Modeling complex flow structures and drag around a submerged plant of varied posture

Although vegetation is present in many rivers, the bulk of past work concerned with modeling the influence of vegetation on flow has considered vegetation to be morphologically simple and has generally neglected the complexity of natural plants. Here we report on a combined flume and numerical model experiment which incorporates time-averaged plant posture, collected through terrestrial laser scanning, into a computational fluid dynamics model to predict flow around a submerged riparian plant. For three depth-limited flow conditions (Reynolds number = 65,000–110,000), plant dynamics were recorded through high-definition video imagery, and the numerical model was validated against flow velocities collected with an acoustic Doppler velocimeter. The plant morphology shows an 18% reduction in plant height and a 14% increase in plant length, compressing and reducing the volumetric canopy morphology as the Reynolds number increases. Plant shear layer turbulence is dominated by Kelvin-Helmholtz type vortices generated through shear instability, the frequency of which is estimated to be between 0.20 and 0.30 Hz, increasing with Reynolds number. These results demonstrate the significant effect that the complex morphology of natural plants has on in-stream drag, and allow a physically determined, species-dependent drag coefficient to be calculated. Given the importance of vegetation in river corridor management, the approach developed here demonstrates the necessity to account for plant motion when calculating vegetative resistance

Patch-scale representation of vegetation within hydraulic models

Submerged aquatic vegetation affects flow, sediment and ecological processes within rivers. Quantifying these effects is key to effective river management. Despite a wealth of research into vegetated flows, the detailed flow characteristics around real plants in natural channels are still poorly understood. Here we present a new methodology for representing vegetation patches within computational fluid dynamics (CFD) models of vegetated channels. Vegetation is represented using a Mass Flux Scaling Algorithm (MFSA) and drag term within the Reynolds-Averaged Navier-Stokes Equations, which account for the mass and momentum effects of the vegetation respectively. The model is applied using three different grid resolutions (0.2, 0.1 & 0.05 m) using time-averaged solution methods and compared to field data. The results show that the model reproduces the complex spatial flow heterogeneity within the channel and that increasing the resolution leads to enhanced model accuracy. Future applications of the model to the prediction of channel roughness, sedimentation and key eco-hydraulic variables are presented, likely to be valuable for informing effective river management