Background The ‘Balbi model’ is a simplified physical model for surface fires which provides the main physical characteristics of a fire front and its rate of spread (ROS) as a function of general environmental conditions. In the first part of this work, we describe a simplification of this model, which we call Balbi operational model, that leads to a set of explicit algebraic equations. Aims After calibrating the model, we aim to assess its performance by comparing the predicted ROS with laboratory- and field-measured ROS. Methods A small set (n = 40) of laboratory fires was used to find the required model parameters. We evaluated the model against (1) a set of laboratory experimental fires (n = 549), representing a range of fuel bed types and arrangements, and (2) a set of shrubland and grassland field fires (n = 357) from different world regions. We assessed the predictive capacity of the model and compared it with other empirical and semi-empirical models. An analysis on the importance of each heat transfer mechanism is performed. Key results The proposed model performs as well as its previous iteration on shrubland fires and is found to increase accuracy when tested against grassland fires. Conclusions The operational ‘Balbi model’ shares many properties with empirical models, while grounded on physical heat transfer principles. The model is suitable for application to several types of fuels and configurations of slope and wind. Implications Its intrinsic characteristics and verified fit make it a candidate to be used in wildfire propagation simulators.

This study presents the Moisture Dynamic Model (MDM), a new semi-physical formulation designed to estimate Fuel Moisture Content (FMC) using only air temperature and relative humidity. The core innovation of this work lies in the introduction of an Arrhenius-type kinetic term into a fuel moisture prediction framework, allowing temperature-driven desorption processes to be explicitly represented within a lightweight operational model. Its predictive capability was assessed through experimental campaigns on Cistus monspeliensis shrublands in Corsica and validated using FireStar3D simulations. A second major contribution is the coupling of the MDM with the physical wildfire simulator FireStar3D to quantify how FMC prediction errors propagate into fire spread predictions. The MDM accurately reproduced the seasonal variability of FMC, achieving strong correlation with experimental data during dry summer periods. When coupled with FireStar3D, discrepancies in the predicted rate of spread remained below 4% under high-risk meteorological conditions. While the model performed robustly during summer, its accuracy decreased during spring, when rainfall events and microclimatic variability introduced greater uncertainty. This work represents a proof of concept demonstrating the potential of a simple physically interpretable FMC model for operational fire behaviour prediction.

Background Previously published versions of the ‘Balbi model’ describing surface fire propagation consist of a set of equations based on simplified conservation laws. Their main equation calculating the fire rate of spread (ROS) relied on an iterative process to account for the effect of environmental drivers. Aims We formulated a new version of this model that considers a 3D flame front composed of peaks and troughs, integrates distinct radiation and convection heat transfer mechanisms, and outputs the physical characteristics of a flame front as they are influenced by weather, fuel and topographical conditions. A simpler operational version, composed of only one equation, is also exhibited. Methods While maintaining its characteristics (physics-oriented, fully predictive and faster than real time) from older versions, the global structure of the proposed model is changed to obtain a set of algebraic equations easy to solve and to code. Key results We described the model and provided an analysis of model response to key environmental variables. Model evaluation against independent data is provided in a companion paper. Conclusions A simplified physical propagation model for surface fires has been exhibited. Implications The algebraic nature of the model’s equations makes it suitable to incorporate into fire management decision-making tools to support suppression activities.

This study investigates the effectiveness of immersive audiovisual simulations in eliciting emotional responses and replicating the psychological and cognitive demands of high-risk operational environments, particularly in firefighting scenarios. Conducted in two successive phases, the research first employed a pilot study involving 90 participants (45 firefighters and 45 students) who were exposed to a controlled audiovisual simulation. Emotional responses were assessed using the Differential Emotion Scale (DES), the Emotion Regulation Questionnaire (ERQ), and the Perceived Stress Scale (PSS). The second phase involved an immersive room experiment with 36 firefighters, where the same audiovisual stimulus was presented in a fully immersive environment, integrating interactive decision-making tasks to enhance ecological validity. The findings indicate that both methods effectively elicited the targeted emotional responses, including stress, fear, anger, and serenity, with firefighters exhibiting greater emotional regulation and adaptive coping strategies compared to students. The immersive room environment significantly amplified emotional engagement, resulting in stronger emotional responses from the first scene onward. These results underscore the potential of immersive training tools in preparing emergency responders for high-stress situations by strengthening psychological resilience, improving emotional regulation, and optimizing decision-making under pressure. The study contributes to advancing evidence-based training methodologies in emergency response, public safety, and crisis management, emphasizing the importance of integrating immersive technologies into professional training programs.

