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DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Wildfire Mitigation Plans in Power Systems: A Literature Review

Some of the deadliest wildfires in the U.S., such as California’s 2018 wildfires, have been ignited by power systems. In an effort to prevent and minimize the ignition of wildfires, or control them if ignited, energy companies have developed wildfire mitigation plans. This paper provides energy companies and power system operators, engineers, researchers, and suppliers an overview of the state-of-the-art studies that address key topics in these wildfire mitigation plans and compares the wildfire mitigation plans of several energy companies. The key topics include grid design and system hardening, asset management and inspection, situational awareness and forecasting, operational response, vegetation management, public safety power shutoff, and risk-spend efficiency. Here this paper also presents a comparison of several energy companies’ decision-making criteria for initiating a public safety power shutoff. Finally, we discuss opportunities for future research studies that could help energy companies prevent wildfire ignitions.

42 ENGINEERING↗

DOE OSTI2021

Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A two-stage optical fusion framework for wildfire severity mapping across the conterminous United States

Accurate wildfire severity mapping (WSM) is essential for post-fire recovery planning, erosion risk assessment, ecosystem monitoring, and disaster risk reduction. Although Landsat and Sentinel optical imagery have been widely used for burn severity assessment, the added value of fusing multiple optical sensors has not been sufficiently quantified across diverse fire events, particularly since the launch of Landsat-9. This study evaluates whether multisensor optical fusion improves wildfire severity mapping relative to single-sensor baselines using Sentinel-2, Landsat-8, and Landsat-9 imagery across 40 wildfire events in the conterminous United States. We tested a two-stage fusion framework that combines feature-level fusion with pixel-level dimensionality reduction. First, feature-level fused datasets were created through early fusion by combining standardized post-fire bands from each sensor into a single predictor stack. Both raw reflectance bands and pairwise spectral transforms were retained to capture within- and cross-sensor spectral interactions. Second, Linear Discriminant Analysis was applied to both single-sensor and fused datasets to produce comparable low-dimensional feature spaces. Six machine-learning classifiers were then used to benchmark model performance with repeated spatially buffered train–test splits. Results show that Landsat-9 was the strongest single-sensor baseline. Among the fusion strategies, Sentinel-2 + Landsat-9 produced the most consistent improvement and reduced performance variability. Landscape-condition analysis further showed that this fusion was most beneficial in shrubland-dominated and high-terrain fires, where it achieved the highest overall mean accuracy and the fewest failures. In contrast, its benefits were less reliable in evergreen forests, mixed vegetation, and low- to moderate-elevation terrain. In operational settings, the Sentinel-2 + Landsat-9 configuration offers a practical solution for post-fire recovery planning, erosion-risk assessment, watershed management, and ecological monitoring when field observations are available and timely satellite-based information is needed.

Landsat↗

NASA NTRS2020

SMARt-STEReO: Preliminary Model Description

Wildfires have increasingly become major threat to US towns and cities, with California alone having its most destructive wildfire seasons to date in 2017 and 2018 and 2020 already becoming one of the worst fire years on record, causing the large-scale evacuations, the destruction of towns and property, and a significant release of hazardous smoke over the entire west coast. Thus, the U.S. Forest Service recently spent over 50% of its budget on wildfire management – funds which could otherwise be directed to science that could support fire prevention. Aerial support plays a major role in fighting wildfires. Airtankers, helicopters, and other aerial assets support the construction of fire-lines, gather data, and transport crews and equipment. However, presently, aerial firefighting operations rely on relatively unsophisticated technologies for communications, such as over-the-air radios, which limit the ability of pilots and management to relay fire data and coordinate operations. Aerial operations in and around fires are additionally high-risk activities due to the variable, dangerous conditions and complex, technically difficult maneuvers which must be performed to, for example, conduct a retardant drop. Thus, between 2000 and 2013, of the 298 wildland firefighter fatalities, 26% were related to aerial operations. As a result, there is significant potential to both improve the performance and resiliency of wildfire response while reducing risk to human operators.

