Downdrift shoreline recession associated with the construction of a shore-crossing hard structure represents one of coastal erosional hotspots that must be addressed for an integrated, sustainable coastal zone management. To prevent siltation within the navigation channel, two rubber-mounted jetties were installed at the Sheyang River mouth on the open mesotidal muddy coast in Jiangsu province, China, in October 2013. The north jetty is 7.9 km long, while the south jetty is 7.8 km long. The net longshore sediment transport is from the north to the south due to flood-tide dominance. As disclosed by high-resolution satellite images, a 36-km-long downdrift shoreline stretch had experienced remarkable retreats at alongshore varying rates by March 2019. The eroding shoreline planform does not resemble a classic “S” shape, a crescentic shape, or a parabolic shape but an irregularly indented curved shape. Transect topographic survey also reveals an almost immediate response of the downdrift coast from the original accretionary scenery to an erosional regime, with the erosion front translocating downcoast at a much faster speed than a normal speed of 1–1.5 km/yr. Using FVCOM and SWAN, 2DH process-based numerical simulations are performed to simulate the flow, the sediment transport, and the yearly-magnitude accretion/erosion distribution in the jetty-affected area by a representative tidal force and an annual-magnitude wave force. The results demonstrate that the reciprocal tidal flow is predominantly responsible for the muddy sediment accretions at downdrift intertidal and surf zones shallower than a 4.0-m isobath, whereas big wind waves play a decisive role in triggering and developing the downdrift erosional process. The predicted spatial extent of the downdrift erosional segment matches closely the actual eroding front. The loss of the net annual longshore sediment transport volume, i.e., 3.08 million m³ due to the blockage by the twin jetties is recovered from a much larger spatial extent than the 36-km-long retreating shoreline stretch. With regard to the Bruun model, the one-line model, the headland-bay model, and the 2DH numerical model, the potential maximum recession length and the planform shape of the downdrift erosional shoreline arc are further elaborated to gain new insights into the spatial and temporal impact of a hard structure on the adjacent shoreline and flat (beach).

Reservoir construction alters the hydrodynamic characteristics of the flow and sediment regimes, resulting in the enhancement of the hysteresis effect between the flood and sediment peaks. In this study, a 3D numerical model was adopted to investigate the propagation characteristics of sediment peak and the management method of reservoir sediment release. The results indicate that the incoming flow rate and the storage water level have a great influence on the propagation time of the sediment peak, and the incoming flow rate has a large influence on the attenuation rate of the sediment peak while the storage water level and the incoming suspended sediment concentration have a small effect on the attenuation rate of the sediment peak. An empirical formula based on inflow rate, water level elevation, water depth and length and storage capacity of reservoirs was established to predict the lag time between the flood and sediment peaks. The asynchronous movement between the incoming flood and sediment peaks has a clear influence on the propagation characteristics of the sediment peak. The hysteresis effect of the flood and sediment peaks can be fully utilized by reservoir managers to reduce reservoir sedimentation and improve sedimentation distribution.

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.

Adjustment of daily discharge and sediment content in the Lower Jinsha River Basin has changed dramatically. However, the adjustment mechanism of daily sediment content under reservoir operation remains unclear. The Double Mass Curve (DMS) method was used to divide different periods of daily discharge-sediment content relationship change, and the Flow Duration Curve (FDC) was used to calculate the energy dissipation of streamflow by reservoirs. With the operation of large reservoirs, the average flood discharge and its proportion significantly decreased. With the variation in flow regime, the quantile relationship and Lower boundary relationship of daily discharge and sediment content both showed a downward trend, from 1999 to 2019. Under different periods, adjustment of the cross-flow profile was decreased with larger daily discharge, which was characterized by the ratio of sediment content to the lower boundary. An improved flow duration curve method was proposed to calculate the energy dissipation of streamflow. We discovered a novel model between the relative reduction of sediment content and relative energy dissipation of the daily discharge regime, with a good fitness of 0.97. In this study, the effect of the flow regime constructed on sediment content change was emphasized. It is helpful to evaluate the sediment reduction of the total basin caused by reservoirs.

Physics‐informed neural networks (PINNs) provide a promising framework for river hydrodynamic simulation and parameter inversion under sparse observations. However, spatial heterogeneity in channel geometry and roughness causes strong variations in flood‐wave propagation and parameter sensitivity, challenging local conservation and joint state‐parameter estimation. This study proposes a Characteristic‐aligned Control‐volume Physics‐Informed Neural Network for Roughness Estimation (CC‐PINN‐RE). It constructs dynamic diamond‐shaped space‐time control volumes from local characteristic speeds of the Saint‐Venant equations, enforces mass and momentum conservation in integral form, and combines adaptive control‐volume management with local‐sensitivity‐weighted roughness regularization. The method is evaluated on three one‐dimensional channel cases of increasing complexity against strong‐form PINN‐RE and fixed‐control‐volume cvPINN‐RE. CC‐PINN‐RE achieves the lowest errors in eight of nine relative metrics for water depth, discharge, and roughness. In Case 3, where channel width, bed slope, and roughness vary spatially, it reduces the corresponding errors by 57.0%, 82.2%, and 57.3% relative to PINN‐RE and reduces the maximum absolute error in peak water depth by 69.7%. Ablation experiments with three random seeds support the contributions of the three proposed components. Observation‐deployment experiments show that increasing the number of monitoring stations is generally more effective than increasing temporal sampling frequency at individual stations. Under 0%–2% observational noise in Case 3, the model remains stable. These results indicate that CC‐PINN‐RE provides a physically consistent framework for integrating characteristic propagation, local conservation, and parameter inversion, offering a useful basis for joint hydrodynamic reconstruction and spatially varying roughness estimation in heterogeneous river channels.