bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling wildfire effects on the coevolution of soils and flammable temperate forests
Authors: Inbar Assaf , Nyman Petter , Lane Patrick , Sheridan Gary
Published: October 2022

Climate drives the coevolution of vegetation and the soil that supports it. Wildfire dramatically affects many key ecoâ€hydroâ€geomorphic processes, but its potential role in coevolution of soilâ€forest systems has been largely overlooked. The steep landscapes of southeastern Australia provide an excellent natural laboratory to study the role of fire in the coevolution of soil and forests, as they are characterized by temperate forest types, fire frequencies, and soil depths that vary systematically with aridity. The aims of this study were (i) to test the hypothesis that in Southeastern Australia, fireâ€related processes are critical to explain the variations in coevolved soilâ€forest system states across an aridity gradient and (ii) to identify the key processes and feedbacks involved. To achieve these aims, we developed a numerical model that simulates the coevolution of soilâ€forest systems which employ ecoâ€hydroâ€geomorphic processes that are typical of the flammable forests of southeastern Australia. A stepwise model evaluation, using measurements and published data, confirms the robustness of the model to simulate ecoâ€hydroâ€geomorphic processes across the aridity gradient. Simulations that included fire replicated patterns of observed soil depth and forest cover across an aridity gradient, supporting our hypothesis. The contribution of fire to coevolution increased in magnitude with aridity, mainly due to the higher fire frequency and lower postâ€fire infiltration capacity, increasing the rates of fireâ€related surface runoff and erosion. Our results show that critical feedbacks between soil depth, vegetation, and fire frequency dictate the trajectory and pace of the coevolution of flammable temperate forests and soils.
Agricultural fires in France: a first national overview from data mining
Authors: Vallet Lilian , Mouillot Florent , Ourcival Jean-Marc
Published: October 2022

INTRODUCTION â€¢ Even if the agricultural fires correspond to a high proportion of burned areas, their inventory is insufficient. â€¢ Considering the central role of agriculture in France, understanding agricultural fire regimes appears to be central to the objective of food security. â€¢ Most cropland or rangeland fires are directly or indirectly related to human activities, facilitating their control. MATERIEL AND METHODS â€¢ A data mining analysis of non-scientific literature was conducted between 2000 and 2021 to study the temporal and spatial evolution of agricultural fires. â€¢ This database is compared to MODIS hotspots in order to validate this active detection method and to define its limits. â€¢ An estimate of the carbon footprint is made at the French level. RESULTS â€¢ The data mining study allowed the inventory of more than 500 fire events per year. â€¢ The high spatial heterogeneity of agricultural fires is mostly explained by the variation of crop types across the territory as well as by topoclimatic conditions. â€¢ Some years, such as 2003 and 2009, are characterized by a particularly large number of agricultural fires, linked to strong heat waves. â€¢ Crop fires occur primarily during the summer months when weather and fuel conditions are most favorable. Pasture fires, mainly prescribed fires, occur before and after winter to limit their spread. Building fires occur throughout the year. DISCUSSION â€¢ This first attempt at inventorying agricultural fires in France allowed us to describe spatial and temporal patterns specific to these types of fires. â€¢ Carbon emissions from these fires are currently largely underestimated and contribute to a significant proportion of the national carbon budget.
Authors: Pérez-Romero Javier , Campo Antonio del , González-Sanchis María , Molina Antonio J. , Cano Laura Blanco , Lucas-Borja Manuel Esteban
Published: October 2022

BADE is a support tool for forest researchers and technicians programmed in Google Earth Engine (GEE) platform that serves to detect forest areas that have been burned after a wildland fire, as well as fire severity. It allows the evaluation of vegetation recovery with the visualisation of time series grouped by fire severity and for different spectral indices from which the user can choose. Its use is very simple because of the graphical interface that the user can adjust for a target area of study by selecting the date of the fire, the index to evaluate in the graph and drawing the study area where the dNBR is going to be mapped. Both the map and the graph can be easily downloaded by the user.
Developing an Integrated Capitals Approach to Understanding Wildfire Vulnerability: Preliminary Considerations from a Literature Review
Authors: Martino Simone , Roberts Michaela , Wooldridge Tami , Pol Paola Ovando , Mouillot Florent , Pernice Umberto , Ortega Macarena , Velea Ramona , Laterza Riccardo , Moreira Bruno
Published: October 2022

