Low-flow Runoff Prediction Using the Grey Self-memory Model

Combined the grey theory with self-memory theory, a grey self-memory model was set up to predict the low-flow runoff volumes. The Chabagou catchment located in the Loess Plateau was selected to test the model. The least square method was used to determine the memory coefficients; so the prediction equation was obtained to calculate the simulation values. Compared with the grey model (1,1) (GM(1,1)), the grey self-memory model has a better fit between the simulation and measurement data during the fitting period. The pass-rate of the prediction values for two models are 100%, but the grey self-memory model is better than GM (1,1). The fitting and prediction results showed the grey self-memory model is capable of predicting the low-flow runoff volumes in the Loess Plateau.