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Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide

Author(s): Jane G. Cawson, Petter Nyman, Christian Schunk, Gary J. Sheridan, Thomas J. Duff, Kelsy E. Gibos, William D. Bovill, Marco Conedera, Gianni B. Pezzatti, Annette Menzel
Year Published: 2020
Description:

Field measurements of surface dead fine fuel moisture content (FFMC) are integral to wildfire management, but conventional measurement techniques are limited. Automated fuel sticks offer a potential solution, providing a standardised, continuous and real-time measure of fuel moisture. As such, they are used as an analogue for surface dead fine fuel but their performance in this context has not been widely evaluated. We assessed the ability of automated fuel sticks to predict surface dead FFMC across a range of forest types. We combined concurrent moisture measurements of the fuel stick and surface dead fine fuel from 27 sites (570 samples), representing nine broad forest fuel categories. We found a moderate linear relationship between surface dead FFMC and fuel stick moisture for all data combined (R2 = 0.54), with fuel stick moisture averaging 3-fold lower than surface dead FFMC. Relationships were typically stronger for individual forest fuel categories (median R2 = 0.70; range = 0.55-0.87), suggesting the sticks require fuel-specific calibration for use as an analogue of surface dead fine fuel. Future research could identify fuel properties that will enable more generalised calibration functions.

Citation: Cawson, Jane G.; Nyman, Petter; Schunk, Christian; Sheridan, Gary J.; Duff, Thomas J.; Gibos, Kelsy E.; Bovill, William D.; Conedera, Marco; Pezzatti, Gianni B.; Menzel, Annette. 2020. Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide. International Journal of Wildland Fire 29(6):548-559. https://doi.org/10.1071/WF19061
Topic(s): Fuels, Risk
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 21423
FRAMES RCS number: 61392
Record updated: Jul 7, 2020