Flexible submerged vegetation plays a pivotal role in ecosystem. Understanding the complex impact of flexible vegetation bending on flow drag is crucial. The wide variability in drag coefficients within flexible vegetation poses challenges in accurately predicting flow drag. In this paper, the developed prediction model of velocity profile based on multi-factor-dependent drag coefficient is derived based on Euler-Bernoulli beam assumption, dual-layer averaged velocity model and the relationship between the averaged inclination angle of bent vegetation and Cauchy number. This model makes it possible to calculate the drag coefficients and velocity profiles at the same time, instead of using an assumed constant drag coefficient, and the application of this prediction model is highly favorable with experimental data. Meanwhile, new function of the depth-averaged drag coefficient applicable to submerged and emergent vegetation are presented, describing its relationship with the deformation angle of canopy, Reynolds number, submergence and water depth. The result shows that the drag coefficients for the same vegetation are smaller at higher submergence and Reynolds number. The findings of this study may provide valuable insights into the variability of drag coefficients and the flow structure with submerged flexible vegetation, and being applicable for the restoration and management of freshwater ecosystems.

中文翻译：

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基于多因素相关阻力系数的水下柔性植被稳定流速度剖面

灵活的沉水植被在生态系统中起着至关重要的作用。了解灵活植被弯曲对水流阻力的复杂影响至关重要。灵活植被内阻力系数的广泛变化给准确预测水流阻力带来了挑战。本文基于欧拉-伯努利梁假设、双层平均速度模型以及弯曲植被平均倾角与柯西数之间的关系，推导了基于多因素相关阻力系数的速度剖面预测模型。该模型使得可以同时计算阻力系数和速度剖面，而不是使用假设的恒定阻力系数，并且该预测模型的应用非常有利于实验数据。同时，提出了适用于沉水和挺水植被的深度平均阻力系数的新函数，描述了其与冠层变形角、雷诺数、淹没度和水深的关系。结果表明，相同植被的阻力系数在较高的淹没度和雷诺数下较小。这项研究的结果可以为阻力系数的变化和水下柔性植被的流动结构提供有价值的见解，并适用于淡水生态系统的恢复和管理。