ASSESSMENT OF WILDFIRE DANGER IN KAZAKHSTAN USING THE FWI AND FFDI INDICES
DOI:
https://doi.org/10.54668/2789-6323-2026-123-3-79-96Keywords:
wildfires, fire danger index, meteorological data, Kazakhstan, climate changeAbstract
The article presents the results of calculating fire danger indices for the territory of Kazakhstan for the period of July 20…31, 2025, based on meteorological data and satellite observations of active fires. It also presents an analysis of forecast meteorological data from the Global Forecast System model for the period April-September 2025; the calculations took into account key meteorological parameters: air temperature, relative humidity, wind speed, and precipitation amount. Validation of the obtained results was carried out using thermal anomaly (hotspot) data recorded by MODIS and VIIRS satellite sensors. A comparative analysis was conducted for two widely used fire danger indices: the Australian Forest Fire Danger Index (FFDI) and the Canadian Fire Weather Index system (FWI). The results indicate that maximum fire danger levels were observed in July, driven by a combination of high temperatures (up to 30...36 °C), low relative humidity (down to 13...15%), and precipitation deficit. Spatial analysis revealed elevated fire danger in the southern, southeastern, and central regions, whereas northern territories were characterized predominantly by low to moderate risk levels. The comparison of indices showed that the FWI system demonstrates greater sensitivity to the combined effects of meteorological factors, including fuel dryness accumulation and prolonged drought conditions, while the FFDI is more responsive to short-term extreme weather variations, particularly wind speed. Analysis across seven Koppen–Geiger climate zones confirmed a statistically significant (p < 0.001) agreement between the FWI and FFDI indices (r = 0.86…0.98) regardless of climate type. The results confirm the validity of the combined use of these indices to improve the accuracy of fire danger forecasting and support their integration into early warning systems for wildfires, taking into account regional climatic characteristics of Kazakhstan.
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Copyright (c) 2026 Гульсезим Жусупова, Даникер Чепашев, Диас Мерекеев, Эльмира Жилкибаева, Дастан Аманкешулы
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