Quantifying catastrophic and climate impacted hazards based on local expert opinions. (1st January 2018)

• Record Type: Journal Article
• Authors: Keighley, Tim; Longden, Thomas; Mathew, Supriya; Trück, Stefan
• Is Part Of: Journal of environmental management. Volume 205(2018)
• Page Start: 262
• Page End: 273
• Publication Date: 2018-01-01
• Subjects: Decision making -- Environmental management -- Catastrophic risks -- Climate impacted hazards -- Expert opinions -- Loss distribution approach; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.08.035
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Quantifying the potential costs of catastrophic and climate impacted hazards is a challenging but important exercise as the occurrence of such events is usually associated with high damage and uncertainty. At the local level, there is often a lack of information on rare extreme events, which means that the available data is not sufficient to fit a distribution and derive parameter values for frequency and severity distributions. This paper discusses the use of local assessments of extreme events and utilises expert elicitation in order to obtain values for distribution parameters that will feed into management decisions with regards to quantifying catastrophic risks. We illustrate a simple approach, where a local expert is required to only specify two percentiles of the loss distribution in order to provide an estimate for the severity distribution of climate impacted hazards. In our approach we use heavy-tailed distributions to capture the severity of events. Our method allows local government decision makers to focus on extreme losses and the tail of the distribution. An illustration of the method is provided utilising an example that quantifies property losses from bushfires for a local area in northern Sydney. We further illustrate how key variables, such as discount rates, assumptions about climatic change and adaptation measures, will impact the estimates of losses. Highlights: An approach for quantifying catastrophic risks at the local level is developed. We use expert elicitation in order to estimate the parameters of loss distributions. Our method informs decision makers about worst case scenarios and extreme outcomes. We illustrate the approach evaluating risks from bushfires for a local area in Australia. Using our methodology, managers can easily conduct sensitivity analysis for key variables.