In this article researchers and industry will learn how to reduce uncertainty in hydrological predictions. It presents the recommendations of a recent study published in the Water Resources Research journal [1].

For the first time, we have identified the best error model to use for representing uncertainty in predictions for hydrological modelling applications. So you can use the recommendations most effectively, we begin by explaining the importance of estimating uncertainty in hydrological predictions.

This was an outcome of a long-term collaboration between the University of Adelaide, University of Newcastle and the seasonal streamflow forecasting team at the Bureau of Meteorology.

The long-term goal of this research is to improve streamflow forecasts around Australia (see impact).

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