A capitals approach consists in considering the value of the impacts and dependencies on capital stocks (e.g., natural, human, social and produced capital) into account to inform decision-making. Traditional assessments focus on the analysis of the dependencies and impacts of one capital at time such as natural or human capital. Conversely, a multi-capital assessment involves more than one relevant capital and presents the results for each capital together. This paper presents preliminary findings on developing an Integrated Capitals Approach (ICA) for wildfire vulnerability analysing the impacts on natural assets (ecological and economic values), damages on human capital (e.g., health), and the interactions between wildfire and social capital. Although some studies have recently introduced the effect of adaptation to fire, expressed mainly as the institutional capacity of improving fuel management and firefighting, the effect of social bonding such as training, capacity building, beliefs and volunteering actions at community scale, as a mean of reducing social vulnerability, is not yet thoroughly investigated. We think that it is necessary to extend the current wildfire risk frameworks proposed in the literature by adding social capital in its plurality of forms and by integrating them with the current analysis of natural, human, and economic capital assets as a tool to mitigate wildfires vulnerabilities.
Joint Drought-Temperature conditions as factors contributing to the occurrence of forest fires in Portugal: a NUT III clustering perspective in a monthly/seasonal time scale
Authors: Moreira Nuno , Novo Ilda , Silva Pedro , Cardoso Edna , Silva Álvaro , Ferreira João , Ramos Ricardo
Published: October 2022

The objective of the present work is to find a joint relation of drought and temperature regimes as factors contributing to the occurrence of forest fires in the period 1981-2018 in mainland Portugal. To meet this goal PDSI drought data in NUT III regions from automatic weather stations were matched with temperature regimes obtained from a 3 km downscaling using WRF model and ERA5 reanalysis as forcing data. Clustering analysis was used to aggregate seasons from June to October, according to the weather-climate conditions provided together by drought and temperature regimes. The method proposed in the present work can be used to check in which cluster every new future season fits better, thus providing a tool to, e.g, better assess the success of the implementation of forestry and forest fire management policies.
Rate of spread models in dynamic global vegetation models: A comparison of approaches
Authors: Hetzer Jessica , Forrest Matthew , Hickler Thomas
Published: October 2022

Rate of spread (ROS) is a key determinant of a fire regime and rate of spread models have a long tradition in fire research. Initially they were used to assess fire risk on a local level. Latest approaches combine them with scalable models to investigate fire risk globally. However, correctly simulating ROS across large spatial extents requires good knowledge of how fuel characteristics vary across the region of interest. For this purpose, both observed fuel characteristics and effective model representation of the characteristics are indispensable. To facilitate investigation of ROS dynamics and fuel characteristics, dynamic global vegetation models (DGVMs) can link vegetation characteristics (e.g., biomass composition, vegetation type) to fuel characteristics and simulate rate of spread over various spatial and temporal scales. Earlier studies compared rate of spread models for various sites of different biomes. Insights in site specific performance thereby supported decision-making regarding the choice of the model. Here, we address this issue for modelled forest types and biomes across Europe incorporating fire-vegetation interaction by DGVMs. We investigate two common rate of spread models: The Rothermelâ€™s Rate of Spread model (Rothermel, 1972) as well as a related modified approach proposed by Wilson (1990). Using the global dynamic vegetation model LPJ-GUESS in combination with the fire-enabling module SPITFIRE we investigate predicted values for rate of spread, burnt area, and burnt biomass on a European scale. Finally, we discuss the implementation in DGVM models as well as the differences in simulations regarding the choice of the underlying rate of spread model.
Spatial predictions of human and natural-caused wildfire likelihood across Montana (USA)
Authors: Jiménez-Ruano Adrián , Jolly W.Matt , Freeborn Patrick , Vega-Nieva Daniel José , Monjarás-Vega Norma Angélica , Briones-Herrera Carlos Iván , Rodrigues Marcos
Published: October 2022

Spatial wildfire ignition predictions are needed to ensure efficient and effective wildfire response but robust methods for modelling wildfire occurrence have not been fully evaluated. Here we leverage high resolution, static spatial data to predict the ignition locations of human and naturally-caused wildfires across the state of Montana (USA). We leveraged a 25-year historical wildfire dataset (1992-2017) and four high resolution spatial variables that capture fuel availability, topography, geographic location and human transport infrastructure. We combined these data to train spatial logistic regression Generalized Additive Models (GAM) designed for big datasets (BAM) for both human and natural ignitions and we tested the efficacy of incremental changes in model complexity. Results showed that the best human and natural-caused ignition models were highly capable of distinguishing locations with and without new wildfire occurrences statewide (AUC = 0.89 and 0.84 respectively). Natural-caused ignitions were strongly influenced by slope and location, while human-caused fires were best predicted by distance to roads as well as terrain and fuel availability. Finally, these spatial fire occurrence models can be combined with temporally-variant data to predict the spatial and temporal distribution of wildfires across the state with the view that these methods can be used to develop predictive models at larger scales.
The influence of packing ratio on forest fuel fire spread on a laboratory scale: no wind, no slope
Authors: Boutchiche Hanane , Sahila Adel , Reis Luís , Viegas Domingos Xavier , Zekri Nouredine
Published: October 2022

