The processes of ripple evolution are studied through numerical simulation using a coupled computational fluid dynamics (CFD)–discrete particle method (DPM) model with focus on discussing the effect of the size of the computational domain on ripple evolution. Ripple-induced form resistance and bed load transport rate are also discussed. Fluid movement is simulated using the CFD computation with the introduction of large eddy simulation for turbulent closure. The movement of sediment particles is simulated using the DPM. It is found from the results of simulation that for a two-dimensional case the ripple evolution involves three stages from wavelet, merging of wavelets to equilibrium. The ripple sizes increase during the merging process and reach a stable state at the end of the merging process. The ripple sizes obtained in the final equilibrium stage are closely related to the streamwise size of the computational domain and have an upper bound for given sediment and flow conditions. If the streamwise size of the computational domain is set to approximately 6 times the ripple length or beyond, the discrepancies among the equilibrium ripple lengths obtained from using different streamwise size of computational domain can be below 9.2%. The ripple lengths modeled in the wavelet stage agree well with the experimental results. During the process of ripple merging, an abrupt reduction in the form resistance and an increase in the bed load transport rate are observed.

The processes of sediment transport in high flow intensity are studied through numerical simulation using a coupled CFD (computational fluid dynamics)-DPM (discrete particle method) model with a focus on discussing the co-existence problem of bed load and suspended load and the corresponding sediment concentration distribution. It is shown that for the sediment-laden flows, the components of turbulence intensity decrease slightly as sediment concentration increases. The bed load and suspended load both coexist in a transition layer. Particle collision plays an important effect on the velocity of bed load movement. The total sediment transport rate obviously increases with the increase of flow intensity, but the bed load transport rate does not clearly increase. In the present study, the maximum value of suspended sediment concentration curve is about 7%, and increases with the increase of the flow intensity. The simulation results are generally consistent with experimental observation.

The processes of sediment particle movement were studied through numerical simulation using a coupled method with focus on discussing the characteristics of sliding or rolling and saltation sediment particles, respectively. Turbulent flow was simulated using large eddy simulation (LES). The sediment particle was simulated using the combined finite-discrete element method (FDEM). The interaction forces of turbulent flow and sediment particle were calculated using the immersed boundary method (IBM). It indicated that the collisions of saltating particle with low concentration increase the saltation length and flight time. In response, sediment particle velocity also increases. The particle angular velocity is largest at the takeoff moment, and decreases gradually in the saltation progress. The drag and lift forces near the bed are large, and away from the bed decrease and trend to be a stable value, gradually. From the relative magnitudes of the drag and lift forces, the lift force plays a more important role than the drag force in the sediment saltation. The relative magnitudes of drag and lift forces influence the incident and takeoff angles. The sediment transport rate calculated based on the characteristics of saltation sediment particles is overestimated, ignoring the effect of sliding or rolling sediment particles and inter-particle collisions.

A weakly compressible smoothed particle hydrodynamics (WCSPH) method was developed to model open‐channel flow over rough bed. An improved boundary treatment is proposed to quantitatively characterize bed roughness based on the ghost boundary particles (GBPs). In this model, the velocities of GBPs are explicitly calculated by using evolutionary polynomial regression with a multiobjective genetic algorithm. The simulation results show that the proposed boundary treatment can well reflect the influence of wall roughness on the vertical flow structure. A fully developed open channel is established, and its flume length, processing time, and turbulent model are discussed. The mixed‐length‐based subparticle scale (SPS) turbulence model is adopted to simulate uniform flow in open channel, and this model is compared with the Smagorinsky‐based one. For the modified WCSPH model, the results show that the calculated vertical velocity and turbulent shear stress distribution are in good agreement with experimental data and fit better than the calculations obtained from the traditional Smagorinsky‐based model.

Sensitivity analysis is necessary in numerical models to establish the optimal model configuration and simulate turbidity currents accurately. The sensitivity of turbidity currents simulated by a three-dimensional numerical model named the semi-implicit cross-scale hydroscience integrated system model (SCHISM) was assessed using domain discretization, the turbulence closure model, and the transport scheme. The results show that a higher horizontal resolution with an appropriate aspect ratio, localized sigma coordinates with shaved cells (LSC²) grid with sufficient layers, a two-phase mixture turbulence closure model, and transport schemes with critical depth ratio lower than 1 could improve the model performance on the turbidity currents. The study can provide helpful guidance to establish accurate turbidity current simulations in complex water environments.