This paper presents a research program called CP2DIMG conducted at the Federation of Environment and Society Research at the University of Corsica. The goal of CP2DIMG is to better understand the influence of emotions on operational personnel’s decision-making, aiming to test training systems dedicated to individuals facing high stress during their professional activities. This type of training system is intended to enhance emotional and mental resilience, thereby improving decision-making ability in uncertain situations under the influence of emotions related to the event. For implementation, the method will be tailored to the specificities of two categories of operational personnel: firefighters and municipal police officers. The expected results will address significant demands from operational professionals in the Mediterranean region for firefighting safety but also for large-scale or highly complex interventions. This study fully integrates into the challenges of the Mediterranean region: forest management, risk prevention plans, and preparedness of local actors responsible for crisis management. Furthermore, individuals responsible for crisis management, including local government officials and risk management and security personnel, will be able to use the obtained results for effective decision-making.

This paper reports two experimental fires conducted at field-scale in Corsica, across a particular mountain shrubland. The orientation of the experimental plots was chosen in such a way that the wind was aligned along the main slope direction in order to obtain a high intensity fire. The first objective was to study the high intensity fire behavior by evaluating the propagation conditions related to its speed and intensity, as well as the geometry of the fire front and its impact on different targets. Therefore, an experimental protocol was designed to determine the properties of the fire spread using UAV cameras and its impact using heat flux gauges. Another objective was to study these experiments numerically using a fully physical fire model, namely FireStar3D. Numerical results concerning the fire dynamics, particularly the ROS, were also compared to other predictions of the FireStar2D model. The comparison with experimental measurements showed the robustness of the 3D approach with a maximum difference of 5.2% for the head fire ROS. The fire intensities obtained revealed that these experiments are representative of high intensity fires, which are very difficult to control in the case of real wildfires. Other parameters investigated numerically (flame geometry and heat fluxes) were also in fairly good agreement with the experimental measurements and confirm the capacity of FireStar3D to predict surface fires of high intensity.

A safe separation distance (SSD) needs to be considered during firefighting activities (fire suppression or people evacuation) against wildfires. The SSD is of critical interest for both humans and assets located in the wildland–urban interfaces (WUI). In most cases, the safety zone models and guidelines assume a flat terrain and only radiant heating. Nevertheless, injuries or damage do not result exclusively from radiant heating. Indeed, convection must be also considered as a significant contribution of heat transfer, particularly in the presence of the combined effects of sloping terrain and a high wind velocity. In this work, a critical case study is considered for the village of Sari-Solenzara in Corsica (France). This site location was selected by the operational staff since high-intensity fire spread is likely to occur in the WUI during wind-blown conditions. This study was carried out for 4 m high shrubland, a sloping terrain of 12° and a wind speed of 16.6 m/s. The numerical simulations were performed using a fully physical fire model, namely, FireStar2D, to investigate a case of fire spreading, which is thought to be representative of most high wildfire risk situations in Corsica. This study is based on the evaluation of the total (radiative and convective) heat flux received by two types of targets (human bodies and buildings) located ahead of the fire front. The results obtained revealed that the radiation was the dominant heat transfer mode in the evaluation of the SSD. In addition, the predictions were consistent with the criterion established by the operational experts, which assumes that in Corsica, a minimum SSD of 50 m is required to keep an equipped firefighter without injury in a fuelbreak named ZAL. This numerical work also provides correlations relating the total heat flux to the SSD.

This paper reported a high intensity experimental fire conducted during a field-scale experiment on a steep sloped terrain (28) as part of a winter prescribed burns campaign managed by the local firefighter service in the north-western region of Corsica. The rate of spread (ROS) of fire, measured using UAV cameras (thermal and visible), was evaluated at 0.45 m/s. The experiment was numerically reproduced using a completely physical 2D model, namely FireStar2D, and the comparison with the experimental measurements mainly concerned the fire ROS and the heat fluxes received by three distant targets placed at the end of the plot. The results analysis shows that the considered fire has a wind-driven regime of propagation with a fire intensity higher than 7 MW/m. The numerical results are in fairly good agreement with the experimental measurements, within 11% difference for the ROS and 5% for the heat fluxes, validating consequently the relevance of the numerical approach to tackle such high-intensity wildfires. Despite the unfavorable wind and humidity conditions for fire propagation (U = 1.67 m/s and RH = 82%), this experiment confirms that such fire can exhibit a dangerous behavior due to the steep slope of the terrain.

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 model’s under-predictions or over-predictions trends (FB, Fractional Bias).

