Prediction of Suspended Sediment Concentration by Artificial Neural Networks at the Vu Gia-Thu Bon Catchment, Vietnam

Suspended sediment concentration (SSC) is a key hydrological phenomenon that influences river engineering sustainability. Sediment has a significant impact on many water resources engineering problems, such as reservoir design and water quality. The approaches for estimating sediment based on the characteristics flow and sediment have some limitations due to lack of multiple observed factors. Therefore, an artificial neural network (ANN) model is used in this study to estimate monthly SSC at the catchment. The model adopts monthly observed time series of river discharge (Q) and SSC at the Vu Gia-Thu Bon catchment in Vietnam. The effectiveness of the model was evaluated using the Nash-Sutcliffe model efficiency coefficient (NSE), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results show that ANN may be used as a competent tool to forecast SSC.