Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Correction 3D modelling of surface spreading and underground dam groundwater recharge: Egri creek subbasin, Turkey(Springer, 2023) Şahin, Yavuz; Tayfur, GökmenArticle Citation - WoS: 4Citation - Scopus: 53d Modelling of Surface Spreading and Underground Dam Groundwater Recharge: Egri Creek Subbasin, Turkey(Springer, 2023) Şahin, Yavuz; Tayfur, GökmenThis study investigated surface spreading and underground dam recharge methods to replenish groundwater in Turkey's Egri Creek Sub-basin of the Kucuk Menderes River Basin. A three-dimensional numerical model was employed for this purpose. Field and lab data are provided to the model for realistic simulations. Pumping test results were used to determine the aquifer parameters. The laboratory works involved sieve analysis, permeability tests, and porosity and water content prediction. The numerical model's boundary conditions were determined from the geological and hydrogeological characteristics of the study area. Initial conditions were expressed regarding water content and pressure head in the vadose zone. The numerical model was satisfactorily validated by simulating water levels in three different pumping wells in the study area. Seven different scenarios, each having a different pool size, were investigated for the surface spreading recharge method. The results showed that a pool size of 30 x 30 m with a 6-m depth basin was the most optimal choice, raising the groundwater level to about 29.3 m. On the other hand, it was found that an underground dam could raise the levels by an average of 9.5 m, which might not be significant to warrant the construction.Article Citation - WoS: 35Citation - Scopus: 38Historical Trends Associated With Annual Temperature and Precipitation in Aegean Turkey, Where Are We Heading?(MDPI, 2022) Mersin, Demirhan; Tayfur, Gökmen; Vaheddoost, Babak; Safari, Mir Jafar SadeghThe trend analysis of annual temperature (daily average) and total precipitation has been conducted for 14 stations located in the Aegean Region, Turkey. The Sen, Spearman’s rho, and Mann-Kendall test methods are used in the detection of the historical trends in the region. The Pettitt test is also implemented to find the significance of the trend, while the Theil-Sen approach is applied to detect the change point(s) in the time series. Findings of the following study indicate that both precipitation and temperature time series in the selected stations depict statistically significant trends with increasing nature. The rate of increase in precipitation and temperature by the Theil-Sen test is found to be 4.2–7.9 mm/year and 0.20–0.35 °C/decade, respectively. It is also found that the turn points of the temperature trends determined by the Pettitt test occurred in 1998 for all the stations. According to the results, the magnitude of the extreme events would change in the future, which may help in conceptualizing the framework and the resilience of the infrastructures against climate change.Article Citation - WoS: 24Citation - Scopus: 27Drought Assessment in the Aegean Region of Turkey(Springer, 2022) Mersin, Denizhan; Gülmez, Ayşe; Safari, Mir Jafar Sadegh; Vaheddoost, Babak; Tayfur, GökmenDrought indices are commonly used to monitor the duration and severity of droughts. In this regard, the continuously changing climate regardless of its cause or effect pushes the limit of the water deficit through time and space. Izmir is a raising city in Turkey, which owns various water resources including but not limited to seashores, lakes, river streams, and groundwater aquifers. In this study, the long-term precipitation and temperature records from 14 meteorological stations between 1973 and 2020 (for 47 years) are used to investigate the drought characteristics in Buyuk Menderes, Kucuk Menderes, and Gediz basins located in the Aegean region of Turkey. For this, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), Percent of Normal (PNI), and the so-called Discrepancy Precipitation Index (DPI) are used with consideration to 1-, 3-, 6-, and 12-month moving averages to investigate the drought patterns. Results showed that the monthly indices depict very similar results for the entire region. However, in the 1980s and 2010s droughts were more severe than the rest of the historical records. When the moving average operator is implemented in the analysis (3-, 6- and 12-month periods), neither SPI nor the SPEI showed the same results at any stations. It is illustrated that the periods of severe and normal drought have occurred in the past, yet the indices that are obtained using average values are generally within the normal limits, but extreme values (extremely arid or extremely wet) occurred occasionally. It is also concluded that although there is a similarity between the implemented indices, the DPI and PNI depict the highest resemblance.Article Citation - WoS: 5Citation - Scopus: 5Developing Predictive Equations for Water Capturing Performance and Sediment Release Efficiency for Coanda Intakes Using Artificial Intelligence Methods(MDPI, 2022) Hazar, Oğuz; Tayfur, Gökmen; Elçi, Şebnem; Singh, Vijay P.Estimation of withdrawal water and filtered sediment amounts are important to obtain maximum efficiency from an intake structure. The purpose of this study is to develop empirical equations to predict Water Capturing Performance (WCP) and Sediment Release Efficiency (SRE) for Coanda type intakes. These equations were developed using 216 sets of experimental data. Intakes were tested under six different slopes, six screens, and three water discharges. In SRE experiments, sediment concentration was kept constant. Dimensionless parameters were first developed and then subjected to multicollinearity analysis. Then, nonlinear equations were proposed whose exponents and coefficients were obtained using the Genetic Algorithm method. The equations were calibrated and validated with 70 and 30% of the data, respectively. The validation results revealed that the empirical equations produced low MAE and RMSE and high R2 values for both the WCP and the SRE. Results showed outperformance of the empirical equations against those of MNLR. Sensitivity analysis carried out by the ANNs revealed that