Sloping Perspectives: Investigating Flow Hydrodynamics in Vegetated Open-Channels Under Varying Bed Slope

Abstract

Vegetated open channels play a crucial role in shaping the dynamics of riverine ecosystems. This study, conducted in two distinct phases under sub-critical flow conditions, aimed to understand the impact of altering the channel bed while maintaining a constant flow discharge. In the initial phase, a vegetated open channel, featuring vegetation followed by a moat, was utilized to experimentally investigate hydrodynamic parameters such as the reduction of fluid force (RFI%), moment index (RMI%), and overflow volume (∆Q%). Moving to the second phase, an artificial neural network (ANN)-based model incorporating six and nine different neurons was applied to the experimental data. The experimental results show that RFI% and RMI% enhanced with enhancing Fr from 0.35 to 0.65. It was noticed that the maximum RFI% and RMI% were 72.84% and 69.39% when Froude number reached at 0.65 for vegetation followed by a moat (VM) respectively. It was noticed that ∆Q% decreased with enhancing the Fr. The maximum value of ∆Q% was noticed to be 44.98%. The ANN model yielded superior results with increased coefficients of determination (R2) and Nash-Sutcliffe efficiency (NSE) when configured with nine neurons in each hidden layer. Conversely, it exhibited reduced values for root square mean error (RSME), sum of square error (SSE), and mean absolute error (MAE). The finding of the study concluded that varying channel bed slopes have a greater influence on the reduction of hydrodynamic parameters.