Field-scale experiments have been conducted on steep sloped terrains in Speluncatu and Letia, north-western and southern regions of Corsica. This work lies within the GOLIAT project framework and it was provided by the Fire and Rescue Service of North Corsica and the Corsican DFCI (Défense de la Forêt Contre l’Incendie) Group. This work reported high intensity fires propagating through shrub vegetation areas (Genista Salzmannii) lying between 60 cm and 85 cm. These sites were selected because of the density of the vegetation, the high slope angle values with a wind direction aligned with the main slope, which can generate a fire close to wildfire behaviour. A detailed experimental protocol is used in order to determine the propagation conditions and the fire behaviour using UAV cameras and heat flux gauges. In order to investigate the different phenomena encountered in these types of fires, numerical simulations were conducted using a complete physical fire model, based on multiphase formulation, namely FireStar2D. Numerical predictions were used to examine the fire front dynamics related to the fire’s rate of spread and fireline intensity. Despite the unfavourable wind and humidity conditions, experimental results analysis showed that the fireline intensity was higher than 7 MW/m, which means that these fires fall into the category of the very high fire severity. Numerical results predicting the fire’s rate of spread, fireline intensity and fire impact were in good agreement with the experimental data.

The ‘Balbi model’ is a simplified rate of fire spread model aimed at providing computationally fast and accurate simulations of fire propagation that can be used by fire managers under operational conditions. This model describes the steady-state spread rate of surface fires by accounting for both radiation and convection heat transfer processes. In the present work the original Balbi model developed for laboratory conditions is improved by addressing specificities of outdoor fires, such as fuel complexes with a mix of live and dead materials, a larger scale and an open environment. The model is calibrated against a small training dataset (n = 25) of shrubland fires conducted in Turkey. A sensitivity analysis of model output is presented and its predictive capacity against a larger independent dataset of experimental fires in shrubland fuels from different regions of the world (Europe, Australia, New Zealand and South Africa) is tested. A comparison with older versions of the model and a generic empirical model is also conducted with encouraging results. The improved model remains physics-based, faster than real time and fully predictive.

The GOLIAT project is a consortium of academics and firefighting operators and land-use planning professionals of Corsica. One goal of GOLIAT project is to provide four operational decision support tools. To reach this goal, a survey of past fires occurred in Corsica since the twentieth century beginning is made. This inventory contributes to build up a database with a web display interface easy to use as fire patterns history. A fire behavior and impact simulator prototype for vegetation fires, a geolocation tool for hot spots using UAV images, and a guide of good practices of prescribed fires in the undergrowth are building. At the same time, experimental fires are carried out to improve knowledge about high intensity fire and the experimental results were compared to the predictions provided by a complete physical 3D model, namely FireStar3D.

Nowadays, the needs for decision making tools useful for people involved in firefighting and/or in landscape management becomes more and more crucial, especially with the dramatic increase of the fire dangerousness and fire severity. These tools have to be accurate enough and faster than real time. Up to now, simulators and other tools are mainly based on empirical or semi-empirical models but the lack of physics in their formulation is a major flaw. The Balbi model is a simplified physical propagation model for surface fires which explicitly depends on the topography, the wind velocity and several fuel characteristics. It is a set of algebraic equations built from usual physical conservation laws (mass, momentum etc.) with some strong assumptions. This work aims at providing a new version of the Balbi model in which the resolution of the rate of spread (ROS) does not need any iterative method any more. This simplification is helpful in implementing the equations set into a fire propagation simulator or a coupled fire-atmosphere simulator. It needs a complete change in the structure of the model and the predicted ROS was tested at the field scale against 179 shrubland fires (burnt in Australia, South Africa, Turkey, Portugal, Spain, New Zealand) and 178 Australian grassland fires with a very good agreement with the observed ROS. Two statistical tools are used to check this agreement (Normalized Mean Square Error, NMSE and Mean Absolute Percentage Error, MAPE) and the Fractional Bias (FB) aims at understanding when the model over-predicts or under-predicts the ROS. The proposed model is accurate and its model parameters are calibrated against a small training dataset which makes it fully predictive whatever the environmental and topographic conditions and the fuel bed characteristics. Its more simple structure allows it to be a good candidate for the heart of a simulation or land management decision making tool.

The safety during prescribed burnings could be achieved by conducting these operations under marginal conditions of fire propagation. This type of fire can or cannot propagate on account of small deviations of the burning conditions, mainly the wind speed, the fuel load, and the fuel moisture-content. In this context, numerical simulations of grassland fires were conducted under marginal conditions in order to relate the moisture-content threshold of propagation success to the wind speed and the fuel load. The simulations were conducted using FireStar2D, a complete physical 2D fire simulator based on a multiphase modelling approach. The 10 m-open wind speed ranged from 0 to 10 m/s and the fuel load varied from 0.1 kg/m2 to 0.7 kg/m2. The effects of wind speed and fuel moisture-content on the fire behaviour and on the flame parameters are discussed. The results show that the moisture threshold increases with the fuel load until it reaches a value beyond which there is no dependence. A similar dependence of the moisture threshold on the wind speed is also observed. Finally, empirical formulae were constructed to relate the fuel moisture content threshold to the wind speed and the fuel loading implicitly through Byram's convective number.