The Yellow River Delta has undergone significant changes, developing a temperate chalk-sand silty coast with expansive and level tidal flats. However, the area is currently facing the threat of erosion due to coastal area construction, decreased river sediment discharge into the sea, and intensified marine hydrodynamic forces. Remote sensing technology has important applications in spatial and temporal monitoring of tidal flats. This study employs tidal data to establish the threshold range for the extraction of tidal flats in the Yellow River Qingshuigou sub-delta, using the water frequency method based on the image element proposed by previous authors. The study successfully identifies and analyzes the range of tidal flats, and further delves into their evolutionary process and underlying mechanisms. The study concludes that the area of tidal flats has shown a decreasing trend and was divided into a “rapid decline phase” and an “overall stabilization phase” with 2006 as the boundary. The spatial and temporal evolution of tidal flats is primarily influenced by three main factors: river sediment discharges, marine hydrodynamic forces, and anthropogenic reclamation activities. Specifically, the river sediment discharges and marine hydrodynamic forces impact the extent of tidal flats by modifying the boundary conditions, primarily at the sea boundary. Reclamation activities have a direct and rapid effect on the extent of tidal flats, primarily at the land boundary. In this study, we determined the contribution of three factors to the spatial and temporal evolution of tidal flats in different periods. During the two phases of the tidal flats’ spatial and temporal evolution in the Yellow River Qingshuigou sub-delta, the driving mechanisms were identified as “reclamation - marine hydrodynamic forces - river sediment discharges” and “marine hydrodynamic forces - river sediment discharges - reclamation”.

Laizhou Bay’s coastline has undergone multiple alterations due to human activities such as land reclamation and port construction. These changes in the coastline have led to modifications in the bay’s hydrodynamic conditions, which, in turn, can impact the marine environment and potentially result in a decline in biodiversity. To date, there has been no comprehensive study focusing on the coastline changes and hydrodynamic variations in Laizhou Bay. Therefore, this study utilizes coastline and water depth data from four time points—1990, 2003, 2013, and 2023—to establish a two-dimensional tidal current model of Laizhou Bay using Delft3D. Based on the good agreement between the simulated tidal current results and the observed data, this study further investigates the changes in tidal prism and water exchange in Laizhou Bay. The results indicate that tidal currents dominate the bay, with significant influences of topographic changes on the velocity and direction of tidal flows. The Eulerian residual current velocity is substantially lower than the tidal current velocity. Both tidal and residual currents play a role in controlling the distribution of materials within Laizhou Bay. Over the past three decades (1990-2023), the tidal prism in Laizhou Bay has shown a downward trend, with the tidal prism during spring, intermediate, and neap tides in 2023 reduced by 2.03%, 6.36%, and 10.19%, respectively, compared to 1990. The water exchange capacity has also weakened, with the half-exchange time being 71 days in 1990, increasing to 73 days in 2003 and 81 days in 2013, and showing a slight increase of 1 day in 2023 compared to 2013. Thus, changes in the coastline and water depth of Laizhou Bay can alter its hydrodynamic conditions, significantly impacting the tidal prism and water exchange, leading to a decrease in tidal prism and exchange rate, an increase in the water exchange period, a slower dispersion rate of pollutants, and a reduced water environmental carrying capacity. This research provides a scientific reference for protecting the marine environment and coastal management in Laizhou Bay.

Laizhou Bay, a semi-enclosed bay, is prone to storm surges from cold waves due to its geographic and environmental characteristics. This study uses satellite data, in situ measurements, and the MIKE numerical model to analyze storm surges along Laizhou Bay’s coast under no-dike conditions. It examines the surges caused by cold waves with different intensities and directions. This study provides the storm surge disaster risk levels along Laizhou Bay’s coast. The results show that the maximum sustained wind speed during cold waves is distributed between the NW and NE. The NE wind direction causes the most severe storm surge along Laizhou Bay. Under NE-directed cold waves with level 12 wind, the maximum risk areas for Level III and IV are approximately 1341 km² and 1294 km², respectively. Dongying, Shouguang, and Hanting exhibit large Level I and II risk zones. The maximum seawater intrusion distance along the Kenli coast is about 41 km. The coastal segment from Kenli to Changyi is most severely affected by storm surges. It is recommended to effectively maintain and heighten seawalls along this segment to mitigate storm surge disasters caused by strong NE winds.

