Validating the effect of fuel moisture content by a multivalued operator in a simplified physical fire spread model. (June 2023)

• Record Type: Journal Article
• Authors: Asensio, M.I.; Cascón, J.M.; Laiz, P.; Prieto-Herráez, D.
• Is Part Of: Environmental modelling & software. Volume 164(2023)
• Publication Date: 2023-06
• Subjects: Fuel moisture content -- Rate of spread -- Multivalued operator -- Wildfire spread simulation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2023.105710
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Fuel moisture content (FMC) plays a significant role in wildfire behavior and rate of spread (ROS). In addition, FMC is a highly dynamic factor and very vulnerable to climate variations. Understanding the effect of FMC on the behavior of fire spread models is crucial, and detailed analysis of specific aspects of complex models is a very effective way to improve them. The simplified physical fire spread model PhyFire considers the effect of FMC in a novel way, involving a multivalued maximal monotone operator. Several numerical experiments have been carried out to confirm that the behavior of the ROS simulated with PhyFire involving FMC is as expected in the reviewed literature: an exponential decrease in fire ROS compared to FMC, for different scenarios, considering different fuel types, terrain slopes and wind speeds. PhyFire performs very accurately, proving that the multivalued operator used is suitable and consistent. Highlights: Fuel moisture content plays a significant role in wildfire behavior and its rate of spread, and it is one of the primary variables in many fire behavior prediction models. PhyFire is a simplified two-dimensional one-phase physical fire spread model based on energy and mass conservation equations that models fuel moisture content through a multivalued operator. The PhyFire model has been confirmed to be highly consistent with an exponential decay of fire ROS compared to FMC alone, and also in the presence of wind speed and terrain slope.