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ENGAGING STAKEHOLDERS WITH UNCERTAINTY

ENGAGING STAKEHOLDERS WITH UNCERTAINTY . Hazel Faulkner & Simon McCarthy. ?. FHRC research for FRMRC1/2 INTERVIEWS with Environment Agency professionals Insurers Floodplain planners How can FRM optimise risk and uncertainty communications at the professional interface?

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ENGAGING STAKEHOLDERS WITH UNCERTAINTY

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  1. ENGAGING STAKEHOLDERS WITH UNCERTAINTY Hazel Faulkner & Simon McCarthy ?

  2. FHRC research for FRMRC1/2 • INTERVIEWS with • Environment Agency professionals • Insurers • Floodplain planners • How can FRM optimise risk and uncertainty communications at the professional interface? • Why the reluctance to use uncertainty tools • ....barriers?

  3. stakeholders at sources of information ‘science’ Information receptors, category I BARRIERS? MANY SCIENTIFIC ,PROFESSIONAL AND LAY STAKEHOLDERS As webs of influence vary, agendas vary, information needs vary, risk communication strategies & appropriate tools will be totally different Stakeholders in information pathways professionals Information receptors, Category II floodplain stakeholders stakeholders outside floodplain

  4. BARRIERS? SCIENTIFIC AND DECISION MAKERS DIFFER IN THEIR UNDERSTANDING OF THE SOURCES OF UNCERTAINTY SCIENTIFIC UNCERTAINTY Uncertainty in the science of flood forecasting and runoff prediction models are largely associated with their assumptions, structure, and boundary conditions, and confidence in validation procedures given uncertainties about climatic and societal futures PROFESSIONALS experience BINARY DECISION UNCERTAINTY (Decision rule uncertainty) • The implication of this is that scientific uncertainty is an relatively unwelcome part of the risk message they are charged with translating for the public

  5. BARRIERS? THE LANGUAGE OF SCIENCE IS OPAQUE TO THE NON-SCIENTIFIC PROFESSIONAL • If originally formulated in Bayesian terms, the language may be too opaque for translation to be effective – do professionals have sufficient statistical familiarity? • Bayesian statistics ? • Prior probability distributions? • fuzzy set methods ? • info-gap methods ? • NUSAP? • match tool to communication interface • The implication of this is that the language used to communicate the uncertainty must match the needs and agenda of the agencies involved in the communication being undertaken

  6. Bayesian uncertainty tools – GLUE Phone warnings Newspaper/TV /twitter stakeholder consultation ’traffic lights’ webpages/leaflets stakeholders at sources of information ‘science’ Information receptors, category I THE WAY FORWARD: TRANSLATIONAL DISCOURSES? LANGUAGE AND TOOLS TO DESCRIBE UNCERTAINTY VARY Rt = H x V 1;100/1;1000 fuzzy edged Stakeholders in information pathways professionals Information receptors, Category II floodplain stakeholders stakeholders outside floodplain

  7. FINDINGS • Our research (Faulkner et al 2007;McCarthy et al. 2009), both the interviews undertaken with professionals and from the ‘experiment’ undertaken at the co-location workshop in Exeter, found that : • The power of VISUALISATIONS AND ANIMATIONS in realising the uncertainty estimates was potentially great; • The professionals questioned initially struggled to comprehend scientifically defined flood forecast uncertainties (probabilistic and/or ensemble forecasts) without FURTHER TRANSLATION OF THE SCIENCE. When this was available as perhaps a ‘translational discourse’, the preparedness to embrace a more sophisticated expression of the model’s uncertainties was welcomed. • Better DECISION-SUPPORT TOOLS are needed. FINDINGS

  8. The WIKI Decision-support tool Decision Tree and Wiki Pages at http://www.floodrisknet.org.uk/methods/

  9. A ‘TRANSLATIONAL DISCOURSE’ BRAINSTORMING Brainstorming sessions involving professionals/scientists and practitioners A GUIDANCE MANUAL how to involve all stakeholders, especially professionals at local level is needed – professional input here important; MORE DECISION SUPPORT TOOLS NEEDED......

  10. Acknowledgement The research reported in this presentation was conducted as part of the Flood Risk Management Research Consortium with support from the: • Engineering and Physical Sciences Research Council • Department of Environment, Food and Rural Affairs/Environment Agency Joint Research Programme • United Kingdom Water Industry Research • Office of Public Works Dublin • Northern Ireland Rivers Agency Data were provided by the EA and the Ordnance Survey.

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