The coastline of the Yellow River Delta has undergone continual alterations due to both natural forces and human activity. Studying these changes is crucial for promoting economic growth and preserving the region’s ecological balance. Based on imagery captured by the Landsat5 and Landsat8 satellites, this study uses statistical data from the Digital Shoreline Analysis System (DSAS), including Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR), to analyze the changes in the Yellow River Delta coastline from 2009 to 2019. This being the case, a hydrodynamic model under different shoreline conditions was established using Delft3D to compare and analyze the impact of shoreline changes on the tidal current field. From 2009 to 2019, the coastline in the study area exhibited an average movement distance of 1285m (NSM) and an annual change rate of 127.7m/a (LRR). The average increase in the area of the current estuary was 7.68km²/a, while the average decrease in the area of the old estuary was 4.91km²/a. Shoreline evolution is primarily influenced by the influx of water and sediment into the ocean. Following the implementation of water and sediment regulation, the existing estuary’s shoreline experienced a rapid initial accumulation of silt, which subsequently decelerated over time. Conversely, the former estuary has consistently undergone erosion. The greater the change in shoreline, the closer to the coast, and the greater the change in the tide. From 2009 to 2019, flow velocity and direction in the Yellow River Delta generally showed a decreasing trend, with changes ranging from 0.34% to 25.94%. The residual flow velocity near the current estuary gradually increased by about 2cm/s, while that near the abandoned old estuary gradually decreased by about 1cm/s, with no significant changes offshore. The sediment transported by the Yellow River is deposited at the current estuary, causing the coastline to move northeastward. In the abandoned estuary, there is erosion, causing the coastline to retreat.

In 2020, Yellow River runoff was more than twice as much as past years, and the proportion of strong winds was also higher than that in past years, which will inevitably lead to a change in salinity plume distribution in the Yellow River Estuary and Laizhou Bay. Based on FVCOM numerical modelling, this paper presents the spatial salinity distribution and dispersion of the Yellow River Estuary and Laizhou Bay during the wet and dry seasons in 2020. We used data from six tidal and current stations and two salinity stations to verify the model, and the results showed that the model can simulate the local hydrodynamic and salinity distribution well. The influence of river discharge and wind speed on salinity diffusion was then investigated. The simulation results showed that under the action of residual currents, fresh water from the Yellow River spread to Laizhou Bay, and the low salinity area of Laizhou Bay was mainly distributed in the northwest. The envelope area of 27 psu isohaline can account for about one-quarter of Laizhou Bay in the wet season, while the low-salinity area was only concentrated near the estuary of Yellow River in the dry season. River discharge mainly affects the diffusion area and depth of fresh water, and wind can change the diffusion structure and direction. In the wet season, with the increase in wind speed, the surface area of the plume decreased gradually, and the direction of the fresh water plume changed counterclockwise from south to north. During the dry season, the plume spread to the northwest along the nearshore. The increase in wind speed in the early stage increased the surface plume area, and the plume area decreased above a wind speed of 10 m/s due to the change in the turbulence structure. The model developed and the results from this study provide valuable information for establishing robust water resource regulations for the Yellow River. This is particularly important to ensure that the areas with low salinity in the Yellow River Estuary will not decrease and affect the reproduction of fish species.

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.

The evolution of renewable energy technologies may surmount fossil fuel disadvantages. Wave energy is considered one of the best alternatives to fossil energy due to its advantages. The 40-year (1979–2018) spatio-temporal distribution of wave energy is presented using European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) datasets. In addition, the common formula used for wave energy evaluation is derived from the linear wave theory in deep water, which is not applicable in shallow water. Therefore, a new equation that is suitable for both shallow and deep water is derived, which improves the accuracy of the wave energy evaluation for various water depths. The main aim is to investigate the spatio-temporal wave energy for offshore China from 1979 to 2018 and combine the new standard of classification to recommend the optimal area. The nearshore zone from Zhejiang province to Guandong province is considered the ideal zone, and the average annual wave energy density in this area is above 10 kW/m.