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Wildland-Urban Interface (WUI) Fire Data Collection on Parcel Vulnerabilities

Summary

The Wildland-Urban Interface (WUI) is defined as the location where structures and communities meet or intermingle with undeveloped wildland. In the U.S., over 46 million homes in over 70,000 communities have been built in the wildland-urban interface and are potentially at risk from WUI fires. Between 2002 and 2016, an average of over 3,000 structures per year were lost to WUI fires in the U.S. In 2009, an estimated $14 billion was spent on WUI fire suppression and damages. The problem is worsening. In 2017, WUI fires in California destroyed 6200 homes and killed 44 people, and in 2018, the Camp Fire in Butte County CA destroyed 14,000 homes and killed 85 people. The total losses in California due to the 2018 Camp Fire and Woolsey Fires have been estimated at $15-$19 billion. An improved understanding of WUI fire dynamics and structure ignition mechanisms is critical to improving structure and community resistance to WUI fires. Post-fire data collection and analysis reveal how WUI fire behavior is driven by the interactions among fuel, weather, and terrain and the roles played by heat, embers, and direct flame impingement. This knowledge is organized through a WUI fire and ember exposure scale. Post-fire analysis also shows how fire behavior is modified by defensive actions, both active and passive. 

This project focuses on understanding the science behind WUI fires in order to reduce losses to communities, including deaths, injuries, property losses, and short- and long-term economic impacts. Previous work has focused on structure vulnerabilities identified through post-fire analysis of communities exposed to WUI fires. Full-scale experiments investigated flame spread and firebrand spotting to a nearby structure from combustible landscaping components, including fences and woodpiles. The current phase expands this work to vulnerabilities on a parcel scale. This includes the effects on WUI fire spread of interactions among combustible and non-combustible elements as well as design features of the structure and its surroundings. Data collected through this project supports development and validation of the NIST Fire Dynamic Simulator (FDS) fire model for outdoor fires, which in turn provides insight into the wind and fire dynamics. Economic analysis details the ways in which WUI fires impact the community, and social science research on decision-making by policymakers, first responders, and homeowners helps to reduce the losses.

The increased understanding and data are presented to standards organizations to provide the scientific basis for new performance-based requirements and guide the development of new codes and standards, with the intent of making structures more resistant to fire and firebrand attack. The results of this research will allow improved fire resistance of building components, structures and communities, which will improve the resilience of WUI communities.

Description

A member of a joint NIST-Texas Forest Service study team collects data on a Amarillo, Texas, building damaged by wildfires in February 2011. Photo credit: NIST.

OBJECTIVE:

To develop the measurement science needed to mitigate the effects of wildland-urban interface (WUI) fires by providing technical guidance on structures, landscaping elements, and community designs that resist ignition and limit the spread of WUI fires.

TECHNICAL IDEA:

The new technical idea is to address structure and community vulnerabilities to WUI fires through development of fire resistant design and advanced materials, based on reliable post-incident data, and promoted through incorporation into codes, standards, and best practices.

Post-fire analysis of WUI fires provides the knowledge to focus experiments and modeling on critical vulnerabilities of structures. Pathways for fire may implicate structure design, materials, and landscaping elements. Standard data collection methodologies generate reliable post incident data for inclusion in NIST’s Disaster and Failure Studies Repository. Documentation of defensive actions during WUI fire incidents is critical to the understanding of WUI structure survivability and the effectiveness of risk reduction methodologies.

Vulnerabilities identified through post-fire analysis, as well as potential mitigation techniques, can be investigated through experiments under controlled conditions in the field or in a large wind test facility. Each of the physical and chemical mechanisms involved in transporting fire to a structure, including firebrand generation and transport, radiation, and ignition processes, dominates the behavior under certain conditions. As those conditions are understood, methods to disrupt the pathways by which fire reaches and ignites a structure will become more apparent. Mitigation techniques are needed for both existing structures and for new construction. Statistical methods may be used to evaluate the relative contribution of various factors that affect structure ignitions (e.g., structural spacing, distance to wildland, topography, and fuel treatments) during WUI fires.

