This PhD project aims to devise a simplified, generic version of the fire-spread algorithm used operationally by the US and other fire services, and embedded in several global fire models (Rothermel’s ROS).
In the first stage, we aim to gather and harmonize data from wind tunnel experiments and remote sensing, then reproduce some of Rothermel’s analysis to predict the rate of spread, and infer fewer and simpler empirical relationships with vegetation structure, moisture, and fire radiative power (FRP).
In the second stage, physically-based models to predict ROS from the literature will be tested and merged, where needed, with the empirical equations found in the first stage to construct a robust and realistic model, but as simple as possible.
This research builds on two computational Masters projects previously supervised by Colin Prentice and involves advanced engineering mathematics skills and familiarity with thermodynamics, remote sensing and landscape-scale modelling
Project duration – expected end 2021