FIRE MODELLING TO ASSESS SPATIAL PATTERNS OF WILDFIRE EXPOSURE IN ARDABIL, NW IRAN

We present a new hierarchical fuel classification system with a total of 85 fuels that is useful for preventing fire risk at different spatial scales. Based on this, we developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. We validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, we developed a crosswalk for standard fuel models as a first assignment of fuel parameters.

Assessing landscape wildfire connectivity supported by wildfire spread simulations can improve fire hazard assessment and fuel management plans. Weather severity determines the degree of fuel patch connectivity and thus the potential to spread large and intense wildfires. Mapping highly connected patches in the landscape highlights patch candidates for prior fuel treatments, which ultimately will contribute to creating fire-resilient Mediterranean landscapes.

This work aimed to calibrate FARSITE simulator using a set of wildfires that occurred in north Iranian forests. Fire modeling showed a high potential for estimating spatial variability in fire spread and behavior of the case studies selected. This paper represents a first step in the application of fire spread modeling in northern Iran in wildfire risk monitoring and management. The methodology can be replicated in other Caspian ecosystems to characterize fire spread and behavior.