Wildfires have increasingly become a point of concern, especially with notable incidents like the 2017 Knysna fire. These naturally occurring phenomena, despite their disruptive nature, are crucial for the sustainability of certain ecosystems. At the heart of understanding wild-fires lies the relationship between climate, vegetation, topography, and human land use, with topography standing out as a significant determinant. This thesis delves into the fundamen-tal role of topography, emphasizing its effect on the ignition, propagation, and behaviour of wildfires.
Utilizing Digital Elevation Models (DEMs), the research extracts invaluable topographic data aiming to augment the understanding of wildfires, especially in mixed natural forest and fyn-bos ecosystems. Existing fire models have shown certain shortcomings, often overlooking crucial localized wind data, which has profound implications for predicting fire behaviour. By bridging this gap, the study explores the potential of computational fluid dynamics in modelling surface winds based on topography for fire research. The research systematically addresses several key objectives: Mapping the current land-scape of topography-cantered wildfire research and investigating the utility of DEM-derived surface wind in refining fire propagation models, identifying and analysing historical fire patterns to pinpoint fire refugia in the Knysna/Tsitsikhama region, employing machine learning techniques, to determine if topographic variables extracted from DEMs can antici-pate fire refugia. The findings underscore the salience of topography in wildfires. Especially significant is the role of aspect in determining fire refugia, emphasizing that a combination of multiple variables offers the most accurate insights. Machine learning, notably the XGBoost model, showcases potential in identifying critical topographical features impacting fire behaviours. Furthermore, the research sheds light on the pivotal influence of wind chan-nels, formed by topographical features, in both the inception and spread of wildfires. In summary, this thesis underscores the integral role of topography in understanding wild-fires. It charts a roadmap for future research, emphasizing the importance of high-quality validation data, a more comprehensive mapping of fire refugia, and an acknowledgement of the influence of human activity on fire regimes. By building on the methodologies and in-sights presented, there lies an opportunity to advance sustainable wildfire management so-lutions that benefit both ecosystems and human communities.
KEYWORDS: Wildfire, Topography, Fire refugia, Fynbos, Afrotemperate forest