Abstract
Considerations for selection of a real-time flood forecasting system are presented with particular emphasis on the procedure known as updating. A case study, the development and implementation of a real-time flood forecasting system for the Ganaraska River at Port Hope, is described. The forecasting model has three components: (i) a snowmelt model which requires temperature data, (ii) an abstraction model based on a variable runoff coefficient which requires rainfall, snowmelt and temperature data and (iii) a transfer-function noise (TFN) model which requires measured streamflow data. The TFN model transforms the net water inputs into streamflow and updates forecasts automatically in terms of previous forecast errors. The model has good forecasting accuracy up to a lead time of 18 hours, requires minimal real-time data or expertise and is embedded into a menu-driven computer-user interface.
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