The influence of Pinus Pinaster needles packing ratio on fire spread at laboratory scale is investigated experimentally and compared to other wildland fuels. The packing ratio was varied from up to 10% by changing the fuel bed load and thickness. An optimum ratio of 5.5% is obtained corresponding to a maximum rate of spread. This optimum ratio is close to that found by Rothermel for crib fuels. However, the rate of spread increases again for higher porosity, which suggests the existence of a second optimum ratio. Two optimum ratios were also observed by Rothermel for excelsior fuels and recently by He et al for experiments using laser-cut cardboard. Recently, two optimum ratios corresponding to a minimum ignition time were observed using Pinus Halepensis needles. The minimum ignition time for spreading fuels correspond to a maximum rate of spread. These ratios have been attributed to a maximum heat flux absorption by the fuel. The heat flux absorption effect on the rate of spread is discussed by using the fuel optical length. The obtained optimum ratio corresponds to a small optical length (12 mm), which means that the heat flux is absorbed by the surface of the fuel bed. The second optimum ratio may correspond to an optical length much larger than the fuel bed thickness (around 50 mm). This corresponds to a bulk absorption of the heat flux. Further analyses of the mass-loss rate are provided to discuss thermochemical effects.
The loss of ecosystem multifunctionality in Pinus pinaster forests as one of the main footprints of large wildfires
Authors: Calvo Leonor , Huerta Sara , Fernández-García Víctor , Fernández-Guisuraga José Manuel , Monte Paula , Tárrega Reyes , Valbuena Luz , Taboada Ángela , Turiel Sara , Marcos Elena , Suárez-Seoane Susana
Published: October 2022

The main objective of this study was to analyse the effect of recurrence and burn severity on ecosystem multifunctionality in Pinus pinaster forests. We selected a large wildfire that occurred in the Sierra del Teleno in 2012 (NW Spain), where we differentiated two recurrences and two burn severity situations. As a result, four scenarios were identified: low recurrence plus low severity, low recurrence plus high severity, high recurrence plus low severity, high recurrence plus high severity. In each one, a number of 1 m x 1 m plots proportional to the burned area were established. Three years after the wildfire we evaluated in each plot: (1) percentage of covered soil, (2) total percentage cover of herbaceous species, (3) percentage cover of each woody species, (4) total plant species richness. Also, a composite soil sample was collected from each plot. Chemical (total organic carbon, total nitrogen and available phosphorus) and microbiological (microbial biomass carbon) properties were analysed in each soil sample. The following variables were used as indicators of ecosystem functions: percentage of covered soil, total cover of herbaceous species, Pinus pinaster cover, total plant richness, total organic carbon, total soil nitrogen, available phosphorus and microbial biomass carbon. Another indicator of ecosystem functions was calculated: floral colours of shrub species diversity using the Shannon index. The values of each ecosystem function indicator were standardized. The indicators/functions of regulating ecosystem services were: Climate regulation (indicator: total % of organic soil carbon) and Erosion protection (indicator: covered soil %). The functions/ indicators of supporting ecosystem services were: soil fertility (indicator: total nitrogen and available phosphorous) and soil quality (indicator: microbial biomass C). The indicators/functions of cultural ecosystem services were: species diversity (indicator: plant species richness) and aesthetic value (indicator: the Shannon index of floral colours). The functions/indicators of provisioning ecosystem services were: grass for livestock (indicator: % cover of herbaceous species) and timber production (indicator: % cover of Pinus pinaster). The results indicated that all scenarios apart from low recurrence plus low severity negatively affected the multifunctionality of the ecosystems.
Assessing the benefits of a national fuel break network to reduce wildfire exposure and risk in Portugal
Authors: Aparício Bruno A. , Alcasena Fermín , Ager Alan , Chung Woodam , Pereira José M. C. , Sá Ana C.L.
Published: October 2022

The impact of rural fires in the Mediterranean Basin is rapidly increasing as extreme fire seasons become the new norm. Following the catastrophic 2017 fire season in Portugal, a national-scale fuel break network (FBN) was designed by the Rural Fire Management Agency (AGIF), and the implementation of fuel treatments along the fuel break network was initiated. Despite growing interest in developing extensive fuel treatment programs to prevent catastrophic wildfires and reduce exposure and risk in the Mediterranean region, there is still little information on the effectiveness of such programs. The Portuguese nation-wide FBN is part of the fuel management plan aiming to prevent loss of lives, reduce large fires (> 500 ha) and decrease annual burned area is under implementation. In this study, we used Monte Carlo methods and mechanistic wildfire spread modeling to simulate plausible wildfire events in Portugal. The modeling system was calibrated to local fuels and weather at monthly time steps. We then examined how the proposed fuel break network was intersected by simulated fires and the effectiveness in terms of protecting residential buildings and designated protected areas. The fuel breaks burn over percentage, i.e. the percentage of fires that are not contained by the FBN was modeled as a function of pre-defined flame length thresholds for individual FBN segments. From these outputs, we were able to compare priorities as determined from the simulation system to the FBN implementation plan by AGIF. Our results show that the full implementation of FBN can provide tactical opportunities for rural fire suppression and containment. The FBN has the potential to reduce up to 1) 13% in the annual burned area due to large fires; 2) 8% in the annual number of residential buildings exposed, and 3) 14% in the annual burned area in protected areas. However, the results also reveal that in many cases the FBN intersects fires after they have grown to over 500 ha, hence representing minimal potential in preventing large fires. The expected burn-over percentage was highly variable among the segments. An overall average decrease of 40% of the total benefits was estimated, with the most important fuel breaks typically showing a high percentage of fire burn over. Our results suggest that additional landscape-scale fuel reduction strategies are required to meet short-term national wildfire management objectives.
Designing an effective risk communication plan as a tool to reduce the risk associated with traditional burning practices in Portugal
Authors: Souza Mayara Emilia Barbosa , Pacheco Abílio Pereira , Teixeira Jorge Grenha , Pereira José Miguel Cardoso
Published: October 2022

