@article {BF-4267,
	title = {Uncertainty associated with model predictions of surface and crown fire rates of spread},
	journal = {Environmental Modelling \& Software},
	volume = {47},
	year = {2013},
	month = {2013},
	pages = {16-28},
	chapter = {16},
	abstract = {The degree of accuracy in model predictions of rate of spread in wildland fires is dependent on the
model{\textquoteright}s applicability to a given situation, the validity of the model{\textquoteright}s relationships, and the reliability of
the model input data. On the basis of a compilation of 49 fire spread model evaluation datasets involving
1278 observations in seven different fuel type groups, the limits on the predictability of current operational
models are examined. Only 3\% of the predictions (i.e. 35 out of 1278) were considered to be exact
predictions according to the criteria used in this study. Mean percent error varied between 20 and 310\%
and was homogeneous across fuel type groups. Slightly more than half of the evaluation datasets had
mean errors between 51 and 75\%. Under-prediction bias was prevalent in 75\% of the 49 datasets analysed.
A case is made for suggesting that a 35\% error interval (i.e. approximately one standard deviation)
would constitute a reasonable standard for model performance in predicting a wildland fire{\textquoteright}s
forward or heading rate of spread. We also found that empirical-based fire behaviour models developed
from a solid foundation of field observations and well accepted functional forms adequately predicted
rates of fire spread far outside of the bounds of the original dataset used in their development.},
	keywords = {bushfire behaviour, bushfire spread, Fire behaviour, fire spread},
	doi = {http://dx.doi.org/10.1016/j.envsoft.2013.04.004},
	author = {Cruz, Miguel G. and Alexander, ME}
}
@article {BF-2466,
	title = {Assessing crown fire potential in coniferous forests of western North America: a critique of current approaches and recent simulation studies},
	journal = {International Journal of Wildland Fire},
	volume = {19},
	year = {2010},
	month = {2010},
	pages = {377},
	abstract = {To control and use wildland fires safely and effectively depends on creditable assessments of fire potential, including the propensity for crowning in conifer forests. Simulation studies that use certain fire modelling systems (i.e. NEXUS, FlamMap, FARSITE, FFE-FVS (Fire and Fuels Extension to the Forest Vegetation Simulator), Fuel Management Analyst (FMAPlus{\textregistered}), BehavePlus) based on separate implementations or direct integration of Rothermel{\textquoteright}s surface and crown rate of fire spread models with Van Wagner{\textquoteright}s crown fire transition and propagation models are shown to have a significant underprediction bias when used in assessing potential crown fire behaviour in conifer forests of western North America. The principal sources of this underprediction bias are shown to include: (i) incompatible model linkages; (ii) use of surface and crown fire rate of spread models that have an inherent underprediction bias; and (iii) reduction in crown fire rate of spread based on the use of unsubstantiated crown fraction burned functions. The use of uncalibrated custom fuel models to represent surface fuelbeds is a fourth potential source of bias. These sources are described and documented in detail based on comparisons with experimental fire and wildfire observations and on separate analyses of model components. The manner in which the two primary canopy fuel inputs influencing crown fire initiation (i.e. foliar moisture content and canopy base height) is handled in these simulation studies and the meaning of Scott and Reinhardt{\textquoteright}s two crown fire hazard indices are also critically examined.},
	doi = {10.1071/WF08132},
	author = {Cruz, Miguel G. and Alexander, ME}
}
@article {BF-1004,
	title = {Evaluating a model for predicting active crown fire rate of spread using wildfire observations.},
	journal = {Canadian Journal of Forest Research},
	number = {36},
	year = {2006},
	month = {11/30/2006},
	pages = {3015-3028},
	url = {http://www.ingentaconnect.com/content/nrc/cjfr/2006/00000036/00000011/art00030},
	author = {Alexander, ME and Cruz, Miguel G.}
}
