Skip to main content
Author(s):
Trent D. Penman, Sarah C. McColl-Gausden, Brett Cirulis, D. Kultaev, Dan Ababei, Lauren T. Bennett
Year Published:

Cataloging Information

Topic(s):
Fire Behavior
Fire Prediction
Simulation Modeling
Fuels
Risk

NRFSN number: 24225
FRAMES RCS number: 64428
Record updated:

Wildfire extent and their impacts are increasing around the world. Fire management agencies use fire behaviour simulation models operationally (during a wildfire event) or strategically for risk assessment and treatment. These models provide agencies with increased knowledge of fire potential to improve identification of the best strategies for reducing risk. One of the greatest areas of uncertainty in fire simulations is the data relating to fuel, which are usually based on simplified response trajectories with time since fire within vegetation communities. There is a clear need to better predict relevant fuel variables across landscapes to reduce uncertainties in fire simulations. In this study, we compare the performance of fuel hazard models based on environmental variables (environmental model) with those currently implemented based on a negative exponential relationship with time since fire (NEGEXP) using the state of Victoria in south-eastern Australia as an environmentally diverse case study. The models predicted similar broadscale patterns in fuel hazard but with considerable regional variation. The NEGEXP model was less accurate than the environmental model, which had 41-47% accuracy on an independent data set cf. 24-35% for NEGEXP. Model differences resulted in significant differences in the extent and spatial location of predicted fires with NEGEXP consistently predicting larger fires. Fuel is made up of the live and dead components of vegetation, both of which are influenced by a range of environmental factors. As our study highlights, ignoring environmental factors in simple fuel models based on broad vegetation types (like NEGEXP) will likely compromise the predictive accuracy of fire behaviour models. Only when environmental factors are accounted for can we more accurately predict fuels across landscapes and thereby improve the accuracy of fire behaviour predictions and the estimation of fire risks.

Citation

Penman, Trent D.; McColl-Gausden, Sarah C.; Cirulis, Brett A.; Kultaev, D.; Ababei; Dan A.; Bennett, Lauren T. 2022. Improved accuracy of wildfire simulations using fuel hazard estimates based on environmental data. Journal of Environmental Management 301:113789. https://doi.org/10.1016/j.jenvman.2021.113789

Access this Document

Treesearch

publication access with no paywall

Check to see if this document is available for free in the USDA Forest Service Treesearch collection of publications. The collection includes peer reviewed publications in scientific journals, books, conference proceedings, and reports produced by Forest Service employees, as well as science synthesis publications and other products from Forest Service Research Stations.