Climate change increases the average temperature and reduces precipitation, leading to an increased risk of rural fires around the world, but mainly in regions with a Mediterranean climate, such as Portugal. Despite the high risk of rural fires, fire is still a traditional land management practice. Beyond fire misused risk, the accumulation of fuel loads, due to the high population dispersion and lower interaction of communities with the land, also drives rural fires risks. Thus, researchers have sought to understand the key features of communication practices to achieve the most desired natural risk management results in relation to rural fires. According to the Committee on Risk Perception and Communication, in 1989, risk communication is defined as â€œan interactive process of exchanging information and opinions between individuals, groups, and institutionsâ€. However, there is a need for dialogue between the responsible for communication and relevant stakeholders. The Carnegie Mellon mental-models approach encompasses participatory processes to translate the nature and magnitude of the risk, allowing for a deeper understanding of what can be done to mitigate social and environmental impacts in the future. Considering rural fires risks and risk communication challenges, this study aims to design an effective risk communication plan oriented to the rural population, in the context of rural fires. For this objective to be achieved, the mental models approach was developed, exploring the underlying reasons for resistance to behavioral change and defining guidelines to support the design of new risk communication strategies, including the dissemination of new behaviors and practices that mitigate the ignition of rural fires. This systemic approach has been applied and tested in the rePLANT project, whose purpose is the development of research activities, innovation and transfer of knowledge and technology, to increase sustainable forest management, the competitiveness of the Portuguese forestry sector and reduce the impact of rural fires. Preliminary findings show what must be communicated about rural fires risk, how must be communicated, target audiences' profiles, the role of actors for effective risk communication on rural fires, attributes of good risk communication on rural fires, evaluation of the risk communication results. Finally, it is expected that this research provides guidelines to help decision-makers and stakeholders to design an effective risk communication plan oriented to prevent traditional burning practices, as well as to mitigate socioeconomic and environmental impacts in the future. This approach also highlights the importance of exploring the underlying reasons for resistance to behavioral change and defining guidelines to support the design of new risk communication strategies.
Development of a fire-smoke modelling system to integrate crown fire behaviour
Authors: Menezes Isilda Cunha , Rodrigues Luiz , Freitas Saulo , Braz Rodrigo , Freitas Mateus Ferreira e , Longo Karla , Fernandes Ana Patrícia , Lopes Diogo , Ferreira Joana , Lopes Myriam , Miranda Ana Isabel
Published: October 2022

Over the last decades, several real-time smoke prediction systems have been developed worldwide for air quality forecast to support decision making to control and manage anthropogenic pollutantions and smoke impacts. In Portugal, smoke modelling, as well as air quality forecast, has been developed by the research group GEMAC at the University of Aveiro, Portugal. However, the current forecast system does not integrate wildfire emissions. The ability from modelling to predict the behaviour of fire smoke in rural areas is an effective way to improve the efficiency of air quality and to prevent public health consequences. From 1980 to 2017, 4.4 Mha of cumulative burned area in rural fires, accounting for roughly half of Portugal's continental area, causing damage to infrastructure and lives. Hence, the forecast of smoke emissions has become of vital importance. There is a wide variety of models available to simulate fire-smoke phenomena. Nonetheless, it is necessary to consider computational aspects, resources, and goals to choose a suitable model to fit the purpose. In the ongoing FIRESMOKE project, developed by the GEMAC research group from University of Aveiro in Portugal, and GMAI from the Center for Weather Forecasting and Climate Studies in Brazil, the meteorological weather forecast model BRAMS-SFIRE is implemented to be part of the new version 5.6.2 of BRAMS. BRAMS-SFIRE model was coupled to simulate a broad integration between the surface fire fluxes and the atmospheric environment and presented a good accuracy in terms of the physics of the atmosphere and fire interaction. This project aims to improve the SFIRE model to include the crown fire behaviour. The goal is the incorporation of some formulations of the â€œcrown fire potentialâ€ by linking models of surface and crown fire behaviour from Scott and Reinhardt (2001) and injecting fire smoke into the chemistry module of BRAMS. These developments are part of a whole system for forecasting and monitoring forest fire smoke emissions that incorporates other anthropogenic and biogenic sources of air pollution, to provide a public access service of atmospheric scope, over the domain of continental Portugal.
Regeneration of quaking aspen (Populus tremuloides) after fire risk reduction treatments
Authors: Trudgeon Allison , Nesbit Kristin , Yocom Larissa , DeRose R. Justin
Published: October 2022

