Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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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 ResearchBook Part Citation - Scopus: 4Application of Fuzzy Logic in Water Resources Engineering(Elsevier, 2022) Tayfur, GökmenThis chapter introduces the fundamentals of fuzzy logic (FL), fuzzy sets, and fuzzy model components such as the fuzzification, the fuzzy rule base, the fuzzy inference engine, and the defuzzification. The processes of the fuzzy model components are presented by working on the examples from the water resources engineering application problems. This chapter also discusses the merits and the shortcomings of the fuzzy modeling. Hydrological processes have inherent source of uncertainty, for which the fuzzy set theory can be an effective solution tool. © 2023 Elsevier Inc. All rights reserved.Book Part Citation - Scopus: 1Developments in Sediment Transport Modeling in Alluvial Channels(Elsevier, 2022) Tayfur, GökmenThis chapter discusses the developments in the mathematical modeling of sediment transport dynamics in alluvial channels. Starting with early experimental and empirical studies, it goes on to treating the processes in 1D, 2D, and 3D uniform sediment transport. Finally, it describes the treatment of the processes in 3D nonuniform sediment transport considering turbulence effects. While introducing the advancements in mathematical modeling of the dynamics, the chapter also discusses the outstanding issues like the treatment of the particle fall velocity, the particle velocity, and sediment transport rate function. © 2023 Elsevier Inc. All rights reserved.Book Part Citation - Scopus: 3Real-Time Flood Hydrograph Predictions Using Rating Curve and Soft Computing Methods (ga, Ann)(Elsevier, 2022) Tayfur, GökmenThis chapter introduces hydraulic and hydrologic flood routing methods in natural channels. It details hydrological flood routing methods of the Rating Curve and Muskingum. Based on the rating curve method (RCM), it presents real-time flood hydrograph predictions using the genetic algorithm (GA-based RCM) model. In addition, it presents how to make real-time flood hydrograph predictions using the artificial neural network (ANN). The chapter briefly introduces the basics of GA and details how to calibrate and validate the GA-based RCM model using measured real-time flood hydrographs. Similarly, after giving the basics of ANN, it shows how to train and test the ANN model using measured hydrographs. Real hydrograph simulations by the RCM, GA-based RCM, and ANN are presented, and merits of each model are discussed. © 2023 Elsevier Inc. All rights reserved.Article Citation - WoS: 10Citation - Scopus: 11Experimental Investigation of Sediment Movement as a Result of Homogeneous Earth-Fill Dam Overtopping Break Over a Simplified Urban Area(Elsevier, 2023) Taşkaya, Ebru; Bombar, Gökçen; Tayfur, GökmenWhen an earth-fill dam breaks, dam body sediment and water flow simultaneously move to downstream area causing devastation. Dam break studies in the literature have concentrated mostly on the water flow part while ignoring the sediment movement by designing the dam body as a movable metal gate. This study, however, is the first one experimentally investigating flow and sediment transport due to an earth-fill dam break by constructing the dam body from sediment. Sediment propagation as a result of homogenous earth-fill dam overtopping break was experimentally studied in a laboratory flume of 18.4 m long and 2.0 m wide, and 0.88 m in height in the Hydraulics Laboratory of Izmir Katip Celebi University, Izmir, Turkey. Downstream section right after the dam body was designed as a smooth bed and rough bed. The rough bed, resembling a simplified urban area, was created by using thirteen 10 × 10 × 10 cm sized concrete blocks. The dam body was constructed as homogenous with uniform material having D50 = 0.441 mm. The earth-fill dam body was built using the standard compression methods; each layer of sediment with a thickness of 10 cm was laid in layers, and the body was prepared with a crest width of 10 cm, a transverse base width of 200 cm, a longitudinal base width of 202 cm and height of 60 cm with upstream and downstream slopes of 1:1.6. The water level behind the dam was gradually raised until it overtopped the crest level. A pre-breach was formed at the top of the dam to trigger the break. During each dam break event, water depths were measured by three ULS-40D level meter sensors at different locations, and the final sediment bathymetry map was generated using the ULS-40D Probes at 10 × 10 cm grids. The results showed that, in both smooth and rough downstream bed cases, the dam body eventually collapsed while a great portion of it was carried away by the flood flow. The sediment spreading occurred all over the downstream area, showing significant non-uniform variation in thickness both longitudinally and transversely, especially in the simulated urban area. All the residential areas, while breaking in motion, were submerged under the muddy flow. Some blocks were