Artificial reefs are being implemented around the world for their multi-functions including coastal protection and environmental improvement. To better understand the hydrodynamic and morphodynamic roles of an artificial reef (AR) in beach protection, a series of experiments were conducted in a 50 m-long wave flume configured with a 1:10 sloping beach and a model AR (1.8 m long × 0.3 m high) with 0.2 m submergence depth. Five regular and five irregular wave conditions were generated on two types of beach profiles (with/without model AR) to study the cross-shore hydrodynamic and morphological evolution process. The influences of AR on the processes are concluded as follows: (1) AR significantly decreases the incident wave energy, and its dissipation effect differs for higher and lower harmonics under irregular wave climates; (2) AR changes the cross-shore patterns of hydrodynamic factors (significant wave height, wave skewness and asymmetry, and undertow), leading to the movement of shoaling and breaking zones; (3) the beach evolution is characterized by a sandbar and a scarp which respectively sit at a higher and lower location on the profile with AR than natural beach without AR; (4) the cross-shore morphological features indicate that AR can lead to beach state transformation toward reflective state; (5) the scarp retreat process can be described by a model where the scarp location depends linearly on the natural exponential of time with the fitting parameters determined by wave run-up reduced by AR. This study demonstrates cross-shore effects of AR as a beach protection structure that changes wave dynamics in surf and swash zone, reduces offshore sediment transport, and induces different morphological features.

As an area frequently suffering from storm surge, the Yangtze River Estuary in the East China Sea requires fast and accurate prediction of water level for disaster prevention and mitigation. Due to storm surge process being affected by the long-term and short-term correlation of multiple factors, this study attempts to introduce a data-driven idea into the water level prediction during storm surge. By collecting the observed meteorological data and water level data of 12 typhoons from 1986 to 2016 at the Lusi tidal station of Jiangsu Province, China near the north branch of the Yangtze River Estuary, a Long Short-Term Memory (LSTM) neural network model was constructed by using multi-factor time series to predict the water level during the storm surge period. This study concludes that the LSTM model performs precisely for 1 h prediction of water level during the storm surge period and it can provide a 15 h prediction of water level within a limited error, and the prediction performance of the LSTM model is visibly superior to the four traditional ML models by 41% in terms of Accuracy Coefficient.

No abstract

Beach nourishment, a common practice to replenish an eroded beach face with filling sand, has become increasingly popular as an environmentally friendly soft engineering measure to tackle coastal erosion. In this study, three 200 m long offshore submerged sandbars were placed about 200 m from the shore in August 2017 for both coastal protection and beach nourishment at Shanhai Pass, Bohai Sea, northeastern China. A series of 21 beach profiles were collected from August 2017 to July 2018 to monitor the morphological changes of the nourished beach. Field observations of wave and tide levels were conducted for one year and tidal current for 25 h, respectively. To investigate the spatial-temporal responses of hydrodynamics, sediment transport, and morphology to the presence of three artificial submerged sandbars, a two-dimensional depth-averaged (2DH) multi-fraction sediment transport and morphological model were coupled with wave and current model and implemented over a spatially varying nested grid. The model results compare well with the field observations of hydrodynamics and morphological changes. The tidal range was around 1.0 m and the waves predominately came from the south-south-east (SSE) direction in the study area. The observed and predicted beach profiles indicate that the sandbars moved onshore and the morphology experienced drastic changes immediately after the introduction of sandbars and reached an equilibrium state in about one year. The morphological change was mainly driven by waves. Under the influences of the prevailing waves and the longshore drift toward the northeast, the coastline on the leeside of the sandbars advanced seaward by 35 m maximally while the rest adjacent coastline retreated severely by 44 m maximally within August 2017–July 2018. The model results demonstrate that the three sandbars have little effect on the tidal current but attenuate the incoming wave significantly. As a result, the medium-coarse sand of sandbars is transported onshore and the background silt is mainly transported offshore and partly in the longshore direction toward the northeast. The 2- and 5-year model simulation results further indicate that shoreline salient may form behind the sandbars and protrude offshore enough to reach the sandbars, similar to the tombolo behind the breakwater.

Green tides have increasingly become a nuisance worldwide in recent years, and especially in China. Since 2015, green tides have started recurring in Jinmeng Bay, Qinhuangdao, western Bohai Sea of China, and have severely deteriorated the tourism environment there. In order to investigate the migration process of the green tides in Jinmeng Bay, a hydrodynamic model and a particle-tracking model were applied based on the latest green tide event in August 2021. The hydrodynamic model was applied with triple-level 2DH meshes with different refinements and scales, which provided the hydrodynamics to drive the green macroalgae into the particle-tracking model. From the model results, the semi-enclosed waters surrounded by multiple artificial structures are a low-energy hydrodynamic environment, which is not helpful for water exchange and thus the dispersal of nutrients. The green macroalgae are distributed substantially within the semi-enclosed waters, and few are transported out with low biomass. The effects of wind and artificial structures both increase the coverage of the green macroalgae trajectories; the effect of wind plays a more important role. A sensitivity analysis of the effect of wind showed that 6 m/s wind in ENE led to the maximum coverage of the green macroalgae trajectories in the cases of different magnitudes and directions of winds. This study can provide references for the pre-warning and mitigation of green tides in Jinmeng Bay and other similar places.