Quaking aspen (Populus tremuloides Michx.) is a keystone species in the western US, and typically requires high-severity disturbance (historically stand-replacing fire) to regenerate and maintain population health when coexisting with conifers. Aspen forests are declining due to fire suppression, herbivory, and drought, and restoration is a priority for many forest managers. Prescribed fire and harvest are currently the only fuel reduction treatments in practice, imposing limitations on land managers. A mechanical treatment method, called â€˜roller-felling,â€™ has been developed to mimic stand-replacing fire by reducing fuel loading and resetting succession of late-seral stage, conifer-dominated, aspen communities. We examined the ecological impact of roller-felling by investigating factors contributing to post-treatment aspen regeneration, ultimately determining the feasibility of this method as an alternative, stand-replacing disturbance treatment. Specifically, I quantified aspen regeneration stem densities to determine if the result emulated stand-replacing fire. I also measured other metrics of treatment â€œsuccessâ€, with additional factors influencing aspen regeneration, including the ratio of suckers to true seedling establishment, ungulate browsing pressure, and herbaceous understory diversity before and after treatment. Preliminary, single-growing season, results indicate densities exceed threshold-related objectives, while related ecological impacts remain less conclusive. A second year of sampling in this upcoming field season will allow for more definitive, short-term results on the comprehensive, ecological impact of roller-felling. This research could allow for widespread application in remote areas where logging is unfeasible and in Wildland Urban Interface areas, where prescribed fire can pose a risk to communities. Additionally, this will set groundwork for long-term monitoring of roller-felled areas, furthering understanding of aspen regeneration dynamics, and will apply to forest and fire management regionally, where goals are to reduce fire risk and maintain aspen communities across the western US.
A multimodal approach to understand and improve cognitive decision-making during firefighting
Authors: Dionísio Ana , Duarte Isabel Catarina , Correia Rita , Oliveira Joana , Simões Marco , Redondo João , Caldeira Salomé , Castelhano João , Castelo-Branco Miguel
Published: October 2022

Day-to-day we have to make choices. Even simple decisions involve complex cognitive processes that are still not clearly understood. When it comes to critical decisions which may lead to impactful and irreversible consequences, the understanding of the decision-making process is highly relevant. Dysfunctional coping responses may lead to stress and ultimately to trauma. In the present project, we aim to understand decision-making in the context of firefighting and to study how neurocognitive control and stress management strategies affect decision-making. We present here a functional brain imaging paradigm coupled with biosensors while firefighters play a decision-making task. In this computerized task, the firefighter faces the dilemma of entering or not in a burning house, with variable risk of house collapsing, variable number of victims in danger and variable probability of the victims saving themselves. We present here the preliminary results from a cohort of 13 firefighters, of which none presented clinically significant symptoms of post-traumatic stress disorder. We found brain regions, including the ventromedial and dorsolateral prefrontal cortices and angular gyrus, showing a parametric pattern of activation during the decision phase, i.e. the lower the risk of collapsing, the higher the neural activity in these areas. This suggests that these regions are processing that risk information and signalling the chances of being successful in the rescue phase. We also found that the power in high frequencies of the pulse rate variability of this cohort of firefighters is higher when they decide to enter for the rescue. It is suggestive that deciding not to enter for rescue causes an increase in arousal, which may be related to the expectation about the victimsâ€™ outcome (whether they survived or not). Concerning coping strategies, we found that active coping used in personal context was significantly correlated with the age and the years of experience in our sample of firefighters. We aim to understand if this pattern of brain activity reflects the coping strategies and if, in turn, it is reflected in the physiological signals we measure. Concurrently, we are recruiting firefighters with post-traumatic stress disorder and non-firefighters to perform the same task. We will investigate whether the decision processes in firefighters are different from non-firefighters, and we will address if post-traumatic stress disorder impairs decision-making in this context. Biosignals will also be used in a second phase of the project to inform training systems about the physiological state of the firefighter during virtual reality simulation. This may help developing optimal neurocognitive control and better coping strategies to deal with stress.
Analysis of thermal behaviour of merging fire fronts in crop field experiments
Authors: Filkov Alexander , Cirulis Brett , Holyland Brendan , Penman Trent
Published: October 2022

