Research advances on real-time correction methods for flood forecasting
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Abstract:
The background of real-time correction for flood forecasting is reviewed, and the research advances in real-time correction are summarized. On this basis, real-time correction was divided into two categories such as the terminal bias correction and process bias correction. The correction methods in these two approaches were sorted out, and the research results and progress were prsented. Five representative real-time correction algorithms,i.e., feedback simulation, autr-regressive(AR), recursive least squares(RLS), Kalman filtering(KF), and dynamic system response curve(DSRC),w ere introduced, and their characteristics and applicability were analyzed.The future development direction and research hotspots of real-time correction for flood forecasting were predicted.
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