The Scientific Diversity, Scientific Uncertainty and Risk Mitigation Policy and Planning BNHCRC project examines three case studies in which scientific knowledges and scientific uncertainties play a significant role in the mitigation of bushfire and/or flood risk. Through these case studies, the project examines how diverse knowledge practices—including scientific knowledge, professional experience, local knowledge, and Indigenous knowledge—and key scientific uncertainties are encountered, managed and utilised by practitioners and decision-makers involved in bushfire and/or flood risk mitigation. This paper suggests that a better understanding of the interaction and evaluation of different knowledges and forms of uncertainty in such mitigation practices will enable industry to better articulate decisions to stakeholders, inquiries, and other audiences.

Scientific uncertainties are those ‘known unknowns’ and ‘unknown unknowns’ that emerge from the development and utilisation of scientific knowledges. They are the things we have comparatively limited knowledge about, whether we know it or not, because of limits in available data or modelling methods. These uncertainties are an irreducible component in any practice that utilises scientific knowledges, and, as such, they play a significant role in bushfire and flood risk mitigation professionals’ attempts to anticipate hazard behaviour within non-linear dynamical systems such as weather and climate. This is not to suggest these uncertainties are overwhelming, but that, as Moore et al. suggest (2005), risk mitigation professionals must ‘embrace uncertainty’ if they hope to comprehensively manage a given risk. This paper will survey both the key findings of the project’s literature review of relevant scientific uncertainties and the initial results of interviews and a scenario exercise involving mitigation professionals from the project’s first case study in the Barwon-Otway area of southwest Victoria. Over the past decade, this region has been the site of multi-agency efforts to reduce the residual bushfire risk using ensemble forecast modelling and fuel reduction burning.