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Showing 2 results for Roshun
Investigation the Effect of Sand and Gravel Mining on Bed Sediment Morphometric Characteristics (Case Study: Zaremrood River, Mazandaran Province)
S. H. Roshun, Gh. Vahabzadeh, K. Solaimani, A. Khaledi Darvishan,
Volume 21, Issue 3 (Fall 2017)
Abstract

Sand and gravel mining from the most of our country rivers causes morphological, hydrological and geomorphological changes in these rivers. This study investigates the effects of removal of sand and gravel from the river bed on sedimentological features of Zaremrood River in Mazandaran province. For this purpose, by determining four sections before and four sections after the sand removing point, the river bed sediments sampling in combined approach and in a plot within the river were performed and sedimentology features such as the large, medium and small diameters (a, b and c), roundness (Rc), form factor (Sf), normal diameter (D), sphericity (S), and width ratio (W), were measured and calculated in the laboratory and analyzed by SPSS software. The results showed that the variations of sediment statistics a, b, c, Sf, D, S and W in the pre- and post- harvest location has a significant difference but the Rc statistic does not show any significant difference. The reduction of the triple diameters after the excavation site is caused by the fracture of the sediments in the mining area, so that the sphericity of grains also decreased in the mining area. Roundness of sediment particles after the excavation site is decreasing up to 600 meters reach and then it tends to increase.
 


Comparison of the Performance of ANN and SVM Methods in Rainfall-Runoff Process Modeling (Case Study: North Karun Watershed)
S. H. Roshun, K. Shahedi, M. Habibnejad Roshan, J. Chormanski,
Volume 25, Issue 2 (Summer 2021)
Abstract
The simulation of the rainfall-runoff process in the watershed has particular importance for a better understanding of hydrologic issues, water resources management, river engineering, flood control structures, and flood storage. In this study, to simulate the rainfall-runoff process, rainfall and discharge data were used in the period 1997-2017. After data qualitative control, rainfall, and discharge delays were determined using the coefficients of autocorrelation, partial autocorrelation, and cross-correlation in R Studio software. Then, the effective parameters and the optimum combination were determined by the Gamma test method and used to implement the model under three different scenarios in MATLAB software. Gamma test results showed that today's precipitation parameters, precipitation of the previous day, discharge of the previous day, and discharge of two days ago have the greatest effect on the outflow of the basin. Also, the Pt Qt-1 and Pt Pt-1 Qt-1 Qt-2 Qt-3 combinations were selected as the most suitable input combinations for modeling. The results of the modeling showed that in the support vector machine model, the Radial Base kernel Function (RBF) has a better performance than multiple and linear kernels. Also, the performance of the Artificial Neural Network model (ANN) is better than the Support Vector Machine model (SVM) with Radial Base kernel Function (RBF).

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