Fire Suppression Resources Research Articles

Trends in prescribed fire weather windows from 2000 to 2022 in California

As increasing wildfire activity puts pressure on wildland fire suppression resources both nationally and within the state of California, further development of programs and infrastructure that emphasize preventative fuels treatments, e.g. prescribed burning, is critical for mitigating the impacts of wildfire at large spatial scales. Among many factors that limit the use of prescribed fire, weather and fuel moisture conditions are among the most critical. We analyzed a 2-km gridded hourly surface weather dataset over a 23-yr period to explore the relationship between climatological trends and prescribed fire weather windows. Pairing this dataset with burn prescription parameters provided by experienced regional fire practitioners, we seek to identify the timing and extent of changes in weather-related opportunities for prescribed fire in two distinct geographic regions within California. We found an increasing trend in opportunities for prescribed fire use in Sonoma County, a representative coastal Mediterranean region of CA, and a decreasing trend in Plumas County, a montane region that extends through the Northern Sierra Nevada. Seasonally, we see more nuances—increased winter opportunities in both counties, as well as increased summer opportunities in Sonoma. Most notably, we see great variation spatially in the occurrence of suitable weather windows for prescribed burning. Fire management resource availability and air quality regulations further constrain burn windows. We observed a greater influence of these factors in Sonoma County vs. Plumas. Resource availability is the greatest constraint in the Summer and Fall, during wildfire season, and air quality regulations are a greater constraint in the Winter. Our findings provide information to decision-makers and regulators at the county and other government levels to more effectively support use of prescribed fire to achieve land management and fuels reduction goals.

Modelling the vulnerability of urban settings to wildland–urban interface fires in Chile

Abstract. Wildland–urban interface (WUI) regions are particularly vulnerable to wildfires due to their proximity to both nature and urban developments, posing significant risks to lives and property. To enhance our understanding of the risk profiles in WUI areas, we analysed seven fire case studies in central Chile. We developed a mixed-method approach for conducting local-scale analyses, which involved field surveys, remote-sensing through satellite and drone imagery, and GIS-based analysis of the collected data. The methodology led to the generation of a georeferenced dataset of damaged and undamaged dwellings, including 16 variables representing their physical characteristics, spatial arrangement, and the availability of fire suppression resources. A binary classification model was then used to assess the relative importance of these attributes as indicators of vulnerability. The analysis revealed that spatial arrangement factors have a greater impact on damage prediction than the structural conditions and fire preparedness of individual units. Specifically, factors such as dwelling proximity to neighbours, distance to vegetation, proximity to the border of dwelling groups, and distance from the origin of the fire substantially contribute to the prediction of fire damage. Other structural attributes associated with less affluent homes may also increase the likelihood of damage, although further data are required for confirmation. This study provides insights for the design, planning, and governance of WUI areas in Chile, aiding the development of risk mitigation strategies for both built structures and the broader territorial area.

The wildfire suppression problem with multiple types of resources

The frequency and impact of wildfires have considerably increased in the past decade, due to the extreme weather conditions as well as the increased population density. The aim of this study is to introduce, model, and solve a wildfire suppression problem that involves multiple types of fire suppression resources and their operational characteristics. Two integer programming (IP) formulations, a basic IP and its reformulation with combinatorial Benders’ cuts, are presented. The performances of the proposed formulations are evaluated on a set of randomly generated instances. The results indicate that the proposed formulations are able to obtain high quality upper and lower bounds. Extensive numerical experiments are performed to analyse the effects of several operational constraints on the computational performance of the models. A case study arising in Yatağan district of Muğla province of Türkiye is presented.

Dataset of United States Incident Management Situation Reports from 2007 to 2021

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.

