Abstract
Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.
Highlights
Wildfire intensity and occurrence rate have risen alarmingly in recent years[1]
Wildfires are a part of nature, both inevitable and necessary, pointing to only one foregone conclusion - Wildfire management needs to be driven by regulating vulnerability of communities[10,14]. This includes, but not necessarily limited to, selective wildland fuel treatment at the community interface, reduction of stray vegetation in the house ignition zone, reinforcing households with fire proof methodologies and sustainable urban planning geared towards reduction of fire risk
While robust computational fluid dynamic (CFD) models exist for simulating structure-fire interactions on a community scale[25], their complexity and computational demand
Summary
Wildfire intensity and occurrence rate have risen alarmingly in recent years[1]. The consequences of these wildfires, when interacting with communities, have been dire and have resulted in substantial socio-economic losses all over the world[2,3]. Wildfires are a part of nature, both inevitable and necessary, pointing to only one foregone conclusion - Wildfire management needs to be driven by regulating vulnerability of communities[10,14] This includes, but not necessarily limited to, selective wildland fuel treatment at the community interface, reduction of stray vegetation in the house ignition zone, reinforcing households with fire proof methodologies and sustainable urban planning geared towards reduction of fire risk. These models on urban and wildland fire simulation were based on the concept of minimum travel time While it is a suitable performance metric, and even necessary for on-site managers, the rate of spread of a wildfire may not necessarily represent its true damage potential. The model is calibrated to conditions similar to the historic Oakland fire and tested to identify the underlying factors affecting community vulnerability to wildfires
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