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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Enrichments of Anaerobic Selenium Oxyanion Reducers from FGD Wastewater Effluent

Flue gas desulfurization systems (FGD) mitigate air pollutants from coal fired power plants. However, such systems produce wastewater that contains other pollutants such as mercury, arsenic, nitrogen, and selenium that must be removed before the water is released back into the environment. Selenium is of interest because chronic low doses of selenium (ng/L) can cause detrimental ecological consequences. Biological treatment can be utilized to remove selenium from FGD wastewater, but the microorganisms involved in this process and environment within the FGD effluent have not been well studied. This study identifies the microorganisms in selenate-enriched and selenite-enriched FGD effluent that can reduce selenium oxyanions to elemental selenium. Knowing more about these organisms can lead to an eventual optimization in the biological removal of selenium species in these wastewaters.

Sarkar, Preom↗
DOE OSTI2024

Wildland–urban interface wildfire increases metal contributions to stormwater runoff in Paradise, California

The 2018 Camp Fire was a large late-year (November) wildfire that produced an urban firestorm in the Town of Paradise, California, USA, and destroyed more than 18 000 structures. Runoff from burned wildland areas is known to contain ash, which can transport contaminants including metals into nearby watersheds. However, due to historically infrequent occurrences, the effect of wildland-urban interface (WUI) fires, such as the Camp Fire, on surface water quality has not been well-characterized. Therefore, this study investigated the effects of widespread urban burning on surface water quality in major watersheds of the Camp Fire area. Between November 2018 and May 2019, 140 surface water samples were collected, including baseflow and stormflow, from burned and unburned watersheds with varying extent of urban development. Samples were analyzed for total and filter-passing metals, dissolved organic carbon, major anions, and total suspended solids. Ash and debris from the Camp Fire contributed metals to downstream watersheds via runoff throughout the storm season. Increases in concentration up to 200-fold were found for metals Cr, Cu, Ni, Pb, and Zn in burned watersheds compared to pre-fire values. Total concentrations of Al, Cd, Cu, Pb, and Zn exceeded EPA aquatic habitat acute criteria by up to 16-fold for up to five months after the fire. To assess possible transport mechanisms and bioavailability, a subset of 18 samples was analyzed using four filters with nominal pore sizes ranging from 0.22 to 1.2 μm to determine the particulate size distribution of metals. Trace and major metals (Al, Ba, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) were found mostly associated with larger grain sizes (>0.45 μm), and some metals (Al, Cr, Fe, and Pb) also included a substantial colloidal phase (0.22 to 0.45 μm). This study suggests that fires in the wildland–urban interface increase metal concentrations, mainly through particulate driven transport. The metals with the largest increases are likely from anthropogenic disaster materials, though biomass ash also is a major contributor to water quality. In conclusion, the increase in metals following WUI burning may have adverse ecological impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-xBR NEON Bartlett Experimental Forest (BART)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART). This is the FLUXNET version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART) produced by applying the standard ONEFlux (1F) software. Site Description - The Bartlett Experimental Forest is an actively managed forest; managed portions (30%) reflect a range of forest patch sizes and structural distributions. The Bartlett forest has a history of logging dating from colonial times through the beginning of the 20th century. Approximately 70% of the land area has remained uncut since the early 1900s. Natural disturbances include late 19th century fire, beech scale-Nectria complex (beech bark disease) beginning in the 1940s, severe wind disturbance resulting from hurricanes in 1938 and 1954 and a damaging ice storm in 1998.

Network), NEON (National Ecological Observatory↗
DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗
DOE OSTI2026

Section 3 Reporting: Preserve America

Brookhaven National Laboratory (BNL) is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and countless advances in science and technology. For over 75 years, the Laboratory has played a leading role in the Department of Energy (DOE) Science and Technology mission and continues to contribute to the DOE’s missions in energy resources, environmental quality, and national security. The Laboratory is operated and managed by Brookhaven Science Associates (BSA), which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a non-profit applied science and technology organization. BNL is committed to longstanding partnerships with researchers, academic institutions, industry, students, teachers, and the surrounding community. BNL is located near the center of Suffolk County on Long Island, New York within Brookhaven Township, about 60 miles east of New York City. Most of BNL’s principal facilities are located near the center of the 5,265-acre (8.23 square mile) site (Figure 1). The developed area encompasses approximately 1,820 acres, consisting of: ▪ 500 acres originally developed by the Army (as part of WW II Camp Upton) and still used for offices and other operational buildings. ▪ 200 acres occupied by large, specialized research facilities. ▪ 520 acres occupied by outlying facilities, such as the Sewage Treatment Plant, research agricultural fields, housing facilities, and fire breaks. ▪ 400 acres of roads, parking lots, and connecting areas. ▪ 200 acres developed for the Long Island Solar Farm. The balance of the site, approximately 3,400 acres, is largely wooded and represents a native pine barrens ecosystem. In November 2000, DOE set aside 530 acres of undeveloped land at BNL as the Upton Ecological and Research Reserve. The Upton Reserve preserves this portion of the pine barrens ecosystem and provides an area for ecological research and education activities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

State changes: insights from the U.S. Long Term Ecological Research Network

Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long-term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER)network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in50 or 100 yr based on long-term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the “state change” theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo(tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds(the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea-level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate-induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across adverse range of ecosystems and highlight the need for long-term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Assisted migration in a warmer and drier climate: less climate buffering capacity, less facilitation and more fires at temperate latitudes?

