Probabilistic Wildfire risk assessment methodology and evaluation of a supply chain network

Increasing wildfire risks have significantly disrupted supply chain systems in the United States, which accounts for a large portion of wildfire-induced economic losses and affects the regional and national economies. While it is important to understand wildfire effects on supply chains in meeting customer needs and achieving regional economic stability, such effects have not yet been extensively studied. This paper proposes a probabilistic framework for quantitatively assessing wildfire risk to a supply chain network. It provides rigorous probabilistic descriptions of wildfire ignition likelihood and growth, the interaction between supply chain components and wildfire, consequent component damage, and network-level performance reduction. A hypothetical forest -residuals-to-sustainable-aviation-fuel supply chain network is utilized as an illustrative example to demonstrate the capability and applicability of the proposed framework. The simulation re-sults indicate that wildfire-induced damages to feedstock nodes are insignificant (i.e., 0.1% re-duction in total feedstock availability per year), whereas total supply chain cost still increases considerably due to high unmet demand penalty and detours. Moreover, the findings further demonstrate the weakness of network configuration under wildfire risk: a failure of the process-ing facility located in the Inland Northwest of the United States results in significant increases in total transportation costs and time, which suggests that the construction of additional processors in this region could reduce wildfire risk significantly. Thus, the proposed framework can be used as a planning tool to evaluate network performance subject to a set of what-if scenarios and assess the effect of pre-and post-wildfire risk mitigation measures.