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Four data-driven hydrological flood forecasting methods are applied at 20 locations in Pahang River basin, Malaysia (area 30 000 km 2 ). Models are calibrated and validated using historical monsoon flood data. To improve real-time forecast accuracy with 48-h lead time, continuous error correction is applied. An analysis of model performance above the alert water level shows that key forecast points along the main reach are best predicted using a stage regression method, whereas the upstream-most stations are best modelled using rainfall-stage correlation. The unit hydrograph method and Sugawara’s tank model perform well in the intermediate tributaries. Contrary to applying a single model to multiple points of interest or an ensemble model which requires evaluation of multiple models during operation, the multi-model approach allows the practical use of only the best-performing primary or secondary models at different points of interest within a large river basin to produce a reliable overall forecast with equal lead time.

Multi-model approach of data-driven flood forecasting with error correction for large river basins