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Öğe A Case Study for Determination of the Best Underground Dam Sites, Bursa Province, Turkey(Wiley, 2024) Aras, Egemen; Boz, Burak; Vaheddoost, Babak; Yilmaz, DamlaWater constitutes an indispensable resource vital for sustaining life. In this context, groundwater stands out as a paramount global water source. Throughout history, underground dams (UGDs) have been employed to augment the storage capacity of local aquifers. This study employs a multistep elimination approach to identify optimal locations for constructing UGDs in the Bursa district, Turkey. Initially, the Digital Elevation Model (DEM) is utilized to pinpoint the potential construction sites at the watershed scale. Criteria such as suitable topographic slope range, proximity to the transport infrastructures, presence of natural or artificial reservoirs, distance to active or inactive faults, proximity to the urban and rural settlements, location of the irrigation zones, geological conditions, distance to the consumption hubs, thickness of alluvium layer, and the groundwater depth are used to establish the buffer zones for exclusion of potential sites. Then, storage volume in the proposed sites is determined, and formal requests from the local communities are taken into consideration for determining the best UGD sites. The study concludes that five UGDs for irrigation and one for drinking water purposes could be recommended for further implementation. The potential locations of underground dams have been determined in the city of Bursa, which has a very high underground water potential. Twelve different criteria were applied to determine the project location. After all criteria were applied, six different underground dam locations were determined depending on the city's water and irrigation needs. imageÖğe A CMIP6-ensemble-based evaluation of precipitation and temperature projections(Springer Wien, 2024) Yilmaz, Banu; Aras, Egemen; Nacar, SinanUnderstanding climate change's effects on dam basins is very important for water resource management because of their important role in providing essential functions such as water storage, irrigation, and energy production. This study aims to investigate the impact of climate change on temperature and precipitation variables in the Alt & imath;nkaya Dam Basin, which holds significant potential for hydroelectric power generation in T & uuml;rkiye. These potential impacts were investigated by using ERA5 reanalysis data, six GCMs from the current CMIP6 archive, and two Shared Socioeconomic Pathways (SSP2 - 4.5 and SSP5 - 8.5) scenario data. Four Multi-Model Ensemble (MME) models were developed by using an Artificial Neural Network (ANN) approach (ENS1), simple averaging (ENS2), weighted correlation coefficients (ENS3), and the MARS algorithm (ENS4), and the results were compared to each other. Moreover, quantile delta mapping (QDM) bias correction was used. The 35-year period (1980-2014) was chosen as the reference period, and further evaluations were conducted by dividing it into three future periods (near (2025-2054), mid-far (2055-2084), and far (2085-2100)). Considering the results achieved from the MMEs, variations are expected in the monthly, seasonal, and annual assessments. Projections until the year 2100 indicate that under optimistic and pessimistic scenarios, temperature increases could reach up to 3.11 degrees C and 5.64 degrees C, respectively, while precipitation could decrease by as much as 19% and 43%, respectively. These results suggest that the potential changes in temperature and precipitation within the dam basin could significantly impact critical elements such as future water flow and energy production.Öğe A LABORATORY SCALE INVESTIGATION OF MANNING ROUGHNESS COEFFICIENT IN OPEN CHANNEL BED WITH DIFFERENT GRAIN SIZE AND SLOPES(2023) Yılmaz, Damla; Aras, Egemen; Vaheddoost, BabakEfforts for getting the maximum efficiency from the existing water resources and to implement new projects are getting more attention these days. Determining the flow resistance for the project design and control process in open channels requires sophisticated applications. It is usually essential to be aware of the characteristics of the channel and flow to determine the hydraulic roughness, which represents the resistance of the flow. Hence, empirical calculation and evaluation of the hydraulic roughness will support future design and planning processes. In this study, four different particle sizes (d50= 28mm, 17.5mm, 4mm, and 1.75mm) that were fixed on blocks were used. These particle sizes were then used as the bed covering together with, three different horizontal bed slopes, and flow rates in the experiments to determine the associated Manning roughness, n. During the experiment, Froude number values were examined and it was determined that, in 32 experiments the flow regime can be considered as subcritical. Alternatively, the Lotter method was used to confirm the roughness values obtained by the Manning equation. It was concluded that the roughness values obtained by the selected methods have good concordance with each other.