Wind Field Uncertainty in Forest Fire Propagation Prediction

Abstract

Forests fires are a significant problem especially in countries of the Mediterranean basin. To fight against these disasters, the accurate prediction of forest fire propagation is a crucial issue. Propagation models try to describe the future evolution of the forest fire given an initial scenario and certain input parameters. However, the data describing the real fire scenario are usually subject to high levels of uncertainty. Moreover, there are input parameters that present spatial and temporal variation that make the prediction less accurate. Therefore, to overcome such uncertainty and improve accuracy it is necessary to couple complementary models such as the case of the wind field model. Such models use the meteorological forecasted wind to provide the wind direction and speed depending on the topography of the terrain. We use WindNinja as wind field simulator. This simulator takes a lot of time to deliver the predictions and it is a serious problem because fire propagation prediction must accomplish strict time constraints. To solve this problem, we propose map partitioning and solving independently for each one of the parts. However, the model has problems concerning boundary effects which is an additional source of uncertainty. Therefore, it is necessary to apply certain degree of overlapping among parts to reach a stable wind field without inconsistencies and a minimum uncertainty.