Using cellular automata to simulate field-scale flaming and smouldering wildfires in tropical peatlands

Peat wildfires are the largest fires on Earth involving both flaming and smouldering combustion, with one leading to other. A common ignition source of in tropical peatlands intentional used clear surface vegetation. To capture behaviour these fires, it is necessary consider interaction between vegetation peat. However, doing so infeasible state-of-the-art wildfire models, as they do not transition from computationally too expensive at field-scale hundreds hectares. In this work, we overcome limitations model using cellular automata: that a discrete mathematical uses simple rules complex while remaining light. The was calibrated against existing experiments literature predict effect peat moisture content peatland wildfires. shows how creates hotspots merge – spreads rapidly, consuming vegetation, leaving behind which consumes most then applied study real prescribed fire 573 ha Borneo 2015, observed by drone footage. captured spread patterns predicted 2.9 burnt after 3 months 70% (dry-based). This ioutcome could have been reduced 0.02 if had above 100%. work improves fundamental understanding field scale has received little attention until now.