CAUSES of Extreme WILDFIRE SPREAD EVENTS
In my new postdoctoral research position at Western Colorado University with Dr. Jonathan Coop, I have an opportunity to apply the geospatial modeling skills I acquired through my GIS minor at NCSU to help solve a problem that increasingly threatens the western communities and landscapes I love. Specifically, I am collaborating with a wonderful team of forest and fire ecologists from across the US and Canada to identify drivers of "extreme" wildfire spread events. "Extreme" wildfire spread events are defined as fire growth by >1100 hectares (2720 acres or 4.25 square miles) within a 24 hour period. Extreme wildfire spread is poorly understood, yet it is disproportionately responsible for wildfire impacts; in recent years, the top 1% of fire spread events account for 20% of total area burned! Furthermore, previous work from my collaborators indicates that the frequency of extreme wildfire events could double under near-future climate conditions. Through our ongoing work identifying the landscape, vegetation, and climatic conditions that drive extreme wildfire spread events, we can work with land management partners to develop strategies to reduce growing wildfire risks to human and ecological communities.
So how are we identifying drivers of extreme wildfire spread? Our analysis will utilize remotely sensed and other geospatial data from across the United States and Canada, and possibly Mexico. First, we need to quantify daily wildfire spread for 1000's of wildfires that occurred from 2002-2021. Our approach to quantifying daily wildfire spread leverages the final perimeters of areas burned by wildfires, which are mapped by various government entities within each country. For example, below is the final perimeter of the Sparks Lake Fire, which burned in southern British Columbia west of Kelwona from June 28th through August 16th, 2021 (yellow star on inset map). This wildfire was caused by nonindustrial human activity, likely some recreational incident (such as a campfire or ATV). It ultimately burned 86826 hectares (~335 square miles!)
So how are we identifying drivers of extreme wildfire spread? Our analysis will utilize remotely sensed and other geospatial data from across the United States and Canada, and possibly Mexico. First, we need to quantify daily wildfire spread for 1000's of wildfires that occurred from 2002-2021. Our approach to quantifying daily wildfire spread leverages the final perimeters of areas burned by wildfires, which are mapped by various government entities within each country. For example, below is the final perimeter of the Sparks Lake Fire, which burned in southern British Columbia west of Kelwona from June 28th through August 16th, 2021 (yellow star on inset map). This wildfire was caused by nonindustrial human activity, likely some recreational incident (such as a campfire or ATV). It ultimately burned 86826 hectares (~335 square miles!)
Next, infrared "hotspot" detection data from MODIS and VIIRS satellites allow us to identify where and when fire moved throughout the region. In the image below, red dots overlaying the fire perimeter are individual hotspot detections, each with unique date and time information.
Through a geospatial modeling technique called interpolation, we can use the many hotspot detections' date and time information to construct a map that represents the fire's progression over time within the final burn perimeter, called a "Day of Burning" (DOB) map. Below, regions are colored by the day they burned.
Using these DOB maps, we can quantify the area burned each day. In this example, you can easily see that a huge area burned during the early days of the fires progression, shown in blue. For example, 20314 hectares (~78 square miles) burned on day 182! That's 23% of the total area burned by this fire, in a single day! Furthermore, "extreme" spread >1100 hectares/day occurred on 22 of the 48 days the fire burned. Why did this fire spread so much so quickly??
Well, after interpolating DOB maps for nearly 20 years of wildfires, the next steps are to build geospatial and statistical models that use landscape, vegetation, fuels, climate, and daily fire weather data to predict the area burned each day. More on that soon!
Well, after interpolating DOB maps for nearly 20 years of wildfires, the next steps are to build geospatial and statistical models that use landscape, vegetation, fuels, climate, and daily fire weather data to predict the area burned each day. More on that soon!