A new model for predicting the drag exerted by vegetation canopies

The influence of vegetation canopies on the flow structure in streams, rivers, and floodplains is heavily dependent on the cumulative drag forces exerted by the vegetation. The drag coefficients of vegetation elements within a canopy have been shown to be significantly different from the well‐established value for a single element in isolation. This study investigates the mechanisms that determine canopy flow resistance and proposes a new model for predicting canopy drag coefficients. Large Eddy Simulations were used to investigate the fine‐scale hydrodynamics within emergent canopies with solid area fractions ( λ) ranging from 0.016 to 0.25. The influences of three mechanisms in modifying canopy drag, namely, blockage, sheltering, and delayed separation, were investigated. While the effects of sheltering and delayed separation were found to slightly reduce the drag of very sparse canopies, the blockage effect significantly increased the drag of denser canopies ( λ≳0.04). An analogy between canopy flow and wall‐confined flow around bluff bodies is used to identify an alternative reference velocity in the definition of the canopy drag coefficient; namely, the constricted cross‐section velocity (Uc). Through comparison with both prior experimental data and the present numerical simulations, typical formulations for the drag coefficient of a single cylinder are shown to accurately predict the drag coefficient of staggered emergent canopies when Uc is used as the reference velocity. Finally, it is shown that this new model can be extended to predict the bulk drag coefficient of randomly arranged vegetation canopies. Key Points Drag coefficients of vegetation canopies in aquatic flows can significantly exceed those of the canopy elements in isolation This drag increase is due to the blockage effect, where high velocities adjacent to canopy elements reduce the wake pressure A new formulation for canopy drag coefficients is presented and validated against numerical simulations