Assisted tree migration has been proposed as a conceptual solution to mitigate lags in biotic responses to anthropogenic climate change. The rationale behind this concept is that tree species currently growing under warmer and drier climates will be more resistant and resilient to the new climatic conditions than tree species naturally growing in currently wetter and colder climates. However, we hypothesize that, by being more stress‐tolerant to warmer and drier conditions, translocated species should exhibit different functional attributes, which could induce important ecological and societal costs and overcome the desired benefits of maintaining wood production and other ecosystem services. We used principal component analysis (PCA) to analyze variation in seven traits of 106 tree and tall shrub species from contrasting latitudinal distributions in western North America and Europe to predict the potential functional changes of forest ecosystems due to the translocation of tree species from low to high latitudes. We show that species from both continents differed primarily by their position on the leaf economy spectrum (LES) and their size traits. Even though, in Europe, differences in LES were significantly correlated to species southern latitudinal positions, in both continents differences in size traits were significantly correlated to latitude. These results suggest that assisted migration by translocating more conservative species of shorter stature in currently cooler climates should decrease the buffering capacity of forest canopies, decrease facilitation for understory species, and increase wildfire risks, whose effects have the potential to accelerate climate warming through negative atmospheric feedback processes. As an alternative solution to assisted migration that may accelerate rather than mitigate climate change, we recommend that foresters gradually diversify the vertical structure and layering of the existing forest canopy to maintain a sustainable water cycle and energy balance between the soil, the tree and the atmosphere without increasing the wildfire risk.

Environmental Sciences & Ecology↗
DOE OSTI2024

Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama

Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.

Environmental Sciences & Ecology↗
DOE OSTI2025

Wildfire‐Induced Losses of Soil Particulate and Mineral‐Associated Organic Carbon Persist for Over 4 Years in a Chaparral Ecosystem

ABSTRACT Wildfires can lower soil carbon (C) stocks directly through combustion, but also indirectly during post‐fire recovery if microbial C demands outpace photosynthetic C inputs. However, how much C is respired by soil microorganisms post‐fire may depend on wildfire effects on particulate organic carbon (POC; mostly plant material accessible to microbes) and/or mineral‐associated organic carbon (MAOC; considered C protected by minerals from decomposers), meaning assessment of wildfire impacts on these pools is necessary to predict microbial decomposition rates and, thus, the fate of soil C. Here, we measured POC, MAOC, pyrogenic organic matter C, plant cover, extracellular enzyme activity (EEA), and microbial community abundance and composition 17 days, and 1, 3, and 4 years after the Holy Fire burned 94 km 2 of fire‐adapted chaparral. The wildfire immediately decreased POC by 50% (from 51 ± 21 to 26 ± 6 g C kg −1 ) and MAOC by 33% (from 9.3 ± 0.9 to 6.3 ± 0.9 g C kg −1 ), consistent with MAOC being less vulnerable to loss than POC. POC decreased by another 38% 1 year post‐fire, consistent with increases in microbial abundance and EEA suggesting increased microbial decomposition. Between 1 and 4 years after the fire, cover of the dominant shrub (Arctostaphylos glandulosa) increased from 3.9% ± 1.6% to 16% ± 5.4% (compared to 58% ± 4.6% in unburned plots), marking the end of net soil C losses. Still, soil C did not increase between 1 and 4 years post‐fire, suggesting plant C inputs did not outpace microbial respiration, a finding consistent with isotopically heavier C from microorganisms raising bulk soil δ 13 C values. As global changes favor increases in wildfire frequency and severity, C losses via combustion and decomposition may outpace plant C inputs during the first 4 years post‐fire in chaparral, slowing the replenishment of soil C stocks.

Biodiversity & Conservation↗
DOE OSTI2024

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Abstract Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Environmental Sciences & Ecology↗
DOE OSTI2023

Post-fire soil emissions of nitric oxide (NO) and nitrous oxide (N 2 O) across global ecosystems: a review

Wildfires may increase soil emissions of trace nitrogen (N) gases like nitric oxide (NO) and nitrous oxide (N 2 O) by changing soil physicochemical conditions and altering microbial processes like nitrification and denitrification. When 34 studies were synthesized, we found a significant increase in both NO and N 2 O emissions up to 1 year post-fire across studies spanning ecosystems globally. However, when fluxes were separated by ecosystem type, we found that individual ecosystem types responded uniquely to fire. Forest soils tended to emit more N 2 O after fire, but there was no significant effect on NO. Shrubland soils showed significant increases in both NO and N 2 O emissions after fires; often with extremely large but short-lived NO pulses occurring immediately after fire. Grassland NO emissions increased after fire, but the size of this effect was small relative to shrublands. N 2 O emissions from burned grasslands were highly variable with no significant effect. To better understand the variation in responses to fire across global ecosystems, more consistent measurements of variables recognized as important controls on soil fluxes of NO and N 2 O (e.g., N cycling rates, soil water content, pH, and substrate availability) are needed across studies. We also suggest that fire-specific elements like burn severity, microbial community succession, and the presence of char be considered by future studies. Our synthesis suggests that fires can exacerbate ecosystem N loss long after they burn, increasing soil emissions of NO and N 2 O with implications for ecosystem N loss, climate, and regional air quality as wildfires increase globally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover

Wildfires produce smoke that can affect an area >1000 times the burn extent, with far-reaching human health, ecologic, and economic impacts. Accurately estimating aerosol load within smoke plumes is therefore crucial for understanding and mitigating these impacts. We evaluated the effectiveness of the latest Collection 6.1 MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in estimating aerosol optical depth (AOD) across the U.S. during the historic 2020 wildfire season. We compared satellite-based MAIAC AOD to ground-based AERONET AOD measurements during no-, light-, medium-, and heavy-smoke conditions identified using the Hazard Mapping System Fire and Smoke Product. This smoke product consists of maximum extent smoke polygons digitized by analysts using visible band imagery and classified according to smoke density. We also examined the strength of the correlations between satellite- and ground-based AOD for major land cover types under various smoke density levels. MAIAC performed well in estimating AOD during smoke-affected conditions. Correlations between MAIAC and AERONET AOD were strong for medium- (r = 0.91) and heavy-smoke (r = 0.90) density, and MAIAC estimates of AOD showed little bias relative to ground-based AERONET measurements (normalized mean bias = 3 % for medium, 5 % for heavy smoke). During two high AOD, heavy smoke episodes, MAIAC underestimated ground-based AERONET AOD under mixed aerosol (i.e., smoke and dust; median bias = −0.08) and overestimated AOD under smoke-dominated (median bias = 0.02) aerosol. MAIAC most overestimated ground-based AERONET AOD over barren land (mean NMB = 48 %). Our findings indicate that MODIS MAIAC can provide robust estimates of AOD as smoke density increases in coming years. Increased frequency of mixed aerosol and expansion of developed land could affect the performance of the MAIAC algorithm in the future, however, with implications for evaluating wildfire-associated health and welfare effects and air quality standards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Detecting ecological signatures of long-term human activity across an elevational gradient in the Šumava Mountains, Central Europe

Central European mountains, including the Šumava Mountains located along the Czechia/Germany border, have a long and rich anthropogenic history. Yet, documenting prehistoric human impact in Central European mountain environments remains a challenge because of the need to disentangle climate and human-caused responses in terrestrial systems. Here, we present the first reconstructed water table depths (WTDs) from two sites, Pěkná and Blatenská slať, located in the Šumava Mountains. We compare these local WTD records with new and published pollen, non-pollen palynomorphs (NPPs), plant macrofossils, geochemistry and archeological records to investigate how changes in local hydrology and human activities impacted forest succession and fire activity throughout the Holocene across an elevational gradient. Using a generalized additive model, our results suggest that changes in forest succession and fire activity have been primarily caused by climate throughout the Holocene. However, humans have been utilizing mountain environments and their resources continuously since ∼4600 cal yr BP, thus playing a secondary role in modifying forest succession to increase resources beneficial to both humans and grazers. Over the last 1000 years, we provide evidence of directly observed human-caused modifications to the landscape. These results contribute to a growing body of literature illustrating human activities and landscape modifications in Central European mountains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗
DOE OSTI2020

Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Antecedent Hydrometeorological Conditions of Wildfire Occurrence in the Western U.S. in a Changing Climate

Abstract Wildfires have significant hydrological and ecological impacts in the western U.S. Using a high‐resolution regional climate simulation and wildfire observations for 1984–2018, this study investigates the antecedent hydrometeorological conditions (AHCs) of wildfires in the western U.S. During the warm season (April‐September), the wildfire AHCs feature diverse surface pressure (PS), soil moisture, and longwave/shortwave radiation (LW/SW) conditions. K‐means clustering classifies wildfires into four types with distinct AHCs: low‐PS‐type and high‐PS‐type with lower and higher PS anomalies, respectively, LW‐type featuring intense LW but weak SW anomalies, and wet‐soil‐type with wet soil anomalies. Each fire cluster represents 22%–27% of all the wildfires, featuring different combinations of climate and vegetation conditions and their diverse relations to regional hydrometeorological conditions, with wet‐soil‐type fires often exhibiting opposite correlations with AHCs compared to those of the other three types. In five major Köppen climate zones over the western U.S., clustering‐based predictions improve the seasonal wildfire prediction accuracy ( R 2 ) by 10% compared to prediction without classification. Such improvement comes from separating the opposite relationships between wet‐soil‐type fires and their seasonal AHCs from the other three types, along with separating LW‐type fires, which include most of the lightning‐ignited fires that occur more randomly. Increases in wildfire occurrence during 1984–2018 are dominated by the increases in the LW‐type fires, while the wet‐soil‐type fires have decreased, consistent with the long‐term drying in the western U.S.

54 ENVIRONMENTAL SCIENCES↗