Prediction model of moisture content of dead fine fuel in forest plantations on Maoer Mountain, Northeast China

Abstract

Preventing and suppressing forest fires is one of the main tasks of forestry agencies to reduce resource loss and requires a thorough understanding of the importance of factors affecting their occurrence. This study was carried out in forest plantations on Maoer Mountain in order to develop models for predicting the moisture content of dead fine fuel using meteorological and soil variables. Models by Nelson (Can J For Res 14:597–600, 1984) and Van Wagner and Pickett (Can For Service 33, 1985) describing the equilibrium moisture content as a function of relative humidity and temperature were evaluated. A random forest and generalized additive models were built to select the most important meteorological variables affecting fuel moisture content. Nelson's (Can J For Res 14:597–600, 1984) model was accurate for Pinus koraiensis, Pinus sylvestris, Larix gmelinii and mixed Larix gmelinii—Ulmus propinqua fuels. The random forest model showed that temperature and relative humidity were the most important factors affecting fuel moisture content. The generalized additive regression model showed that temperature, relative humidity and rain were the main drivers affecting fuel moisture content. In addition to the combined effects of temperature, rainfall and relative humidity, solar radiation or wind speed were also significant on some sites. In P. koraiensis and P. sylvestris plantations, where soil parameters were measured, rain, soil moisture and temperature were the main factors of fuel moisture content. The accuracies of the random forest model and generalized additive model were similar, however, the random forest model was more accurate but underestimated the effect of rain on fuel moisture.

Keywords

Forest plantations / Fine fuel moisture content / Weather factors / Prediction models

References

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