Daniel E Hulse↗

NASA NTRSDate not supplied

Wildfire Emergency Response Hazard Extraction and Analysis of Trends (HEAT) through Natural Language Processing and Time Series

Emerging wildfire operations aim to improve safety and performance through the integration of technologies including UAS and UTM. Recent advances in natural language processing (NLP) techniques, as well as the availability of wildfire incident reports, has made possible a large-scale analysis of wildfire hazards and trends. Identifying longitudinal trends will help us target risk mitigation and safety management activities. Note: This presentation does not include sound please disregard icon.

Sequoia R. Andrade↗

DOE OSTI2025

Postfire Biogeochemical Processes: Implications to Source Water Quality in Fire-Influenced Watersheds

Forested watersheds are instrumental in providing purified and reliable water to millions of people worldwide. The changing climate has increased the frequency and severity of global fire events. Forested watersheds and their ecosystem functions are greatly disrupted during fire activity. Postfire concerns in forested watersheds include unpredictable and potentially simultaneous alterations in source water quality and hydro-biogeochemical processes. Here, the degree of fire severity can complexly modify water quality through the production of fire-transformed constituents on the burned forest floor (i.e., nutrients, metal(loid)s, dissolved organic matter, and the formation of disinfection byproducts). Correspondingly, fire severity and postfire rainfall patterns can refine hydro-biogeochemical processes that influence the transport of the fire-transformed constituents (i.e., vegetation function, soil structure, hydrological pathways, and microbial communities). Postfire alterations to water quality and hydro-biogeochemical processes introduce further complexity with varying temporal influence, which ranges from months to decades. As postfire water quality and watershed response research progresses, it is essential to homogenize interdisciplinary expertise to bridge knowledge gaps between fields ranging from forest ecology, hydrology, microbiology, and geochemistry. A multidisciplinary approach in wildfire research will facilitate a comprehensive perception of the diverse water quality risks associated with fire activity and mitigate fire concerns on a global level.

Disinfection Byproducts↗

NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Over the past decade, due in large part to heavy investment in the field of Advanced Air Mobility (AAM), significant progress in rotorcraft-focused modeling tools has been made. Such progress has notably increased AAM rotorcraft modeling capabilities in the topics of conceptual design, preliminary design, and more recently flight dynamics. Yet, due to recent and persistent increases in extreme weather events, an emerging interest has been raised in utilizing such modeling capabilities for aiding in emergency relief efforts and other public good missions. This paper uses wildfire fighting as a representative public good mission and demonstrates the relevance of the NASA Revolutionary Vertical Lift Technology (RVLT) rotorcraft toolchain to such missions. An emphasis is placed on flight dynamics modeling and control because of the hazards and challenges associated with the atmospheric environment of wildfires. In this work, the NASA FlightCODE tool was used to analyze both a UH-60 and the NASA six-passenger quadcopter reference model hovering in an experimentally informed wildfire turbulent environment. Preliminary results of this study estimate actuator usage exceedances and disturbance rejection capabilities of the vehicles’ translational rate command systems. Leveraging the RVLT toolchain, refinement and expansion of this work could lead to handling qualities envelope estimation and design optimization for wildfire turbulent environments. This would provide pilots with additional information to make real-time decisions in high-risk scenarios and begins preparations for simulating these dangerous environments for pilot training and experimentation.

