Development and testing of models for predicting crown fire rate of spread in conifer forest stands

Abstract

The rate of spread of crown fires advancing over level to gently undulating terrain was modeled through nonlinear regression analysis based on an experimental data set pertaining primarily to boreal forest fuel types. The data set covered a significant spectrum of fuel complex and fire behavior characteristics. Crown fire rate of spread was modeled separately for fires spreading in active and passive crown fire regimes. The active crown fire rate of spread model encompassing the effects of 10-m open wind speed, estimated fine fuel moisture content, and canopy bulk density explained 61% of the variability in the data set. Passive crown fire spread was modeled through a correction factor based on a criterion for active crowning related to canopy bulk density. The models were evaluated against independent data sets originating from experimental fires. The active crown fire rate of spread model predicted 42% of the independent experimental crown fire data with an error lower then 25% and a mean absolute percent error of 26%. While the models have some shortcomings and areas in need of improvement, they can be readily utilized in support of fire management decision making and other fire research studies.

Canopy fuel characteristics and potential crown fire behavior in Aleppo pine (Pinus halepensis Mill.) forests

“…Agee [1] analyzed post fire data from several stands and identified a CBD threshold of 0.10 kg/m 3 , below which active crown fire spread is greatly limited. This threshold value is also supported by Alexander [7] and Cruz et al [25], in detailed wildfire case-studies analysis. Johnson [42] considers a CBD of 0.05 kg/m 3 as a critical threshold value for active crown fire development.…”

“…Although Rothermel's [68] and Van Wagner's [80,81] models have empirical character and present various assumptions and limitations, nevertheless they have been incorporated in most wildland fire predictions systems such as the Canadian Forest Fire Prediction System [32], FARSITE [31], NEXUS [70] and BehavePlus version 3 [12]. Cruz et al [22,25] modeled crown fire rate of spread through non-linear regression analysis based on an experimental dataset which covered a broad spectrum of fuel complexes and fire behavior characteristics. The active crown rate of spread model was created as a function of wind speed, fine fuel moisture content and CBD.…”

“…The new physical model overestimated the crown fire rate of spread and required large computation time. On the contrary, the Cruz et al [22,25] model adequately predicted the crown fire rate of spread in most cases [76]. The ICFME is the only extensive evaluation of crown fire models published so far.…”

“…Until recently, fuel complex characterization has been limited to surface fuel beds [10,27], due to the restricted applicability of fire behavior simulation models only to surface fuels [11,16]. The development of fire behavior models and systems designed to predict crown fire behavior [24,25,31,32,70,79,80] made necessary the measurement of canopy fuel data. Recently, the risk of wildland fire as a forest stand management optimization problem was analyzed [34,35].…”

Modelling natural disturbances in forest ecosystems: a review

“…More complex dynamic vegetation models employ state-transition approaches (Keane et al, 1996: FIRE-BGC), they simulate age cohorts (Mladenoff and He, 1999: LANDIS) or individual trees (Miller and Urban, 1999: ZELIG;Schumacher et al, 2004: LAND-CLIM) explicitly. The latter fine-grained dynamic approaches not only track fuel dynamics and accumulation, but also provide indicators of vertical fuel structure (e.g., canopy base height, foliar density), an important input for the simulation of crown fires (van Wagner, 1977;Cruz et al, 2005).…”