Structure vulnerabilities can also be explored using simulation tools. WUI fires can occur over a large range of spatial and temporal scales. Modeling the details of flame spread requires very high spatial resolution of O(1 mm) and temporal resolution of O(1 ms). At the same time, regional-scale forest fires can extend over hundreds of kilometers and persist for days or even weeks. The ability for NIST to make an impact in this area is based on the capability of the NIST Fire Dynamics Simulator (FDS) to simulate phenomena on length and time scales appropriate for studying fire spread within a community. Using a grid resolution of 0.1 m to 10 m, FDS is well-suited for studying structures and surrounding combustibles such as fences, decks, and vegetation. The FDS model can both resolve the local topography that is critical for understanding flame spread and ingest time-resolved wind data from global models and / or measurements.

The WUI Fire Hazard Scale addresses both ember and fire exposure and provides a framework for characterizing the impact that the fuel (structural and vegetative), weather (wind, humidity), and terrain play in WUI structure fire spread. Since the scale is based on the exposure to flames and embers and not on specific vegetation or materials, the exposure scale is broadly applicable across WUI communities. The exposure scale provides a basis for development of science-based performance metrics and representative test methodology for components, buildings, and communities, which will allow new materials, designs, and technologies to be evaluated under more realistic conditions. To realize these benefits, the scale must be populated with data linking fuel, weather, and terrain to potential fire exposure.

A better understanding of the social dimensions of WUI fires, including decision-making by policymakers, firefighting entities, and the public, can further the impact of the physical science-based research findings and recommendations developed by NIST. There is also a need to develop a better understanding of the relationship between the cost paid by a community for fire protection, the level of protection afforded, and the losses resulting from a WUI fire.

The new insights from this project will be incorporated into the design of new buildings and communities and retrofitting of existing buildings. The results will be disseminated to homeowners through existing community outreach programs and incorporated into existing WUI fire and building codes. Factors that may affect firefighting tactics will be communicated to organizations that fight WUI fires.

RESEARCH PLAN:

The research plan proceeds from obtaining an understanding of the vulnerabilities of structures and communities, finding ways to address them, and disseminating the new knowledge. It includes the following components:

a.     Case Studies and Post Incident Data Repository

Post-fire data collection and analysis on WUI fires identify vulnerabilities for structures, parcels, and communities and illuminate the roles of defensive actions, fuel management, and mitigation strategies in modifying the event and reducing the hazard. The analysis results help to set the research agenda at NIST. Future post-fire deployments will seek to add to the knowledge obtained in previous case studies on three major fires:  the Witch Creek-Guejito fire (San Diego, CA, 2007), the Tanglewood Complex fire (Amarillo, TX, 2011), and the Waldo fire (Colorado, CO, 2012). Planning for deployments includes: identifying the WUI event criteria for data collection that will direct future research; establishing contacts; pre-planning with local Authorities Having Jurisdiction (AHJs); identifying and preparing data collection and analysis methodologies and tools; and training of field data collectors. Data collection methodologies that were standardized during previous case studies will be updated in collaboration with partners. Data collected from NIST WUI fire deployments can be integrated into the NIST Disaster and Failure Studies Repository.

b.      WUI Data Collection Partnerships

The NIST/USFS WUI data collection efforts in the three case studies (Witch Creek 2007, Tanglewood Complex 2011, and Waldo 2012) were accomplished through partnerships with the fire services of CA, TX and CO respectively. The standardized post-fire data collection methodologies developed through these case studies recognize that budget and time limitations also impose limitations on interpretation of the results. For example, a determination of the effects of reducing fuels around the home requires extensive work to establish the timeline and locations of defensive actions throughout the community in addition to an investigation of structural damage and exposure to fire and embers. NIST has collected data from WUI fires in which structures were damaged (not destroyed) in Virginia and from historical fires in Texas. Collaborations with national, state, and local organizations collecting WUI community data pre- and post-fire will continue to be pursued, with the goals of continuing to develop best practices and of adding to the body of knowledge on the vulnerabilities of structures and communities to WUI fires.

c.     Ignition and Fire Spread Behavior Towards Structures

Analysis of post-fire data has identified some key vulnerabilities of buildings to WUI fires, including fences, decks, garage doors, woodpiles, landscaping timbers, ornamental vegetation, mulch, and leaf litter. Research is required on ignition and flame spread along these materials adjoining homes, as well as the role that they play in the ignition of buildings.  A series of experiments will quantify the fire and ember exposures generated by combustible materials on the parcel under a variety of wind conditions. The capability of mitigation approaches to reduce the exposure level will also be tested. This project complements ember studies being carried out under the project on Reduced Ignition of Building Components in Wildland Urban Interface Fires. Some experiments may be conducted in technical partnership with the Insurance Institute for Business and Home Safety (IBHS. The results will be used to develop technically sound codes, standards, and best practices for homeowners and communities.

