Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 18Citation - Scopus: 18In-Depth Exploration of Temperature Trends in Morocco: Combining Traditional Methods of Mann Kendall With Innovative Ita and Ipta Approaches(Springer Basel Ag, 2024) Qadem, Zohair; Tayfur, GökmenThis study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann-Kendall, Sen's estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 degree celsius. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 degrees C. A decrease of 0.4 degree celsius for T-min and 1.6 degree celsius for T-max were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 degree celsius T-min and 2.6 degree celsius T-max) and Taza (1.1 degree celsius T-min and 2.6 degree celsius T-max) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 degree celsius per year in Rabat Sale to 0.0076 degree celsius per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco.Article Citation - WoS: 3Citation - Scopus: 3Ensemble and Optimized Hybrid Algorithms Through Runge Kutta Optimizer for Sewer Sediment Transport Modeling Using a Data Pre-Processing Approach(Elsevier, 2023) Safari, Mir Jafar Sadegh; Gül, Enes; Dursun, Ömer Faruk; Tayfur, GökmenUncontrolled sediment deposition in drainage and sewer systems raises unexpected maintenance expenditures. To this end, implementation of an accurate model relying on effective parameters involved is a reliable benchmark. In this study, three machine learning techniques, namely extreme learning machine (ELM), multilayer perceptron neural network (MLPNN), and M5P model tree (M5PMT); and three optimization approaches of Runge Kutta (RUN), genetic algorithm (GA), and particle swarm optimization (PSO) are applied for modeling. The optimization and ensemble hybridization approaches are applied in the modeling procedure. For the case of hybrid optimized models, the ELM and MLPNN models are hybridized with RUN, GA, and PSO algorithms to develop six hybrid models of ELM-RUN, ELM-GA, ELM-PSO, MLPNN-RUN, MLPNN-GA, and MLPNN-PSO. Ensemble hybrid models are developed through coupling the ELM and MLPNN models with the M5PMT algorithm. The data pre-processing approach is applied to find the best randomness characteristic of the utilized data. Results illustrate that the RUN-based hybrid models outperform the GA- and PSO-based counterparts. Although the MLPNN-RUN and MLPNN-M5PMT hybrid models generate better results than their alternatives, MLPNN-M5PMT slightly outperforms MLPNN-RUN model with a coefficient of determination of 0.84 and a root mean square error of 0.88. The current study shows the superiority of the ensemble-based approach to the optimization techniques. Further investigation is needed by considering alternative optimization techniques to enhance sediment transport modeling. © 2023 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion ResearchArticle Citation - WoS: 16Citation - Scopus: 19Meteorological Drought Assessment and Trend Analysis in Puntland Region of Somalia(MDPI, 2023) Muse, Nur Mohamed; Tayfur, Gökmen; Safari, Mir Jafar SadeghDrought assessment and trend analysis of precipitation and temperature time series are essential in the planning and management of water resources. Long-term precipitation and temperature historical records (monthly for 41 years, from 1980 to 2020) are used to investigate annual drought characteristics and trend analysis in Somalia's northern region. Six drought indices of the normal Standardized Precipitation Index (normal-SPI), the log normal Standardized Precipitation Index (log-SPI), the Standardized Precipitation Index using the gamma distribution (Gamma-SPI), the Percent of Normal Index (PNI), the Discrepancy Precipitation Index (DPI), and the Deciles Index (DI) are used in this study for the annual drought assessment. The log-SPI, the gamma-SPI, the PNI, and the DPI could capture historical extreme and severe droughts that occurred in the early 1980s and over the last two decades. The results indicate that Somalia has gone through extended drought periods over the past quarter century, exacerbating the existing humanitarian situation. The normal-SPI, gamma-SPI, and PNI indicate less and moderate drought conditions, whereas log-SPI, DPI, and DI accurately capture historical extreme and severe drought periods; thus, these methods are recommended as annual drought assessment tools in the studied region. Not only are the PNI and DPI less correlated to each other, but their correlation coefficient (CC) with SPI-based drought indices are not as high as SPI-based indices which are close to unity. For the purpose of the trend analysis, the Mann Kendall (MK) test, the Spearman's rho (SR) test, and the Sen test are used. Furthermore, the Pettitt test is implemented to detect the change points and the Thiel-Sen approach is used to estimate the magnitude of trend in the precipitation and temperature time series. The results indicate that there is overall warming in the region which has experienced a significant shift in trend direction since 2000. The trend analysis of annual precipitation data time series shows that Bossaso and Garowe stations have significant positive trends, while the Qardho station has no trend. In 1997 and 1998, respectively, abrupt changes in annual precipitation are detected at Qardho and Garowe stations. Due to the civil war of more than three decades in Somalia and the non-institutionalized governance to inform historical drought conditions in the country, determining the most appropriate meteorological drought index would help to develop a drought monitoring system for states and the entire country.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: 8Citation - Scopus: 9Empirical, Numerical, and Soft Modelling Approaches for Non-Cohesive Sediment Transport(Springer, 2021) Tayfur, GökmenThis paper reviews the modelling approaches and outstanding issues with regard to non-cohesive sediment transport which has been experimentally and numerically studied for many decades owing to its importance to hydraulic structures, morphology and related areas. About 311 papers are reviewed that included laboratory experiments, field observations, and analytical and numerical modelling studies. The reviewed papers cover the period 1938-2020. Of 311, 95 papers are included in this paper. The modeling approaches include empirical, physics-based, spatially averaged, and soft methods. The empirical models have oversimplified the process while the physics-based models are indispensable when the detailed analysis is required. On the other hand, when the objective is to obtain cumulative sediment loads, it would be advantageous to employ the spatial averaging modelling and/or the soft computing methods due to less computational burden and data requirements. The outstanding issues are related to the particle fall velocity, particle velocity, incipient motion, and transport function that require further experimental investigations especially for unsteady non-uniform transport processes.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: 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 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.
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