results showed an ascending trend for EC and TDS along the river. The trend in simulated HCO₃ was found to be similar to that over the past few years and was equal to the long-term average. The trend for Cl was ascending at upstream stations and also similar to the long-term average at downstream stations. In general, the simulations of water quality parameters EC, TDS, pH, and HCO₃ were evaluated to be highly satisfactory and the one for Cl satisfactory. https://www.wwjournal.ir/article_2159_ddd9dda6bfaf0bb1525a8a27c3ee6131.pdf