Öğe A new solution proposal for pedestrian-vehicle traffic: Uzun street sample in Turkey(Peter Lang AG, 2019) Aras, Aylin; Aras, EgemenThis chapter was made in order to propose a solution to ease the traffic flow of Uzun Street where the pedestrian and motor vehicle traffic is dense. In the scope of the study, a structural walking platform at the levels of the second floors of the buildings lined up along the axis of Uzun Street will be built. Motor vehicle traffic will be made possible under the platform and passages to the side streets will be built. Thus, both the pedestrian density of the street will be eased and the second-floors will be used as stores.Öğe A Statistical Assessment of Drinking Water Quality: A Case Study of Doburca Treatment Plant, Bursa(2024) Yılmaz, Damla; Aras, Egemen; Vaheddoost, BabakIn order to provide and maintain urban health standards, assessing the quality of drinking water is an essential step. As a result of different pollutant factors (climate, heavy metals, vegetation, human activities, etc.), it is inevitable that the quality of water resources decreases day by day. In this study, the data of 21 water samples taken between January 2021 and June 2021 from the water drinking facility providing drinking water to Bursa were examined. Firstly, the strength and direction of the relationship between 10 different parameters (electrical conductivity (EC), copper (Cu), nickel (Ni), nitrate (?NO?_3^-), arsenic (As), iron (Fe), total dissolved substances (TDS), total alkalinity (TA), total hardness (TH) and dissolved oxygen (DO)) were evaluated with the help of relation analysis, water quality index, and polynomial curve fitting. The relationship of the parameters that do not have a linear correlation was also interpreted and finally, as a result of using the weighted arithmetic water quality index (WAWQI), it was determined that the potability of the water quality in the allocated water reservoir was at the 'excellent' level and fulfills the requirements.Öğe Biochemical oxygen demand prediction in wastewater treatment plant by using different regression analysis models(Desalination Publ, 2019) Baki, Osman Tugrul; Aras, Egemen; Akdemir, Ummukulsum Ozel; Yilmaz, BanuThe management and operation of the wastewater treatment plants (WWTP) have an important role in the controlling and monitoring of the plants' operations. Various performance data are taken into account in the controlling of the WWTP. The irregularities between operating parameters often lead to management problems that cannot be overcome. The aim of this study is to provide a simple and reliable prediction model to estimate the biochemical oxygen demand (BOD) with specific water quality parameters like wastewater temperature, pH, chemical oxygen demand, suspended sediment, total nitrogen, total phosphorus, electrical conductivity, and input discharge. The data records in this study were measured between June 2015 and May 2016 and obtained from the laboratory of Antalya Hurma WWTP. In the creation of the model, classical regression analysis, multivariate adaptive regression splines (MARS), artificial bee colony, and teaching-learning based optimization were used. The root mean square error and the mean absolute error were used to evaluate performance criteria for each model. When the results of the analyses were compared with each other, it was observed that the MARS method gave better estimation results than the other methods used in the study. As a result, it was evinced that the MARS method produces acceptable results in the BOD estimation.Öğe Estimation of BOD in wastewater treatment plant by using different ANN algorithms(Techno-Press, 2018) Baki, Osman Tugrul; Aras, EgemenThe measurement and monitoring of the biochemical oxygen demand (BOD) play an important role in the planning and operation of wastewater treatment plants. The most basic method for determining biochemical oxygen demand is direct measurement. However, this method is both expensive and takes a long time. A five-day period is required to determine the biochemical oxygen demand. This study has been carried out in a wastewater treatment plant in Turkey (Hurma WWTP) in order to estimate the biochemical oxygen demand a shorter time and with a lower cost. Estimation was performed using