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Type: Journal Article
Author(s): Miguel G. Cruz; Martin E. Alexander; Paulo A. Martins Fernandes; Musa Kilinc; Ângelo Sil
Publication Date: 2020

The prediction of wildfire rate of spread and growth under high wind speeds and dry fuel moisture conditions is key to taking proactive actions to warn and in turn protect communities. We used two datasets of wildfires spreading under critical fire weather conditions to evaluate an existing rule of thumb that equates the forward rate of fire spread to 10% of the average open wind speed. The rule predicted the observed rates of fire spread with an overall mean absolute error of 1.7 km h−1. The absolute error magnitude was consistent across the range in observed rates of fire spread, resulting in a reduction in percent error with an increase in spread rates. Mean absolute percent errors close to 20% were obtained for wildfires spreading faster than 2.0 km h−1. The implications of model errors in the forecasting of fire spread with respect to community warning and safety are discussed.

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Citation: Cruz, Miguel G.; Alexander, Martin E.; Fernandes, Paulo A. Martins; Kilinc, Musa; Sil, Ângelo. 2020. Evaluating the 10% wind speed rule of thumb for estimating a wildfire's forward rate of spread against an extensive independent set of observations. Environmental Modelling & Software 133:104818.

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Topics:
Regions:
Alaska    California    Eastern    Great Basin    Hawaii    Northern Rockies    Northwest    Rocky Mountain    Southern    Southwest    International    National
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Keywords:
  • Australia
  • Canada
  • conifer forests
  • critical fire weather
  • crown fire
  • dead fuel moisture content
  • dead fuels
  • dry eucalypt forests
  • fine fuels
  • fire prediction
  • fire propagation
  • fire spread
  • fuel moisture content
  • fuel type
  • high intensity fires
  • model error
  • North America
  • ROS - rate of spread
  • temperate shrublands
  • wildfires
  • wind speed
  • winds
Record Last Modified:
Record Maintained By: FRAMES Staff (https://www.frames.gov/contact)
FRAMES Record Number: 61777