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Forests 2017, 8(11), 408; https://doi.org/10.3390/f8110408

Visual Assessment of Surface Fuel Loads Does Not Align with Destructively Sampled Surface Fuels

School of Ecosystem and Forest Sciences, University of Melbourne, 4 Water Street, Creswick, VIC 3363, Australia
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Received: 16 September 2017 / Revised: 14 October 2017 / Accepted: 26 October 2017 / Published: 27 October 2017
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Abstract

Fuel load and structure are fundamental drivers of fire behaviour. Accurate data is required for managers and researchers to better understand our ability to alter fire risk. While there are many ways to quantify fuel, visual assessment methods are generally considered the most efficient. Visual hazard assessments are commonly used by managers, government agencies and consultants to provide a fuel hazard score or rating but not a quantity of fuel. Many systems attempt to convert the hazard score or rating to a fuel load for use in fire behaviour models. Here we investigate whether the conversion table in the widely used Overall Fuel Hazard Guide (OFHG) matches destructively sampled fuel loads from 116 sites across five forest types. We specifically examine whether there are quantifiable differences that can be attributed to forest type. We found there is overlap between the two methods for low, moderate and high hazard categories, however for the very high and extreme hazard categories, visual assessment overestimated fuel load in four of the five forest types. Using a commonly applied fire behaviour model, we found that the overestimation of fuel load in very high and extreme hazard categories leads to an overestimation of fire behavior in these hazard categories. View Full-Text
Keywords: visual fuel assessments; fuel load estimates; bushfire; wildfire; fire behaviour; fire risk; fine fuel; fire management visual fuel assessments; fuel load estimates; bushfire; wildfire; fire behaviour; fire risk; fine fuel; fire management
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McColl-Gausden, S.C.; Penman, T.D. Visual Assessment of Surface Fuel Loads Does Not Align with Destructively Sampled Surface Fuels. Forests 2017, 8, 408.

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