A Systematic Review and Bibliometric Analysis of Wildland Fire Behavior Modeling

Abstract

Wildland fires have become a major research subject among the national and international research community. Different simulation models have been developed to prevent this phenomenon. Nevertheless, fire propagation models are, until now, challenging due to the complexity of physics and chemistry, high computational requirements to solve physical models, and the difficulty defining the input parameters. Nevertheless, researchers have made immense progress in understanding wildland fire spread. This work reviews the state-of-the-art and lessons learned from the relevant literature to drive further advancement and provide the scientific community with a comprehensive summary of the main developments. The major findings or general research-based trends were related to the advancement of technology and computational resources, as well as advances in the physical interpretation of the acceleration of wildfires. Although wildfires result from the interaction between fundamental processes that govern the combustion at the solid- and gas-phase, the subsequent heat transfer and ignition of adjacent fuels are still not fully resolved at a large scale. However, there are some research gaps and emerging trends within this issue that should be given more attention in future investigations. Hence, in view of further improvements in wildfire modeling, increases in computational resources will allow upscaling of physical models, and technological advancements are being developed to provide near real-time predictive fire behavior modeling. Thus, the development of two-way coupled models with weather prediction and fire propagation models is the main direction of future work.

2D Simplified Wildfire Spreading Model in Python: From NumPy to CuPy

“…Regarding empirical models we can mention FARSITE [15] or ELMFire [16], but as well as coupled models, they are outside the scope of this article. For more details of forest fire models see [7] or [17].…”

“…This section aims to represent (17) as an Initial Value Problem (IVP) and solve it numerically. Rewriting (17) as…”

Probabilistic Wildfire Risk Assessment and Modernization Transitions: The Case of Greece

“…Remarkable progress is achieved regarding fire research's physical and biological fundamentals, especially the modeling pillar, which derives most explanations and predictions from fire as a systemic phenomenon [24]. The gradual emergence of the cultural paradigm in wildfire science indicates the conceptual striving for fire to be considered as an organizing device for human occupation of the planet [11].…”