The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine

Evaluation and prediction of sediment transport and associated processes have been one of the main issues of hydraulic and river engineers. There are some variables which affect the amount of bed load of a stream or river which may carry such as hydraulic, hydrological and sediment parameters caused the complexity of sediment transport phenomenon. Furthermore, gravel-bed rivers have features that distinguish them from sand-bed rivers and caused problems and challenges in their analysis. Considering the influential parameters to predict bed load transport rate in 20 gravel-bed rivers, in this study, the accuracy of support vector machine was investigated in different intervals of hydraulic and sediment parameters. The obtained results confirm the superiority of the model with input parameters of Froude number, the ratio of average velocity to shear velocity (), the ratio of hydraulic radius to the median grain diameter () and shields number () with Nash-Sutcliffe efficiency (NSE) of 0.806. In a second step, the data in different intervals are categorized according to the hydraulic and sediment characteristics using trial and error. Obtained results show that prediction of bed load transport with the median diameters of sediment particles (D50) ranging from 1 to 1.4 mm led to significant outcomes of NSE= 0.952, as well as flow condition in the intervals of 0.65 and 0.75 of Froude number generate better predictive ability with NSE= 0.925. Besides, it is found that hydraulic conditions govern the rivers flow in specific intervals of Shear Reynolds number and bed slope of channel led to better predictive ability of bed load transport rate in gravel-bed rivers.