Forecasters priorities for improving probabilistic flood forecasts

Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by hydrometeorological agencies. The most obvious advantages of HEPS are that more of the uncertainty in the modelling system can be assessed; and that ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the technical aspects of the model systems themselves. However, in this paper we argue that there are other areas of HEPS that need urgent attention; such as assessment of the full uncertainty in the forecast chain, multimodel approaches, robust forecast skill assessment and further collaboration and knowledge exchange between operational forecasters and the model development community. In light of limited resources we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement in operational HEPS.