Diurnal variation models for fine fuel moisture content in boreal forests in China

Abstract

Studying diurnal variation in the moisture content of fine forest fuel (FFMC) is key to understanding forest fire prevention. This study established models for predicting the diurnal mean, maximum, and minimum FFMC in a boreal forest in China using the relationship between FFMC and meteorological variables. A spline interpolation function is proposed for describing diurnal variations in FFMC. After 1 day with a 1 h field measurement data testing, the results indicate that the accuracy of the sunny slope model was 100% and 84% when the absolute error was < 3% and < 10%, respectively, whereas the accuracy of the shady slope model was 72% and 76% when the absolute error was < 3% and < 10%, respectively. The results show that sunny slope and shady slope models can predict and describe diurnal variations in fine fuel moisture content, and provide a basis for forest fire danger prediction in boreal forest ecosystems in China.