The Integration of CFD and Cutting-edge Multivariate Modeling in Future Forest Fire Research

Forest fires, as highly destructive natural disasters, are showing a trend of higher frequency and greater intensity against the backdrop of global climate change. This has put forward an unprecedented and urgent demand for the accuracy and timeliness of fire spread prediction models to support effective disaster prevention and mitigation decisions. To predict and research forest fires effectively, researchers have applied many methods and techniques to simulate forest fire models to find out some discipline that can swiftly turn into reality. The review aims to propose four main techniques used in forest fire simulation: computational fluid dynamics (CFD), cellular automata (CA), semi-empirical models with data assimilation and artificial intelligence-based techniques. Discuss and compare their advantages and disadvantages. Then gives out future prospective applications of hybrid modeling in fire simulation research and potential challenges that cannot be ignored.