Abstract: In the process of applying the hydrological model to hydrological forecasting, there are many simplifications and assumptions in the structure of the basin hydrological model, which will bring errors to the hydrological forecasting results. Therefore, error correction technology is needed to improve the accuracy of the hydrological model in real-time forecasting. The system differential response method uses the system response function to modify the forecast results by modifying the inputs, state variables and parameters of the hydrological model.This method has a solid theoretical foundation, simple structure, and the advantages of not losing the forecast period. It has been widely used in multiple watershed hydrological model with good results. VIC model is a large-scale distributed hydrological model, which divides the watershed into multiple grids of the same size to simulate runoff generation and concentration results within the grid. This paper takes the Jianyang Basin of the Minjiang River as the research area, constructs a basin VIC model for runoff simulation, applies the system differential response error correction method to the VIC model, corrects the forecast results by modifying the rainfall in the model input, and compares and analyzes it with the traditional autoregressive model error correction method（AR model）. The results show that the system differential response method has a good correction effect in the VIC model, with the Nash efficiency coefficient increasing from 0.752 to 0.895 before correction, and the relative error of runoff decreasing from 7.89% to 5.71%. The Nash efficiency coefficient of the AR model correction result is 0.807, and the relative error of runoff is 6.77%. The results of these two correction methods indicate that the system differential response method is superior to the AR model error correction method. The system differential response correction method has good applicability in the VIC model, which can significantly improve the accuracy of daily runoff simulation in the basin and can be applied to future hydrological forecasting processes.