Variation of Yellow River Runoff and Its Influence on Salinity in Laizhou Bay

Salinity in estuaries has an important influence on sediment deposition,delta formation,and fishery economy.The change of runoff in Yellow River(YR),which is the largest river along the Bohai Sea,has an important effect on the salinity of the sea,particularly in Laizhou Bay.In this study,measured runoff data in Lijin hydrological station from 1950 to 2018 are adopted to examine the change of YR runoff into the sea.The study concludes that the runoff of YR is distributed unevenly throughout the year and the amount of runoff mainly concentrates during the flood season.Results show a decreasing trend at a significant level ofα=0.95,with a range of−6.17×10^9 m^3 yr−1.Three groups of runoff are set by using the Finite-Volume Coastal Ocean Model numerical model to analyze the change of salinity in Laizhou Bay.These modeled effects were compared with water level observations made by Bayuquan,Tanggu,and Penglai gauge stations and salinity surveys conducted by Longkou gauge station.Model results and observations of salinity distributions and coastal water level showed good agreement.We can conclude that the distribution of salinity in Laizhou Bay is high in the east and low in the west.Furthermore,it responded quickly to the change of the runoff from YR.Under conditions of high river discharge,the low-salinity zone increased in horizontal direction and reached the bottom in vertical direction.

Evaluating the Accuracy of ERA5 Wave Reanalysis in the Water Around China

Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height(SWH) of ERA 5 and that of the buoy varies from-0.35 m to 0.30 m for the three shallow locations;for the three deep locations, the variation ranges from-0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large(about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from-1.31 s to 0.4 s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water.