Piles are common support elements for marine and coastal structures. The scour around pile foundations caused by currents is a major threat to the stability and safety of these structures. The empirical equations commonly used for estimating the equilibrium scour depth around pile groups are limited in their predicative capability, especially when the current approaches the pile group at an angle. This study applies a Multi-Layer Perceptron Backpropagation (MLP/BP) neural network to develop a general model for predicting the local maximum equilibrium scour depth around pile groups in steady currents. The input parameters for the model include all relevant non-dimensional hydrodynamic and structural variables taking full account of the effects of the pile group arrangement and its orientation relative to the approaching current. The model’s performance was evaluated by comparing its predictions against those generated by multiple other machine learning methods, as well as against results from widely used empirical formulas. A comprehensive sensitivity analysis is carried out to determine the importance ranking of the input parameters on model accuracy.

!Based on 28 years of hindcast data, this paper describes in detail the long-term variation trend of wave power density in the South China Sea. WAVEWATCH-III (WW3), the third generation wave computing model, which plays an important role in wave prediction. WW3 was used for inverse calculation of wave parameters, with spatial resolution of 0.25°×0.25° and time resolution of 6h. The validity of the data was verified by three typhoon processes and the significant wave height data of the satellite altimeter in 2010. According to 28-year(1990-2017) hindcast data set, the author respectively mapped the South China Sea mean monthly, seasonal, annual wave power density (WPD) and the change trend diagram, including the long-term trend of WPD Mann-Kendall (MK) test, come the following conclusions: (1) Influencing the area WPD change trend of the dominant increasing season is winter (DJF), in which season average growth of WPD is about 1kW/m, and the largest waters is closed to 3kW/m. (2)The dominant growing month for WPD is in December, by compared with the before and next month in the largest growing sea area, it shows an increase and decrease trend of 10kW/m and 20kW/m respectively. (3)MK test results indicate that the long-term change of WPD keep on an increasing trend, but it is not significant, among which WPD had an increased mutation in 2000. (4)The dominant sea area is around Luzon Strait-Taiwan Strait- D.S Islands (116°E, 21°N). The average growth of WPD among these area in 28 years are about 0.15-0.25(kW/m)/yr.

Under the carbon neutrality framework, multiple coastal nuclear power plants in China have received construction approval. This development has drawn increased attention to the impact of thermal discharge on the marine environment. However, research on the diffusion effects caused by different thermal discharge configurations remains limited. This study focused on the Jinqimen Nuclear Power Plant. It employed the MIKE 3 (2014) three-dimensional numerical model, combined with field observations, to systematically investigate thermal plume dispersion. Specifically, it examined the effects of different jet angles at the discharge outlet (0°, 30°, 45°, 60°, 90°, and free diffusion conditions). The results indicate that the jet angle significantly influences the thermal rise envelope area and thermal stratification characteristics. Under free diffusion conditions (without jet velocity), the thermal rise area is the largest, with high-temperature zones concentrated near the surface. As the jet angle increases from 0° to 90°, the area of low-temperature rise gradually decreases, while the area of high-temperature rise expands. Among all tested configurations, the 30° jet angle exhibits the best overall performance. It demonstrates high thermal diffusion efficiency and strong heat dilution capacity. Moreover, it results in relatively smaller temperature rise areas at the surface, middle, and bottom layers. Additionally, tidal dynamics directly affect the thermal dispersion pattern. Smaller high-temperature rise areas are observed during peak flood and ebb tides. In contrast, heat accumulation is more likely to occur during slack tide periods. This study provides a scientific basis for optimizing the layout of nuclear power plant discharge outlets. It also serves as an important reference for mitigating thermal pollution and reducing ecological impacts of coastal nuclear power plants.