Logic-based benders decomposition for wildfire suppression

In this paper we consider a network interdiction problem where the follower is characterised by a spreading phenomenon. As a case study we consider in detail a wildfire suppression problem. The landscape is modelled as a directed graph, with nodes representing regions of the landscape, and arcs representing adjacency relationships. The fire spread is modelled using the minimum travel time principle. The goal is to locate fire suppression resources in a landscape in order to minimise the total area burned. As previous exact algorithms in this space are intractable on reasonable instances, the literature focuses on heuristics. In this paper we propose a new exact algorithm utilising logic-based Benders decomposition. We benchmark the new approach against mixed-integer programming and metaheuristic approaches. Our approach is able to quickly solve instances from the literature. We are also able to solve larger instances to optimality in a reasonable amount of time.

Combining Field Observations and Remote Sensing to Forecast Fine Fuel Loads

Effective wildfire management requires accurate information about the spatial distribution of fuels. While static maps work well for coarse forest fuels with slow turnover, fine fuels—the driver of rangeland fires—often vary dramatically from year to year. Our goal was to develop a fine fuel forecast to help managers optimally allocate fire suppression resources and funding before the start of the fire season and to identify critical gaps in understanding or data that limit forecast skill. We compiled a historical record of fine fuel loads collected in the Great Basin and combined it with remotely sensed data on herbaceous productivity. Using a Bayesian State-Space approach to account for both process and observation error, we built a “Fuels Model” in which the predicted fuel load at a location depends on the fuel load in the previous year and productivity of the current year. Next, we built a “productivity model” to predict current year production based on remotely sensed data available in early spring. Finally, we combined these two models to generate early spring forecasts for summer fuel loads from 1987 to 2020 and quantified the associated uncertainty. We found that current year productivity contributed twice as much as the previous year's fuel load to the current fuel load. Our productivity predictions reduced mean absolute predictive error by 11% compared with a strong null model without early-season weather covariates. However, when we fed the productivity predictions into our fuel model, the resulting fuel load forecasts had too much uncertainty to inform management decisions, with most uncertainty coming from the process error of the Fuels Model. Reducing this uncertainty will require higher-quality observations of fuel loads. Until those are available, our results suggest that managers could rely on productivity forecasts as a reasonable proxy for fuel load forecasts.

Assessing directional vulnerability to wildfire

Wildfires spread along trajectories set by a coincident wind direction. Despite the highly directional nature of wildfire threats to public safety, landscape fire risk assessments are typically omnidirectional. We used a simple metric of landscape fire exposure to develop a systematic and standardized approach for assessing directional vulnerability to wildfire within a circular assessment area centered on locale of interest. First, we defined a viable wildfire trajectory by analyzing 573 sample trajectories delineated within the burned areas of historical fires in the province of Alberta, Canada. On average, sample trajectories intersected locations assessed as having high wildfire exposure for 79% of their length. We, therefore, defined a viable fire trajectory as one with at least 80% of its length traversing high exposure. Using this criterion, we assessed the viability of directional trajectories representing possible wildfire pathways from outlying landscape areas into a locale of interest centered within a roughly 70,000-ha circular assessment area. At each central assessment point (i.e., community centroid), we delineated 360 linear trajectories into the community at 1° directional intervals. Each 15-km trajectory was divided into three 5-km segments for analysis (inner, middle, and outer). The length of each directional trajectory segment that intersected high exposure was computed for all 1080 directional segments in each community assessment area. In total, we evaluated 986,040 directional segments for 913 communities in the province. Communities exhibited highly unique and varied patterns of directional vulnerabilities to wildfire encroachment. Of the communities analyzed, 136 had at least one continuous viable trajectory spanning the full 15-km distance from the community centroid, and 211 communities had at least one continuous viable trajectory spanning 5–15 km from the community centroid. We developed customized rose or polar diagrams for displaying spatially referenced directional vulnerabilities to wildfire for a given community and combined results for all 913 analyzed communities to assess regional vulnerabilities within administrative management areas (i.e., Forest Areas). Potential applications of our directional assessment method are discussed, including prepositioning and prioritizing limited fire suppression resources, planning fuel reduction treatments, proactively identifying candidate locations for operational activities, assessing transportation network vulnerabilities during evacuations, and scenario planning.

