The National Institute of Standards and Technology (NIST) is working to reduce the risk of fire spread in Wildland-Urban Interface (WUI) communities. An objective of this work is to develop first generation tools for improved risk assessment and risk mitigation in WUI communities at risk from wildfires. These tools will be developed and tested through a coordinated effort that includes laboratory and field measurements, physics-based fire behavior models, and economic cost analysis models. NIST and Texas Forest Service (TFS) worked together in October 2010 to train TFS personnel in the NIST-developed WUI data collection methodology. While the fires that started on February 27, 2011 were still burning around Amarillo, NIST and TFS decided to deploy the joint Team and document the WUI fire event loses and fire behavior. The Tanglewood WUI fire in the outskirts of Amarillo was responsible for the destruction of approximately 101 structures including 35 residences. Field measurements included structure particulars, specifically building construction materials, proximity and type of combustibles to the structure, and damage to wildland and residential vegetation. Documentation included over 29 000 photographs. The data collection and analysis will be documented in two phases, an initial reconnaissance/overview report and a technical report. This summary report will address the particulars of the joint NIST/TFS deployment and the data collection methodology used. Additionally, this report provides a summary of the primary structures lost. A second more detailed technical report will provide the event timeline reconstruction and general fire behavior observations as well as investigate the impacts of structure attributes, landscaping characteristics, topographical features and wildland fire exposure on structure survivability.
Citation: Technical Note (NIST TN) - 1708Report Number:
NIST Pub Series: Technical Note (NIST TN)
Pub Type: NIST Pubs
Wildland Urban Interface, WUI, fire behavior, community, Amarillo fires, data collection methodology