Erin J. Belval’s research while affiliated with Colorado State University and other places

Background Wildland firefighters are exposed to hazards when working which can, and do, result in serious injury or death. Understanding the activities in which firefighters are engaged when they are injured, the hazards to which they were exposed during that activity and the resulting injury severity is critical to manage the risk of serious injury to firefighters. Aims This study aims to provide an assessment of wildland firefighter injuries. Methods A set of 435 severe injuries in wildland firefighters in the United States from 2019 to 2023 was classified by activity being performed, hazard encountered and injury severity. Statistical summaries were used to contextualize the data and to examine the frequency and severity of these injuries. Proportional odds models tested the impact of activity, region and fire complexity on injury severity. Key results Aviation activities are associated with higher injury severity; there is no statistically significant difference in injury severity among other activities. Region and fire type do not impact injury severity. Injury frequency and severity vary among hazards and associated activities. Conclusions and Implications Given the hazard mitigations in place, reducing injury frequency and severity may be challenging without clearly defined agency level risk tolerances.

Wildfire activity in the western United States has been on the rise since the mid-1980s, with longer, higher-risk fire seasons projected for the future. Prescribed burning mitigates the risk of extreme wildfire events, but such treatments are currently underutilized. Fire managers have cited lack of firefighter availability as a key barrier to prescribed burning. We use both principal component analysis (PCA) and logistic regression modeling methodologies to investigate whether or not (and if yes, under what conditions) personnel shortages on a given day are associated with lower odds of a prescribed burn occurring in the Okanogan–Wenatchee National Forest. We utilize the logit model to further assess how personnel availability compares to other potential barriers (e.g., meteorological conditions) in terms of association with odds of a prescribed burn occurring. Our analysis finds that fall and spring days in general have distinct constellations of characteristics. Unavailability of personnel is associated with lower odds of prescribed burning in the fall season, controlling for meteorological conditions. However, in the spring, only fuel moisture is observed to be associated with the odds of prescribed burning. Our findings suggest that if agencies aim to increase prescribed burning to mitigate wildfire risk, workforce decisions should prioritize firefighter availability in the fall.

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.

Pre-fire mitigation efforts that include the installation and maintenance of fuel breaks are integral to wildfire suppression in Southern California. Fuel breaks alter fire behavior and assist in fire suppression at strategic locations on the landscape. However, the combined effectiveness of fuel breaks and wildfire suppression is not well studied. Using daily firefighting personnel to proxy the quantity and diversity of potential fire suppression operations (i.e., operational complexity), we examined 15 wildfires from 2017 to 2020 in the Los Padres, Angeles, San Bernardino, and Cleveland National Forests to assess how weather and site-specific fuel break characteristics influenced wildfire containment when leveraged during suppression operations. After removing effects of fuel treatments, wildfire and aerial firefighting, we estimated that expanding fuel break width in grass-dominant systems from 10 to 100 m increased the average success rate against a heading fire from 31 % to 41 %. Likewise, recently cleared fuel breaks had higher success rates compared to poorly maintained fuel breaks in both grass (25 % to 45 %) and shrub systems (20 % to 45 %). Combined, grass and shrub systems exhibited an estimated success rate of 80 % under mild weather conditions (20th percentile) and 19 % under severe weather (80th percentile). Other significant determinants included forb and grass production, adjacent tree canopy cover and terrain. Consistent with complexity theory and previous suppression effectiveness research, our analysis showed signs of suppression effectiveness declining as firefighter personnel increased. Future work could better account for the role of suppression with improved data on firefighting resource types, actions, locations, and timing. https://authors.elsevier.com/a/1jtGp4y2D1kEi5

Background As fire seasons in the Western US intensify and lengthen, fire managers have been grappling with increases in simultaneous, significant incidents that compete for response resources and strain capacity of the current system. Aims To address this challenge, we explore a key research question: what precursors are associated with ignitions that evolve into incidents requiring high levels of response personnel? Methods We develop statistical models linking human, fire weather and fuels related factors with cumulative and peak personnel deployed. Key results Our analysis generates statistically significant models for personnel deployment based on precursors observable at the time and place of ignition. Conclusions We find that significant precursors for fire suppression resource deployment are location, fire weather, canopy cover, Wildland–Urban Interface category, and history of past fire. These results align partially with, but are distinct from, results of earlier research modelling expenditures related to suppression which include precursors such as total burned area which become observable only after an incident. Implications Understanding factors associated with both the natural system and the human system of decision-making that accompany high deployment fires supports holistic risk management given increasing simultaneity of ignitions and competition for resources for both fuel treatment and wildfire response.

Wildfires are increasingly impacting social and environmental systems in the United States (US). The ability to mitigate the adverse effects of wildfires increases with understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis Fire-Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the US. FPA FOD v6 contains information on location, jurisdiction, discovery time, cause, and final size of >2.3×106 wildfires in the US between 1992 and 2020 . For each wildfire, we added physical (e.g., weather, climate, topography, and infrastructure), biological (e.g., land cover and normalized difference vegetation index), social (e.g., population density and social vulnerability index), and administrative (e.g., national and regional preparedness level and jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models. The FPA FOD-Attributes dataset is available at 10.5281/zenodo.8381129 (Pourmohamad et al., 2023).

Background The rising occurrence of simultaneous large wildfires has put strain on United States national fire management capacity leading to increasing reliance on assistance from partner nations abroad. However, limited analysis exists on international resource-sharing patterns and the factors influencing when resources are requested and deployed. Aims This study examines the drivers of international fire management ground and overhead personnel deployed to the United States. Methods Using descriptive statistics and case examples data from 2008 to 2020, this study investigates the conditions under which international personnel are deployed to the United States and their relationship to domestic resource strain. Factors such as fire weather, fire simultaneity, and the impact on people and structures are analysed as potential drivers of demand for international resources. Additionally, barriers to resource sharing, including overlapping fire seasons between countries are examined. Key results The findings indicate that international personnel sharing is more likely when the United States reaches higher preparedness levels, experiences larger area burned, and when fires pose a greater impact on people and structures. However, overlapping fire seasons can limit the ability to share resources with partner nations. Conclusions and implications Understanding the factors influencing resource sharing can help improve collaboration efforts and enhance preparedness for future wildfire seasons.

This paper presents a unique 15-year dataset of Incident Management Situation Reports (IMSR), which document daily wildland fire situations across ten geographical regions in the United States. The IMSR dataset includes summaries for each reported day on national and regional wildfire activities, wildfire-specific activities, and committed fire suppression resources (i.e., personnel and equipment). This dataset is distinct from other wildfire data sources as it provides daily information on national fire suppression resource utilization, national and regional preparedness levels, and management priority for each region and fire. We developed an open-source Java program, IMSR-Tool, to process 3,124 IMSR reports available from 2007 to 2021 to generate this structured IMSR dataset, which can be updated when future reports become available. The dataset presented here and its future extension enable researchers and practitioners to study historical wildfire activity and resource use across regions and time, examine fire management perceptions, evaluate strategies for fire prioritization and fire resource allocation, and exploit other broader usage to improve wildfire management and response in the United States.