Yes / Simulation of the suspended sediment concentration (SSC) has great significance in predicting the sediment transport rate, vegetation growth and the river ecosystem in the vegetated open channel flows. The present study focuses on investigating the vertical SSC profile in the vegetated open channel flows. To this end, a model of the dispersive flux is proposed in which the dispersive coefficient is expressed as partitioned linear profile above or below the half height of vegetation. The double-averaging method, i.e. time-spatial average, is applied to improve the prediction accuracy of the vertical SSC profile in the vegetated open channel flows. The analytical solution of SSC in both the submerged and the emergent vegetated open channel flows is obtained by solving the vertical double-averaging sediment advection-diffusion equation. The morphological coefficient, a key factor of the dispersive coefficient, is obtained by fitting the existing experimental data. The analytically predicted SSC agrees well with the experimental measurements, indicating that the proposed model can be used to accurately predict the SSC in the vegetated open channel flows. Results show that the dispersive term can be ignored in the region without vegetation, while the dispersive term has significant effect on the vertical SSC profile within the region of vegetation. The present study demonstrates that the dispersive coefficient is closely related to the vegetation density, the vegetation structure and the stem Reynolds number, but has little relation to the flow depth. With a few exceptions, the absolute value of the dispersive coefficient decreases with the increase of the vegetation density and increases with the increase of the stem Reynolds number in the submerged vegetated open channel flows. / the Natural Science Foundation of China (Nos. 11872285 and 11672213), The UK Royal Society – International Exchanges Program (IES\R2\181122) and the Open Funding of State Key Laboratory of Water Resources and Hydropower Engineering Science (WRHES), Wuhan University (Project No: 2018HLG01)

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