Climate change effects on the spread of wildfires: A mathematical approach

Lead Research Organisation: Newcastle University
Department Name: Sch of Maths, Statistics and Physics

Abstract

Wildfires are a disturbance to a variety of ecosystems, and vulnerability is likely to increase in areas which are not adapted to these disturbances due to climate change. Climatic variability is a dominant factor affecting large wildfires, if climatic change increases the amplitude and duration of extreme fire weather, we can expect significant changes in the distribution and abundance of dominant plant species in some ecosystems, which would thus affect habitats of sensitive species. Wildfire occurrence requires the influence of several factors e.g. ignitions, continuous vegetation and appropriate atmospheric conditions. Modelling wildfire spread allows for greater understanding of the relationship and dynamics of interacting factors in the environment and landscape. Since these dynamics tend to be affected by abrupt shifts in environment, even small changes in the drivers can cause large changes - making predictions difficult. Models can theoretically aid to find thresholds for spread and predict how abrupt shifts in drivers are affecting overall burnt areas and the rate of spread. Due to recent events, the vulnerability of the UK with regard to wildfire events has raised awareness and highlighted the potential for environmental damage and loss of property and key infrastructure. Most UK wildfires are a result of inadvertent or deliberate human action, but the environmental conditions depend on antecedent and current weather.
This research projects aims:
To improve theoretical knowledge of wildfire spread through physical-based computational models
To model and simulate wildfires spread and its interactions with weather conditions, topography and vegetation types.
To infer model parameters and validate results from real fire event data of the UK.
To use the model to determine management and prevention strategies for wildfires and effects of global climate change.
Wildfires are complex, multi-scale, spatio-temporal systems, therefore we suggest a modelling approach that uses a combination of deterministic and computational techniques. Geographic Information Systems (GIS) have become an important part of ecological modelling to analyse and effectively use environmental spatial data in models that require such input. It is inevitable that the slope of landscape and wind speed and direction are important factors in fire spread - with the use of a GIS module and meteorological data we can estimate fire spread more accurately with regard to these environmental factors. Furthermore, real fire event data for comparative case studies will be supplied by the Global Wildfire Information System, the Department for Environment, Food and Rural Affairs and local drone footage collected from moorland heather burning season. Statistical techniques can be used to validate the model by testing its ability to predict unseen data and infer parameters. Thus, the model can then be used to predict future events, improve management strategies and aid decisions on climate change effects such as outlying weather patterns that may influence fire behaviour.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007512/1 01/10/2019 30/09/2027
2883580 Studentship NE/S007512/1 01/10/2023 31/03/2027 Axa-Maria Lääperi