Pappenberger and Beven (2006; Water Resources Research 42, W05302) discussed seven possible reasons why uncertainty analysis is not typically performed in hydrological and hydraulic modelling, and argued that none of these are tenable – one reason is lacking guidance on methods and applications. Inspired by this we explored the role of statistical knowledge on uncertainty in decision-making processes in long term flood risk management. We analyzed how professionals and board members of water boards in the Netherlands interpret statistical information on uncertainty and how they use this information in making strategic decisions in long term flood risk management. Research questions were:
- In which parts of flood risk management statistical information about uncertainty is presented to professionals of district water boards, and in which forms?
- How is this information interpreted and used by these professionals, and how does this influence decision-making processes in district water boards?
- How can communication about statistically quantified uncertainty be improved?
To answer these questions we conducted interviews and surveys among professionals and board members of Dutch district water boards. Results suggest that statistical information on uncertainty – such as confidence intervals – are hard to interpret by professionals. The amount of statistical information on uncertainty strongly reduces during the decision making process, during which the information transforms from quantitative to qualitative. As a result the statistical information on uncertainty is not utilized to solve flood risk management decision problems. These decision problems are not formulated within statistical frameworks for decision making, and statistical information on uncertainty is not collected and presented with the purpose to be input of such frameworks.
We recommend to involve statistical decision theory in early stages decision problems formulation in long term flood risk management, and to formulate decision problems within a framework of statistical decision making, such as an event-decision tree or NHST. Second, policy makers and hydrologists, supported by experts on statistical decision making, should define the information needed to be collected for the statistical decision framework. Finally, with the support of statistical decision frameworks they can formulate advices for management and investments needed in long term flood risk management.