Rotorcraft↗

NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Rotorcraft↗

NASA NTRSDate not supplied

Anthropogenic Pathways for Modeling and Managing Future Arctic Fires

Wildland fires, including extreme fire events and seasons, are becoming more common in the boreal and Arctic regions due to climate change. Current climate modeling approaches do not include country- or region-specific socioeconomic pathways that specifically address the drivers of and potential mitigation techniques for wildland fires. Forest management, energy extraction, and tourism, together with firefighting capacity and readiness as well as fuels treatment, can have a significant impact on future wildland fire risks and impacts. To assess the impacts of anthropogenic factors and to align with previous work done on shared socioeconomic pathways (SSPs), climate pathways for future wildfires up to 2050 were created for the states that compose the original Arctic Council countries: Canada, the United States, the Kingdom of Denmark, Iceland, Sweden, Norway, and Finland as well as the Russian Federation (with whom the other seven countries withdrew participation from in May 2022 due to the invasion and ongoing war in Ukraine). High and low fire activity and risk pathways for all states comprising the Arctic were made, with expert ‘best guess’ pathways for each state created separately to represent the middle of road. The low activity and low fire risk pathways, named “We Got This”, assume active fire suppression via citizenry participation and official land management, efficient and extensive fuel treatments, and consistent and active wildland firefighting for each new ignition. The high activity and high fire risk pathways, named “Let It Burn”, assume nearly the opposite, due to lack of government and community response and no action on climate change drivers that increase wildland fire risk. The ‘best guess’ pathway, named “The Fire Will Come”, indicates that some countries are currently on the pathway for less fire compared to other Arctic and Boreal states but not a ‘no-fire’ future. For example, in the Nordic countries, human ignition sources from tourism, timber and energy extraction, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In North America, these same risks will apply but also may see an expansion of agriculture that increases the likelihood of open burning in croplands. Drier fuel condition and extreme heat events due to climate change create favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic and boreal lightning is expected to increase, increasing the risk of tundra fires in addition to forest fires in hard-to-reach locations that are more difficult to coordinate and execute wildland firefighting. To move the future Arctic fire SSPs forward, several short-term and long-term actions must be completed. Certain data needs are required, like a harmonized pan-Arctic and pan-boreal fuels geospatial product, while also a need to refine and socialize current definitions of fire seasons and fire management – including developing an open-source system to track and share innovation, mitigation, and adaptation strategies across Arctic states.

Arctic↗

DOE OSTI2024

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2026

Comparative life cycle assessment of bioenergy in Japan from residual biomass-based wood pellets produced in the US Pacific Northwest

The US Pacific Northwest (PNW) faces an increase in wildfires due to forest overcrowding and climate change, posing significant environmental and public health risks. Traditional methods of managing surplus biomass, including prescribed burning, have increased air pollution and global warming. While in the PNW, residual woody biomass is being treated as waste, Japan’s growing demand for bio-based energy presents an opportunity to export value-added biomass as energy pellets. This study investigates whether producing wood pellets from the residual woody biomass from forest operations and sawmills for electricity generation in Japan is truly environmentally beneficial. Accordingly, we conducted a cradle-to-grave Life Cycle Assessment (LCA) to evaluate the environmental impact of residual pellets vs. coal for electricity generation. The assessment covered feedstock production, pellet processing, transportation, and combustion phases. Our findings indicate that replacing coal-based electricity in Japan with PNW residual pellet-based electricity can lower the Global Warming Potential (GWP) by about 90% for every unit of electricity displaced. Furthermore, the results show that repurposing the otherwise burnt harvest slash residues for pellet production would improve local air quality by reducing PM 2.5 and smog in the PNW. However, substituting coal with residual pellets marginally increased carcinogenic and ecotoxicity-related emissions. Based on these results, we conclude that substituting coal with residual wood pellets for electricity generation, particularly harvest-slash residual pellets, is environmentally beneficial across most impact categories, including the GWP. This research underscores how an export‑oriented pellet industry can help address the environmental challenges within the regional US wood products industry and global renewable energy supply.

Velappan, Hemalatha [Univ. of Washington, Seattle,↗

DOE OSTI2022

Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand

Levels of fire activity and severity that are unprecedented in the instrumental record have recently been observed in forested regions around the world. Using a large sample of daily fire events and hourly climate data, here we show that fire activity in all global forest biomes responds strongly and predictably to exceedance of thresholds in atmospheric water demand, as measured by maximum daily vapour pressure deficit. The climatology of vapour pressure deficit can therefore be reliably used to predict forest fire risk under projected future climates. We find that climate change is projected to lead to widespread increases in risk, with at least 30 additional days above critical thresholds for fire activity in forest biomes on every continent by 2100 under rising emissions scenarios. Escalating forest fire risk threatens catastrophic carbon losses in the Amazon and major population health impacts from wildfire smoke in south Asia and east Africa.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

Abstract Background Prescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients’ hospital utilization. Methods We used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients’ primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI). Results Associations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies. Conclusions Area-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Raab, Henry↗

NASA NTRSDate not supplied

Wildfire Emergency Response Hazard Extraction and Analysis of Trends (HEAT) through Natural Language Processing and Time Series

