The causes of wildfires are clear. How they burn through communities is not
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Strategies for hardening communities must be coupled with those for managing wildland fuel. For example, which vegetation is thinned or pruned will affect which homes should be made more fire resistant, and vice versa.
A connected view of vulnerability and risk is familiar from management of other natural hazards. For example, seismic risk is determined by combining the probability of an earthquake with the likelihood of damage to a building. Seismic hazard maps and tools for addressing design vulnerabilities in key buildings such as hospitals are used widely.
Better models of propagation and damage are just a first step to managing wildfire risk. The approach won’t work without better data on the built environment in fire-prone regions, including information on roof materials, cladding types and the sizes and locations of windows. Collecting such data is an enormous task; my team is exploring using machine learning to extract it from online maps using image recognition. Wind data at the level of a single building and data on how extreme heat affects air flow will also be needed to predict vulnerabilities accurately. Such information might be collected in the field, through wind-tunnel testing or with fluid-dynamics simulations.
How climate change will alter ignition likelihood, wind conditions and vegetation characteristics must be clarified through simulations and observational data. Solutions will need to be reassessed and updated periodically. And the social complexities of fire-risk management need to be understood. Studies must examine, for example, whether people who live near fire-prone vegetation should pay more for mitigation, or whether the entire community should pay, given that everyone benefits. How can residents pool their resources to reduce the abundance of a particular fuel or harden specific homes? How can consensus be reached?
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