关键词: 压缩比, 水分变化, 预测模型, 林火管理

Abstract: The timelag method is the most widely used prediction model of litter moisture content. Two key parameters, equilibrium moisture content and timelag, are important for predicting litter moisture content. However, the two key parameter calculation methods currently used are not applicable because they do not consider the effects of bed structure and litter type, which causes errors in the prediction of litter moisture content. Analyzing the influence of driving factors on equilibrium moisture content and timelag, and establishing corresponding prediction models are of great significance for improving the prediction accuracy of litter moisture content. In this study, Quercus mongolica leaves were used as the research material to construct beds with different packing ratios. Through an indoor experiment with different air temperatures and relative humidity, we obtained the water loss situation and the influencing factors of the equilibrium moisture content and timelag, and established the corresponding prediction model, and analyzed the prediction ability of the model. The results showed that moisture content of the litter bed of Q. mongolica decreased exponentially with time under fixed air temperature and humidity. The equilibrium moisture content of litter bed was mainly affected by air temperature and humidity, while the timelag was affected by air temperature, humidity and packing ratio of the fuelbed. It is not feasible to directly use the Nelson model to predict the equilibrium moisture content of litter of Q. mongolica. The Simard model perfomed better than the Nelson model, with the error locating within an acceptable range. The prediction error of the selfbuilt model was not significantly different from that of the Simard model, while the coefficient of variation of the fitting parameters was smaller. A timelag prediction model for the Q. mongolica leaf bed with different packing ratios was established, and the prediction errors were all within an acceptable range. The model reveals the influencing mechanisms of air temperature, humidity, and packing ratio on timelag. Through examining the effects of air temperature, relative humidity and packing ratio of the fuelbed on the equilibrium moisture content and timelag of Q. mongolica and constructing prediction models, this study is of great significance for improving the prediction accuracy of litter moisture content and forest fire prediction.

Key words: packing ratio, moisture change, prediction model, forest fire management.