Optimal Estimation of Secondary Flow Coefficient in Compound Channels with Vegetated Floodplains

This study adopted the Shiono-Knight model (SKM) to estimate the lateral distribution of the depth-averaged velocity within rectangular and trapezoidal compound channels with emergent vegetation in floodplains. To implement the SKM, it was required to estimate the eddy viscosity coefficient, friction coefficient, and secondary flow coefficient. The present study estimated the friction coefficient using the Colebrook–White equation modified by Rameshwaran and Shiono for vegetated beds. An analysis of eddy viscosity models across compound channels indicated that the model was not sensitive to the eddy viscosity coefficient; thus, the eddy viscosity coefficient could be assumed constant across the channel. However, the negligence of the secondary flow in the model would lead to a significant error, and it was required to calibrate the secondary flow coefficient. Thus, this study used a genetic algorithm (GA) to develop equations for the secondary flow coefficient for different sections of the compound channel under two different approaches: (۱) the approach of Abril and Knight (۲۰۰۴), who proposed constant values for the main channel and floodplains, and (۲) the equations of Devi and Khatua (۲۰۱۷), which related the secondary flow coefficient to the relative depth and width ratio. It was found that the secondary flow coefficient was dependent on the relative depth and width ratio. As a result, the equation optimized based on the Devi-Khatua approach outperformed the Rameshwaran-Shiono technique in estimating the lateral distribution of the velocity, with a ۱۰.۲% lower error.

Keywords:

Depth-averaged velocity , Emergent , Shiono-Knight model , Genetic Algorithm , Relative Depth , Width ratio