Wildfires battered Iwate Prefecture in northeastern Japan for 11 days, starting on April 22. The fires burned around 1,600 hectares and forced 3,200 residents to evacuate. With warmer climates, continued expansion of urban areas into forested regions, and the increasing frequency of extreme weather events, disasters like these are becoming more common around the world, underscoring the urgent need for advances in fire safety science and predictive modelling.
To address this growing global challenge, a new international effort to establish standardized approaches for modelling large outdoor fires is now underway under the International Organization for Standardization (ISO). The project, ISO/AWI TS 26520 - Modelling Approaches for Large Outdoor Fires, has officially been added to the work program of ISO Technical Committee 92 (Fire Safety), following the successful approval of a global ballot in March 2026. Standardization is essential to ensure that fire spread models can be consistently evaluated, compared, and applied across different types of large outdoor fire disasters worldwide.
The initiative originated from ISO TC92/WG14, the Large Outdoor Fires and the Built Environment Working Group, which balloted the new work item proposal in January 2026. The project aims to review and evaluate existing fire spread models used for a range of devastating large outdoor fire scenarios, including wildland-urban interface (WUI) fires, urban fires, post-earthquake urban fires, and fires in informal settlements.
The resulting international technical specification will provide a framework for assessing and comparing fire spread models across these diverse fire types. Such guidance is increasingly needed as communities worldwide face growing threats from large outdoor fires driven by climate change, urban expansion, and extreme weather events.
Professor Samuel L. Manzello of the Institute of Fluid Science at Tohoku University serves as the convener of ISO TC92/WG14 and has been appointed the approved project leader for ISO/AWI TS 26520. The working group has three years to develop the technical specification.
"The ability to rigorously assess and compare modelling approaches is essential for improving preparedness and response to future large outdoor fire disasters," said Manzello. "International collaboration is critical to advancing predictive tools that can support communities exposed to increasingly severe fire events."
The project also reflects rapid advances in fire modelling research. Recent studies using specialized firebrand generators developed by researchers at Tohoku University are helping train next-generation predictive models through machine learning and physics-constrained neural networks. These efforts aim to improve understanding of firebrand transport, one of the key mechanisms driving fire spread during WUI fire disasters.
In parallel with these developments, an invited perspective article authored by Professor Manzello was recently published in Fire Technology, the official journal of the Society of Fire Protection Engineers (SFPE) and the National Fire Protection Association (NFPA). The paper examines the 2025 WUI fire disaster in Ofunato City, Japan, and discusses lessons that are broadly applicable to WUI fire disasters in the United States and other fire-prone regions around the world.
As global fire risks continue to intensify, ISO/AWI TS 26520 is expected to provide an important international foundation for evaluating and improving the predictive capabilities of large outdoor fire models used by researchers, engineers, and emergency planners worldwide.
- Publication Details:
Title: The 2025 Wildland-Urban Interface (WUI) Fire Disaster in Ofunato City, Japan
Authors: Sayaka Suzuki and Samuel L. Manzello
Journal: Fire Technology
DOI: 10.1007/s10694-026-01884-5
Title: Prediction of firebrand transport using machine learning and physics-constrained neural networks
Authors: Reita Kameyama, Samuel L. Manzello, and Sayaka Suzuki
Journal: Fire Safety Journa
