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

野火是对各种生态系统的干扰，由于气候变化而不适应这些干扰的地区的脆弱性可能会增加。气候变率是影响大型野火的主要因素，如果气候变化增加了极端火灾天气的幅度和持续时间，我们可以预期某些生态系统中优势植物物种的分布和丰度会发生显著变化，从而影响敏感物种的栖息地。野火的发生需要几个因素的影响，如点火、连续的植被和适当的大气条件。模拟野火蔓延可以更好地理解环境和景观中相互作用因素的关系和动态。由于这些动态往往会受到环境突变的影响，即使驱动因素的微小变化也会引起大的变化，这使得预测变得困难。从理论上讲，模型可以帮助找到蔓延的阈值，并预测驱动因素的突然变化如何影响总体燃烧面积和蔓延速度。由于最近发生的事件，英国在野火事件方面的脆弱性提高了人们的认识，并强调了环境破坏、财产损失和关键基础设施损失的可能性。英国的大多数野火都是人为疏忽或故意造成的，但环境条件取决于之前和当前的天气。本研究项目旨在：通过基于物理的计算模型，对野火蔓延及其与天气条件、地形和植被类型的相互作用进行建模和模拟，提高野火传播的理论知识。从英国的真实火灾事件数据推断模型参数并验证结果。利用该模型确定野火的管理和预防策略以及全球气候变化的影响。野火是复杂的、多尺度的、时空的系统，因此我们建议使用确定性和计算技术相结合的建模方法。地理信息系统（GIS）已成为生态建模的重要组成部分，在需要这些输入的模型中分析和有效地使用环境空间数据。不可避免的是，地形坡度、风速和风向是影响火势蔓延的重要因素——利用GIS模块和气象数据，我们可以根据这些环境因素更准确地估计火势蔓延。此外，用于比较案例研究的真实火灾事件数据将由全球野火信息系统、环境、食品和农村事务部以及从沼泽地石南燃烧季节收集的当地无人机镜头提供。统计技术可以通过测试模型预测未知数据和推断参数的能力来验证模型。因此，该模型可以用来预测未来的事件，改进管理策略，并帮助决定气候变化的影响，如可能影响火灾行为的外围天气模式。

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 modelsTo 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.