A modified Ant Colony System for the asset protection problem

• Time-efficient solutions of the Asset Protection Problem (APP). • The Modified Ant Colony System (MACS) is proposed. • Especially designed solution-improving heuristic techniques. • New best results in large-scale benchmark instances. • MACS outperforms previous APP solution approaches. During an escaped wildfire in a populated area’s vicinity, protective tasks should be carried out to secure crucial community assets, e.g., bridges, hospitals, power stations, and communication towers. In a real-life scenario, an important asset may require the combined effort of different fire suppression resources, which should be dispatched and scheduled to act synchronously in protecting the respective asset. The present research addresses the solution of a challenging routing problem in emergency response, the Asset Protection Problem (APP), which incorporates selective characteristics in routing a heterogeneous vehicle fleet with complex temporal and spatial constraints, i.e., time windows and synchronization requirements. Notably, the Modified Ant Colony System (MACS) algorithm is proposed to obtain effective APP solutions within a time suitable for operational purposes. Based on the conducted experiments, MACS outperforms the previously published solution approaches in the solution of large-scale APP benchmark instances. Notably, MACS obtained superior solutions in 159 out of 240 large-scale instances, while 87 of them represent new best results, considering the solutions achieved by the commercial solver CPLEX with a ten-hour time limit.

Fuel reduction treatments reduce modeled fire intensity in the sagebrush steppe

AbstractIncreased fire size and frequency coupled with annual grass invasion pose major challenges to sagebrush (Artemisia spp.) ecosystem conservation, which is currently focused on protecting sagebrush community composition and structure. A common strategy for mitigating potential fire is to use fuel treatments that alter the structure and amount of burnable material, thus reducing fire behavior and creating access points for fire suppression resources. While there is some recent information on the impacts of fuel treatments on ecological communities, we have little information on fuel treatment effectiveness at modifying fire behavior in sagebrush ecosystems. We present 10 years of data on fuel accumulation and the resultant modeled fire behavior in prescribed fire, mowed, herbicide (tebuthiuron or imazapic), and untreated control plots in the Sagebrush Treatment Evaluation Project (SageSTEP) network in the Great Basin, USA. Fuel data (i.e., aboveground burnable live and dead biomass) were collected in each treatment plot at Years 0 (pretreatment), 1, 2, 3, 6, and 10 posttreatment. We used the Fuel and Fire Tool fire behavior modeling program to test whether treatments impacted potential fire behavior. Prescribed fire initially removed 49% of the total fuel load and 75% of shrubs, and fuel loads remained reduced through Year 10. Mowing shifted fuels from the shrub canopy to the ground surface but did not change the total fuel amount. Prescribed fire and mowing increased herbaceous fuel by the second posttreatment year and that trend persisted through Year 10. Tebuthiuron treatments were ineffective at altering fuel loads. Imazapic suppressed herbaceous vegetation by 30% in Years 2 and 3 following treatment. The modified fuel beds in fire and mow treatments resulted in modeled flame lengths that were significantly lower than untreated control plots for the duration of the study, with shorter term reductions in reaction intensity and rate of spread. Understanding fuel treatment effectiveness will allow natural resource managers to evaluate trade‐offs between protecting wildlife habitat and reducing the potential for high‐intensity wildfire.

Iterated local search for the placement of wildland fire suppression resources

We consider the problem of, given a landscape represented by a gridded network and a fire ignition location, deciding where to locate the available fire suppression resources to minimise the burned area and the number of deployed resources as a secondary objective. We assume an estimate of the fire propagation times between adjacent nodes and use the minimum travel time principle to model the fire propagation at a landscape-level. The effect of locating a resource in a node is that it becomes protected and the fire propagation to its unburned adjacent nodes is delayed. Therefore, the problem is to identify the most promising nodes to locate the resources, which is solved by a novel iterated local search (ILS) metaheuristic. A mixed integer programming (MIP) model from the literature is used to validate the proposed method in 32 grid networks with sizes 6x6, 10x10, 20x20 and 30x30, with two different number of fire suppression resources (64 problems). Our ILS produced optimal solutions in 40 cases out of 41 known optimal lower bounds. The proposed method’s effectiveness is also due to its short computing times and small coefficients of variation of the objective function values.We also provide a categorised literature review on fire suppression deterministic optimisation models, from which we conclude that approximate collaborative approaches seldom have been applied in the past and, according to the results obtained, can successfully address the complexity of fire suppression, reaching good quality solutions even for large scale instances.

