Adaptive wildfire spread prediction for complex terrain: modeling the effectiveness of sprinkler systems

Because the threat of wildfires to global ecosystems and society continues to rise, this study provides an experimental simulation framework that assesses the spread and reduction of wildfires to evaluate the effectiveness of adaptation methods in reducing their impact. The process entails selecting a vulnerable wildfire area and adaptation method, then generating the computational fluid dynamics (CFD) model. Monitoring data are then used to configure the model, set boundary conditions, and simulate the fire. The effectiveness of the adaptation method in minimizing damage in the area of interest is evaluated by comparing simulations with and without the chosen adaptation method. Our focus area was a natural recreational forest in Wonju, Gangwon-do, Korea, and our adaptation method was a water sprinkler system.

Our framework provides aims to provide an experimental means of assessing the wildfire spread path and spread area based on exogenous variables of wind speed, wind direction, relative humidity, and more. The sprinkler adaptation had a reduction effect of 20% in the wildfire spread rate for the 10-h period, which refers to the time limit of the simulation after ignition. We revealed that at higher wind speeds, the fire primarily follows the wind direction; whereas at lower wind speeds, the fire is more influenced by the topography. Additionally, 60 min after ignition, the adaptation methods can suppress wildfire spread by > 70%. Notably, sprinklers reduce smoke concentrations by up to 50% (ppm) over the affected area.

This study demonstrates the potential effectiveness of a comprehensive CFD model in mitigating wildfire spread using sprinkler systems as an experimental analysis. Key results include a 20% reduction in wildfire within 10 h of ignition, significant influence of wind speed on spread patterns, and a reduction of smoke concentrations, improving air quality. These findings highlight the potential of CFD-based frameworks to enhance wildfire response strategies. However, it is important to note that this study’s limitations include the lack of experimental or measured fire behavior data, which should be considered when interpreting the effectiveness of the CFD model.