Merging fires are known as destructive fires resulting in loss of life and houses. Despite growing efforts in the past decade to understand merging fires, there are still many knowledge gaps about their behaviour, especially at the field scale. In this study, we conducted experimental harvested crop burns in Victoria, Australia, in March and April 2021 to better understand thermal behaviour of merging fire fronts. UAVs with visual and thermal cameras were used to capture high-resolution fire propagation and the combustion process of merging fires. During experiments 50 junction fire fronts (32 forward and 18 backward) and 24 coalescence fire fronts were studied. For thermal analysis, 15 forward and 4 backward junction fire fronts, 6 coalescence fire fronts, and 10 parallel fire fronts were considered. Special methods were developed to process IR footages and compare the combustion process of merging fires and linear fire fronts (head and back fires). To do this, regions of interest (ROIs) containing the merging fire and linear fire front were selected in each frame using FLIR Research Studio. The ROIs were then exported using as bitmask images together with radiometric JPEG image containing both fires. Using the R programming platform, we determined the length and shape of the perimeter of fires for each JPEG image and defined buffer zones within the fire perimeter inside the ROI for each fire for further pixel temperature analysis. Thermal analysis showed that for forward junction fires the median temperature of head linear fire fronts was higher than forward junction fires except towards the end of merging. While in backward junction fires, the proportion of pixels with high temperature was much higher than in back linear fire fronts, indicating much larger burning areas. The temperature distributions of coalescence and parallel fires showed a decrease in the number of high-temperature pixels toward the end of the merge for coalescence and throughout for parallel fires. The fire behaviour observed in the field experiments demonstrates the necessity for better understanding of merging of fire fronts and the relationship between fuel, weather and fire line interaction.
Climate adjustment of the physical parametrization for the fire-spotting
Authors: Egorova Vera N. , Pagnini Gianni
Published: October 2022

The aim of the present study is to provide a simple yet complete addition to operational fire spread models for representing the random behavior of fire-spotting in various climate classes through simple inputs related to the wildfires. Results from different test cases highlight the sensitivity of the proposed simple physical parametrization in simulating different scenarios of the generation of secondary fires by fire-spotting under different climatic conditions. Since climate change may cause extreme conditions that contribute to the high fire intensity and larger wildfires, the proposed here parametrization allows us to model the fire-spotting process in various climatic zones and to adjust the existing operational model to the climatic changes. Fire-spotting involves aspects among scales: from the combustion chemistry in microscale, to fire-atmosphere interaction in macroscale. At the meso-scale level, fire-spotting is affected by the mean wind and fireline intensity, which is found to be in a strong interaction with the surrounding factors, such as fuel and local orography. At the macroscopic level, the atmospheric stability conditions impact the fire-spotting pattern. Both, meso- and macro-scale factors are taken into consideration in the proposed probabilistic model devised to provide a physical meaning to the spread of fire by virtue of firebrands, which allows the integration of the diversity of all these parameters into a few differentiable regions. For this purpose, the classification is based on the KÃ¶ppen-Geiger climate classification, as it is done in the study of complex natural systems in a broad range of topics in hydrology, agriculture, biology, and many others. Previous studies show as well that fire-spotting is a vegetation-dependent phenomena, since not all types of vegetation can generate sufficient combustion energy or produce the firebrands. In order to represent the vegetation component of the fire-spotting generation, the biome world map is incorporated, resulting in the integrated climate-biome classification for the fire-spotting generated fires.
Experimental studies on the fire behaviour and smoke toxicity of German pine vegetation (Pinus sylvestris)
Authors: Heydick Lukas , Piechnik Kira , Köhler Florian , Klippel Andrea
Published: October 2022

The mechanisms of fire and smoke spread in forest and vegetation fires have not been fully investigated. Most numerical models often only consider the topography of the area and climatic influences such as wind and temperature. There is a need to understand the fire behaviour of specific vegetation in order to predict how the fire and smoke will spread during a fire incident. Understanding the mechanisms and behaviour of fire is therefore important for both, preventing and fighting fires. The European research project TREEADS and the associated German pilot project 'Fire research in forest fires and derivation of safety measures' deal with these problems. Therefore, several measurement campaigns were carried out to study safety-relevant parameters, fire behaviour, fire spread and spontaneous combustion processes of specific German vegetation and soil samples. The research objectives of the studies focused on the characterisation of fire development and spread as well as smoke composition.
* At the time of acceptance and publishing of this work the project name was DRYADS but it has since been changed to TREEADS for legal reasons.
Firefighting: Challenges of Smart PPE
Authors: Santos Gilda , Marques Rita , Ribeiro J. , Moreira A. , Fernandes P. , Silva Margarida , Fonseca André , Miranda João M. , Campos João B. L. M. , Neves Soraia F.
Published: October 2022

