Uncertainty and Good Practice in Hydrological Prediction
All forms of hydrological prediction involve many different sources of uncertainty. Many of these sources of uncertainty involve knowledge (epistemic) uncertainties that are not necessarily easy to represent statistically. This can create problems for communication and interpretation between modeller and users when uncertain predictions are presented. One way of dealing with this problem is to define Guidelines for Good Practice in the form of a set of decisions that must be agreed and recorded for later evaluation and review. The Catchment Change Network (CCN) is a knowledge transfer project, funded by the UK Natural Environment Research Council, that aims to bring academic research and practitioners together to produce guidelines for good practice
for uncertainty estimation in predicting the future in the areas of flood risk, water quality and water scarcity all of which involve important epistemic uncertainties.