Cigarette butts are an important human firebrand and account for a significant amount of man-made fires. To better address forest fires caused by cigarette butts, the influencing factors governing the ignition probability of cigarette butts can be used to establish a prediction model. This study obtains the influencing factors of the ignition probability of cigarette butts in order to establish a prediction model by constructing fuel beds composed of Mongolian oak leaves with varied fuel moisture content and packing ratios. A total of 2520 ignition experiments were then conducted by dropping cigarette butts on the fuel beds to test the burning probability of the fuels under varied wind speeds. Moisture content, wind speed, and their interaction significantly influenced ignition probability. In the absence of wind, the ignition probability is zero. The maximum moisture content of Mongolian oak leaves that could be ignited by cigarette butts was 15%. A logistic model and self-built model for predicting the ignition probability were established using these results; the mean absolute error values for the two models were 2.71% and 1.13%, respectively, and the prediction error of the self-built model was lower than that of the logistic model. This is important research to mitigate the threat of forest fires due to cigarette butts given the frequent occurrence of these events.

The occurrence and behavior of forest fires are mainly affected by litter moisture content, which is very important for fire risk forecasting. Errors in models of litter moisture content prediction mainly stem from the neglect of diurnal variation. Consequently, it is essential to determine the diurnal variation of litter moisture content and establish a high-precision prediction model. In this study, the moisture contents of litters of Mongolian oak (Quercus mongolica) and Korean pine (Pinus koraiensis) were monitored at 1 h time steps to obtain the diurnal variations of moisture content, and two direct estimation (Nelson and Simard) methods as well as one meteorological factor regression method were selected to establish prediction models at 1 h time steps. The moisture contents of the two litter types showed obvious diurnal variation, and the changes were significantly correlated with the air temperature and relative humidity. The wind speed had no significant effect on the change within 1 h. The mean absolute error (MAE) values of the three prediction models of Mongolian oak were 1.02%, 1.03%, and 1.46%, and those of Korean pine were 0.50%, 0.50%, and 1.95%, respectively. Similarly, the mean relative error (MRE) values of the three prediction models of oak litter were 4.76%, 4.73%, and 6.65%, and those of pine were 3.53%, 3.59%, and 13.26%, respectively. These results indicated that the accuracy of the Nelson and Simard methods was similar, and both met the requirements for the forecasting of forest fire risk. Therefore, the direct estimation method was selected to predict the moisture contents of two litter types in this area.

The fire danger rating method currently used in the northern part of the Daxinganling Region with the most severe forest fires in China only uses weather variables without considering firebrands. The discrepancy between fire occurrence and fire risk by FFDWR (Forest Fire-Danger Weather Rating, a method issued by the National Meteorological Bureau, that is used to predict forest fire probability through links between forest fire occurrence and weather variables) in the northern part is more obvious than that in the southern part. Great discrepancy has emerged between fire danger predicted by the method and actual fire occurrence in recent years since a strict firebrand prohibition policy has significantly reduced firebrands in the region. A probabilistic method predicting fire probability by introducing an Ignition Component (IC) in the National Fire Danger Rating System (NFDRS) adopted in the United States to depict effects of both firebrand and weather-fuel complex on fire occurrence is developed to solve the problem. The suitability and accuracy of the new method in the region were assessed. Results show that the method is suitable in the region. IC or the modified IC can be adopted to depict the effect of the weather-fuel complex on fire occurrence and to rate fire danger for periods with fewer firebrands. Fire risk classes and corresponding preparedness level can be determined from IC in the region. Methods of the same principle could be established to diminish similar discrepancy between actual fire occurrence and fire danger in other countries.