{"id":88041,"date":"2023-06-12T14:48:10","date_gmt":"2023-06-12T18:48:10","guid":{"rendered":"https:\/\/newsroom.carleton.ca\/?post_type=cu_story&p=88041"},"modified":"2025-08-19T09:37:06","modified_gmt":"2025-08-19T13:37:06","slug":"forest-fires-planning-modelling-factors","status":"publish","type":"cu_story","link":"https:\/\/carleton.ca\/news\/story\/forest-fires-planning-modelling-factors\/","title":{"rendered":"Predicting and planning for forest fires requires modelling of many complex, interrelated factors"},"content":{"rendered":"\n
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\n Predicting and planning for forest fires requires modelling of many complex, interrelated factors\n <\/h1>\n \n <\/header>\n <\/div>\n\n \n <\/path>\n <\/path>\n <\/svg>\n <\/div>\n\n \n\n <\/div>\n<\/section>\n\n

This article is republished<\/a> from The Conversation under a Creative Commons licence. All photos provided by The Conversation<\/a> from various sources.<\/p>\n\n\n\n

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Global warming is here. As anticipated for more than 50 years now<\/a>, the temperature and levels of atmospheric CO2 have increased.<\/p>\n\n\n\n

Various models were able to predict these increases with precision<\/a>, and we are seeing the impact now. One of the main effects of the changes in the atmosphere are frequent forest fires<\/a>, which are more common globally<\/a> and have affected Canada in the last month.<\/p>\n\n\n\n

Complex models<\/h2>\n\n\n\n

Mathematical models to predict forest fire behaviours were first introduced in the 1940s<\/a> and they have been evolving for decades<\/a>. They consider various aspects and their complex interrelationships: the type of forest fuel<\/a> (grass, shrub, small trees, large ones), the weather<\/a> (wind direction, temperature, humidity), the topology of the terrain, and the source of the fire<\/a> (human activity, lightning).<\/p>\n\n\n\n

Modelling forest fires and forecasting fire behaviour is a complex endeavour. A model can anticipate the direction and intensity of the fire, and help with evacuation, fire suppression and forecast of smoke pollution<\/a>. The models can predict fire spread, which helps protect human life, housing and infrastructure, including crucial utility companies assets.<\/p>\n\n\n\n

Mathematical models are important, but in the case of forest fires, we also need to build simulation tools to be able to handle the complexity<\/a>. We need to consider the different types of fire fuels in each region, the localized winds within forest fire areas, variations in climate, whether a fire spreads from the crown of the trees or on the ground, and other variations.<\/p>\n\n\n\n

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Many factors can affect how quickly a fire spreads.<\/span>
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Using a computer to build a virtual laboratory for simulations helps with the prediction process in a safe, risk-free and cost-effective fashion. Experiments can be simulated on a computer to inform better decisions in the field, without affecting the environment, people or infrastructure.<\/p>\n\n\n\n

Complex factors, small scale<\/h2>\n\n\n\n

Our lab \u2014 the Advanced Real-Time Simulation<\/a> lab at Carleton University \u2014 has been working on new methodologies for modelling and simulation that improve results at a reduced cost.<\/p>\n\n\n\n

We model forest fire behaviour at a microscopic level. This is because models that work on macro, or larger, scales<\/a> have some constraints when we want to study the low-level interactions between fire, weather and suppression efforts.<\/p>\n\n\n\n

Also, traditional models are harder to interface with Geographical Information Systems (GIS) software applications. We need to be able to interface the models with real-world data coming in real time from a variety of sensors: spectrometers<\/a>, satellites, infrared scanners<\/a>, laser or 3D remote sensing devices<\/a>. Building models that can react to external data needs new methodologies.<\/p>\n\n\n\n