Determination of Turbidity in Filyos Stream Water by Artificial Neural Network

Abstract

Water is in an endless cycle, which is source of life for human beings. During this cycle, substances that are contaminated in water cause physical, chemical or biological alteration of the water’s natural features, that leads to water pollution and therefore causes the environmental balance to deteriorate over time. This quality changes cause deteriorations in ecosystem. For this reason, it is important to investigate the water quality in rivers and water reservoirs which are close to settlement areas. In this study, surface water quality measurements were carried out at downstream of the Filyos stream, which forms the largest sub-basin in the Western Karadeniz Basin, at intervals of thirty days in one year period between September 2015 and August 2016. In the scope of the study, zinc, chromium, calcium, aluminium, manganese and turbidity parameters measured in the laboratory and estimation of the turbidity parameter basaed on parameters of zinc, chromium, calcium, aluminium, manganese was performed by artificial neural networks.

Keywords

• Filyos Stream,Heavy Metal,Turbidity,Artificial Neural Networks

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