Submerged aquatic vegetation (SAV) changes the turbulent structure of rivers, wetlands, estuaries, and lakes. However, few studies have focused on the influence of SAV on hydrodynamic characteristics under wind-induced flow. Therefore, laboratory experiments were conducted to study the effects of SAV on the flow structure and turbulence characteristics under wind-induced flow, and spectral based decomposition method was used to separate turbulence and wave velocity. Result shows that SAV reduced local velocity within canopy and elevates the location of the zero-velocity point. The canopy drag caused by SAV increases the decay rate of turbulent Reynolds stress along depth while hardly influencing wave Reynolds stress. Canopy drag depresses the turbulent RMS (root mean square) velocity and wave orbital velocity. The presence of SAV leads to the decrease in TKE (turbulent kinetic energy) production and dissipation rate within canopy. The canopy drag more effectively diminishes TKE production than it does the dissipation. Research on local isotropy of SAV in wind-induced flows shows that the presence of SAV promotes a gradual transition from local anisotropy to local isotropy in turbulence within canopy. Finally, quadrant analysis reveals that the presence of SAV reduced the probabilities and the contribution to turbulent momentum of ejection and sweep.

The wind drag coefficient, $C_d$, has a great influence on the numerical results obtained from shallow lakes. To analyze the modeling impacts of $C_d$ on wind-driven currents, a series of numerical simulations of Lake Taihu were conducted at three grid resolutions (800 m × 800 m, 400 m × 400 m, and 100 m × 100 m) using the empirical formulae of Flather (F76), Large and Pond (LP81), Large and Yeager (LY04), Andreas (A12), and Gao (G20). The G20 formula produced the optimum results of all the formulae for both the water level and velocity simulations; however, the grid resolution was found to have a significant influence on simulation in G20 cases. Thus, the G20 formula is only recommended when using a high-resolution grid to meet the accuracy requirements of analyzing wind-driven currents in the numerical modeling of Lake Taihu. A combination of the A12 formula and a coarse grid is preferred when taking computational efficiency into consideration.