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Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuelsAuthor(s): David R. Weise; Eunmo Koo; Xiangyang Zhou; Shankar Mahalingam; Frédéric Morandini; Jacques-Henri Balbi
Source: International Journal of Wildland Fire. 25(9): 980-994
Publication Series: Scientific Journal (JRNL)
Station: Pacific Southwest Research Station
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DescriptionFire behaviour data from 240 laboratory fires in high-density live chaparral fuel beds were compared with model predictions. Logistic regression was used to develop a model to predict fire spread success in the fuel beds and linear regression was used to predict rate of spread. Predictions from the Rothermel equation and three proposed changes as well as two physically based models were compared with observed spread rates of spread. Flame length–fireline intensity relationships were compared with flame length data. Wind was the most important variable related to spread success. Air temperature, live fuel moisture content, slope angle and fuel bed bulk density were significantly related to spread rate. A flame length–fireline intensity model for Galician shrub fuels was similar to the chaparral data. The Rothermel model failed to predict fire spread in nearly all of the fires that spread using default values. Increasing the moisture of extinction marginally improved its performance. Modifications proposed by Cohen, Wilson and Catchpole also improved predictions. The models successfully predicted fire spread 49 to 69% of the time. Only the physical model predictions fell within a factor of two of actual rates. Mean bias of most models was close to zero. Physically based models generally performed better than empirical models and are recommended for further study.
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CitationWeise, David R.; Koo, Eunmo; Zhou, Xiangyang; Mahalingam, Shankar; Morandini, Frédéric; Balbi, Jacques-Henri. 2016. Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels. International Journal of Wildland Fire. 25(9): 980-994.
KeywordsAdenostoma fasciculatum, Arctostaphylos glandulosa, Ceanothus crassifolius, Quercus berberidifolia
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