Determination of the Effects of Some Water Quality Parameters on Turbidity Parameters in Filyos River with Artificial Neural Network

Authors : Berna Aksoy, İsmail Hakkı Özölçer, Emrah Doğan

Pages : 85-91

View : 107 | Download : 67

Publication Date : 2024-07-23

Article Type : Research Paper

Abstract :During the water cycle, substances that are contaminated in water cause physical, chemical or biological alterations of the water’s natural features, therefore environmental balance deteriorate over time. Observations and measurements on a river give the necessary information about how to benefit from the river. 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 five observation stations along the main line of the Filyos River, which forms the largest sub-basin in the Western Black Sea Basin, at intervals of thirty days in 2015 year. The turbidity parameter was estimated by artificial neural networks (ANNs) based on water quality parameters such as chromium (Cr+3), chemical oxygen demand (COD), iron (Fe+3), aluminium (Al+3), suspended solids, manganese (Mn+2), zinc (Zn+2), lead (Pb+2) and calcium (Ca+2). The study was conducted with creating two scenarios. In the first scenario, the determined parameters were analyzed by ANN for each station one by one. The obtained data showed that Cr (coefficient of determination [R2] =0.9999) parameter gave the best performance in the estimation of turbidity parameter in the study area. In the second scenario, eight models were created by adding the other best performing parameters one by one to the best performing Cr parameter. The third model formed by Cr, COD, Fe and Al parameters gave the closest result with R2=0.9992.
Keywords : Bulanıklık, Filyos nehri, su kalitesi, yapay sinir ağı

ORIGINAL ARTICLE URL