Assessing the suppression difficulty of wildland fires for initial attack response

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.

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Publication Details

Journal
International Journal of Wildland Fire
Published
2025-11-26
DOI
https://doi.org/10.1071/wf24160
Citations
1
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
1.11
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article

Assessing the suppression difficulty of wildland fires for initial attack response

Adrián Cardíl, Midhun Mohan, Robert M. Clark, Santiago Monedero et al.
1 citations
International Journal of Wildland Fire
Fire effects on ecosystems
1.11
article

Assessing the suppression difficulty of wildland fires for initial attack response

Adrián Cardíl, Midhun Mohan, Robert M. Clark, Santiago Monedero, Raúl Quilez, Geoff Marshall, Scott Purdy, C. L. Waters, Joaquín Sosa Ramírez, Adrián Jiménez-Ruano, José D. Fuentes, Tomás Quiñones, Kristen Allison, Sergio de‐Miguel, Phillip Selegue, Tim Chavez, Tim Metzger
article en
1 citations

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.

International Journal of Wildland FireVol. 34(12)
New York City Fire Department (US), Universitat de Lleida (ES), Forest Science and Technology Centre of Catalonia (ES), Pacific Southwest Research Station (US), Geosyntec Consultants (United States) (US), University of Córdoba (ES), Universidad de León (ES), University of California, Berkeley (US)
Openalex Percentile: Top 17%
Fire effects on ecosystems
1.11
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