Data-Driven Analysis of Stratified Flow Effect on Suspended Sediment Concentration in an Estuary

Abstract

An estuary is an area where a complex circulation pattern appears due to various hydrodynamic parameters such as tides, river discharge, salinity and water density. Especially during a flood, a large amount of freshwater discharge from a river can cause stratified flows due to the difference in density between freshwater and seawater. This makes it difficult to understand the mechanism of behavior of the suspended sediment concentration in an estuary. To elucidate this problem, we investigated field observation data in the Gyeongin Port area in South Korea during the rainy period. It was found that there were stratified flow features of flow velocity, salinity and temperature between the upper and lower layers due to the abruptly increased amount of freshwater from a river in the rainy period. An artificial neural network (ANN), one of the data-driven modeling techniques, was applied to inductively analyze the hydrodynamic factors affecting the suspended sediment concentration in the estuary. The ANN model showed the best performance when including river discharge, and flow velocity and salinity measured at the surface and bottom layer. This shows that stratified flow is important to understand the behavior of suspended sediment concentration in the estuary.