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An integrated hydrological ensemble prediction system (IHEPS) is providing a probabilistic assessment of future stream flow predicitons replacing the traditional forecasting method of a single deterministic flow forecast. The ensemble forecasting system includes multi model approaches where the hydrological forecasts model is driven by weather prediction model outputs to generate an ensemble stream flow forecast predictions. The performance of the IHEP systems intent to increase the credibility of the stream flow forecast predictions at the point of interest. However, quality of the stream flow forecast predictions are influenced by uncertainties originated from various sources in the forecasting chain. This paper identifies the uncertainty sources in IHEPS and describes the most suitable method to reduce their impact on the stream flow forecasts predictions. In order to undertake this assessment the uncertainty sources are separated into two fundamentally different types of uncertainties in hydrological forecast. The first type is due to a lack of knowledge about the behaviour of the hydrological system refers as a epistemic uncertainty in the forecasting chain the second type is due to randomness in the natural system known as a aleatory uncertainty. Both types of uncertainties are addressed with different approaches in order to address them. This paper presents the outcome of the uncertainty assessments of the IHEPS designed for the Nattai River catchment.


Session R42, Risk and Uncertainty in Modeling Applications I



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