d.      Simulation of WUI Wind and Fire Behavior

Wind, topography, and fuel are the main attributes that affect WUI fire behavior. The focus of this effort is to develop fire behavior predictive capabilities at parcel scales through modeling efforts combined with experimental work. Validation cases will be prepared for the FDS repository to confirm model integrity in WUI settings during the development of the model and the associated Smokeview visualization tool. NIST will develop a standard NIST WUI virtual parcel to study the ignition and flame spread on a scale that is suitable for Large Eddy Simulations (LES). Three different standard WUI parcel sizes will be developed at 1/4, 1/2, and 1 acre to reflect different WUI housing densities. The NIST standard WUI parcels will include a standard house, deck, fences, ornamental and wildland vegetation, and will account for the effect of surrounding houses to understand fire spread through a community. Simulation results will be distilled in a simple easy-to-understand graphical user interface (GUI) for providing guidance to Authorities Having Jurisdiction (AHJs), Non-Government Organizations (NGOs), Home Owner Associations (HOAs), and homeowners that want to reduce fire hazards in the WUI.

e.     Filling in the Exposure Matrix of the WUI Fire Hazard Scale

A WUI exposure scale framework has been developed to provide a common scale for quantifying the assault on structures from embers and fire. After it is quantified, the exposure scale can be used to improve building codes, standards, and best practices to meet the survivability requirements of structures in certain fire and ember exposure environments. The exposure scale needs to be populated based upon historical data, field data collected in coordination with state and local agencies, data provided through standardized data collection methodologies, NIST FDS model simulations, and targeted laboratory and field experiments. The assessment will include extreme fire events, in which high winds, rapid changes in wind direction, horizontal roll vortices, and interactions among fuel, weather, and topography lead to rapid and disastrous fire growth.

f.     Social Aspects of WUI Fires

This task explores areas of social science research that NIST can use to enhance its impact on reducing losses from WUI fires. Before, during, and after any WUI fire event, decisions are made by people at all levels within the community to reduce losses from WUI fires. At the individual and household level, people may modify their properties before a fire to mitigate its effects, must respond to a fire as it approaches, and need to deal with the aftermath of the fire as it has affected them. At the organizational level, firefighter situational awareness is key to decisions made about evacuation or deployment during a WUI fire event. At the community level, improvements to codes and standards must be adopted and enforced in order to fully realize the benefits. A better understanding of the social dimensions of WUI fires can further the impact of the physical science-based research findings and recommendations developed by NIST. Situational awareness, evacuation decision-making, emergency communications, and public response are being studied for the November 2016 Chimney Tops 2 fire (Gatlinburg, TN) using a survey instrument. In FY20, providers of emergency information in Tennessee will be interviewed, if

g.      Measurement of the Economic Burden of WUI Fire

Advancements in measurement science are needed to estimate the general economic consequences from WUI fires. Tools are needed to track the economic burden on communities and to assist policymakers, firefighting organizations, and homeowners in their decisions on where investments may be made to reduce the fire problem. Previous work found large uncertainties in the estimation of some costs and losses due to wildfire. These uncertainties can be reduced using a Computable General Equilibrium (CGE) model, which comprises a system of nist-equations representing supply and demand relationships within an economy. Shocks to supply and demand, causing disequilibrium, can be modeled to understand how economies react to various scenarios. The focus in FY19 is to develop a CGE model, and its associated social accounting matrix, which describes economic flows and receipt of payments within an economy, for a region of California that includes the town of Paradise. In FY20, identified economic shocks induced by the 2018 Camp Fire will be modeled to quantify the extent of indirect losses experienced by the region. In addition, combinations of known wildfire-induced shocks (e.g., structure loss, out-migration, business interruption) will be simulated within the CGE environment to identify scenarios that could limit recovery during post-wildfire periods. In FY21, the CGE model will be generalized to inform the economic performance of mitigation options available for several community archetypes.

Created November 2, 2011, Updated October 16, 2019