Probabilistic Risk Assessment of the Economy‐Wide Impacts From a Changing Wildfire Climate on a Regional Rural Landscape

Abstract

Abstract A warmer and drier future combined with rising population trends will result in increased wildfire risk. The design of robust mitigation/adaptation strategies requires the assessment of the economy‐wide risks from potentially more frequent large wildfire events under different futures. This study uses a novel interdisciplinary approach by integrating wildfire climate and land‐use forecasts into probabilistic and simulation models of wildfires to estimate direct impacts using damage curves and indirect impacts as lost Gross Domestic Product (GDP) using a computable general equilibrium model. Based on the financial concept of Value at Risk, a probabilistic measure of extreme economy‐wide impacts was developed using GDP as the representative metric, namely “GDP at Risk (G@R),” under various climatic and socio‐economic scenarios. Using the new metric in the Waikato, New Zealand as a case study, due its primary industries' national relevance, it was identified that there is a 5% probability that the region will experience GDP losses greater or equal to NZ$0.1–1.2 billion (similar to the regional GDP growth in 2021) over a 48‐year period from future potential large wildfires affecting vulnerable primary industries. The regional impacts result in larger national GDP losses by a factor of 5 due to the high dependence of downstream sectors on the regional primary industries. While “G@R” estimates are similar across socio‐economic scenarios, there are no discernible patterns when compared across midcentury climate scenarios. The approach developed could be used to assess the consequences from afforestation projects, driven by mitigation policies, and adaptation strategies to reduce wildfire risk.

Keywords

• probabilistic risk assessment
• computable general equilibrium
• wildfires
• climate change
• stochastic simulation
• value at risk