The ocean chlorophyll-a (Chl-a) concentration is an important variable in the marine environment, the abnormal distribution of which is closely related to the hazards of red tides. Thus, the accurate prediction of its concentration in the East China Sea (ECS) is greatly important for preventing water eutrophication and protecting the coastal ecological environment. Processed by two different pre-processing methods, 10-year (2011–2020) satellite-observed chlorophyll-a data and logarithmic data were used as the long short-term memory (LSTM) neural network training datasets in this study. The 2021 data were used for comparison to prediction results. The past 15 days’ data were used to predict the concentration of chlorophyll-a for the five following days. Results showed that the predictions obtained by both pre-processing methods could simulate the seasonal distribution of the Chl-a concentration in the ECS effectively. Moreover, the prediction performance of the model driven by the original values was better in the medium- and low-concentration regions. However, in the high-concentration region, the prediction of extreme concentrations by the two data-driven LSTM models showed underestimation, considering that the prediction performance of the model driven by the original values was better. Results of sensitivity experiments showed that the prediction accuracy of the model decreased considerably when the backward prediction time step increased. In this study, the neural network was driven only by chlorophyll-a, whose concentration in the ECS was forecasted, and the effect of other relevant marine elements on Chl-a was not considered, which is the current weakness of this study.

Microplastics (MPs), recognized as an emerging global environmental concern, have been extensively detected worldwide, with specific attention directed towards the Yangtze River Estuary (YRE) and East China Sea (ECS) regions. Despite their critical research significance, there remains a knowledge gap concerning the distribution of MPs in the benthic layer within this area, particularly regarding interactions governing their occurrence. Here we illuminate the distribution of MPs within the benthic layer and unravel the intricate interplay between bottom water and sediment in the YRE and ECS. We find that MPs are notably more abundant in bottom water, ranging from 8 to 175 times higher than in surface water. These MPs predominantly consist of polyester fibers, exhibit a size range between 0.5 and 5.0 mm, and display distinct coloration. Co-occurrence network analysis and Principal Coordinate Analysis confirm a robust correlation between MPs in bottom water and sediment, signifying the pivotal role of bottom water in mediating the distribution and transportation of MPs within the benthic layer. Furthermore, a positive correlation between MPs in sediment and bottom water turbidity underscores the impact of surface sediment resuspension and upwelling on MPs distribution. This study clarifies the intricate interactions within the benthic layer and highlights the crucial role of bottom water as a mediator in the vertical distribution of MPs, advancing our understanding of the “source-to-sink” transport processes governing MPs within water-sediment systems.

Tropical cyclones affecting Shenzhen city have shown a remarkable tendency to increase in both intensity and quantity, highlighting the urgency of accurate forecasts of storm surges and flooding for effective planning and mitigation. Utilizing satellite and field observations together with the advanced high-resolution baroclinic wave–current model (SCHISM), a comprehensive investigation aimed at storm surge and flooding in Shenzhen was conducted. Statistical work of historical tropical cyclones revealed that Shenzhen was most vulnerable to cyclones propagating from the southeast toward the northwest and passing Shenzhen down the Pearl River Estuary. Thus, a representative, i.e., super typhoon Hato (2017), was selected for further study. Validations of numerical results suggested satisfactory model performance in mapping the wave, tide, and surge processes. Remarkable differences in spatiotemporal distribution and intensity of storm surge and flooding were found along the Shenzhen coast, which was dominated by the propagation of far-field surge and tidal waves, cooperation between wind direction and coastline orientation, estuary morphology, and the land terrain. Intervention of wave–current interaction improved the simulation of the surge and flooding and triggered an earlier occurrence time of the maximum surge in specific areas. The Pearl River discharge significantly elevated the sea level height inside the estuary and contributed to a more severe surge. Given the extremely complicated river networks and huge freshwater flux of Pearl River and the increasing trend of concurrent heavy precipitation of tropical cyclones, future investigations on compound flooding were suggested.

Tidal current asymmetry (TCA) often occurs in coastal regions. It can significantly influence bedload sediment transport. Recently, the statistical skewness of the tidal current velocity was calculated to represent the TCA. In archipelagic region, the tidal current directions vary temporally and spatially from channel to channel. This creates complexity in finding the flood–ebb axis about which to discuss the axial dissymmetry of tidal currents. In the present work, a method that involves taking the main flood direction (MFD) as the axis to split the tidal current was suggested. The MFD is the most probable direction of the strongest flood flow during each tidal cycle. The method was applied in an archipelagic region: The Zhoushan Islands. The results show that the calculated skewness well represented the TCA in waters around islands, and the degree of the TCA was mainly determined by the residual current. When the direction of the residual current was the same as the MFD, the skewness was positive, which indicated flood dominance. On the contrary, when the direction of the residual current was opposite to the MFD, the skewness was negative, which indicated ebb dominance. The stronger a residual current is, the more significant the TCA will be. Islands play an important role in forming residual circulations. Large ones force flows to move offshore around headlands or along curved channels, because of centrifugal forcing, while small ones often cause segregated flood/ebb conduits and form residual circulations. In the waterways between the Zhoushan Islands, the ebb current generally carries more sediment than the flood current. Therefore, ebb dominance always means sediment is more likely to be deposited, and vice versa. Further research into sediment transport modeling is suggested.