QUIC-Fire: Current Capabilities of a Fast-Running Tool for Prescribed Fire Applications

Prescribed fire is increasingly being looked to as a tool that can support land and fire managers in their efforts towards ecological sustainability and wildfire risk management. As prescribed fire use is considered for treatment of more acres and in more complex settings, practitioners are having to work harder to meet their expanding treatment goals in a safe and environmentally responsible manner. In the context of a prescribed fire, the role of multiple ignitions and complex fire geometries depends heavily on feedbacks between the fire and atmosphere and accentuates the need for explicit representation of these processes in any modeling tools that are to be used to support prescribed fire managers. Computational fluid dynamics models like FIRETEC and WFDS are inherently capable of representing this interaction, but they are too computationally expensive for widespread uses by practitioners for exploration and analysis. We have developed a new simulation tool called QUIC-Fire to capture these fire/atmosphere feedbacks while being orders of magnitude less computationally expensive by coupling the fast-running 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. Here we describe some of the model basics and provide initial demonstration capabilities of a new fast-running modeling tool, QUIC-Fire, that can be applied to prescribed fire planning. QUIC-Fire provides a self-determining fire prediction capability that represents the critical coupled fire/atmosphere feedbacks at scales relevant for prescribed fire. Although, the development of this model is in the nascent stages, initial results show an encouraging capability to capture basic trends in fire behavior, response of fire spread to size of fire, consumption of canopy fuels in prescribed fire scenarios, interaction between multiple firelines and response to heterogeneity in vegetation. Its ability to model response to both ignition patterns and a temporally and spatially variable fire environment without computational expense of CFD solutions is encouraging.