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"Thompson, Matthew P."
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How risk management can prevent future wildfire disasters in the wildland-urban interface
Recent fire seasons in the western United States are some of the most damaging and costly on record. Wildfires in the wildland-urban interface on the Colorado Front Range, resulting in thousands of homes burned and civilian fatalities, although devastating, are not without historical reference. These fires are consistent with the characteristics of large, damaging, interface fires that threaten communities across much of the western United States. Wildfires are inevitable, but the destruction of homes, ecosystems, and lives is not. We propose the principles of risk analysis to provide land management agencies, first responders, and affected communities who face the inevitability of wildfires the ability to reduce the potential for loss. Overcoming perceptions of wildland-urban interface fire disasters as a wildfire control problem rather than a home ignition problem, determined by home ignition conditions, will reduce home loss.
Journal Article
An optimization model to prioritize fuel treatments within a landscape fuel break network
We present a mixed integer programming model for prioritizing fuel treatments within a landscape fuel break network to maximize protection against wildfires, measured by the total fire size reduction or the sum of Wildland Urban Interface areas avoided from burning. This model uses a large dataset of simulated wildfires in a large landscape to inform fuel break treatment decisions. Its mathematical formulation is concise and computationally efficient, allowing for customization and expansion to address more complex and challenging fuel break management problems in diverse landscapes. We constructed test cases for Southern California of the United States to understand model outcomes across a wide range of fire and fuel management scenarios. Results suggest optimal fuel treatment layouts within the Southern California’s fuel break network responding to various model assumptions, which offer insights for regional fuel break planning. Comparative tests between the proposed optimization model and a rule-based simulation approach indicate that the optimization model can provide significantly better solutions within reasonable solving times, highlighting its potential to support fuel break management and planning decisions.
Journal Article
Wildfire risk science facilitates adaptation of fire-prone social-ecological systems to the new fire reality
Large and severe wildfires are an observable consequence of an increasingly arid American West. There is increasing consensus that human communities, land managers, and fire managers need to adapt and learn to live with wildfires. However, a myriad of human and ecological factors constrain adaptation, and existing science-based management strategies are not sufficient to address fire as both a problem and solution. To that end, we present a novel risk-science approach that aligns wildfire response decisions, mitigation opportunities, and land management objectives by consciously integrating social, ecological and fire management system needs. We use fire-prone landscapes of the US Pacific Northwest as our study area, and report on and describe how three complementary risk-based analytic tools-quantitative wildfire risk assessment, mapping of suppression difficulty, and atlases of potential control locations-can form the foundation for adaptive governance in fire management. Together, these tools integrate wildfire risk with fire management difficulties and opportunities, providing a more complete picture of the wildfire risk management challenge. Leveraging recent and ongoing experience integrating local experiential knowledge with these tools, we provide examples and discuss how these geospatial datasets create a risk-based planning structure that spans multiple spatial scales and uses. These uses include pre-planning strategic wildfire response, implementing safe wildfire response balancing risk with likelihood of success, and alignment of non-wildfire mitigation opportunities to support wildfire risk management more directly. We explicitly focus on multi-jurisdictional landscapes to demonstrate how these tools highlight the shared responsibility of wildfire risk mitigation. By integrating quantitative risk science, expert judgement and adaptive co-management, this process provides a much-needed pathway to transform fire-prone social ecological systems to be more responsive and adaptable to change and live with fire in an increasingly arid American West.
Journal Article
Negative consequences of positive feedbacks in US wildfire management
Over the last two decades wildfire activity, damage, and management cost within the US have increased substantially. These increases have been associated with a number of factors including climate change and fuel accumulation due to a century of active fire suppression. The increased fire activity has occurred during a time of significant ex-urban development of the Wildland Urban Interface (WUI) along with increased demand on water resources originating on forested landscapes. These increased demands have put substantial pressure on federal agencies charged with wildfire management to continue and expand the century old policy of aggressive wildfire suppression. However, aggressive wildfire suppression is one of the major factors that drive the increased extent, intensity, and damage associated with the small number of large wildfires that are unable to be suppressed. In this paper we discuss the positive feedback loops that lead to demands for increasing suppression response while simultaneously increasing wildfire risk in the future. Despite a wealth of scientific research that demonstrates the limitations of the current management paradigm pressure to maintain the existing system are well entrenched and driven by the existing social systems that have evolved under our current management practice. Interestingly, US federal wildland fire policy provides considerable discretion for managers to pursue a range of management objectives; however, societal expectations and existing management incentive structures result in policy implementation that is straining the resilience of fire adapted ecosystems and the communities that reside in and adjacent to them.
