Evaluating crown fire rate of spread predictions from physics-based models

C. M. Hoffman (1) , J. Ziegler (1) , J. Canfield (2) , R. R. Linn (2) , W. Mell (3) , C. H. Sieg (4) , François Pimont (5)

1 CSU - Colorado State University [Fort Collins]
2 LANL - Los Alamos National Laboratory
3 Forest Service Pacific Wildland Fire Sciences Laboratory
4 USDA Forest Service Rocky Mountain Forest and Range Experiment Station
5 URFM - Unité de Recherches Forestières Méditerranéennes

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate fire behavior using computational fluid dynamics based methods to numerically solve the three-dimensional, time dependent, model equations that govern, to some approximation, the component physical processes and their interactions that drive fire behavior. Both of these models have had limited evaluation and have not been assessed for predicting crown fire behavior. In this paper, we utilized a published set of field-scale measured crown fire rate of spread (ROS) data to provide a coarse assessment of crown fire ROS predictions from previously published studies that have utilized WFDS or FIRETEC. Overall, 86% of all simulated ROS values using WFDS or FIRETEC fell within the 95% prediction interval of the empirical data, which was above the goal of 75% for dynamic ecological modeling. However, scarcity of available empirical data is a bottleneck for further assessment of model performance

Mots clés: Physics-based model; Fire behavior; HIGRAD/FIRETEC; Wildland Urban; Interface Fire Dynamics Simulator

Domaines: Biodiversité et Ecologie

C. M. Hoffman, J. Ziegler, J. Canfield, R. R. Linn, W. Mell, et al.. Evaluating crown fire rate of spread predictions from physics-based models. Fire Technology, 2016, 52 (1), pp.221-237. ⟨10.1007/s10694-015-0500-3⟩. ⟨hal-01283080⟩