artificial neural network (ANN) method. There are three different methods in the training of artificial neural networks, respectively, multi-layered (ML-ANN), teaching learning based algorithm (TLBO-ANN) and artificial bee colony algorithm (ABC-ANN). The input flow (Q), wastewater temperature (t), pH, chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (tP), total nitrogen (tN), and electrical conductivity of wastewater (EC) are used as the input parameters to estimate the BOD. The root mean squared error (RMSE) and the mean absolute error (MAE) values were used in evaluating performance criteria for each model. As a result of the general evaluation, the ML-ANN method provided the best estimation results both training and test series with 0.8924 and 0.8442 determination coefficient, respectively.Öğe Evaluation of Monthly Groundwater Level at Bursa, Turkey(Bursa Teknik Üniversitesi, 2019) Fidan, Regaip; Aras, Egemen; Vaheddoost, BabakAs an alternative resource to the surface water, groundwater is a vital resource that has been on the interest of many recent studies. Hence, the evaluation of the groundwater potential, its properties, and its availability needs specific dedication. In this study, monthly groundwater level time series at 9 observation wells scattered aligned with Mount Uludağ in Bursa are used. A 12-year period starting from January 2007 to October 2018 is taken into analysis and several statistical properties of the groundwater level time series are projected on maps. These statistical values are mean, coefficient of skewness, coefficient of kurtosis, coefficient of variation, and correlation coefficient. Results indicate that there is a high potential in the groundwater flow towards Yeniceabat. A strong linear correlation between groundwater levels in wells was observed which shows the potential connectivity between aquifers in the region. In addition, the groundwater levels located at the north show irregular patterns, probably due to water withdrawal for agriculture purposes.Öğe Experimental investigation of parametric changes in seepage time and length into the subsoil of hydraulic structures(2023) Yılmaz, Damla; Öksüz, Betül Sena; Aras, Egemen; Cumalı, Bilge Ozdogan; Nemlıoglu, SemıhDams and hydraulic structures are built on rivers in order to protect water resources due to global warming, to collect surface waters to provide drinking water and/or irrigation water, to prevent floods and to establish hydroelectric power plants. Dams, for example, are hydraulic structures that have more or less positive or negative environmental interactions on surface water and groundwater. One of the environmental interactions of dams and similar hydraulic structures is the seepage of accumulated water in its reservoir from upstream bottom of the dam. This seepage can affect the level and location of groundwater, reduce the accumulation of water in the reservoir, and cause piping in the ground below the construction of the dam body. In order to control the seepage, the methods of increasing the seepage length by using sheet pile and clay blanket on the dam foundation are frequently used. In this study, in the physical laboratory model, the variations in the seepage lengths that occur under the hydraulic structure section in the soil with two different grain diameters of 0.85 mm and 1.5 mm, depending on the dam structure, soil and barrier structures (sheet pile and upstream clay blanket), were experimentally investigated. As a result, it was determined that the seepage occurs less in the soil with a smaller grain diameter of 0.85 mm, the smaller the soil particle diameter has a reducing effect on the seepage, and the use of sheet pile increases this effect positively. In addition, it has been determined that the clay blanket in the upstream is effective compared to the general conditions, but the use of sheet pile provides the most efficiency.Öğe Hydrodynamic optimization of full-scale aeration tanks using field measurements and computational fluid dynamics modeling(Aip Publishing, 2025) Celik, Damla Yilmaz; Yilmaz, Naz; Sibil, Rahim; Aras, Egemen; Vaheddoost, BabakImproving energy efficiency and operational performance in wastewater treatment plants largely relies on precise hydrodynamic analysis. In this context, field-based studies are essential for understanding system behavior under real operational conditions. This study was conducted at a full-scale wastewater treatment plant, where flow dynamics in the aeration tank were evaluated through extensive field measurements and computational fluid dynamics modeling. Data were collected from 98 locations across 15 different depth levels using an Acoustic Doppler Current Profiler and a Hach FH950 velocity