There are many aspects of forest fire behaviour where there is incomplete understanding. Understanding the elements of fire spread is critical to reduce its affects. Fire behaviour and modelling research must use the advancing technology and physics-based modelling can contribute to fire behaviour understanding.
Forest fuel composition is quite complex, being comprised of a range of strata whose involvement in combustion is dependent on several fuel and environmental conditions. Usually, a forest’s fuels can be divided into four or five visually distinct layers, broadly identified by a change in bulk density and which can be linked to fire behaviour. Surface fuels are comprised of fallen dead leaves, bark and twigs that are generally horizontally layered and near-surface fuels are comprised of grasses, low shrubs etc. These represent the bulk of fuel consumed on a weight basis. The amount of surface/ near-surface fuel does not, by itself, influence the rate of fire spread (ROS), but it does influence flame height, flame depth and fire intensity and thereby the likelihood of causing ignition of a forest canopy (crown). Once the fire evolves to a canopy fire, its ROS increases significantly and increases the risk of entrapment significantly.
This research will provide insight into the threshold conditions that exist when a forest’s surface fire transitions to a crown fire. Improved understanding of this aspect will provide forest fire managers and fire services timely advice on situational awareness and help them to exercise evidence-informed decision-making for more targeted to ensure a more manageable surface fire does not have the potential to evolve to a devastating and uncontrollable crown fire.
This study will involve data-rich case studies to support operational model improvement, testing and validation. As a result, it will strengthen fire-focused predictive services, including landscape and fuel data, simulation and prediction models.
