Fire Behavior Simulation from Global Fuel and Climatic Information

Abstract

Large-scale fire danger assessment has become increasingly relevant in the past few years, and is usually based on weather information. Still, fuel characteristics also play an important role in fire behavior. This study presents a fire behavior simulation based on a global fuelbed dataset and climatic and topographic information. The simulation was executed using the Fuel Characteristic Classification System (FCCS). The climatic information covered the period 1980-2010, and daily weather parameters were used to calculate the mean monthly fuel moisture content (FMC) and wind speed for the early afternoon period. Also, as the most severe fires occur with extreme environmental conditions, a worst-case scenario was created from the 30 days of each month with the lowest FMC values for the 1980-2010 period. The FMC and wind speed information was grouped into classes, and FCCS was used to simulate the reaction intensity, rate of spread and flame length of the fuelbeds for the average and worst-case monthly conditions. Outputs of the simulations were mapped at global scale, showing the variations in surface fire behavior throughout the year, both due to climatic conditions and fuel characteristics. The surface fire behavior parameters identified the fuels and environmental conditions that produced more severe fire events, as well as those regions where high fire danger only occurs in extreme climatic conditions. The most severe fire events were found in grasslands and shrublands in tropical dry biomes, and corresponding with the worst-case scenario environmental conditions. Also, the results showed the importance of including detailed fuel information into fire danger assessment systems, as the same weather and topographic conditions may have different danger rates, depending on fuel characteristics.

Generation and Mapping of Fuel Types for Fire Risk Assessment

“…Dense grasslands and shrubs are the most flammable fuel types [94]. This agrees with the obtained results, which show that the GR5/GR8/GR9 fuel type or Alpine and Atlantic highly continuous (70-100%) grasses entails the highest fire risk and danger: very highextreme fire potential spread rate and flame length.…”

Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models

“…Land cover classes were converted into the fractional coverage of plant functional types (PFTs). For this conversion, we used the cross-walking approach (Poulter et al, 2011(Poulter et al, , 2015 based on the conversion table in Forkel et al (2017). Individual PFTs combine growth form (tree, shrubs, herbaceous vegetation, or crops) with leaf type (broadleaved or needle-leaved) and leaf longevity (evergreen or deciduous).…”

Fire Danger Observed from Space

“…Some of the largest fuel maps include the one developed by EFFIS for Europe based on CLC information (European Forest Fire Information System 2017), the United States LANDFIRE maps (Nelson et al 2016;Rollins 2009) created from Landsat information, and the Canadian fuel types map (Nadeau et al 2005) from SPOT-VEG-ETATION data (Latifovic et al 2004). There have also been attempts to develop global fuel maps using data derived from different sources, including RS derived products such as vegetation cover, canopy height, and land cover classes (Pettinari and Chuvieco 2016) to be used for coarse-resolution fire danger and behaviour estimations (Pettinari and Chuvieco 2017).…”