Optimizing Prescribed Burn Risk Management: A Computational and Economic Modeling Approach Using QUIC FIRE Simulations

This paper introduces a computational framework for optimizing vegetation removal, modelled via so-called blackline or fireline widths, to enhance efficiency and cost-effectiveness of a prescribed burn for planned reduction of vegetation density. The QUIC FIRE simulation tool is employed to conduct simulations across fireline widths ranging from 8 to 24 m in 2-m increments within a strategically chosen burn unit that covers the usecase of a wildland urban interface located around the region of Auburn, CA. Through visual analysis and quantitative cost function assessment, incorporating polynomial fit and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm within a basin-hopping framework, an optimal fireline width is computed that minimizes costs, efforts and the risk of fire escapes. Findings indicate that strategic adjustments in fireline widths significantly influence the success of prescribed burns, underscoring the value of advanced simulation and optimization techniques. This work provides a foundational framework for subsequent studies, advocating for the development of dynamic, adaptive models that are scalable across varied ecological and geographical settings. Contributions extend to a computational and economic perspective on sustainable risk mitigation, underlining the pivotal influence of technology and advanced modeling in the evolution of prescribed burn strategies.