meter. The numerical model was initially validated with the help of experimental field data, enabling an accurate assessment of flow characteristics at varying depths. Results revealed that the low-velocity zones and non-uniform velocity distributions negatively affect system performance. It is also concluded that the inlet and outlet positions disturb the favorable circulation patterns and flow uniformity. Geometric optimization strategies were implemented to develop solutions, which led to a more uniform velocity distribution and improved hydraulic efficiency. By integrating detailed field measurements with numerical modeling, this study provides a comprehensive understanding of aeration tank hydrodynamics and offers practical design recommendations for improving overall system performance.Öğe Laboratory-Scale Study on the Effect of Underground Dam and Well on the Salinity Intrusion Interface at Coastal Aquifers(Springer Int Publ Ag, 2025) Vaheddoost, Babak; Karayel, Ayse Nur; Epcin, Akif; Aras, EgemenThis study examines the variations in the interface between saltwater and freshwater in coastal areas through laboratory-scale experiments. The experiments are conducted in a Plexiglas sandbox measuring 1400 mm in length, 200 mm in width, 400 mm in height, and 10 mm in thickness. A semi-uniform sand sample (1-2 mm) is used, and the saltwater, with a concentration of 25 g/L, is tinted with 2 g/L of food dye to facilitate observation of saline water movement in an unconfined coastal aquifer. In the experiments, either a Tabular Well (TW) located at depths of 150 or 250 mm from the soil surface, or an Underground Dam (UGD) with a height of 100, 150, or 200 mm placed on an impermeable layer, is used. The TWs or UGDs are positioned at distances of 250, 500, or 750 mm from the coastline for further analysis. Afterward, the movement of the saltwater interface within the sandbox is monitored using Cartesian coordinates, allowing the determination of flow velocity and its distribution across the soil profile. The results are then analyzed to explore the relationship between the depth and location of either the TW or UGD and the changes in velocity. Observations reveal that the TW reduces the horizontal movement velocity of the saltwater, while the interface velocity exhibits nonlinear variations along the x- and y-axes. Additionally, it is concluded that the well's influence remains consistent over time, whereas the impact of the wall diminishes once the saltwater surpasses the crest.Öğe Mapping the evolution of sea outfall research: insights for marine environmental sustainability(Gazi Univ, 2025) Yilmaz, Damla; Yilmaz, Hulya; Erdem, Elif Aybike; Yilmaz, Mustafa Utku; Vaheddoost, Babak; Aras, EgemenEffective management of sea outfall is a critical topic in marine environmental science, sustainability regulations, and adaptation for the road maps. Therefore, the development of sea outfall research is mapped in this study by addressing 248 articles published during 1970 - 2023. A detailed assessment of the field's evolution is provided through a combination of bibliometric and content analysis. Network analysis techniques, including co-occurrence, co-authorship, citation, and bibliographic coupling, are used to identify dominant research topics, citation patterns, and productive authors and countries. Subsequently, content analysis is applied to investigate the attributes, research methods, and gaps in the existing research. A new and detailed classification of sea outfall research is obtained from the content analysis namely: field studies, laboratory experiments, and data analysis, with consideration to the methodologies applied in the studies (modelling, numerical analysis, experimental techniques, simulation, and field studies). The findings not only highlight the progression of sea outfall research but also offer new perspectives that could inform future research and strategic investments aimed at enhancing marine environmental sustainability and managmenet.Öğe Mapping the Evolution of Sea Outfall Research: Insights for Marine Environmental Sustainability(2025) Yılmaz, Damla; Yilmaz, Hulya; Erdem, Elif Aybike; Yilmaz, Mustafa Utku; Vaheddoost, Babak; Aras, EgemenEffective management of sea outfall is a critical topic in marine environmental science, sustainability regulations, and adaptation for the road maps. Therefore, the development of sea outfall research is mapped in this study by addressing 248 articles published during 1970 – 2023. A detailed assessment of the field’s evolution is provided through a combination of bibliometric and content analysis. Network analysis techniques, including co-occurrence, co-authorship, citation, and bibliographic coupling, are