Deploying initial attack resources for wildfire suppression: spatial coordination, budget constraints, and capacity constraints

Abstract

We combine a scenario-based, standard-response optimization model with stochastic simulation to improve the efficiency of resource deployment for initial attack on wildland fires in three planning units in California. The optimization model minimizes the expected number of fires that do not receive a standard response — defined as the number of resources by type that must arrive at the fire within a specified time limit — subject to budget and station capacity constraints and uncertainty about the daily number and location of fires. We use the California Fire Economics Simulator to predict the number of fires not contained within initial attack modeling limits. Compared with the current deployment, the deployment obtained with optimization shifts resources from the planning unit with highest fire load to the planning unit with the highest standard response requirements but leaves simulated containment success unchanged. This result suggests that, under the current budget and capacity constraints, a range of deployments may perform equally well in terms of fire containment. Resource deployments that result from relaxing constraints on station capacity achieve greater containment success by encouraging consolidation of resources into stations with high dispatch frequency, thus increasing the probability of resource availability on high fire count days.