In this study our goal is to understand how leadership behavior affects the well-being of firefighter teams operating under conditions of a simulated rural fire. A virtual reality scenario was developed to replicate a large rural fire. We studied 20 firefighter teams, involved in this scenario, with different leader behaviors, to identify the momentary responses of the team, understand the factors that underlie these responses, and test the moderating role of leader behavior. Our results show that directive leadership style is associated with reduced levels of stress and anxiety in team members and empowering leadership style did not have a significant effect on their levels of stress and anxiety. Although teams with directive leaders started performing well more quickly, their performance plateaued, whereas the emergent cognition and improved learning and coordination capabilities of empowered teams allowed them to improve over time. For teams with short-term or emergent engagements and teams facing emergency situations, such as firefighter teams, a directive style may be most appropriate, as teams must be able to immediately perform at a high level and cannot afford the performance delays learning errors associated with empowered teams. In emergency situations, such as rural fires, studies are scarce and it is not possible to conclude the advantages of these empowering styles.
Evaluating sensitivity to input fuel resolution in popular fire behavior models
Authors: Selvaraj Muthu Kumaran , Carroll Lydia , Sawtelle Sonya , Sprague Jacob , Simeoni Albert
Published: October 2022

Fire behavior models ingest a variety of inputs such as weather, topography, and fuel maps to generate predictions of how a fire will behave. Model prediction accuracy is thus to some degree dependent on the fidelity of the input data sources. For many widely used fire models, however, the exact relationship between fuel input quality and model performance is not well understood. This paper seeks to quantify the relationship between input fuel data and output prediction accuracy in popular fire models based on the Rothermel fire spread equation. In particular, it examines how granularity of fuel classes, spatial resolution, and temporal resolution affect the accuracy of fire behavior predictions. Fuel maps used in the study are generated from remote sensing images using machine learning to map between satellite and ground conditions. Prediction accuracy is evaluated with multiple metrics including rate of spread (ROS) and fire front shape. The outcomes of this study will provide important guidance as to the benefit of producing high fidelity fuel maps when utilizing the Rothermel spread equation to predict fire behavior.
Modeling wind adjustment factor in Mediterranean stands of Southern Europe
Authors: Molina Juan Ramón , Ortega Macarena , Navarro Juan Antonio , Silva Francisco Rodríguez y
Published: October 2022

Wind speed; drag coeffcient; midflame wind; fire behavior; forest characterization
Physical modelling of fires spreading upslope, involved in fire eruption triggering
Authors: Chatelon François Joseph , Balbi Jacques-Henri , Fayad Jacky , Rossi Jean-Louis , Morvan Dominique , Marcelli Thierry , Frangieh Nicolas , Awad Carmen , Accary Gilbert , Meradji Sofiane
Published: October 2022

Eruptive fires are one category of extreme fire behaviour. They are characterized by a sudden and unpredictable change in the fire behaviour which represents an extreme danger for people involved in firefighting. The major point is about the mechanism that turns a usual fire behaviour into an eruptive fire behaviour. Among the different explanations found in the literature, the pioneering interpretation consisting in a feedback effect caused by the convective flow induced by the fire under wind and/or slope conditions, has never been disproved with an example of fire accident. The main goal of this work lies in proposing a physical modelling of this fire induced wind. This modelling attempt is derived from the brand-new version of the Balbi model, which is a simplified physical model for surface fires at the field scale that explicitly depends on the triangle of fire (fuel bed, wind and slope). This work is a first step to the modelling of fire eruption. The model tries to represent accurately the acceleration of the fire rate of spread propagating on different sloped terrain under no-wind or weak wind conditions. It is tested against three sets of experiments carried out at the laboratory scale without external wind and against a high intensity experimental fire spreading on a steep sloped terrain and conducted under weak wind conditions in the north-western of Corsica. Some statistical tools are used to compare predicted and observed rate of spread (NMSE, Normalized Mean Square Error and MAPE, Mean Absolute Percentage Error) and to understand the modelâ€™s under-predictions or over-predictions trends (FB, Fractional Bias).
The economic benefits of planning before the fire
Authors: Bayham Jude , Lee Marissa
Published: October 2022

Wildfire suppression expenditures in the United States regularly exceed a billion dollars and are expected to continue rising due to climate change, high fuel loads, and a growing wildland urban interface. Risk management research suggests that pre-fire planning reduces uncertainty and may lead to better wildfire management outcomes including lower suppression costs, less damage to values at risk and improve safety outcomes. One form of pre-fire planning in US National Forests is known as potential operating delineations (PODs) whereby stakeholders collaboratively identify area on the landscape where wildfire can be safely and effectively engaged. Moreover, the area defined by the PODs are classified based on the level of urgency to suppress fire. The objective of this paper is to test whether fires that have occurred within areas that have undergone the POD process are systematically different from fires that have not undergone PODs. We evaluate the following wildfire outcomes: final fire cost, final fire size, cost per acre, and duration. We employ statistical matching methods to find comparable non-POD fires that serve as â€œcontrolâ€ units for our POD â€œtreatedâ€ fires. Our results suggest that POD fires cost $373 per acre less than non-POD fires, and that the POD fires cost per acre is comparable to prescribed burning cost per acre in the Southwestern US. These results imply that pre-fire planning like the POD process may reduce suppression costs to a level comparable with prescribed burning facilitating the long-standing recommendation from fire ecologists to â€œrestore fire to the landscape.â€
Identifying the most influential parameters in experimental grass fire spread modeling using global sensitivity analysis
Authors: Roubelat Flore C. , Costes Aurélien , Antolin William P. , Rochoux Mélanie C.
Published: October 2022

