The effects of bed-load movement on mean flow characteristics were experimentally investigated using particle image velocimetry (PIV). The gravel beds associated with open-channel flow are hydraulically rough, and two types of grain with different median diameters were used. The flow field and bed load motion images were simultaneously obtained via the particular experimental setup. The mass of sediment particles instantaneously moving on the bed, i.e., the sand-wave, was observed in the experiment. It was found that the sand-waves have an average friction angle of 11.2 • and heights ranging from 2.2 d 50 to 3.8 d 50 . The mean velocity profiles on the mobile bed can also be represented with logarithmic distribution with deviations occurred in the near wall region. Based on the Schultz-Grunow formula, a modified equation is developed in this study to better express the flow resistance factor in terms of the Reynolds number and the ratio of flow depth to roughness height.

Due to the interaction between branch flow and main stream at confluence zone in open channel, the water level of free surface often varies dramatically. In three dimensional simulations of confluence flow, multi-phase models are usually adopted in treating the free-surface boundary, for example, the Volume of Fluid model. The major dilemma for adopting multi-phase modes is that the method consumes more time and computation resources. In this study, the new mesh technique, the dynamic meshes, is adopted to track the position of free surface. The simulation results show that simulation adopting dynamic meshes converges rapidly and is in good agreement with the experimental data. In addition, simulations and comparisons of different turbulence models coupled with dynamic meshes, rigid lid, or the Volume of Fluid method are carried out to investigate the impact by tracing the free-surface boundary. The simulated position of free surface, velocity distribution, and vector field are all compared to the data collected in the flume test. The results of numerical simulations of confluence flow using the dynamic meshes present much better accuracy than those of Volume of Fluid or rigid-lid method, although they take the same turbulence model.

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The flow patterns in confluence channel and the simulation of confluence flow are more complex than that in straight channel. Additional terms in the momentum equations, i.e. dissipation terms, denoting the impact of turbulence, and dispersion terms, denoting the vertical non-uniformity of velocity, show great impacts on the accuracy of numerical simulations. The dissipation terms, i.e. the product of eddy viscosity coefficient and velocity gradient, are much larger than those of the flow in straight channel. In this study, the zero equation model and the depth-averaged k-e model are used to analyse the impact of eddy viscosity. Meanwhile, the dispersion terms in the momentum equation, depending on the vertical non-uniformity of velocity, are usually neglected in routine simulation. With the use of detailed experimental data for verification, this study presents the distribution of parameters of vertical non-uniformity and the intimated connection between non-uniformity parameters and accuracy of numerical simulations of confluence flow with depth-averaged models. The results present that simulation accuracy of confluence flow is very sensitive to the turbulence modes, which cannot be handled by normal, simple turbulence model. On the contrary, the impact of dispersion terms is both flow-condition-dependent and place-dependent, and such impact is negligible when secondary circulation is weak. The results indicate the key elements in modelling confluence flow and are helpful for selecting suitable numerical model and solving engineering problems encountered in confluence channel.

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On 20 August 2019, a flash flood occurred in Sanjiang Town, Sichuan, China, and caused great damage to people living there. The town lies at the junction of five streams, with streams A, B, and C combining at the town and further dividing into streams D and E. The slope of streams A, B, and C is about 3~5%, while the slope of streams D and E is around 0.3%. The Sanjiang Town actually lies in the transition from supercritical slope to subcritical slope. During the flood, huge sediments were released to streams A, B, and C, and further transported to stream E. Due to the rapid change of velocity, only few sediments deposited at the supercritical slope parts of the stream, while plenty of them sedimented at the streams with subcritical slope. In order to simulate the flood with a hydrodynamic model, a field investigation was carried out to collect high DEM (digital elevation model) data, flood marks, sediment grading, etc., after the flood. The discharge curve of the flood was also obtained by the hydrometric station near Sanjiang Town. For the inlet sediment concentrations of streams A, B, and C, we made a series of assumptions and utilized the case which best fits the flood marks to set the inlet sediment concentration. Based on these data, we adopted a depth−averaged two−dimensional hydrodynamic model coupled with a sediment transport model to simulate the flash flood accident. The results revealed that the flash flood enlargement in confluence streams is mainly induced by the inflows, and the flash flood enlargement in bifurcation streams is largely affected by the sediment deposition. The bifurcation of flows can decrease the peak discharge of each branch, but may increase the flooded area near the streams. Flow in the supercritical slope runs at a very fast velocity, and seldom deposits sediment in the steep channel. Meanwhile, most sediment is transported to the streams with flat hydraulic slopes. Due to the functioning of the reservoir, the transition region from supercritical slope to subcritical slope has a much larger probability of being submerged during the flood.

Understanding hydro‐morphological characteristics in mountain river confluences is significant in flood disaster mitigation and mountain river restoration, which is still poorly explored. This study employed a 2D hydro‐morphological model based on the finite element method to simulate the major bed morphological features in a mountainous‐type flume confluence and evaluate the effects of main controlling factors on these features. The modelling results show that the dominant bed morphological features in mountain river confluences can be well produced by the 2D model. Five controlling factors including downstream water level (H), branch discharge ratio (Qr), main channel sediment supply ratio (ψ), tributary slope (St) and confluence angle (α) reflecting different flow‐sediment‐geometry scenarios were adopted into a sensitive study. The upstream reach of the main channel is controlled by H and ψ and their decreases lead to bed degradation. The increase in Qr, St, and α mainly results in bed aggradation and steepening in the tributary, attaining a higher sediment transport rate. This contrasts the existing experimental results, due to the difference in sediment feeding. The size of the bank‐attached bar is promoted by the increase in Qr, St, and α and the decrease in H and ψ. A quantitative analysis shows that the water surface slope well correlates with various dimensions of the scour hole and bar morphology (correlation = 0.58–0.8). Meanwhile, the bank‐attached bar displays a strong self‐similarity (correlation = 0.84–0.98) regarding its geometric dimensions. This study provides new insights into the existing knowledge of the hydro‐sediment‐morphodynamics of mountain river confluences obtained from laboratory studies and field investigations.