High-severity wildfire potential – associating meteorology, climate, resource demand and wildfire activity with preparedness levels

National and regional preparedness level (PL) designations support decisions about wildfire risk management. Such decisions occur across the fire season and influence pre-positioning of resources in areas of greatest fire potential, recall of personnel from off-duty status, requests for back-up resources from other areas, responses to requests to share resources with other regions during fire events, and decisions about fuel treatment and risk reduction, such as prescribed burning. In this paper, we assess the association between PLs assigned at national and regional (Northwest) scales and a set of predictors including meteorological and climate variables, wildfire activity and the mobilisation and allocation levels of fire suppression resources. To better understand the implicit weighting applied to these factors in setting PLs, we discern the qualitative and quantitative factors associated with PL designations by statistical analysis of the historical record of PLs across a range of conditions. Our analysis constitutes an important step towards efforts to forecast PLs and to support the future projection and anticipation of firefighting resource demand, thereby aiding wildfire risk management, planning and preparedness.

Relationship Between Fire and Forest Cover Loss in Riau Province, Indonesia Between 2001 and 2012

Forest and peatland fires occur regularly across Indonesia, resulting in large greenhouse gas emissions and causing major air quality issues. Over the last few decades, Indonesia has also experienced extensive forest loss and conversion of natural forest to oil palm and timber plantations. Here we used data on fire hotspots and tree-cover loss, as well as information on the extent of peat land, protected areas, and concessions to explore spatial and temporal relationships among forest, forest loss, and fire frequency. We focus on the Riau Province in Central Sumatra, one of the most active regions of fire in Indonesia. We find strong relationships between forest loss and fire at the local scale. Regions with forest loss experienced six times as many fire hotspots compared to regions with no forest loss. Forest loss and maximum fire frequency occurred within the same year, or one year apart, in 70% of the 1 km2 cells experiencing both forest loss and fire. Frequency of fire was lower both before and after forest loss, suggesting that most fire is associated with the forest loss process. On peat soils, fire frequency was a factor 10 to 100 lower in protected areas and natural forest logging concessions compared to oil palm and wood fiber (timber) concessions. Efforts to reduce fire need to address the underlying role of land-use and land-cover change in the occurrence of fire. Increased support for protected areas and natural forest logging concessions and restoration of degraded peatlands may reduce future fire risk. During times of high fire risk, fire suppression resources should be targeted to regions that are experiencing recent forest loss, as these regions are most likely to experience fire.

Fire activity and burned forest lands decreased during the last three decades in Spain

Fire activity has decreased in the last decades in Spain as a whole and in most provinces. However, fire risk factors have increased. Wildfires are burning preferentially treeless areas. Flammable pine areas burn less, while the less flammable oak forests burn more. This decreasing fire activity coincides with increasing fire suppression resources. Climate and other fire risk factors are changing across the world, including the Mediterranean region. It is important to determine how fire activity is responding to such changes. To identify spatio-temporal changes in fire frequency and size, main tree species burned, and their association with changes in climate, land-use and land-cover, and fire suppression. Analysis of trends, breakpoints, and association among the time series of fire variables and fire risk factors during 1980–2013 in Spain at country and provincial levels. Wildfires in Spain have been decreasing in number, burned area, mean, and largest fire sizes. Fires are more frequently burning treeless areas than forests. Pine forests are burning less, while oak forests are burning more. Fire suppression resources, particularly aerial ones, increased significantly. Risk factors like the mean summer fire weather index, and the forested and the artificial areas all increased. Despite increasing fire risk factors, wildfires have decreased at the country as a whole and in most provinces in Spain during the last 34 years.

