Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Application of Artificial Neural Network for Predicting Peak Discharge From Breached Embankment Dam(International Association for Hydro-Environment Engineering and Research (IAHR), 2024) Okan, M.; Bor, A.; Tayfur, G.Estimation of peak discharge is a key parameter for risk assessment in case of dam failure, and has attracted great attention from researchers in recent years. Many formulas are available in the literature, but these cannot cover all experimental scenarios. Existing models are typically inadequate to address the complexities of dam breaches. This research attempted to predict the peak discharge in the breached embankments with an artificial neural network (ANN) model, which is effective in nonlinear problems, using datasets obtained from various dam breaches cited in the literature. The ANN model is useful in the preparation of emergency action plans since it enables prediction of peak discharge. Multilayer Perceptron (MLP) with Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms was used to predict peak discharges from breached embankments. The dataset was divided into three: 56% for training, 20% for validation and 24% for testing. Different scenarios were created using different input combinations. Performance evaluation was based on the root-mean squared error (RMSE), percent bias (PBIAS), determination of coefficient (R2), Nash-Sutcliffe efficiency (NSE) and RMSE-observations standard deviation ratio (RSR). A comparison of training algorithms revealed that LM showed the best performance when the best ANN was selected from 1000 networks. Volume of water above the breach bottom (Vw) had a greater effect on model performance than the depth of water above the breach bottom (Hw). The best performance was obtained when both Vw and Hw were used as input. © 2024 ISHS. All Rights Reserved.Conference Object Citation - Scopus: 1Water Quality Evaluation Using Various Water Quality Indices: a Case Study for B. Menderes River, Turkey(International Association for Hydro-Environment Engineering and Research, 2022) Bor, A.; Elgi, Ș.Water quality is an important factor for public health and aquatic life, and it has become an increasingly important problem due to the growth ofthe population, urban expansion, and development. Forthis reason, the evaluation of surface water quality is an important issue for countries. Water quality indexing is widely used to present complex water quality data in a more comprehensible form and provides decision-makers and non-technical managers ofwater resources with concise information about water quality status. In this study, the water quality is determined based on the water quality monitoring data obtained from the Kocarli Bridge gauging station in the B. Menderes Riverforthe 9 years period between 2006 and 2014. The main pollutants in this region, with parameters exceeding border limit values PH were found to be Sulphate (S04), Nitrate (N03), Ammonia (NH4), Nitrite (N02), Phosphate (P04), Electrical Conductivity (EC), Total Dissolved Solids (TDS) Calcium (CA), Magnesium (MG), Sodium (Na), Potassium (K) and Bacteriological Parameters (E-coli, F-Strp, and Total Coli). In addition, five different WQI performances are compared so that the data can be easily interpreted. The methods used were the weighted arithmetic index (WAI-WQI) Environmental Water Quality Index (CCME-WQI) Canadian Council of Canada (CCME-WQI), Universal Water Quality Index (UWQI), Oregon Water Quality Index (0WQI), and Aquatic Toxicity Index (ATI). The applicability of different methodologies is discussed, and significant inconsistencies were observed between the classification results. © 2022 IAHR.