Hydrogeomorphology
ahmad godarzi; hojatolah younesi; babak shahinejad; hassan torabi
Abstract
In rivers, sediment load monitoring is mainly confined to suspended load measurement; as a result, maximizing resources and reducing the damage caused by river flow is critical. The goal of this study was to use Mike3D.2018 software to create a three-dimensional simulation of the Kashkan river flow in ...
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In rivers, sediment load monitoring is mainly confined to suspended load measurement; as a result, maximizing resources and reducing the damage caused by river flow is critical. The goal of this study was to use Mike3D.2018 software to create a three-dimensional simulation of the Kashkan river flow in the spring of 2019. For this objective, HEC-RAS5.0.7 software is introduced and input according to the production of altitude cultivar (coming from mapping) from the bed and floodplain of the analyzed river with a length of 1200 meters and a scale of 1: 1000 for numerical modeling. Flood, suspended sediment, and transition sediment were estimated using data from the Kashkan-Poldakhtar hydrometric station for return periods of 25, 200, 1000, and 1250 years. Floods were highest at 1200 and 1100 cross sections and lowest at 50 and 350 cross sections, according to the model's findings. By comparing the values with the observed values, it was discovered that the simulation at Kashkan-Poldakhtar hydrometric station performed better. Total sediment simulated 207.45 million tons per day and suspended load utilizing Young’s relation with + 11.87 percent error. The amount of transitional suspended sediments in April (5132779/31) was also higher than in January (9890/55), February (41083/73), March (149629/75), and May (15/112617), according to the findings. In addition, compared to the typical silt in the Kashkan River, the amount of sediment in this month is quite large.
reza dehghani; hassan torabi; hojatolah younesi; babak shahinejad
Abstract
River flow prediction is one of the most important key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and the occurrence of droughts. In order to predict the flow rate of rivers, various approaches have been introduced in ...
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River flow prediction is one of the most important key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and the occurrence of droughts. In order to predict the flow rate of rivers, various approaches have been introduced in hydrology, in which intelligent models are the most important ones. In this study the application of hybrid wavelet vector hybrid model to estimate the discharge of Kharkhe basin rivers on daily discharge statistics of hydrometric stations located upstream of dam during the statistical period (2008-2018) has been evaluated and its performance with vector machine model The backup was compared. The correlation coefficients, root mean square error, mean absolute error was used for evaluation and also comparison of the performance of models in this research. The results showed that the hybrid structures presented acceptable results in the modeling of river discharge. Comparison of models also showed that the hybrid model of support-wavelet vector machine has better performance in flow forecasting. .Overall, the results showed that using a hybrid backup vector machine model can be useful in predicting daily discharge.
