Automatic Error Correction of Rainfall-Runoff models in Flood Forecasting Systems

Physical modelling of the dynamics of a catchment area produces simulation models with a limited forecasting accuracy for the discharge of rivers. The discrepancies between the simulation model and the actually observed past discharges can be used as additional information for error correction. With a time series model of the recent past error signal, an improved discharge forecast can be made for the next few days. The best type and order of the time series model can be selected automatically. Adaptive modelling in data assimilation calculates updates of the time series model estimated from the error data of only the last few weeks. The use of variable updated models has advantages in periods with the largest discharges, which are most important in flood forecasting