Learn More
Keywords: Crown fire Fire dynamics Model development Model performance Physics-based models Rate of fire spread a b s t r a c t Evaluation is a crucial component for model credibility and acceptance by researchers and resource managers. The nature and characteristics of free-burning wildland fires pose challenges to acquiring the kind of quality data(More)
multiple use management of the Nation's forest resources for sustained yields of wood, water, forage, wildlife, and recreation. Through forestry research, cooperation with the States and private forest owners, and management of the national forests and national grasslands, it strives—as directed by Congress—to provide increasingly greater service to a(More)
A mathematical model is presented for predicting the maximum potential spot fire distance from an active crown fire. This distance can be estimated from the height of the flame above the canopy top, wind speed at canopy-top height and final firebrand size (i.e. its residual size on alighting), represented by the diameter of a cylinder of woody char. The(More)
—Model evaluation should be a component of the model development process , leading to a better understanding of model behavior and an increase in its credibility. In this paper a model evaluation protocol is proposed that encompasses five aspects: (1) model conceptual validity, (2) data requirements for model validation , (3) sensitivity analysis, (4)(More)
Keywords: Fire behaviour Fire dynamics Fire environment Fire modelling Model applicability Model input accuracy a b s t r a c t The degree of accuracy in model predictions of rate of spread in wildland fires is dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data.(More)
This paper constitutes a digest and critique of the currently available information pertaining to the influence of live fuel or foliar moisture content (FMC) on the spread rate of crown fires in conifer forests and shrublands. We review and discuss the findings from laboratory experiments and field-based fire behaviour studies. Laboratory experimentation(More)
graphs depicting 20 individual flame length–fire intensity relationships grouped by four different fuel complex types or settings (forest, grassland, shrubland, and laboratory) and 12 individual fireline intensity–crown scorch height relationships for two broad forest stand types (conifer-and eucalypt-dominated) are presented. Users will find these quick(More)
Accurate prediction of bushfire behaviour is essential for effective fire management. Such knowledge allows for the timely determination of the potential threat and impacts of a fire and provides the basis for sound fire-management decision-making. Fire behaviour prediction combines quantitative and qualitative information sources that are based on(More)