STM Article Repository

This paper aims to obtain a relation for estimating the median size of bed sediment, , at the bends of meandering rivers based on real data. To achieve such a purpose, field data, including topographic, sediment sampling, and flow measurements, were collected from various rivers in Iran at different times of the year. Then, the Buckingham Π-theorem was applied to identify the effective dimensionless numbers such as the Shields function, Reynolds particle number, Froude number, submerged specific gravity of sediment, and aspect and curvature ratios. A correlation analysis was conducted between such factors to eliminate those dependent on others. In the following, three regression techniques, containing the power function approach, the general additive model (GAM), and the multivariate adaptive regression spline (MARS), were chosen to achieve the best relation. The obtained results indicated that the developed MARS model produced a better result than the others and was much more satisfactory, with a coefficient of determination (R2) of 0.96 and 0.95 and root-mean-square error (RMSE) of 140.64 and 140.47 for the training and testing phases, respectively. Furthermore, the MARS outputs were validated with an analytical method, which showed that MARS fitted with the field data much better. Consequently, the distinguished merit of this study is the development of a relation for determining that shows which geometric and hydraulic parameters have the most effect on sediment size in the river bend.