Jiadong Fan

With the recent development from grey infrastructures to green infrastructures, artificial reefs become more popular in coastal protection projects. To investigate the responses of beach profile evolution to the presence of an artificial reef, a non-hydrostatic model is established. Both hydrodynamic and morphodynamic evolution for the beach with and without an artificial reef are compared under regular wave conditions. In addition, the protected beach profile evolution by an artificial reef is discussed under irregular wave conditions. Three key parameters in non-hydrostatic simulation are considered for sensitivity analysis, including maximum wave steepness criterium (maxbrsteep), water depth factor (depthscale), and equilibrium sediment concentration factor (sedcal). The numerical results under regular wave conditions indicate that the artificial reef enhances wave attenuation by inducing wave breaking. In addition, the artificial reef reduces local flow velocity and offshore sediment transport by 51%, therefore decrease the total erosion by 53%. Over the artificial reef, wave skewness and asymmetry go through a drastic change. Under irregular wave conditions, short waves contribute to the wave energy mainly and reflection-induced standing wave effects decline considerably. It demonstrates that the artificial reef can protect the beach from regular and irregular waves by reducing erosion and offshore transport of suspended sediments. Moreover, in the wave breaking area, the increase of maximum wave steepness criterium may give arise to the wave height. The morphological evolution is more sensitive to water depth factor than equilibrium sediment concentration factor, because the former is a controlling factor for beach profile characteristics while the latter forms the sandbar varying irregularly in shape.

Recurrent green tide has been widely studied due to its severe damage to coastal ecosystem. Jinmeng Bay, a popular resort in northeastern China, has suffered from green tide events since 2015, after the constructions of artificial islands and submerged reefs. To investigate the potential impacts of artificial islands and reefs on the water quality in Jinmeng Bay, a MIKE 21 numerical model was established by coupling a hydrodynamic model with a transport model of Chemical Oxygen Demand (COD) and nitrate ion (NO₃⁻). The changes in the water quality in Jinmeng Bay by the initial, first-stage and current construction conditions of artificial islands and submerged reefs were simulated. The model results indicated that: (1) The artificial islands and reefs in Jinmeng Bay hinder the tidal currents and weaken the tidal actions. (2) The weakened tidal actions at the estuary lead to the accretion of COD and NO₃⁻. The neap tides generate a littoral zone with the high concentration of COD and NO₃⁻, and the spring tides maintain the zone at the estuary. (3) NO₃⁻ is more sensitive than COD to the variation of hydrodynamic conditions. The NO₃⁻ concentration in the north of Conch artificial island is altered significantly, where the construction of the artificial structures decrease the concentration by ~30%, while the demolition of the connection road increases the concentration beyond its initial values by 16~21%. (4) Under the current construction conditions, the rising concentrations of COD (up to 2%) and NO₃⁻ (up to 40%) increase the frequency and scale of green tides in Jinmeng Bay considerably. Therefore, continuous monitoring of water quality is required for this region.

Oil spills are major threat to marine ecosystem and have long-lasting effect on marine life and water quality. In this study, a two-dimension hydrodynamic and oil spill transport model of the Yangtze River Estuary is established based on MIKE21 with a special attention to wind-wave-current interaction (WWCI). The model agrees well with the observed data on water level, current velocity, and the real oil spill event during Typhoon Fongwong. This study is mainly focused on the oil particle trajectory and spread. The model results show: (1) when the oil spill occurs during a typhoon period, the oil film can rapidly deposit under high WWCI, decreasing the swept area to about 20% compared with the normal weather condition; (2) strong current and large wave enlarge the oil film coverage whereas high wind speeds cause the oil particles to deposit in the shallow water area; and (3) the oil particles move farther and the swept area is far greater under the winter wind than under the summer wind, and the two times of the winter wind show the greatest effect on the oil spill. This study considers the drift, dispersion, evaporation, and emulsification of oil during the moving period under different wind, wave and current conditions, providing a good guidance for the oil spill prevention and mitigation in other estuaries.

Qinhuangdao, a famous coastal resort city in northeastern China, has been affected by the rapid growth of harmful algae. The brown tide induced by Aureococcus anophagefferens (A. anophagefferens) first occurred along Qinhuangdao’s coastline in 2009, and it then developed into a harmful alga for the Bohai Sea. Based on MIKE 21, we construct a 2D coupled hydrodynamic and transport model to study the variation and distribution of total nitrogen (TN), and establish the relationship between A. anophagefferens, dissolved organic nitrogen (DON), and TN to provide a fast forewarning system for brown tide in Qinhuangdao. This model considers the decay, diffusion, and settling of TN, and the model results are in good agreement with the measured tidal level, current, and TN, indicating that the model is capable of capturing the observed TN distribution during the brown tide period. The transfer function relating TN to A. anophagefferens leads to a reliable fast forewarning and monitoring system. Moreover, the transferred A. anophagefferens cell density can be used to forecast the regional risk level of brown tide with a specific color indicator. The implementation of national policy relating to marine ecosystems decreases the nearshore concentration of N, P, and other nutrients, and therefore decreases harmful algal blooms. The fast routine assessment of brown tide by the present warning system provides robust guidance for the government to take action.

A tidal lagoon system has multiple environmental, societal, and economic implications. To investigate the mechanism of influence of the geomorphological evolution of a tidal lagoon, the effect of critical erosion shear stress, critical deposition shear stress, sediment settling velocity, and initial bed elevation were assessed by applying the MIKE hydro- and morpho-dynamic model to a typical tidal lagoon, Qilihai Lagoon. According to the simulation results, without sediment supply, an increase of critical erosion, deposition shear stress, or sediment settling velocity gives rise to tidal networks with a stable terrain. Such an equilibrium state can be defined as when the change of net erosion has little variation, which can be achieved due to counter actions between the erosion and deposition effect. Moreover, the influence of the initial bed elevation depends on the lowest tidal level. When the initial bed elevation is below the lowest tidal level, the tidal networks tend to be fully developed. A Spearman correlation analysis indicated that the geomorphological evolution is more sensitive to critical erosion or deposition shear stress than sediment settling velocity and initial bed elevation. Exponential sea level rise contributes to more intensive erosion than the linear or the parabolic sea level rise in the long-term evolution of a tidal lagoon.

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.