Coupled atmosphere/fire models are recognized as an efficient and representative way to simulate wildland fire behavior at geographical-to-meteorological scales by representing the two-way interactions between the fire front propagation and the surrounding atmosphere. They rely on a rate-of-spread (ROS) parameterization to represent the fire front propagation speed with respect to environmental factors characterizing biomass fuel properties and moisture content, near-surface wind conditions and terrain slope. In actual wildfire events, these input parameters are only partially known and induce significant uncertainties in the coupled model predictions. To estimate the envelope of plausible wildland fire behavior for a given event, we aim at designing a perturbed-physics ensemble prediction capability based on a coupled atmosphere/fire model. To make the approach feasible, it is essential to identify the relevant subset of parameters to perturb to generate an ensemble of fire front positions and shapes. In the present study, we perform a global sensitivity analysis based on Sobolâ€™ indices to rank the environmental factors by order of influence on the Balbiâ€™s ROS parameterization, and thereby identify the parameters that contribute most to the variability of ROS. Results show the predominance of the near-surface wind speed on the ROS variability, followed by the leaf area index LAI, the ignition temperature T_i, the dead fuel moisture content M_d, the dead fuel particle mass density
ho_d, and the fuel layer height e. Results also indicate that the sensitivity of each fuel parameter to the ROS is not constant with respect to the near-surface wind speed, and that the most influential input parameters differ between the head and the back of a fire. This indicates the importance of exploring the spatial and temporal dependencies of coupled model sensitivities in future work.
Increasing the resilience of transmission power lines to extreme events
Authors: Ribeiro Luís Mário , Almeida Miguel , Viegas Domingos Xavier , Marques Pedro , Gaspar João , Rodrigues Tiago
Published: October 2022

Powerlines are a critical asset that is often associated to wildfire ignitions but is also regularly affected by their propagation. Fuel management near these structures has specific rules, at least in Portugal, with the objective of protecting the infrastructure itself and minimizing the risk of ignition due to an electrical discharge or the physical contact of the vegetation with the conductors. The extent of the powerline network may hinder the application of extensive fuel management actions, and in many cases the vegetation that falls outside the fuel management network may also pose a danger. This work explores the possibility of combining LiDAR with ancillary data and specific algorithms to identify those trees that may put the powerline in danger in case they fall due to any external or internal circumstances. As a result of the application of the proposed methodology, it was possible to classify individual trees according to a risk class, as well as critical areas of intervention. With this information the Portuguese company REN, responsible for the Very High-Tension power network, was able to plan and calendarize critical fuel management interventions in vegetation that fell outside the mandatory fuel breaks that they manage, but that posed imminent risk to the infrastructure.
Leveraging a wildfire risk prediction metric with spatial clustering
Authors: KC Ujjwal , Aryal Jagannath
Published: October 2022

Fire authorities have started widely using operational fire simulations for effective wildfire management. These fire simulation outputs, when aggregated on a massive scale, create an opportunity to apply the evolving data-driven approach to closely estimate wildfire risks even without running computationally expensive simulations. We explored this opportunity in one of our previous works where we proposed a probability-based risk metric that gives a series of probability values for a fire starting at a start location under a given weather condition, to fall into different risk categories. The metric considered each fire start location as a unique entity, which could face scalability issues when the metric is used for a larger geographic area and make the metric hugely compute-intensive. In this work, we investigate if the spatial clustering of fire start locations based on historical fire areas can address the issue without significantly compromising the accuracy of the metric. Additionally, as spatial clusters are significantly fewer than fire start locations in a geographic area, spatial clustering can further reduce the overall computational requirements of the metric with a rational compromise of accuracy.
Optimization with fire spread simulation for forest management
Authors: Alvelos Filipe , Martins Isabel , Marques Susete , Dias Mariana , Cunha Eduardo , Neto David
Published: October 2022

We propose a method for forest management in which wildfire is modeled explicitly through the integration of optimisation and simulation. Given a forest, the decision problem is to select a plan (i.e. a prescription and a periodicity for brush cleaning) for each of its stands. Each plan is associated with values for a set of criteria for each period of the temporal horizon. Considered criteria are net present value, biodiversity, carbon stock, and erosion. The problem is modelled by a mixed integer programming (MIP) with the objective of maximizing the net present value and imposing limits for the remaining criteria. A fire spread simulator, based on shortest path algorithms following the minimum travel time principle, is responsible to identify sets of plans that are not acceptable together as they result in a high rate of fire spread. That information is included in the MIP as constraints. This cycle optimization-simulation is repeated until the plans provided by the MIP are acceptable in all scenarios. Data from a real landscape case-study has been collected and processed to obtain management and fire parameters required to validate the proposed method, which is being implemented in Python (with Gurobi as a MIP solver, GeoPandas for managing and processing geospatial data, and NetworkX implementation of graph algorithms).