Prediction of suspended sediment concentration in the lower Yellow River in China based on the coupled CEEMD-NAR model

Abstract

The scientific and accurate prediction of suspended sediment concentrations is of great importance for river management in the lower reaches of the Yellow River and for the scheduling of water conservancy projects in the upper and middle reaches. In order to solve the influence of the non-linear and non-smooth characteristics of the suspended sediment concentration series in the lower Yellow River on the prediction results and improve the prediction accuracy, this paper proposes a coupled model based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) and non-linear autoregressive (NAR) model. Take the predicted suspended sediment concentrations in the lower reaches of the Yellow River at the Huayuankou hydrographic station as an example. The accuracy and stability of the coupled CEEMD-NAR model were verified through the Gaocun and Lijin hydrological stations. The CEEMD-NAR model predicted suspended sediment concentrations with a Nash-Sutcliffe efficiency (NSE) factor of 0.93. The three statistical evaluation indicators of the CEEMD-NAR model, mean absolute error (MAE), mean relative error (MRE), and root mean square error (RMSE) were 2.12 kg/m³, 1.07, and 3.75 kg/m³ respectively. In contrast to the NAR, EMD-NAR, and EEMD-NAR models, the coupled CEEMD-NAR model has good stability and high prediction accuracy and can be used in non-linear, non-smooth suspended sediment concentration long series prediction.

Keywords: Complementary Ensemble Empirical Mode Decomposition; Lower Yellow River; Nonlinear autoregressive model; Predicted suspended sediment concentrations.