Wildland–urban interface


A wildland–urban interface is a zone of transition between wildland and human development. Communities in the WUI are at risk of catastrophic wildfire and their presence disrupts the ecology.

Definitions

In the United States of America, the wildland-urban interface has two definitions. The US Forest Service defines the wildland-urban interface qualitatively as a place where "humans and their development meet or intermix with wildland fuel." Communities that are within of the zone are included. A quantitative definition is provided by the Federal Register, which defines WUI areas as those containing at least one housing unit per.
The Federal Register definition, combined with a quantitative criteria, splits the WUI into two categories:
Structures in intermix WUI are interspersed with vegetation, whereas homes in interface WUI are adjacent to heavy vegetation.

WUI growth and causes of hazards

Throughout the world, human development has increasingly encroached into the wildland-urban interface in parallel with a climate change driven increase in large wildland fires which has caused an increase in fire protection costs. The threat increase is real and measurable through measuring expenditures which indicates an economic risk. In the United States, beginning in the late 20th century, federal wildfire suppression expenditures tripled from $0.4 billion per year to $1.4 billion per year. A tripling in expenditures indicates a tripling in threat. The wildland-urban interface has shifted to a denser population to become more hazardous.

Population shifts

The WUI was the fastest-growing land use type in the United States between 1990 and 2010. Factors behind the growth include population shifts, expansions of cities into wildlands, and new vegetation growth. The primary cause has been migration not vegetation growth. Of new WUI areas, 97% were the result of new housing. In the United States there are population shifts towards the WUIs in the West and South; increasing nationally by 18 percent per decade, covering 6 million additional homes between 1990 and 2000 which in 2013 was 32 percent of habitable structures. Globally, WUI growth includes regions such as Argentina, France, South Africa, Australia, and regions around the Mediterranean sea. Going forward the WUI will continue to expand, an anticipated amenity-seeking migration of retiring baby-boomers to smaller communities close to scenic natural resources will contribute to WUI growth.

Ecological factors

Ecological factors have resulted in a more arid and populated WUI. An arid landscape is a more flammable WUI landscape – factors include climate change driven vegetation growth and non-native insects and plant diseases. Vegetation growth has been a minor factor in WUI growth; accounting for 3% of all WUI growth in the United States. The larger factor is a climate change driven shift in temperature and precipitation that changes the wildlife composition. Wildfires in the United States exceeding has steadily increased since 1983; the bulk occurred after 2003. In addition to an increase in arid flammability, climate change is driving population shifts into the WUI which has ecological consequences.

Fire mitigation impact on environment

Environmental issues related to WUI growth extend beyond the increased risk of wildfire damage to human settlements. For example, housing growth in WUI regions can displace and fragment native vegetation. Additionally, the introduction of non-native species by humans through landscaping can change the wildlife composition of interface regions. Other factors can also have impacts on the environment, including pets which can kill large quantities of wildlife.
Forest fragmentation is another impact of WUI growth, which can lead to unintended ecological consequences. For instance, increased forest fragmentation can lead to an increase in the prevalence of Lyme disease. One possible reason for this effect is the production of high-density isolated populations of transmission vectors such as ticks and mice. Isolated forest patches in fragmented environments tend to be surrounded by unfavorable habitats, which hinders the dispersal of infected species and increases their local density. Additionally, disease vectors in isolated patches can undergo genetic differentiation, increasing their survivability as a whole.
Increases in wildfire risk pose a threat to conservation in WUI growth regions. Between 1985-94 and 2005–14, the area burned by wildfires in the United States nearly doubled from 18,000 to 33,000 square kilometers, and this increase can partly be attributed to WUI growth. In North America, Chile, and Australia, unnaturally high fire frequencies have resulted in incidences of exotic annual grasses replacing native shrublands.

Wildfire risk assessment

Calculating the risk posed to a structure located within a WUI is through predictive factors and simulations. Identifying risk factors and simulation with those factors help to understand and then manage the wildfire threat.
For example, a proximity factor measures the risk of fire from wind carried embers which can ignite new spot fires over a mile ahead of a flame front. A vegetation factor measures the risk those wind carried embers have of starting a fire; lower vegetation has a lower risk.
A quantitative risk assessment simulation combines wildfire threat categories. Areas at the highest risk are those where a moderate population overlaps or is adjacent to a wildland that can support a large and intense wildfire and is vulnerable with limited evacuation routes.

