Runoff error correction in real-time flood forecasting based on dynamic system response curve

To improve the accuracy of real-time flood forecasting, a new effective error correction method based on dynamic system response curve (DSRC) was proposed in this paper. The dynamic system response curve was introduced to construct a dynamic error updating model for correcting the flood forecasting errors. In this study, the water sources separation and watershed concentration modules of the Xin'anjiang model were utilized as a response system. Substituting the linear difference for partial differential values of the response function in a nonlinear system, the system response curves of runoff time series can be obtained. Based on the observed and calculated discharge, the calculated runoff was corrected using the least square estimation, and the discharge hydrograph was recalculated with the corrected runoff. The method was tested in both ideal scenario and real case study. Comparing to the second-order autoregressive error forecast model, the new method can significantly improve the accuracy of real-time flood forecasting. The new method has a simple structure without newly introduced parameters and effective.