almost submerged while sediment heights reached half level of some blocks at the end of the experiment. Sediment heights were higher in the urban area.Article Citation - WoS: 13Citation - Scopus: 12Identification of Groundwater Potential Zones in Kabul River Basin, Afghanistan(Elsevier, 2021) Tani, Hamidullah; Tayfur, GökmenGroundwater (GW) plays a vital role in the socio-economic growth of Kabul River Basin (KRB) in Afghanistan. Since the GW resources in the basin have not been properly managed, there is a need for sound strategies by first identifying the potential GW zones. This study assesses the potential groundwater zones for the KRB using the Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). In this direction, seven different thematic maps of rainfall, lithology, land use/land cover, slope, soil, drainage density, and lineament density are first prepared using the GIS. The AHP is then employed to assess the weights of different themes. Finally, the weighted overlay option in the GIS is used to generate the map of the groundwater potential zones (GWPZ). The Very Good zones are mostly located in the downstream and central parts of the KRB, covering around 1543 km(2) area. The Good and the Poor zones are found to be randomly distributed, covering about 39 444 km(2) and 27 658 km(2), respectively. The Very Poor zones are located in the west, southwest, and in some central parts of the basin, covering about 2272 km(2). It is found that only 18% of the total average annual precipitated water of 6.88 x 10(9) m(3)/year infiltrates into the subsurface and ultimately contributes to recharging of the groundwater.Article Citation - WoS: 27Citation - Scopus: 27Discrepancy Precipitation Index for Monitoring Meteorological Drought(Elsevier, 2021) Tayfur, GökmenWidely employed precipitation drought indices, one way or another, impose probability distribution functions to the data when performing the drought analysis. This may be a plausible approach when the data do not have strong discrepancy which can impede the distribution. The precipitation data in semi-arid and especially in arid regions do have a strong discrepancy due to the sporadic rainfall occurring in such regions. Therefore, in the analysis of the drought for such regions, imposing any probability distribution function to the data could be futile. This study hence developed a new drought index called the Discrepancy Precipitation Index (DPI) for assessing and monitoring the meteorological drought. The method does not impose any probability distribution on the precipitation data. The method is based on the discrepancy of the data with respect to the mean value. The drought classifications are proposed based on the D-score values. Its drought classification ranges are straightforward as those of the Standard Precipitation Index (SPI). The method is applied to assess the meteorological drought at several stations located at different climatic regions such as the arid climate (Mauritania), semi-arid climate (Afghanistan) and the Mediterranean climate (Turkey). The results reveal that the DPI is more representative drought assessment tool for the arid climate regions. At semi-arid climate regions, the DPI can be an alternative drought index to the widely employed (the log-SPI and/or the gamma-SPI) indices. For the Mediterranean climate regions, the DPI can be used together with the other indices. The Discrepancy Measure (DM) is introduced to assess the strength of the discrepancy of the precipitation data series. As the DM of a precipitation series increases, the DPI captures more historical droughts.Article Citation - WoS: 32Citation - Scopus: 34Spatial and Temporal of Variation of Meteorological Drought and Precipitation Trend Analysis Over Whole Mauritania(Elsevier, 2020) Yacoub, Ely; Tayfur, GökmenUsing monthly precipitation data from 15 stations, well spread over whole Mauritania, and recorded for a long period of time (1919-2016) of almost 100 years, a classification of drought is performed, based on its intensity and duration. For this purpose, the gamma-Standardized Precipitation Index (gamma-SPI) is used to detect drought events (drought frequency, duration and intensity). The Mann-Kendall Test (MK test) is employed for the trend analysis of the precipitation data at all stations and the Thiel-Sen Approach is used to calculate the magnitude of the slopes of the trends. The drought analysis results show that there were severe and extreme drought conditions seen all over the country, especially in 1970s and 1980s. This serious case seems to be emerging in early 2010s. The drought conditions in recent years seems to be more pronounced in the central and southern regions of the country. The trend analysis results reveal that there is no depletion observed in precipitation at the northern region. The total deficit in precipitation is about 100 mm or less during almost 100 year period at the western region. However, the results show that there is pronounced decrease in precipitation at the southern region, reaching to almost a total of 300 mm deficit in nearly 100-year period.