used to identify dominant research topics, citation patterns, and productive authors and countries. Subsequently, content analysis is applied to investigate the attributes, research methods, and gaps in the existing research. A new and detailed classification of sea outfall research is obtained from the content analysis namely: field studies, laboratory experiments, and data analysis, with consideration to the methodologies applied in the studies (modelling, numerical analysis, experimental techniques, simulation, and field studies). The findings not only highlight the progression of sea outfall research but also offer new perspectives that could inform future research and strategic investments aimed at enhancing marine environmental sustainability and managmenet.Öğe Prediction of hydroelectric power generation with machine learning and innovative combined deep learning techniques(Springer, 2026) Yilmaz, Banu; Aras, Egemen; Samadianfard, SaeedDams provide energy production by the accumulation and storage of water. Therefore, changes in weather conditions directly affect production capacity and energy efficiency. While the amount of precipitation determines the circulation capacity of water resources, temperature affects the evaporation rate of water and thus water levels. Flow is one of the critical parameters required to determine the amount of water needed for energy production and to ensure efficient energy production. Within the scope of this study, energy production forecasting models have been established for the Alt & imath;nkaya Dam Basin, which has significant potential for hydroelectric energy production in Turkey. In addition to long-short-term memory (LSTM) and feed-forward neural network (FFNN) methods, TPAFFNN-LSTM, which combines these methods with an innovative temporal pattern attention (TPA) mechanism, was also used. Random forest (RF) and extreme gradient boosting (XGB) are also used to evaluate the efficiency and accuracy of the proposed models. As a feature selection method, LASSO regression was applied before the analyses. Shapley Additive Explanations (SHAP) and Regression Receiver Operating Characteristic (RROC) analyses were used in the evaluation phase of all models. According to the results obtained, the nRMSE and NSE criteria of the TPAFFNN-LSTM method were obtained as 0.16 and 0.69, respectively. These results were found to be 18% and 19% more successful than the other methods. The proposed method represents a significant advancement in hydropower energy generation forecasting, providing a robust framework that combines depth of analysis with clarity of insights.Öğe Prediction of suspended sediment loading by means of hybrid artificial intelligence approaches(Springer International Publishing Ag, 2019) Yilmaz, Banu; Aras, Egemen; Kankal, Murat; Nacar, SinanThe main aim of the research is to use the artificial neural network (ANN) model with the artificial bee colony (ABC) and teaching-learning-based optimization (TLBO) algorithms for estimating suspended sediment loading. The stream flow per month and SSL data obtained from two stations, Inanli and Altinsu, in Coruh River Basin of Turkey were taken as precedent. While stream flow and previous SSL were used as input parameters, only SSL data were used as output parameters for all models. The successes of the ANN-ABC and ANN-TLBO models that were developed in the research were contrasted with performance of conventional ANN model trained by BP (back-propagation). In addition to these algorithms, linear regression method was applied and compared with others. Root-mean-square and mean absolute error were used as success assessing criteria for model accuracy. When the overall situation is evaluated according to errors of the testing datasets, it was found that ANN-ABC and ANN-TLBO algorithms are more outstanding than conventional ANN model trained by BP.Öğe Refinement of field-measured velocity profiles via CFD comparison: A case study on single-phase flow in aeration tanks(Elsevier Sci Ltd, 2026) Celik, Damla Yilmaz; Vaheddoost, Babak; Aras, Egemen; Sibil, RahimThe accuracy of field measurements obtained from aeration tanks is of critically important for the validation of Computational Fluid Dynamics (CFD) models. In many cases, the employed validation metrics serve as a fundamental keystone for evaluating both the credibility of experimental data and the accuracy of numerical simulations. In this study, a novel data refinement approach is developed to assess the physical plausibility of velocity measurements collected from a full-scale aeration tank. Unlike conventional validation approaches, the CFD model is utilized as a reference framework within a reverse-approach perspective