Mapping Wildfire Evacuation Vulnerability in the Western US: the Limits of Infrastructure

In recent decades wildfire severity and occurrence has increased significantly due to a combination of climate change factors such as drought cycles, and population densities in fire prone areas. An increasing point of concern is the emergence of population centers within the wildland urban interface (WUI). This is the area where structures are integrated with or immediately surrounded by areas of moderate to high fire risk and are directly linked to fuel types and topographic features. When population centers in these areas have limited access routes, immediate egress in the event of a severe wildfire threat, becomes an additional hazard for these communities. Cova et al. (2011), focused on identifying some of these high risk communities in the eleven western states. The authors found that there was an inordinate quantity of high risk, densely populated communities with three or fewer evacuation routes in southern California as compared with the rest of the western United States. They imply that more attention should be paid during the planning and development of future communities in WUI areas, as well as taking certain fuels treatment measures to address safety in extant high risk WUI areas. –Lindon Pronto

Cova, Thomas J., Theobald, David M., Norman III, John B., Siebeneck, Laura K., 2011. Mapping Wildfire Evacuation Vulnerability in the Western US: the Limits of Infrastructure. GeoJournal, Springer Science+Business Media B.V. 2011.

Climate conditions are increasingly blamed for an increase in wildfire severity and occurrence which has resulted in a high loss of structures and property damage over the past couple of decades. Furthermore, there are an estimated 12.5 million homes in what is considered to be the high risk, fire prone, wildland urban interface (WUI) in the western United States. Many communities are situated in the WUI but are not safely suited or adequately designed for a scenario in which an immediate, mass evacuation would be warranted due to a sudden severe threat of an approaching wildfire. This study projects a worst case scenario where most of a communities’ population is at home (such as during night hours), and evaluates the number of egress routes (supply) against the number of households reliant upon them (demand). Cova et al. evaluated the eleven western states of AZ, CA, CO, ID, MT, NM, NV, OR, UT, WA, and WY,  but divided CA into NoCal and SoCal for a total of 12 files. Important additional factors in evaluating risk include understanding fuel loading and fuel types, localized fire regimes, and identifying topographic features that enhance fire activity. The latter elements critically influence overall computed fire danger when coupled with the identified population centers.
The approach used for identifying these at-risk communities was a combination of initial heuristic assumptions, refined US 2000 census data, geographic information systems (GIS) data for identifying road networks and topography, and a previously established integer programming model. The programming model Critical Cluster Model (CCM) combines contiguous intersections—or “nodes”, within a community (node set), with egress routes (exit links) in a pattern of arcs to extrapolate the maximum ratio of population-to-exits in a community. Constraints of the CCM were addressed through a region-growing algorithm. To acquire the initial data sets, a fire danger layer and a road network layer were applied; this resulted in the immediate removal of areas such as large cities or some desert areas where high fire danger/spread was not present, as well as all unpopulated areas. Through visual and computer generated location sorting, communities were identified that contained up to 100 contiguous intersections, had a minimum median fire hazard of 0.7 on a 0–1 scale, and had a minimum households-to-exit ration of 200 to one.
The computer generated results were grouped as communities with one, two, or three exits. These communities were then identified by state, number of nodes (intersections), and number of homes, fire hazard, and home-to-exit ratio. The highest home-to-exit ratios were then ranked within the three exit categories for identifying communities that exhibited the greatest concern for safety in an immediate egress situation.  Cova et al. found that among all the western states, Southern California consistently exhibited a disproportionately high prevalence of communities of very limited egress with high fire hazard and topographical restraints. For example, they compare a community in WA that had a home-to-exit ratio of 320.9 to 1 (3 exits, 962.7 homes), with a community in SoCal that had a home-to-exit ratio of 1,566.8 to 1 (3 exits, 4,700.3 homes).
This study provides the first rigorous analysis covering a broad geographic area, which identifies and compares low-egress communities in fire-prone areas in the West.  The authors however, strongly caution against using these results beyond the initial enumeration and ranking of fire-prone, low-egress communities in the western United States. They identified a number of significant limitations of their methods and results, largely based on outdated US census data (2000) and the potential of serious miscalculation on the basis of inaccurate GIS street network data for individual communities. This study can however be valued in terms of demonstrating cases of unchecked development in the WUI with little regard to public safety and emergency planning. It can serve as encouragement to local governments to more seriously consider this relatively new threat to public safety and property, by an environmental concern that is noticeably being exacerbated through climate change.

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