Fire modeling tool aims to predict how prescribed burns behave in hot, dry weather
The Southwest’s fire season is lasting longer and getting worse, according to researchers. Fire officials do have a trick up their sleeve: prescribed or planned burns.
The Los Alamos National Laboratory is creating a tool that uses physics and data modeling to predict how a prescribed burn might behave before it’s lit. But, in hot, dry weather it’s harder to keep them under control.
KUNM sat down with Senior Scientist Rod Linn to learn more.
ROD LINN: The planning for prescribed fire usually starts around a set of objectives. Those could be reducing the risk of catastrophic wildfires or they might be for ecological benefits. How do we meet those objectives safely? For most prescribed fire planning, it's a process by where experts weigh those different factors, and try to understand the conditions under which they can achieve their goals in a safe manner. The other big constraint that they're oftentimes looking at is where are they putting the smoke from their fires? They try to avoid putting smoke in communities, for instance, or on critical infrastructure.
KUNM: Can you talk to me more about this tool that you're developing called QUIC-fire? How does it work? And, what does it mean for forest management here in the Southwest, specifically?
LINN: So, QUIC-fire is a tool that's been developed by the Los Alamos National Laboratory, in partnership with the U.S. Forest Service, Tall Timbers, and now the U.S. Geological Survey. The goal of QUIC-fire has been to capture or represent the most critical physical phenomena that determine fire behavior, so that we can model or simulate prescribed fires. Prescribed fires are extremely challenging, because they're often done in mild conditions. That's a little counterintuitive to most people, because in mild conditions, most people would think that would be the easy time to model or simulate a fire or predict where a fire is going to go. And in reality, those are oftentimes more challenging to simulate or predict, than stronger fires. That's because the fluctuations and the winds, that would be gusts, or variability in the vegetation can mean a lot more under mild fire conditions.
The other piece of that is when the winds change, either unexpectedly or expectedly, that can cause big changes in fire behavior, both wildfire and prescribed fire. So, the planning process for prescribed fires always includes an effort to understand how the conditions are going to evolve over the day or over the duration of that fire.
KUNM: With all that we know to be true about fire seasons essentially going out the window, how is fire modeling adapting to the unpredictability of climate change right now?
LINN: As you mentioned, with climate change or evolving conditions, combined with evolving ecosystem conditions that are partially caused by the exclusion of fire for nearly a century, we're having to work harder to anticipate how fire will behave in various ecosystems. That's especially hard if you start thinking about the addition of other disturbances such as insect or bark beetle outbreaks that kill trees and change the ecosystem conditions. That translates to a need for fire behavior models or fire prediction tools. They're built from an understanding of the basic physical phenomenology that drives fires––because that basic physics isn't changing, even when the conditions change. Whereas, if you simply observed fire in the past under one set of conditions, it's not a guarantee that fire will behave exactly the same under future conditions, whether those be climate changed or fuel accumulation changed. What we're really working to do in the field of fire behavior modeling is tie our predictions and our simulation tools much more to the fundamental physics that responds to those evolving fire conditions.
KUNM: All right, well, thanks for taking the time to join us today.
LINN: Thank you.