Assessing the suppression difficulty of wildland fires for initial attack response

Abstract

Background: Fire simulation frameworks and decision support systems (DSSs) are critical tools in fire response dispatching that need to consider factors influencing fire spread and suppression difficulty while provide easily interpreted indexes. Aims: We present a new user-friendly Initial Attack Assessment (IAA) index, ranging from 1 to 5, designed to quickly and efficiently evaluate wildfires from their onset. Methods: We used 26,907 California’s wildfire ignitions to run automatic simulations. The Fire Behavior Index (FBI), Terrain Difficulty Index (TDI) and IAA were determined using size-based and fire behavior outputs from each simulation. Initial attack success was evaluated by comparing simulations with real fire sizes. Binary models were calibrated and validated to predict success based on IAA, FBI and TDI, and suppression response time. Key results: The IAA effectively identified fires exceeding suppression capacity. Higher levels of IAA, FBI and TDI were associated with reduced success odds, IAA=5 giving a 90% decrease in the odds of initial attack success. Response time and its interaction with terrain difficulty were also influential. Conclusions: The IAA is a powerful index to feed DSSs, prioritizing fire response and predicting the probability of control at a small size. Implications: This ensures practicality for end-users, allowing agencies and utilities to better respond to wildfires.