Fundamentals - Wildland Fuel Fundamentals and Applications - page 22

Fig. 2.3 The theoretical flame of fire spread used in the development of the one-dimensional fire
spread models
bulk density, may not provide great predictive power when fire is simulated for one
point in space.
Another great need for fire behavior simulation was to predict fire effects. Byram
( 1958 ) noted the importance of predicting the impact of fire on living vegetation,
and Rothermel and Deeming ( 1980 ) noted fire behavior was critical for predicting
fire effects. Yet ironically, fuel inputs to most fire models were engineered to fit
combustion relationships without an ecological context. Successful prediction of
fire effects requires that the model to be designed so that the inputs make ecological
sense (Keane and Finney 2003 ) and that the outputs are germane to the assessment
of fire effects. Grouping all log biomass into one size class, for example, ignores
the great importance of log size on fuel properties and subsequent combustion, and,
more importantly, on the effects of burning different-sized logs on soil heating and
smoke production. Moreover, some fire effects models use fuel properties that are
not used in fire behavior simulation algorithms (Trakhtenbrot et al. 2014 ). Mecha-
nistic fire-caused tree mortality models, for example, use thermal conductivity to
simulate heat flow through bark (Mitchell 2013 ).
And last, it is important to note that most operational fire behavior models are
quasi-empirical in design (Sullivan 2009b ) in that they predict fire spread and inten-
sity using physically based statistical algorithms. As Finney et al. ( 2013 ) mention,