GIS-based forest fire risk mapping using the analytical network process and fuzzy logic

This research investigates the efficiency of combining the Analytical Network Process (ANP) and fuzzy logic for developing a fire risk map. Major factors influencing the occurrence of forest fires were identified from the literature. The importance of each factor was determined by an ANP ranking procedure, which yielded the criteria weights, while fuzzy logic was employed for assessing the weights of the subcriteria. Then, GIS-based aggregation functions were employed to produce a fire risk map. In order to validate the results, forest fire locations were identified using field data, satellite images, and national reports. This validation revealed a very high accuracy of 0.819 for the fuzzy ANP model. The results will serve as guidelines for researchers and scientists by introducing new and robust MCDA methods. In general, the mentioned Hybrid method can be applied to early warning, fire suppression resources planning, and allocation work in the study area.

A simulation and optimisation procedure to model daily suppression resource transfers during a fire season in Colorado

Sharing fire engines and crews between fire suppression dispatch zones may help improve the utilisation of fire suppression resources. Using the Resource Ordering and Status System, the Predictive Services’ Fire Potential Outlooks and the Rocky Mountain Region Preparedness Levels from 2010 to 2013, we tested a simulation and optimisation procedure to transfer crews and engines between dispatch zones in Colorado (central United States) and into Colorado from out-of-state. We used this model to examine how resource transfers may be influenced by assignment shift length, resource demand prediction accuracy, resource drawdown restrictions and the compounding effects of resource shortages. Test results show that, in certain years, shortening the crew shift length from 14 days to 4 days doubles the yearly transport cost. Results also show that improving the accuracy in predicting daily resource demands decreases the engine and crew transport costs by up to 40%. Other test results show that relaxing resource drawdown restrictions could decrease resource transport costs and the reliance on out-of-state resources. The model-suggested assignments result in lower transport costs than did historical assignments.

Spatial patterns and controls on burned area for two contrasting fire regimes in Southern California

AbstractAn improved understanding of the mechanisms that regulate wildfire risk at local to regional scales is needed for the design of effective fire and ecosystem management. We investigated the spatial distribution of burned area in Southern California during 1960–2009 using five different data‐driven methods: multiple linear regression, generalized additive models (GAMs), GAMs with spatial autocorrelation, non‐linear multiplicative models, and random forest models. We used each method to separately develop burned area risk maps for Southern California's two distinct wildfire regimes: Santa Ana (SA fires), which occur during high wind events mostly in autumn, and non‐Santa Ana fires (non‐SA fires), which occur mostly during the hot and dry Mediterranean‐climate summer. The different methods explained 38–63% of the spatial variance in burned area for SA fires and 21–48% for non‐SA fires. The two fire regimes had contrasting drivers, with Fosberg fire weather index, relative humidity, minimum temperature, and distance to housing most important for SA fires, and shrub cover, road density, and distance to minor and major roads most important for non‐SA fires. Our modeling framework carries implications for the strategic placement of fire suppression resources, and for prevention planning in areas facing increasing human and climate pressures.

A Comparative Analysis of Forest Fire Suppression Resources According to Facilities in Forest

본 연구는 산림 내 주요시설물별 산불진화자원 현황을 분석하기 위하여 산림 내에 가장 많이 소재하고 있는 요양소, 펜션, 휴양림, 사찰 등 총 69개소에 대해 현장조사를 실시하였다. 시설물별 산불진화자원 현황 조사는 안전관리 인적현황(2항목), 재난발생 시 협조체계 현황(2항목), 안전관리(3항목), 소화설비(4항목), 방범설비 및 매뉴얼(3항목)등 총 14개 항목에 대하여 실시하였다. 연구결과 산불이 발생될 경우 대응가능 인원 중 시설물 관리자 및 상주하는 사람을 대상으로 소방안전관리자로 선임할 필요성이 있는 것으로 조사되었다. 또한, 산불발생시 관공서와의 접근거리는 사찰이 평균 10km(18.6분)로 가장 멀고, 진출입로, 선회 공간 등이 부족한 것으로 조사되었고, 펜션의 경우 안전교육을 거의하지 않는 것으로 나타나 교육 훈련이 필요한 것으로 나타났다. 또한, 시설물별 소화설비 및 장비의 확충과 화재대응 매뉴얼 구축이 필요한 것으로 나타났다.In this study, we investigated sanatoriums, pensions, recreation forests, buddhist temples and others mainly located in forest in order to analyze the present conditions on forest fire suppression resources. By investigating 69 facilities in the study area, we found that a facility administrator and resident persons would need to be appointed as a fire administrator to effectively respond to forest fires. It is found that buddhist temples are located the most distant from a public office, with the average distance of approximately 10 km (the access time was 18.6 minutes), and thus should be provided with more access routes and spaces for more prompt responses to the forest fire risk. We also found that the forest fire safety education has been rarely conducted in pensions. This findings of this study recommend that an extinguishing system and equipment should be further expanded and the forest fire response manual should be provided in all facilities.

