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ABSTRACT
An important issue in taking account of uncertainty in flood inundation mapping is the communication of the meaning of the outputs from an uncertainty analysis. In part this is because uncertainty estimation in this domain is not a simple statistical problem in that it involves knowledge uncertainties as well as statistical (aleatory) uncertainties in most of the important sources of uncertainty (estimated upstream discharges, effective roughness coefficients, flood plain and channel geometries and infrastructure, choice of model, fragility of defences, etc.). Thus, assumptions are required associated with the knowledge or lack of knowledge about these different sources of uncertainty. A framework has been developed in the form of a sequence of condition trees to help define these assumptions. Since stakeholders in the process can potentially be involved in making and recording decisions about those assumptions the framework also serves as a means of communicating the assumptions. Recording the decisions also serves to provide an audit trail for later evaluation of the decisions and hence the resulting analysis. Communication can also be helped in this type of spatial problem by effective visualization techniques and a visualization tool has been developed for both a web-based service using Google Maps™ and a desktop application using the Matlab™ numerical package.
Acknowledgements
Jeff Neal is thanked for carrying out the model likelihood evaluations. We are grateful to the EA for agreement to make use of the case study data.
Funding
This work was funded by the UK Flood Risk Management Research Consortium, and the NERC Catchment Change Network Knowledge Transfer and CREDIBLE projects.