WUI Fire Risk - A Collection of Resources
Historical wildfire ignition locations and NOAA’s hourly time series of surface weather at 2.5 km resolution are used to drive ELMFIRE to produce wildfire hazards representative of the 2022 and 2052 conditions at 30 m resolution, with the future weather conditions scaled to the IPCC CMIP5 RCP4.5 model ensemble predictions. Winds and vegetation were held constant between the 2022 and 2052 simulations, and climate change’s impacts on the future fuel conditions are the main contributors to the changes observed in the 2052 results. Non-zero wildfire exposure is estimated for 71.8 million out of 140 million properties across CONUS. Climate change impacts add another 11% properties to this non-zero exposure class over the next 30 years, with much of this change observed in the forested areas east of the Mississippi River. “Major” aggregate wildfire exposure of greater than 6% over the 30-year analysis period from 2022 to 2052 is estimated for 10.2 million properties. The FSF-WFM represents a notable contribution to the ability to produce property-specific, climate-adjusted wildfire risk assessments in the US.
Overview: This presentation will share key findings from a recent Joint Fire Science Project, specifically on: 1) the multiple types of boundaries in managing wildfire risk, and the boundary spanning features that can help cross them; 2) what strategies actors utilized for wildfire risk reduction across five case studies in the West; and 3) questions and ideas for future research and practice. This work is intended to help wildfire practitioners and managers better understand and address these organizational complexities as they work toward greater collective impact.
Presenters: Heidi Huber-Stearns, University of Oregon; Emily Jane Davis, Oregon State University; Tony Cheng, Colorado State University
In this study, we used wildfire simulations and building location data to evaluate community wildfire exposure and identify plausible disasters that are not based on typical mean-based statistical approaches. We compared the location and magnitude of simulated disasters to historical disasters (1984–2020) in order to characterize plausible surprises which could inform future wildfire risk reduction planning. Results indicate that nearly half of communities are vulnerable to a future disaster, that the magnitude of plausible disasters exceeds any recent historical events, and that ignitions on private land are most likely to result in very high community exposure. Our methods, in combination with more typical actuarial characterizations, provide a way to support investment in and communication with communities exposed to low-probability, high-consequence wildfires.
We produce a framework needed to compute the livelihood vulnerability index (LVI) for the top 14 American States that are most exposed to wildfires, based on the 2019 Wildfire Risk report of the acreage size burnt in 2018 and 2019: Arizona, California, Florida, Idaho, Montana, Nevada, New Mexico, Oklahoma, Oregon, Utah, Washington, and Wyoming. The LVI is computed for each State by first considering the State’s exposure, sensitivity, and adaptive capacity to wildfire events (known as the three contributing factors). These contributing factors are determined by a set of indictor variables (vulnerability metrics) that are categorized into corresponding major component groups. The framework structure is then justified by performing a principal component analysis (PCA) to ensure that each selected indicator variable corresponds to the correct contributing factor. The LVI for each State is then calculated based on a set of algorithms relating to our framework. LVI values rank between 0 (low LVI) to 1 (high LVI). Our results indicate that Arizona and New Mexico experience the greatest livelihood vulnerability, with an LVI of 0.57 and 0.55, respectively. In contrast, California, Florida, and Texas experience the least livelihood vulnerability to wildfires (0.44, 0.35, 0.33 respectively). LVI is strongly weighted on its contributing factors and is exemplified by the fact that even though California has one of the highest exposures and sensitivity to wildfires, it has very high adaptive capacity measures in place to withstand its livelihood vulnerability. Thus, States with relatively high wildfire exposure can exhibit relatively lower livelihood vulnerability because of adaptive capacity measures in place.
The Fireshed Registry is a geospatial dashboard and decision tool built to organize information about wildfire transmission to communities and monitor progress towards risk reduction for communities from management investments. The concept behind the Fireshed Registry is to identify and map the source of risk rather than what is at risk across all lands in the continental United States. While the Fireshed Registry was organized around mapping the source of fire risk to communities, the framework does not preclude the assessment of other resource management priorities and trends such as water, fish and aquatic or wildlife habitat, or recreation. The Fireshed Registry is also a multi-scale decision tool for quantifying, prioritizing, and geospatially displaying wildfire transmission to buildings in adjacent or nearby communities.
The fire spread rate within WUI communities is determined for nine wildfires that were ranked among the most destructive wildfires in North America. An improved quasi-empirical model that considers radiation and fire spotting as modes of fire spread inside a community is proposed. The new model is validated using the documented spread rates during the 2007 Witch and Guejito fires and the 2017 Tubbs fire. The proposed model is computationally efficient and can be used to quantify fire spread rate and the number of affected structures inside a community during a wildfire event.
Wildfire risk is shared across landscapes, ownerships, and administrative boundaries. Consequently, successful efforts to mitigate this risk depend on coordination of individual and collective actions across sets of public and private institutions and individuals associated with managing components of fire-prone landscapes. We need to understand how these diverse sets of actors, including individual residents, communities, non-profit organizations, and local, state, tribal, and federal agencies can and do interact and make decisions that affect fire and risk based on their rules, processes and social norms. Initiated in 2017, the Co-Management of Wildfire Risk Transmission Partnership (CoMFRT) brings together wildfire researchers, practitioners and decisionmakers to co-produce knowledge and actionable recommendations to support people and institutions successfully working together across scales and circumstances to best mitigate fire risk and build adaptation to wildfire. This presentation will provide an overview of the CoMFRT Partnership, key results and recommendations to date, and next steps all designed to underscore approaches for a variety of actors responsible for managing wildfire risk to better live with fire.
Wildfire Risk to Communities is a national tool with interactive maps, charts, and resources to help every community in the U.S. understand, explore, and reduce wildfire risk. In the fall of 2020, the website was updated with new data and features, including new map views and GIS data available for download. During this webinar, see a demonstration of the Wildfire Risk to Communities and learn about data updates. Wildfire Risk to Communities was created by the USDA Forest Service under the direction of Congress and builds on nationwide LANDFIRE data.
Lowell Ballard, Director of Geospatial Solutions with Timmons Group will be presenting the latest developments in the Shared Wildfire Risk Mitigation (SWRM) Dashboard Tool that uses GIS data to provide mapped communities at risk, a consistent approach across 13 states (so far), completed in collaboration with local governments, and consistent scoring based on fire adaptation. Please join us to hear and provide feedback on how this tool can be used to identify and assist in the collaborative, cross-boundary decision-making process.
Description: Learn about the science and data used to calculate and map wildfire risk nationwide in the new Wildfire Risk to Communities website. Hear from the project’s technical lead about the use of LF and other input datasets, the methods for modeling and mapping wildfire risk, and the data products available through the website. See a demonstration of the website and how to download geospatial and tabular data.
Presenters: Greg Dillon, Frank Fay, Jim Menakis, Kelly Pohl, Joe Scott