Destruction caused by wildfires in the U.S. has significantly increased in the past two decades. An average of 72,400 wildfires burned an average of 7 million acres of U.S. land each year since 2000, more than double the average number of acres scorched by wildfires from 1980 to 1999. In 2018, the deadliest fire in California history, the Camp Fire, killed at least 88 people and destroyed about 14,000 homes and more than 500 commercial structures. The federal government spent more than $3 billion of taxpayers’ money putting out fires in 2018. While the spending has been increasing almost consistently, wildfire severity has been on the rise as well. Despite the current technological advancements, wildfire is growing as an outstanding threat to our communities’ prosperity, well-being, and infrastructures.

 

Figure shows annual wildfire burned area in million acres (blue) and annual federal firefighting cost in billion dollars (red) across U.S. (corrected for the CPI-U inflation rate). The blue and red lines show the 5-year moving average of burned area and firefighting cost, respectively.

Data source: National Interagency Fire Center, "Fire Information and Statistics," available at https://www.nifc.gov/fireInfo/fireInfo_statistics.html [Accessed August 2019].

 

 

Inspired by experience in the field of engineering risk assessment and disaster resilience, our vision is to develop an overarching computational platform for wildfire risk management at different spatial, temporal, and uncertainty scales. The vision will be accomplished by creating and integrating transdisciplinary scientific knowledge and techniques in the fields of data (data harnessing: collection, processing, fusion, and uncertainty quantification), computational modeling (wildfire, urban-fire, and social quality-of-life models), stochastic simulation, and model-based inference. The objective is to develop scientific foundations for a live digital platform that evolves with data as they become available, to dynamically update the pre-ignition wildfire risk from long-term (seasons-month ahead) to short-term (weeks-days ahead) at regional and community scales, and the post-ignition wildfire behavior at near-real-time (hours-days) for situational awareness.

 

 

 

Our vision is to develop an overarching computational platform, which absorbs an evolving streamline of data, updating the pre-ignition wildfire risk from long-term to short-term at regional and community scales, and post-ignition wildfire behavior at local fire scale in near-real-time.

 

 

Through a 5-year research project, funded by the National Science Foundation (NSF) Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP HI) program, we have assembled a cross-disciplinary team of engineers and scientists to tackle this critical challenge. Our plan is to integrate research tools and thinking modalities from various disciplines and integrate them under an engineering leadership to develop technological solutions. The project is led by Dr. Hamed Ebrahimian from the University of Nevada, Reno, Department of Civil and Environmental Engineering. Please reach out to him (hebrahimian@unr.edu) if you are you interested to get involved.