A methodology for Hazard Extraction and Analysis of Trends (HEAT) is proposed and conducted on a data set of wildfire incident response forms, known as ICS-209-PLUS.The HEAT processes: (1) extract a set of hazards from a data set, (2) calculate hazard-relevant metrics in a primary analysis, (3) analyze trends over time in metrics using timeseries, and (4) examine potential explanations for metric trends using a secondary analysis. Hazards are extracted from narrative data in the ICS-209-PLUS based on a framework previously developed by the authors, using natural language processing. Metrics examined for each hazard include operational time to occurrence, rate of occurrence, frequency, and severity. Primary results include a taxonomy of hazards present in the data set with relevant quantitative metrics. The most frequent hazards identified are environmental and include hazardous terrain. Most hazards occur on average between 35-55% containment. Incidents with hazards tend to have a higher average severity score when compared to the average score for all incidents. Time series of the metrics and relevant predictors, including fire characteristics, fire intensity, and operations, are created to facilitate further analysis. Secondary results used to determine which factors best predict hazard frequency include a correlation matrix and regression analysis. These findings are relevant to safety for current, as well as emerging wildfire operations, and are an exploratory first step in developing historical data-driven risk assessment models.

Sequoia R. Andrade↗

DOE OSTI2024

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

Modern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience. Projected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services. This study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO)

Wildfire emergency response has remained rooted in relatively low-tech solutions for coordination between ground and aerial assets. These low-tech solutions are robust for the remote environments in which wildfires are usually fought, but limit strategic cross-organizational support and the ability to deploy and effectively utilize aerial assets. As aircraft become more advanced and new technology, including drones, become available to firefighters, a new, more modern method of asset coordination is needed. NASA is working on a project called ‘Scalable Traffic Management for Emergency Response Operations’ (STEReO) to integrate unmanned aerial systems (UAS)and UAS traffic management (UTM)into wildfire response. STEReO’s goals include simplifying the coordination of aerial assets, improving the existing UAS framework, and increasing the role of additional autonomous systems to reduce human risk and to increase system resilience. This paper describes the development of the ‘System Modeling and Analysis of Resiliency in STEReO’ (SMARt-STEReO) project, which aims to model wildfire response and to quantify the additional system resilience that STEReO technology provides firefighters. This paper verifies SMARt-STEReO and defines its scope; it includes experimental and statistical analysis of the impact that the addition of UAS has on both performance metrics and also on performance resiliency response to a given fault. SMARt-STEReO is a grid-based model of fire propagation that incorporates varying crew responses. Through the use of a Python package called ‘fmdtools’, the model easily allows for the addition of faults to the system. These faults allow analysts to investigate various response parameters. Factors including terrain, fuel type and wind speed can be modified to affect the fire propagation; additionally, the number of ground crews, engines, fixed wing aircraft, helicopters, and UAS can be changed to affect the crew response. The communication lines between actors mimic those used in real life situations. This paper explains the development of SMARt-STEReO including background research, verification and validation, and preliminary experimental analysis of system resilience to both a minor and major fault in systems with and without UAS.

Resiliency↗

NASA NTRS2022

Growing Impact of Wildfire on Western US Water Supply

Streamflow often increases after fire, but the persistence of this effect and its importance to present and future regional water resources are unclear. This paper addresses these knowledge gaps for the western United States (WUS), where annual forest fire area increased by more than 1,100% during 1984 to 2020. Among 72 forested basins across the WUS that burned between 1984 and 2019, the multibasin mean streamflow was significantly elevated by 0.19 SDs ( P < 0.01) for an average of 6 water years postfire, compared to the range of results expected from climate alone. Significance is assessed by comparing prefire and postfire streamflow responses to climate and also to streamflow among 107 control basins that experienced little to no wildfire during the study period. The streamflow response scales with fire extent: among the 29 basins where >20% of forest area burned in a year, streamflow over the first 6 water years postfire increased by a multibasin average of 0.38 SDs, or 30%. Postfire streamflow increases were significant in all four seasons. Historical fire–climate relationships combined with climate model projections suggest that 2021 to 2050 will see repeated years when climate is more fire-conducive than in 2020, the year currently holding the modern record for WUS forest area burned. These findings center on relatively small, minimally managed basins, but our results suggest that burned areas will grow enough over the next 3 decades to enhance streamflow at regional scales. Wildfire is an emerging driver of runoff change that will increasingly alter climate impacts on water supplies and runoff-related risks.

wildfire↗