the geometric parameters of the intake were comparably more sensitive than the flow characteristics.Article Citation - WoS: 5Citation - Scopus: 6Prediction of Rainfall Runoff-Induced Sediment Load From Bare Land Surfaces by Generalized Regression Neural Network and Empirical Model(Wiley, 2020) Tayfur, Gökmen; Aksoy, Hafzullah; Eriş, EbruBased on three rainfall run-off-induced sediment transport data for bare surface experimental plots, the generalized regression neural network (GRNN) and empirical models were developed to predict sediment load. Rainfall intensity, slope, rainfall duration, soil particle median diameter, clay content of the soil, rill density and soil particle mass density constituted the input variables of the models while sediment load was the target output. The GRNN model was trained and tested. The GRNN model was found successful in predicting sediment load. Sensitivity analysis by the GRNN model revealed that slope and rainfall duration were the most sensitive parameters. In addition to the GRNN model, two empirical models were proposed: (1) in the first empirical model, all the input variables were related to the sediment load, and (2) in the second empirical model, only rainfall intensity, slope and rainfall duration were related to the sediment load. The empirical models were calibrated and validated. At the calibration stage, the coefficients and the exponents of the empirical models were obtained using the genetic algorithm optimization method. The validated empirical models were also applied to two more experimental data sets: (1) one data set was from a field experiment, and (2) one set was from a laboratory experiment. The results indicated the success of the empirical models in predicting sediment load from bare land surfaces.Article Citation - WoS: 27Citation - Scopus: 29Fuzzy, Ann, and Regression Models To Predict Longitudinal Dispersion Coefficient in Natural Streams(IWA Publishing, 2006) Tayfur, GökmenThis study developed fuzzy, ANN, and regression-based models to predict longitudinal dispersion coefficient in natural streams from flow discharge data. 92 sets of field data were employed to calibrate and validate the models. 63 sets of data were used for the calibration while the remaining data were used for the validation of the models. The model-prediction results revealed the superiority of the developed models over the existing equations. The developed models predicted the measured data satisfactorily with minimum errors and maximum accuracy rates. The three models had comparable performances although the fuzzy model had the highest accuracy rate (79%) and lowest mean relative error (0.85).Article Citation - WoS: 44Citation - Scopus: 47Predicting Flood Plain Inundation for Natural Channels Having No Upstream Gauged Stations(IWA Publishing, 2019) Kaya, C. Melisa; Tayfur, Gökmen; Güngör, OğuzFlow hydrographs are one of the most important key elements for flood modelling. They are recorded as time series; however, they are not available in most developing countries due to lack of gauged stations. This study presents a flood modelling method for rivers having no upstream gauged stations. The modelling procedure involves three steps: (1) predicting upstream hydrograph by the reverse flood routing method which requires information about channel geometric characteristics, downstream flow stage and downstream flow hydrographs; (2) modelling flood wave spreading using HEC-RAS. The hydrograph predicted by the reverse flood routing in the first step becomes an inflow for the HEC-RAS model; (3) delineating the flood-risk areas by overlapping the Geographical Information System (GIS)-based flood maps produced by the HEC-RAS to the related orthophoto images. The developed model is applied to Guneysu Basin in Rize Province in Eastern Black Sea Region of Turkey. The model-produced flood map is compared to the observed one with success.Article Two dimensional bed deformation model in turbulent streams(Taylor & Francis, 2019) Gharehbaghi, Amin; Kaya, Birol; Tayfur, GökmenA coupled model is developed to simulate two dimensional water surface profile, suspended sediment load and bed deformation in unsteady open channels. The hydrodynamical component employs the two dimensional shallow water equations to obtain the hydraulic variables. These, in turn, are used in the morphdynamical component to determine the bed deformation. For the turbulence variables; two turbulence models are supervened to the governing equations. Triangular meshes were developed to discretize the domain of open channel. In order to discretize the governing equations, the explicit finite volume method is used by the total variation diminishing (TVD) schemes. The performance of the developed model is compared to that of the Flow3D software. The comparison results are in good agreement.Article Citation - WoS: 33Citation - Scopus: 37Trend Analysis of Temperature and Precipitation in Trarza Region of Mauritania(IWA Publishing, 2019) Yacoub, Ely; Tayfur, GökmenTrend analysis of annual temperature and precipitation time series data collected from three stations (Boutilimit (station 1), Nouakchott (station 2) and Rosso (station 3)) has been used to detect the impacts of climate change on water resources in Trarza region, Mauritania. The Mann-Kendall, the Spearman's rho, and the Sen trend test were used for the trend identification. Pettitt's test was used to detect the change point of the series while the Theil-Sen approach was used to estimate the magnitude of the slope in the series. For precipitation, two stations (1 and 3) indicated statistically significant increase in trends. In the case of temperature, almost all the stations show statistically significant increasing trends in the maximum, minimum, and average temperatures. The magnitude of precipitation detected by the Theil-Sen test for stations 1 and 3, respectively, was found to be at the rate of 2.93 and 3.35 mm/year at 5% significance level. The magnitude trend of temperature detected by the Theil-Sen approach was found to be at the rate of 0.2-0.4 degrees C per decade for almost all the stations. The change points of temperature trends detected by Pettitt test are found to be in the same year (1995) for all the stations.