Risk factors

The Calkin framework predicts a catastrophic wildfire in the Wildland-urban Interface, with three categories of factors. These factors allow for an assessment of a degree of wildfire threat. These are ecological factors that define force, human factors that define ignition, and vulnerability factors that define damage. These factors are typically viewed in a geospatial relationship.
The ecological factor category includes climate, seasonal weather patterns, geographical distributions of vegetation, historical spatial wildfire data, and geographic features. The ecological determines wildfire size and intensity.
The human factor category includes arrangement and density of housing. Density correlates with wildfire risk for two reasons. First, people cause fires; from 2001 to 2011, people caused 85% of wildfires recorded by the National Interagency Fire Center. Second, housing intensifies wildfires because they contain flammable material and produce mobile embers, such as wood shakes. The relationship between population density and wildfire risk is non-linear. At low population densities, human ignitions are low. Ignitions increase with population density. However, there is a threshold of population density at which fire occurrence decreases. This is true for a range of environments in North America, the Mediterranean Basin, Chile, and South Africa. Possible reasons for a decrease include decreases in open space for ember transmission, fuel fragmentation due to urban development, and higher availability of fire-suppression resources. Areas with moderate population densities tend to exhibit higher wildfire risk than areas with low or high population densities.
The vulnerability factor category is measured with evacuation time through a proximity of habitable structures to roads, matching of administrators to responsibilities, land use, building standards, and landscaping types.

Risk simulations

Wildfire spread is commonly simulated with a Minimum Travel Time algorithm.
Prior to MTT algorithms, fire boundaries were modeled through an application of Huygens' principle; boundaries are treated as wave fronts on a two-dimensional surface.
Minimum Travel Time methods build on Huygens' principle to find a minimum time for fire to travel between two points. MTT assumes nearly-constant factors such as environmental factors for wind direction and fuel moisture. The MTT is advantageous over Huygens in scalability and algorithm speed. However, factors are dynamic and a constant representation comes at a cost of a limited window and thus MTT is only applicable to short-timescale simulations.

Risk management

Structure and vegetation flammability is reduced through community-focused risk management through reduction of community vulnerabilities. The degree of control of vulnerability to wildfires is measured with metrics for responsibilities and zones of defenses.

Reducing risk through responsibility distribution

The probability of catastrophic WUI wildfire is controlled by assignment of responsibility for three actionable WUI objectives: controlling potential wildfire intensity, reducing ignition sources, and reducing vulnerability. When these objectives are met, then a community is a fire-adapted community. The U.S. Forest Service defines fire-adapted communities as "a knowledgeable and engaged community in which the awareness and actions of residents regarding infrastructure, buildings, landscaping, and the surrounding ecosystem lessens the need for extensive protection actions and enables the community to safely accept fire as a part of the surrounding landscape."
Three groups are responsible for achieving the three WUI objectives, these are land management agencies, local governments, and individuals.
Fire-adapted communities have been successful in interacting with wildfires.
The key benefit of fire-adapted communities is that a reliance on individuals as a core block in the responsibility framework reduces WUI expenditures by local, regional, and national governments.

Reducing risk through zone defenses

The risk of a structure to ignite in a wildfire is calculated by a Home Ignition Zone metric. The HIZ includes at a minimum the space within a radius around a structure. The HIZ is a guideline for whoever is responsible for structure wildfire protection; landlords and tenants are responsible for physically constructing and maintaining defense zones while local government defines land use boundaries in a way that defense zones are effective :
There are three challenges.
An example of the Fire-adapted Communities performance interacting with wildfire was demonstrated in November 2018 when a wildfire passed through the community of Concow in Butte County, CA. This was the Camp Fire. The Concow community was a Fire-adapted community. This late season fire provided a stress test of the Fire-adapted Communities theory. The Concow community was destroyed. The wildfire continued through the community without demonstrating the expected slowing of the flame front. If there was a slowing it was less than anticipated though any slowing contributed to allowing residents to evacuate ahead of the flame front. The wildfire continued through wildlands between the community of Concow and the town of Paradise, CA. The wildfire then destroyed the town of Paradise which was in the process of developing into a fire-adapted community. The wildfire ignition is suspected to have originated with unhardened electrical transmission line infrastructure which had recently been redesigned though had not been reconstructed and the new design did not include hardening against ignition where it passed through the WUI. The Camp Fire demonstrated limitations of the fire-adapted community theory in late season wildfires driven by Katabatic winds, and in the land management agencies' responsibility in controlling infrastructure ignition sources.