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Conference Object Citation - WoS: 22Citation - Scopus: 21Predicting dominant phytoplankton quantities in a reservoir by using neural networks(Springer, 2003) Gurbuz, H; Kivrak, E; Soyupak, S; Yerli, SVThe Levenberg-Marquardt algorithm was used to train artificial neural networks to predict the abundance of Cyclotella ocellata Pant. and Cyclotella kutzingiana Thwaites using time, depth, temperature, pH, dissolved oxygen, and electrical conductivity as input parameters for the oligo-mesotrophic Kuzgun Dam Reservoir, Turkey. The data were collected in monthly intervals during two ice-free seasons: between April 2000-November 2000 and April 2001-November 2001. To reduce over-fitting of the neural network based models, we employed single hidden layer networks with early stopping of training. Correlation coefficients, of neural network predictions with measurements of abundance of Cyclotella ocellata Pant. and Cyclotella kutzingiana Thwaites were 0.88 and 0.86, respectively.Article Citation - WoS: 26Citation - Scopus: 31Impact Assessment of Different Management Scenarios on Water Quality of Porsuk River and Dam System - Turkey(Springer, 2005) Muhammetoglu, A; Muhammetoglu, H; Oktas, S; Ozgokcen, L; Soyupak, SPorsuk Dam Reservoir (PDR), which is located on Porsuk River, is the main drinking water resource of Eskisehir City-Turkey. Both the river and the reservoir are under the threat of several domestic and industrial point sources and land-based diffuse pollution. The river water quality is very poor with high concentrations of nitrogen and phosphorus compounds at the entrance to Porsuk Reservoir. The reservoir shows symptoms of a hypertrophic lake. The expected responses of the whole river and reservoir system under different pollution control scenarios were estimated to develop plausible water quality management strategies. The adopted scenarios assumed different levels of treatment for the major domestic point sources that include conventional treatment and tertiary treatment. The contemporary Turkish Allowable Discharge Limits (ADLs) and the best available technology choices were the investigated treatment options for the major industries. The expected improvements of water quality characteristics under the management scenario options have been estimated by means of mathematical models. The model choices were the QUAL2E for the river and BATHTUB for the reservoir. Recommendations for different levels of treatment were derived in order to improve the water quality both within the river and in the reservoir.
