A Study Of Vertical Distribution's Rule Of Suspended Sediment Concentration In The East China Seas

The movement of silty fine sand and the variety of the erosion and deposition are very important factor in the project of deep navigable channel regulation.The research of silty fine sand movement and suspended sediment concentration (SSC) is the key. AS to researching the SSC, the first step is the research of horizontal and vertical distribution. Meanwhile, vertical concentration is the core of research of suspended sediment three-dimensional distribution in seawater.Based on the observation data of SSC collected in the areas adjacent to Changjiang River Estuary in August, 2006. This paper takes the classical theoretical diffusion model and the microscopic kinetic theoretical model for dilute solid-liquid two-phase flows as the theoretical foundation. This paper statistically analyzed the features of vertical distribution of SSC in the sea water in the areas adjacent to Changjiang River Estuary, and established some linear regression models of vertical distribution of SSC adapting to this sea area on the basis of correlation analysis. In order to better reveal the effect of the hydrodanamic condition to shallow water shelf area of suspended sediment, this paper uses the tidal current quasi-harmonic method for short-term data to analyze the tidal current characteristics at three stations anchored in the East Sea.The harmonic component in North and East of 6 tidal constituents are calculated. Because of the turbulent information in the original records, we calculate the current regular hourly observations after pretreatment, and join the current data into the regression models. Throughout the study and verified suspension of the regional concentration of vertical distribution model.The conclusions are as following: The relative water depth is the main factor which closely affects the magnitude of SSC.As the bottom SSC and the currunt are known, the SSC at different depth layer can be calculated by using regression models. The validation tests of these models show high confidence score and the estimated values of SSC indicated that these models are more reliable and accurate when predicting the SSC in the upper and intermediate layers.