Analysis of factors influencing deployment of fire suppression resources in Spain using artificial neural networks

Abstract: In Spain, the established fire control policy states that all fires must be controlled and put out as soon as possible. Though budgets have not restricted operations until recently, we still experience large fires and we often face multiple-fire situations. Furthermore, fire conditions are expected to worsen in the future and budgets are expected to drop. To optimize the deployment of firefighting resources, we must gain insights into the factors affecting how it is conducted. We analyzed the national data base of historical fire records in Spain for patterns of deployment of fire suppression resources for large fires. We used artificial neural networks to model the relationships between the daily fire load, fire duration, fire type, fire size and response time, and the personnel and terrestrial and aerial units deployed for each fire in the period 1998-2008. Most of the models highlighted the positive correlation of burned area and fire duration with the number of resources assigned to each fire and some highlighted the negative influence of daily fire load. We found evidence suggesting that firefighting resources in Spain may already be under duress in their compliance with Spain’s current full suppression policy.

Mapping fire behaviour under changing climate in a Mediterranean landscape in Greece

Understanding how future climate periods influence fire behaviour is important for organizing fire suppression strategy and management . The meteorological factors are the most critical parameters affecting fire behaviour in natural landscapes; hence, predicting climate change effects on fire behaviour could be an option for optimizing firefighting resource management. In this study, we assessed climate change impacts on fire behaviour parameters (rate of fire growth, rate of spread and fireline intensity) for a typical Mediterranean landscape of Greece. We applied the minimum travel time fire simulation algorithm by using the FlamMap software to characterize potential response of fire behaviour for three summer periods. The results consisted of simulated spatially explicit fire behaviour parameters of the present climate (2000) and three future summer periods of 2050, 2070 and 2100, under the A1B emissions scenario. Statistical significant differences in simulation outputs among the four examined periods were obtained by using the Tukey’s significance test. Statistical significant differences were mainly obtained for 2100 compared to the present climate due to the significant projected increase in the wind speed by the end of the century. The analysis and the conclusions of the study can be important inputs for fire suppression strategy and fire management (deployment of fire suppression resources, firefighter safety and exposure, transportation logistics) quantifying the effect that the expected future climate periods can have on fire suppression difficulty in Mediterranean landscapes.

The economic benefit of localised, short-term, wildfire-potential information

Wildfire-potential information products are designed to support decisions for prefire staging of movable wildfire suppression resources across geographic locations. We quantify the economic value of these information products by defining their value as the difference between two cases of expected fire-suppression expenditures: one in which daily information about spatial variation in wildfire-potential is used to move fire suppression resources throughout the season, and the other case in which daily information is not used and fire-suppression resources are staged in their home locations all season. We demonstrate the method by constructing a hypothetical wildland management unit calibrated to represent a region typical in the US West. The method uses estimated suppression costs and probabilities of significant fire, as provided by an information service, to estimate expected suppression costs. We analyse differences in expected suppression costs for a range of risk scenarios. Economic savings occur for the majority of risk scenarios. This approach can be used to evaluate investments in wildfire-potential information services, and for assessing the value of investing in new resources.