WRRC 2026 Spring Seminar

March 20, 2:00pm - 3:00pm
Mānoa Campus, https://hawaii.zoom.us/meeting/register/nBU0J6MNTaOruZjI23D6QA

Predictive Understanding of Wildfire Ignitions Across the Western United States By Dr. Mojtaba (Moji) Sadegh Wildfire prevention is one of the most effective and economical risk mitigation strategies. Human-started wildfires account for more than 60% of all recorded wildfires across the western United States and are responsible for the vast majority of wildfire-related societal impacts, underscoring the value of effective wildfire prevention strategies. To address this need, Dr. Sadegh and his team developed machine learning models that not only effectively predict spatial and temporal patterns of wildfire ignitions but reveal the nuanced interactions among physical, biological, social, and administrative factors that govern wildfire ignition outcomes. Annual temperature (climate), discovery day-of-year (seasonal pattern), fire year (trend), and national preparedness level (management and fire danger) were the primary governing factors in models of all ignitions, natural ignitions, and human-caused ignitions. Secondary governing factors of natural and human-caused ignitions, respectively, were weather-related attributes, and weather and social attributes. Their results indicated that although daily ignition probabilities generally track weather patterns, they can remain persistently high in areas where human factors dominate. Their results also show that models relying solely on weather do not accurately predict wildfire ignitions, reinforcing the fact that ignitions are caused by complex interactions among diverse factors.


Event Sponsor
Water Resources Research Center, Mānoa Campus

More Information
Diana Hirabayashi, 808-956-3096, dianahi@hawaii.edu,

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