Application of a stochastic compartmental model to approach the spread of environmental events with climatic bias

• Published in: Ecological informatics Vol. 77; p. 102266
• Main Authors: Boters Pitarch, Joan, Signes Pont, María Teresa, Szymański, Julian, Mora Mora, Higinio
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2023
• Subjects: Climatic variables; Epidemiological models; Monte Carlo method; SIR paradigm; Monte Carlo method; Epidemiological models; Climatic variables; SIR paradigm
• ISSN: 1574-9541
• DOI: 10.1016/j.ecoinf.2023.102266

•The model considers the fluctuation and the unpredictability of the event.•This model is adaptive and uses parameters to adjust the estimated scope.•Our model simplifies the dynamics of Moore and Von Neumann to particular cases.•The model can function as a Monte Carlo-based classification method. Wildfires have significant impacts on both environment and economy, so understanding their behaviour is crucial for the planning and allocation of firefighting resources. Since forest fire management is of great concern, there has been an increasing demand for computationally efficient and accurate prediction models. In order to address this challenge, this work proposes applying a parameterised stochastic model to study the propagation of environmental events, focusing on the bias introduced by climatic variables such as wind. This model’s propagation occurs in a grid where cells are classified into different compartments based on their state. Furthermore, this approach generalises previous non-stochastic models, which are now considered particular cases within this broader framework. The use of the Monte Carlo method is highlighted, which allows for obtaining probabilistic estimates of the state of the cells in each time step, considering a level of confidence. In this way, the model provides a tool to obtain a quantitative estimate of the probability associated with each state in the spread of forest fires.