Wildfires are becoming more catastrophic, because of their size, severity, and the increasing number of homes, businesses, and other assets located in harm’s way. As a result, the costs of government-funded wildfire suppression and recovery, property insurance, utilities, and public health are growing.
Facing these rising costs, decision makers are turning to data tools that assess and measure determinants of wildfire risk, such as the vulnerability of properties to fire, or weather patterns that can make fires worse. The good news is that these models are beginning to drive decision-making as the public and private sectors reckon with wildfire risk. However, when it comes to applying these rapidly developing sources of information to public budgeting for wildfire management, opportunities are still being missed.
On October 18, 2023, The Pew Charitable Trusts and the Government Finance Officers Association (GFOA) co-hosted a workshop that brought together wildfire risk data and modeling experts from nonprofits, government, and the private sector in an effort to connect the growing field of wildfire risk data and modeling to state and local budget decision-making. Participants in the virtual event reviewed current research and tools and then broke out in small groups to discuss barriers to accessing and using these tools in budget decisions.
Several themes emerged from these conversations, which can form the basis for future efforts to introduce better data into wildfire budgeting
Complex data tools require more translation for effective policy use
Data tools allow users to collect, organize, and analyze information in order to characterize the scope of a problem. Ideally, the data these tools provide can offer insights, demonstrate trends, set predictions, and help make short- or long-term decisions possible.
But because data tools are complex for various reasons—they take information from numerous sources and places, they sometimes require data input from the user, and they can include technical elements and other parameters that require familiarity and expertise—state and local governments do not always have the specific capability to analyze the data.
Event participants discussed the need for intermediaries, in the form of either personnel or software, to help translate terminology, complex data, and other technical elements into usable information. This approach could entail an easy-to-use search function, data summaries, and jargon-less language. For example, First Street Foundation’s Fire Factor model of wildfire behavior allows users to search an address and receive a simplified score (one to 10) assessing their fire risk, with the option of exploring more detailed risk information. Personnel with the appropriate expertise could also work with legislators and executive officials to help them decipher the data.
Policy questions need to be further refined to identify where tools could aid decisions
When it comes to wildfires, policymakers face a diverse set of problems and potential solutions. For instance, the costs of wildfires include damage to homes and communities and deteriorating air quality due to smoke—on top of the resources needed to extinguish them. Developing tools that capture a fuller picture of wildfire risks would provide policymakers and practitioners with more robust information upon which to make decisions.
To develop more comprehensive tools, however, the scientific community needs to understand decision-makers’ most pressing problems and the questions they need more information to answer. A feedback loop or channel for communication is, therefore, necessary. Event participants shared that nonprofits or membership associations could play a role in helping decision-makers define their challenges and formulate the right questions for the scientific community; in fact, some organizations already have a stated purpose to better connect scientists and end users, such as the Climate and Wildfire Institute, a nonprofit working to “connect science to public policy and decision-making to accelerate solutions to a fast-changing climate.” Probability Management is a nonprofit that has created data structures, called SIP Libraries, for communicating risk. GFOA and Aon, a reinsurer, used this open standard data storage method to connect Aon’s complex wildfire model to a GFOA model. Local governments could provide this data for use to manage exposures to risks, including natural disasters.
Centralization and standardization of data tools would facilitate their use by policymakers and practitioners
A multitude of data tools exist to inform decisions about wildfire management and mitigation. But the tools target different audiences, leverage different data sources, and address different short- or long-term needs. This assortment can make it challenging for state and local governments to know which tools to use. What’s more, many of the tools are proprietary and fee-based, which can result in a patchwork of access to them across jurisdictions.
Workshop participants noted that a centralized location, or clearinghouse, could consolidate information about existing tools and help direct governments to the tools. Such a clearinghouse could also provide helpful information about the advantages and limitations of these tools, as well as their intended use and audience. Government leaders could play a role in creating a minimum or standardized set of information that all tools share; the private sector could augment that with additional features or information. The development of a minimum, standard functionality across tools could address the disparities in access to the proprietary tools.
A potential host for this concentration of information could come in the form of a Fire Environment Center, a government interagency office for data and science-based decision-making services related to wildfire. In its September 2023 final report to Congress, the Wildland Fire Mitigation and Management Commission—a 50-member congressionally mandated group comprised of representatives from federal agencies; state, local, and Tribal governments; and experts from the private sector—recommended the establishment of such a center.
Further work is needed to connect the growing field of wildfire risk data to state and local decision-making on budgeting for wildfire management—but the opportunities are great. Doing so could present a model for how data tools can be used to identify and manage other emerging risks to state and local budgets, such as a changing climate and increased economic uncertainty. Pew and GFOA are eager to continue their collaboration, bridging these fields to help states and localities better prepare for, and mitigate, their long-term fiscal risks.
Andrea Snyder is a senior associate and Colin Foard is a senior manager with Pew’s managing fiscal risks project. Shayne Kavanagh is a senior manager of research with the Government Finance Officers Association.
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