Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 13Citation - Scopus: 14Soil Erosion Model Tested on Experimental Data of a Laboratory Flume With a Pre-Existing Rill(Elsevier Ltd., 2020) Aksoy, Hafzullah; Gedikli, Abdullah; Yılmaz, Murat; Eriş, Ebru; Ünal, N. Erdem; Yoon, Jaeyoung; Tayfur, GökmenPrediction of sediment discharge transported within flow is strongly needed in order to provide measures for a well-established erosion control and water quality management practice. Initiated by runoff generation and erosion processes sediment transport is influenced by microtopography over hillslopes of hydrological watersheds. Consideration of microtopography provides more accurate results. In this study, a process-based two-dimensional rainfall-runoff mathematical model is coupled with erosion and sediment transport component. Both the rainfall-runoff and sediment transport components make simulations in rills and over interrill areas of a bare hillslope. Models at such fine resolution are rarely verified due to the complexity of rills and interrill areas. The model was applied on a data set compiled from laboratory experiments. Erosion flume was filled with granular sand to replace a bare soil. A longitudinal rill and an interrill area were pre-formed over the soil in the flume before the simulated rainfall exerted on. The flume was given both longitudinal and lateral slopes. The simulated rainfall was changed between 45 mm/h and 105 mm/h and exerted on granular uniform fine and medium sand in the erosion flume with longitudinal and lateral slopes both changing from 5% to 20%. Calibration of the model shows that it is able to produce good results in terms of sedigraphs, which suggest also that the model might be considered an important step to verify and improve watershed scale erosion and sediment transport models.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: 18Citation - Scopus: 24Empirical Sediment Transport Models Based on Indoor Rainfall Simulator and Erosion Flume Experimental Data(John Wiley and Sons Inc., 2017) Aksoy, Hafzullah; Eriş, Ebru; Tayfur, GökmenLand degradation processes start with accelerated runoff and sediment delivery. In this study, rainfall-runoff induced sediment transport is investigated using data from an indoor laboratory experimental setup consisting of a rainfall simulator and an erosion flume. The data are analysed to develop empirical models using sediment discharge, slope, flow discharge, rainfall intensity and sediment size. Fine and medium sands are considered as bare soil in experiments. Four rainfall intensities (45, 65, 85 and 105 mm h−1) are applied with combinations of lateral and longitudinal slopes of 5%, 10%, 15% and 20%. Eighty experiments are conducted. Flow is measured, and sediment within flow is separated and weighted. Experimental data are used for developing empirical models through multiple regression with parameters optimized by genetic algorithm. Results show that slope is the main contributing variable to the sediment transport over hillslopes. Accommodating variables among slope, rainfall intensity, flow discharge and median diameter of sediment as independent variables, one-variable, two-variable and four-variable models are developed considering also that higher number of parameters increases the performance of the model with higher cost of parameterization.Article Citation - WoS: 17Citation - Scopus: 19Rainfall-Runoff Model Considering Microtopography Simulated in a Laboratory Erosion Flume(Springer Verlag, 2016) Aksoy, Hafzullah; Gedikli, Abdullah; Ünal, Necati Erdem; Yılmaz, Murat; Eriş, Ebru; Yoon, Jaeyoung; Tayfur, GökmenA comprehensive process-based rainfall-runoff model for simulating overland flow generated in rills and on interrill areas of a hillslope is evaluated using a laboratory experimental data set. For laboratory experiments, a rainfall simulator has been constructed together with a 6.50 m × 1.36 m erosion flume that can be given adjustable slopes changing between 5 % and 20 % in both longitudinal and lateral directions. The model is calibrated and validated using experimental data of simulated rainfall intensities between 45 and 105 mm/h. Results show that the model is capable of simulating the flow coming from the rill and interrill areas. It is found that most of the flow occurs in the form of rill flow. The hillslope-scale model can be used for better prediction of overland flow at the watershed-scale; it can also be used as a building block for an associated erosion and sediment transport model.