Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

被引:118
作者
Bar Massada, Avi [1 ]
Radeloff, Volker C. [1 ]
Stewart, Susan I. [2 ]
Hawbaker, Todd J. [3 ]
机构
[1] Univ Wisconsin, Dept Forest & Wildlife Ecol, Madison, WI 53706 USA
[2] US Forest Serv, No Res Stn, Evanston, IL 60201 USA
[3] US Geol Survey, Rocky Mt Geog Sci Ctr, Denver, CO 80225 USA
关键词
Fire risk; Fire spread; FARSITE; MTT; Simulation modeling; WUI; ASSESSING FIRE RISK; MANAGEMENT; VEGETATION; PATTERNS; SPREAD; FUELS;
D O I
10.1016/j.foreco.2009.07.051
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions. the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60.000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability. and risk to structures The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:1990 / 1999
页数:10
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