The depth-averaged equation of flow in a rectangular compound channel with secondary flows is established by analyzing the forces acting on the elemental water body and using Newton’s second law. The analytical solution to the transverse variation of depth-averaged velocity is presented that includes the effects of lateral momentum transfer and secondary flow in addition to bed friction. Different forms of boundary conditions at the internal wall between the rectangular main channel and the adjoining floodplain are presented. A comparison with the published experimental data demonstrates that the present model is capable of predicting the distributions of depth-averaged velocity and boundary shear stress. The results also indicate that the secondary flow and boundary conditions have influences on them. Finally, the key parameters in the model, such as the Darcy–Weisbach coefficient, the momentum transfer coefficient, and the secondary flow coefficient are also discussed and analyzed.

Based on the momentum transfer theory, an analytical model is proposed for the velocity and discharge distributions in compound channels with submerged vegetation on the floodplain. The partially vegetated channel was divided into three sub-regions, i.e. the main channel region, the floodplain region with submerged vegetation and the floodplain region without vegetation. For each region, the force balance relationship was established, and the momentum transfer between different regions was presented. Verification by the experimental data and comparison with the traditional method shows that the proposed method is capable of predicting for the velocity and discharge distributions in compound channels with submerged vegetation and is superior to the conventional method. The results also show that when the momentum transfer between different regions is ignored, the computed discharge will be much lager than the measured data, and the error increases with the discharge, especially in the floodplain region.

This paper conducted an undistorted scaled model test (geometric scale λ_L = 1:80; the others are derived scales based on Froude similitude) of a 1.3 km-long river reach in Shiting River, China, investigating the impacts of the grade control datum (GCD, defined as the crest elevation of the grade control structure) drop on the upstream bed morphology. Three GCDs and six flood events (occurrence probability 1–50%, discharge = 600–4039 m³/s) were tested on the model. Experimental results indicate that, for a constant GCD, the increase in discharge deepens and widens the upstream river bed. For a lower GCD, the increase in channel depth and width caused by the increasing discharge is greater. For each discharge, the decrease in GCD induces a lower and steeper upstream river bed, widening the upstream main channel. For lower discharge, the GCD drop induces a head cut erosion area upstream of the grade control structure and the head cut erosion area is filled by the upstream sediment when the flow discharge is high. Experimental data also indicate that the maximum general scour depth at the 105th Provincial Highway Bridge is approximately independent of discharge for a constant GCD. For a lower GCD, the general scour depth at the 105th Provincial Highway Bridge increases slightly with discharge.

River width is a crucial parameter that correlates and reflects the hydrological, geomorphological, and ecological characteristics of the channel. However, the width data with high spatial resolution is limited owing to the difficulties in extracting channel width under complex and variable riverine surroundings. To address this issue, we aimed to develop an automatic framework specifically for delineating river channels and measuring the bankfull widths at small spatial intervals along the channel. The DeepLabV3+ Convolutional Neural Network (CNN) model was employed to accurately delineate channel boundaries and a Voronoi Diagram approach was complemented as the river width algorithm (RWA) to calculate river bankfull widths. The CNN model was trained by images across four river types and performed well with all the evaluating metrics (mIoU, Accuracy, F1-score, and Recall) higher than 0.97, referring to the accuracy over 97% in prediction. The RWA outperformed other existing river width calculation methods by showing lower errors. The application of the framework in the Lillooet River, Canada, presented the capacity of this methodology to obtain detailed distributions of hydraulic and hydrological parameters, including flow resistance, flow energy, and sediment transport capacity, based on high-resolution channel widths. Our work highlights the significant potential of the newly developed framework in acquiring high-resolution channel width information and characterizing fluvial dynamics based on these widths along river channels, which contributes to facilitating cost-effective integrated river management.

Using longitudinal control lines and sparse measured cross sections with large spaces, a new method for quickly reconstructing digital terrains in natural riverways is presented. The longitudinal control lines in a natural riverway, mainly including the river boundaries, the thalweg, the dividing lines of floodplains and main channel, and the water edges, can be obtained by interpreting satellite images, remote sensing images or site surveys. Then, the longitudinal control lines are introduced into quadrilateral grid generation as auxiliary lines that can control longitudinal riverway trends and reflect transverse terrain changes. Then, by the equal cross-sectional area principle at the same water level, all measured cross sections are reasonably fitted. On the above basis, by virtue of the fitted cross-sectional data and the weighted distance method, the terrain interpolations along the longitudinal grid lines are conducted to obtain the elevation data of all grid nodes. Finally, according to the readable text formats of MIKE21 and SMS, the gridded digital terrain and connection information are output by computer programming to achieve good construction of the data exchange channels and fully exploit the special advantages of various software programs for digital terrain visualization and further utilization.