to evaluate the reliability of field data. Measurement points affected by acoustic noise, surface sludge interference, and turbulence near static structures were identified and excluded through curve-fitting and statistical filtering techniques. Velocity data obtained with the help of an Acoustic Doppler Current Profiler (ADCP) across six lateral and 53 vertical layers were evaluated using the Coefficient of Determination (R2), Relative Error (RE), and Performance Index (PI) metrics. The maximum-elimination combined with polynomial fitting notably enhanced the model accuracy, reducing RE from -123 % to 20 %, increasing R2 from 0.054 to 0.96, and improving PI from 2.6 to 1.16. As a result, the refined dataset provided a more consistent and realistic representation of the flow structure and established a robust observational basis for the future calibration.Öğe Spatial Forecasting of Dissolved Oxygen Concentration in the Eastern Black Sea Basin, Turkey(Mdpi, 2020) Nacar, Sinan; Bayram, Adem; Baki, Osman Tugrul; Kankal, Murat; Aras, EgemenThe aim of this study was to model, as well as monitor and assess the surface water quality in the Eastern Black Sea (EBS) Basin stream, Turkey. The water-quality indicators monitored monthly for the seven streams were water temperature (WT), pH, total dissolved solids (TDS), and electrical conductivity (EC), as well as luminescent dissolved oxygen (LDO) concentration and saturation. Based on an 18-month data monitoring, the surface water quality variation was spatially and temporally evaluated with reference to the Turkish Surface Water Quality Regulation. First, the teaching learning based optimization (TLBO) algorithm and conventional regression analysis (CRA) were applied to three different regression forms, i.e., exponential, power, and linear functions, to predict LDO concentrations. Then, the multivariate adaptive regression splines (MARS) method was employed and three performance measures, namely, mean absolute error (MAE), root means square error (RMSE), and Nash Sutcliffe coefficient of efficiency (NSCE) were used to evaluate the performances of the MARS, TLBO, and CRA methods. The monitoring results revealed that all streams showed the same trend in that lower WT values in the winter months resulted in higher LDO concentrations, while higher WT values in summer led to lower LDO concentrations. Similarly, autumn, which presented the higher TDS concentrations brought about higher EC values, while spring, which presented the lower TDS concentrations gave rise to lower EC values. It was concluded that the water quality of the streams in the EBS basin was high-quality water in terms of the parameters monitored in situ, of which the LDO concentration varied from 9.13 to 10.12 mg/L in summer and from 12.31 to 13.26 mg/L in winter. When the prediction accuracies of the three models were compared, it was seen that the MARS method provided more successful results than the other methods. The results of the TLBO and the CRA methods were very close to each other. The RMSE, MAE, and NSCE values were 0.2599 mg/L, 0.2125 mg/L, and 0.9645, respectively, for the best MARS model, while these values were 0.4167 mg/L, 0.3068 mg/L, and 0.9086, respectively, for the best TLBO and CRA models. In general, the LDO concentration could be successfully predicted using the MARS method with various input combinations of WT, EC, and pH variables.Öğe SUSPENDED SEDIMENT LOAD PREDICTION IN RIVERS BY USING HEURISTIC REGRESSION AND HYBRID ARTIFICIAL INTELLIGENCE MODELS(Yildiz Technical Univ, 2020) Yımaz, Banu; Aras, Egemen; Kankal, Murat; Nacar, SinanAccurate prediction of amount of sediment load in rivers is extremely important for river hydraulics. The solution of the problem has been become complicated since the explanation of hydraulic phenomenon between the flow and the sediment on the river is dependent many parameters. The usage of different regression methods and artificial intelligence techniques allows the development of predictions as the traditional methods do not give enough accurate results. In this study, data of the flow and suspended sediment load (SSL) obtained from Karsikoy Gauging Station, located on Coruh River in the north-eastern of Turkey, modelled with different regression methods (multiple regression, multivariate adaptive regression splines) and artificial neural network (ANN) (ANN-back propagation, ANN teaching-learning-based optimization algorithm and ANN-artificial bee colony). When the results were evaluated, it was seen that the models of ANN method were close to each other and gave better results than the regression models. It is concluded that these models of ANN method can be used successfully in estimating the SSL.