Journal Article
Human ignitions on private lands drive USFS cross-boundary wildfire transmission and community impacts in the western US
Wildfires in the western United States (US) are increasingly expensive, destructive, and deadly. Reducing wildfire losses is particularly challenging when fires frequently start on one land tenure and damage natural or developed assets on other ownerships. Managing wildfire risk in multijurisdictional landscapes has recently become a centerpiece of wildfire strategic planning, legislation, and risk research. However, important empirical knowledge gaps remain regarding cross-boundary fire activity in the western US. Here, we use lands administered by the US Forest Service as a study system to assess the causes, ignition locations, structure loss, and social and biophysical factors associated with cross-boundary fire activity over the past three decades. Results show that cross-boundary fires were primarily caused by humans on private lands. Cross-boundary ignitions, area burned, and structure losses were concentrated in California. Public lands managed by the US Forest Service were not the primary source of fires that destroyed the most structures. Cross-boundary fire activity peaked in moderately populated landscapes with dense road and jurisdictional boundary networks. Fire transmission is increasing, and evidence suggests it will continue to do so in the future. Effective cross-boundary fire risk management will require cross-scale risk co-governance. Focusing on minimizing damages to high-value assets may be more effective than excluding fire from multijurisdictional landscapes.
Journal Article
Modeling Wildfire Incident Complexity Dynamics
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.
Journal Article
Benchmarking performance of annual burn probability modeling against subsequent wildfire activity in California
Wildfire simulation is deployed extensively to support risk management, and in the US has driven billions in federal investment. Foundational to strategic risk analysis is spatial information on the likelihood of burning in a fire year, typically provided by burn probability (BP) models. The recency of BP maps is a key driver of their accuracy, especially in disturbed landscapes that have experienced changes in fire spread potential. Few published examples exist comparing BP values against subsequent fire activity, and none to our knowledge evaluate annually updated BP maps. Here, we present a novel performance evaluation of the operational wildfire simulation system FSim, confronting updated BP maps with subsequent fire activity across the state of California over a 4-year period (2020–2023). Results show strong predictive ability: across 5 equal-area BP classes, 56.7–79.8% of the burned area occurred in the top 20% of mapped area; mean (median) BP values in burned areas were 238.5–348.8% (551.4–880.7%) greater than in unburned areas; differences in empirical cumulative distribution functions of BP for burned/unburned areas were statistically significant; Logarithmic Skill Scores ranged from − 0.072 to 0.389 against two reference models. Findings indicate reliable forecast performance and useful application of up-to-date BP maps, critical to support ongoing wildfire risk mitigation.
Journal Article
Modeling the systemic risks of COVID-19 on the wildland firefighting workforce
Wildfire management in the US relies on a complex nationwide network of shared resources that are allocated based on regional need. While this network bolsters firefighting capacity, it may also provide pathways for transmission of infectious diseases between fire sites. In this manuscript, we review a first attempt at building an epidemiological model adapted to the interconnected fire system, with the aims of supporting prevention and mitigation efforts along with understanding potential impacts to workforce capacity. Specifically, we developed an agent-based model of COVID-19 built on historical wildland fire assignments using detailed dispatch data from 2016–2018, which form a network of firefighters dispersed spatially and temporally across the US. We used this model to simulate SARS-CoV-2 transmission under several intervention scenarios including vaccination and social distancing. We found vaccination and social distancing are effective at reducing transmission at fire incidents. Under a scenario assuming High Compliance with recommended mitigations (including vaccination), infection rates, number of outbreaks, and worker days missed are effectively negligible, suggesting the recommended interventions could successfully mitigate the risk of cascading infections between fires. Under a contrasting Low Compliance scenario, it is possible for cascading outbreaks to emerge leading to relatively high numbers of worker days missed. As the model was built in 2021 before the emergence of the Delta and Omicron variants, the modeled viral parameters and isolation/quarantine policies may have less relevance to 2022, but nevertheless underscore the importance of following basic prevention and mitigation guidance. This work could set the foundation for future modeling efforts focused on mitigating spread of infectious disease at wildland fire incidents to manage both the health of fire personnel and system capacity.
Journal Article
Avoided wildfire impact modeling with counterfactual probabilistic analysis
Assessing the effectiveness and measuring the performance of fuel treatments and other wildfire risk mitigation efforts are challenging endeavors. Perhaps the most complicated is quantifying avoided impacts. In this study, we show how probabilistic counterfactual analysis can help with performance evaluation. We borrow insights from the disaster risk mitigation and climate event attribution literature to illustrate a counterfactual framework and provide examples using ensemble wildfire simulations. Specifically, we reanalyze previously published fire simulation data from fire-prone landscapes in New Mexico, USA, and show applications for post-event analysis as well as pre-event evaluation of fuel treatment scenarios. This approach found that treated landscapes likely would have reduced fire risk compared to the untreated scenarios. To conclude, we offer ideas for future expansions in theory and methods.
Journal Article