A system approach to real-time hydrologic forecast in watersheds

In non-structural measurement of flood control, hydrologic forecasting plays a very important role. Owing to time-variance, non-linearity, and uncertainty of hydrological processes, real-time forecasting has become an efficient approach, The paper addresses an important practical problem: improving short-term hydrological forecasting based on real-time updating in the operation model. A simple nonlinear model with a variable gain parameter (VGPM) is developed. A separated calibration approach for updating parameters used in the runoff generation process and the response function in the flow routing is proposed. State space equations associated with updating model parameters in a real time scheme were developed. The VGPM approach is verified for three types of representative watersheds. The performances of different updating schemes in rainfall-runoff modeling and real-time forecasting were tested. The results indicate that significant improvement in the efficiency of hydrological modeling can be obtained from the VGPM approach, relative to simple linear models (SLM). For the watersheds with a time variant characteristic, moreover, significant improvement in the hydrologic forecasting efficiency can be obtained by adaptive schemes. The efficiency of real-time modeling by the self-adaptive Kalman Filtering algorithm was found to be very close to that of the Recursive Least-Square method.