Abstract

The concentration and spatio-temporal variation of suspended sediment concentration in the estuary area are of great significance to the nearshore engineering, port construction and coastal evolution. Based on multi-period GOCI images and corresponding measured suspended sediment concentration (SSC) data, three inversion models (the linear regression model, the power exponent model and the neural network model) were established after rapid atmospheric correction. The results show that the absolute error of the three models is 0.20, 0.16 and 0.10kg/m3 respectively, and the relative errors are 38%, 23% and 18% respectively. The accuracy of the neural network (8-17-17-1) is the best. The SSC distribution diagrams in an ebb and flow cycle are obtained using this ANN model. The results show that with Yongjiang estuary for segmentation, the high concentration area is located in the north and the lower is in the south around Jintang Island deeper water area. When the tide rises, the water flow disturbs a large amount of sediment, and then the sediment concentration increases and high area high concentrations water body moves along the SE-NW. When the tide falls, flow rate decreases and the sediment concentration decreases. However, with the falling tide, the concentration of suspended sediment in the northern sea areas gradually increases, and is higher than 1kg/m3, and gradually moves along the NW-SE until to the estuary.

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