Modeling Requirements for an Open‐Access Multi‐Physics Approach to Planning of Urban Evacuations Caused by Wildfire Disasters

A wildland fire is an unplanned and uncontrolled fire spreading through vegetative fuels at times involving structures. Large wildfires in wildland-urban interfaces (WUI), like the recent Fort McMurray fire in Canada, are associated with severe negative consequences including massive community evacuation, property losses, damage to infrastructure, injuries, and in some instances even fatalities.

Very often, the wisdom derived from previous wildfire disasters in other regions is the only source available to identify scenarios and plan the response of a given community. But there is no guarantee that these past experiences correlate with the next disaster to be faced. In this context, a simulation toolkit that can test ahead of time, and with little cost, the hypothetical response of a community would be highly useful. The toolkit could predict how the evacuation develops based on different fires spreading at a range of speeds and directions and different evacuation decisions (e.g., staggered evacuation by neighborhoods, arrangement of traffic flow on highways, or the appearance of congestion).

Current models do not allow users to assess and quantify the impact of operational decisions (e.g. order of evacuation, telling residents to remain in place) before they are executed; i.e. how conditions might evolve and might affect and be affected by an evacuating community. To do this, simulation tools would be needed to explore the development of a wildfire, and the impact that this has on the response (e.g. evacuation using vehicles or on foot).

This project will produce a detailed specification of a suite of open-source simulation tools enabling a system to be developed that can forecast the progress of a WUI incident and the effectiveness of pedestrian and traffic responses, according to the time and information available, incident scale, model capabilities and resources available. This study is funded through a grant from NIST.

Download the project summary. (PDF)