Special Issue "Wildfires Modeling: Recent Trends, Current Progress and Future Directions"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 1 June 2023 | Viewed by 2187

Special Issue Editors

IMATH Laboratory, EA 2134, Toulon University, 83160 Toulon, France
Interests: wildfire modeling; theoretical turbulence; computational fluid dynamics; high-performance computing; data assimilation; deep learning
Special Issues, Collections and Topics in MDPI journals
School of Engineering and Information Technology, University of New South Wales Canberra, Canberra, ACT 2610, Australia
Interests: CFD; thermodynamic analysis; waste to energy; thermofluids; environmental sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few decades, considerable efforts have been focused on developing and implementing relatively relevant statistical and physics-based models to account for the interactions between fire, vegetation, and the atmosphere. These models have led to a better understanding of the dynamics of fire spread in a landscape and are continuing to contribute to the state of art of wildfire science. However, despite considerable progress in modeling fire behavior, fire can still create unexpected scenarios for emergency services during real situations and result in significant injury, even fatalities, in addition to the numerous socioeconomic and the irreversible ecological impacts.

This Special Issue offers an opportunity for those involved in wildfire modeling to present their work in a dedicated volume. We therefore invite you to contribute articles to this Special Issue that highlight advances, new concepts, technical issues, and innovative research directions associated with wildfire modelling frameworks. Recently, using data assimilation and deep learning techniques to better predict wildfire behavior has aroused considerable interest. These emerging approaches coupled to standard models seem very promising. Contributions based on these different approaches and their coupling are highly appreciated. Any work on wildfire modeling that can provide new insights is welcome.

It is our hope that this Special Issue, dedicated to the latest developments in wildfire modelling, will help to promote discussion of numerous modeling issues and highlight synergies and connections across the various modeling platforms.

Dr. Sofiane Meradji
Dr. Maryam Ghodrat
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wildfire science
  • wildland fire
  • fire physics
  • heat and mass transfers
  • turbulent flows
  • combustion
  • computational fluid dynamics
  • artificial neural network
  • deep learning
  • data assimilation

Published Papers (3 papers)

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Research

Article
Applying Bayesian Models to Reduce Computational Requirements of Wildfire Sensitivity Analyses
Atmosphere 2023, 14(3), 559; https://doi.org/10.3390/atmos14030559 - 15 Mar 2023
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Abstract
Scenario analysis and improved decision-making for wildfires often require a large number of simulations to be run on state-of-the-art modeling systems, which can be both computationally expensive and time-consuming. In this paper, we propose using a Bayesian model for estimating the impacts of [...] Read more.
Scenario analysis and improved decision-making for wildfires often require a large number of simulations to be run on state-of-the-art modeling systems, which can be both computationally expensive and time-consuming. In this paper, we propose using a Bayesian model for estimating the impacts of wildfires using observations and prior expert information. This approach allows us to benefit from rich datasets of observations and expert knowledge on fire impacts to investigate the influence of different priors to determine the best model. Additionally, we use the values predicted by the model to assess the sensitivity of each input factor, which can help identify conditions contributing to dangerous wildfires and enable fire scenario analysis in a timely manner. Our results demonstrate that using a Bayesian model can significantly reduce the resources and time required by current wildfire modeling systems by up to a factor of two while still providing a close approximation to true results. Full article
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Article
A Study of Two High Intensity Fires across Corsican Shrubland
Atmosphere 2023, 14(3), 473; https://doi.org/10.3390/atmos14030473 - 27 Feb 2023
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Abstract
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 [...] Read more.
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. Full article
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Article
Crown Fire Modeling and Its Effect on Atmospheric Characteristics
Atmosphere 2022, 13(12), 1982; https://doi.org/10.3390/atmos13121982 - 27 Nov 2022
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Abstract
The article is concerned with the experimental study of the crown fire effect on atmospheric transport processes: the formation of induced turbulence in the vicinity of the fire source and the transport of aerosol combustion products in the atmosphere surface layer at low [...] Read more.
The article is concerned with the experimental study of the crown fire effect on atmospheric transport processes: the formation of induced turbulence in the vicinity of the fire source and the transport of aerosol combustion products in the atmosphere surface layer at low altitudes. The studies were carried out in seminatural conditions on the reconstructed forest canopy. It was established that the structural characteristics of fluctuations of some atmosphere physical parameters in the case of a crown fire practically coincide with the obtained earlier values for a steppe fire. The highest concentration of aerosol combustion products was recorded at a height of 10–20 m from the ground surface. It was found that the largest number of aerosol particles formed during a crown fire had a particle diameter of 0.3 to 0.5 µm. As a result of experimental data extrapolation, it is concluded that an excess of aerosol concentration over the background value will be recorded at a distance of up to 2000 m for a given volume of burnt vegetation. It is of interest to further study these factors of the impact of wildfires on atmosphere under the conditions of a real large natural wildfire and determine the limiting distance of aerosol concentration excesses over background values. Full article
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