Taming the forest fires of tomorrow – CleanTechnica

Wildfire has ravaged the western United States for the past decade. More than three million hectares have been burned across the country this year. As fires spark earlier each year and extend into the fall, moving from “fire seasons” to “fire years,” the National Interagency Fire Center reports that many western U.S. regions exhibit above-average fire potential.

From predicting major fires to preventing future fires, researchers at the Department of Energy’s Pacific Northwest National Laboratory (PNNL) tackle the problem of increasingly severe wildfires from different scientific angles. And they keep our lights on in the process.

From discovering where controlled combustion is best applied to protecting energy infrastructure from space, PNNL scientists are applying their research to get a head start on tomorrow’s wildfires. (Video by Sara Levine)

Fighting fires… from space

As firefighters put out fires on the front lines in 2021, a team of scientists helped out from a unique vantage point: outer space. PNNL data scientist Andre Coleman leads RADR-Fire, the satellite image processing system that maps active fires. RADR-Fire helps firefighters, utilities and other decision-makers better understand the behavior of a fire so they can make informed choices in the midst of natural disasters.

One of the many sensors that make up PNNL’s RADR-Fire system rides aboard the International Space Station, where it helps build a more complete picture of active wildfires. (Image: NASA)

But it is also a planning tool. The same information collected by the RADR-Fire system can help utilities assess risk by identifying areas most prone to wildfires and which energy infrastructure needs protection. Sensors riding aboard many different satellites — one of them an experimental sensor aboard the International Space Station — provide a wide view of the Earth’s surface.

Some satellite-based sensors can reveal where the fuel is strong, such as areas of dry, densely packed vegetation. Others show where vulnerable infrastructure, such as transmission lines or generating stations, is within reach of a fire. Coleman’s team has worked with firefighters to add new capabilities to the system, such as the ability to mark where fire retardant droplets have landed. While firefighters fight fires on the ground, RADR-Fire provides valuable information from above.

Conventional fire mapping techniques include nighttime aerial imaging aboard firefighting aircraft. Wildfire analysts process images after the plane returns to base, often drawing the shifting boundaries of the fire by hand based on the aerial images. Those cards help firefighting decision makers to allocate limited resources and manage the fire strategically. But the costly process often takes hours, the view can be obscured by thick clouds of smoke and in bad weather planes can be grounded, which are often unavailable when multiple fires require attention.

RADR-Fire gets the job done quickly and honestly. Where fire-observation aircraft are often deployed for the largest, most dangerous fires, RADR-Fire can assess smaller wildfires that rarely get the attention of aircraft, whether they’re sneaking into cities or moving through uninhabited countryside. The sensors can see through smoke and detect heat, showing exactly where and how hot fires are burning, even when visibility is poor.

However, RADR-Fire is not a panacea on one point. The mapping capability is just one of many critical tools designed to support ongoing wildfire management efforts. Today, Coleman and his team use a similar satellite network to share seasonal, short-term forecasts of fire risks with electric utilities. By processing sensor data that focuses on the vegetation surrounding the energy infrastructure, Coleman maps the “fuel landscape,” especially highlighting water-poor areas rich in dry, fire-supporting fuel.

“These seasonal forecasts are really an extension of our RADR-Fire work,” Coleman says. “At its core, RADR-Fire is about monitoring active forest fires. But we’ve expanded our tools using satellite remote sensing to now understand the state of fuels so we can get the most current and updated picture of what’s going on.”

Coleman’s team helps utilities identify other network-related risks. If a substation or high voltage corridor is surrounded by dry brush and the humidity is low, they can signal not only that fire risk but also the impact of a regional power outage. Utilities need to understand the impact of power outages on a variety of services, including hospitals, assisted living facilities, police stations, water treatment and delivery, and more.

Putting out fires before they start

Techniques such as forest thinning and controlled burning can help tame future fires before they ignite. For example, the flames stopped when they encountered Yosemite’s redwoods earlier this summer — something park administrators attribute to controlled burns. PNNL chief scientist Mark Wigmosta has partnered with the US Forest Service (USFS) to develop a new tool to help government agencies know where to dilute or apply controlled burns. In some cases these are approaches reduce fire risk by 25-96 percent.

Focusing on the Wenatchee region of Washington state, which lays claim to the largest wildfire in state history, the team worked to see how different land use patterns could make this area more resilient to both wildfires and climate change.

“By mimicking nature and adding complexity to landscapes, it helps prevent future fires from getting out of hand,” Wigmosta says.

With approximately 500 million acres of public, private, state, and tribal forests supported by USFS management, it has been challenging to prioritize which areas to focus these limited resource efforts.

Approaches like Wigmosta’s offer other benefits as well, such as reducing smoke from future fires by 33 percent and even boosting power flow by 7 to 10 percent.

“This information will help land managers design a path forward to use their resources for the biggest payoffs — whether it’s reduced wildfire emissions, improved long-term carbon sequestration or even increased power flow,” Wigmosta said.

Predicting the forest fires of tomorrow

Many of the agencies charged with identifying fire risks rely on well-known firefighting factors to estimate the hazard. If you are driving through a public forest, you may see a color wheel indicating the probability of fire: green if the risk is low, red if factors such as high temperatures and high winds indicate increased danger. But wildfires — and all the variables that determine their intensity — are more complex than that.

A few basic factors such as temperature and wind speed can give a rough estimate of the risk. However, to get a more robust and accurate picture of wildfire behavior now and in the future, we need to consider more.

That’s why atmospheric scientist Ruby Leung led a team of scientists in designing a new approach to projecting wildfire behavior. A new pair of models considers a comprehensive list of 28 “wildfire predictors” that predict wildfire behavior now and, combined with models that estimate climate change, several decades into the future.

The dryness of the vegetation, the level of humidity, the number of people living nearby – these and other variables can provide a more complete picture of how likely a fire is to strike, how far it burns and how much smoke it releases into the atmosphere.

Projecting how fire emissions rise and fall in tomorrow’s climate was the original goal of the work, Leung said, which began in partnership with the Environmental Protection Agency and was further supported by HyperFACETS, a climate science project sponsored by the Department of Energy’s Office of Science. . Although future fire behavior will vary by region, fire emissions are expected to increase.

“Some places will see a greater increase in fire emissions, while others will see less,” Leung said. “But across the board, the entire United States will see increasing fire emissions in the future. And that is being driven by warmer temperatures and increasing drought.”

The new approach uses artificial intelligence to find out which variables are most important for predicting fire area and smoke levels. just like a artificial intelligent system can deftly sort pictures of cats and dogsso it can also sort which fire predictive variables are the key to competent predictions.

Unsurprisingly, fuel drought and fuel taxation are the largest contributors. But weather patterns that unfold over the years can also significantly increase risk. Such patterns are usually not taken into account in conventional modeling of fire behavior.

Tracking fire emission levels is important because of the widespread risk to human health, Leung said. But that importance will only increase as the fires burn stronger.

“When we think of pollution,” Leung said, “we often think of emissions from exhaust pipe or by burning fossil fuels. But pollutants from forest fire emissions could exceed those two and become the largest source of pollutants in the future as fire emissions increase, while anthropogenic emissions will be reduced.”

As researchers paint ever more in-depth images of tomorrow’s wildfires, many will benefit. Utilities are better equipped to protect energy infrastructure from natural disasters, decision-makers are better informed in managing responses to a changing climate, and the scientific community has a better understanding of extreme weather.

Thanks to Pacific Northwest National Laboratory (PNNL).

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