A real-time simulator of the rainfall-runoff process

The real-time surveilance of evolving hydrological systems is particularly attractive in situations where models are used in a control capacity. If the parameters of a process are time variant, it is meaningless to approach the identification problem in any way other than to track their variation in real-time. A study is presented of an adaptive rainfall-runoff model specifically designed for use in real-time forecasting situations. The model is essentially a linear input-output model that utilises an estimate of the effective rainfall input to predict the outflow from a catchment some time ahead. The model parameters are re-estimated at each sampling instant by utilising a sequential learning method to obtain the impulse response of the system. The convolution integral is then employed to convert rainfall to runoff. The forecast errors are corrected by using a digital filter, and a combination forecast based upon this correction is issued for several time periods ahead. The model is applied to several actual storm events and indications are given about its practical application and performance.