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 Rothermel model, which has been widely used to predict the rate of forest fire spread, has errors that restrict its ability to reflect the actual rate of spread (ROS). In this study, the fuels from seven typical tree species in the Karst ecosystems in southern China were considered as the research objects. Through indoor burning simulation, three methods, namely directly using the Rothermel model, re-estimating the parameters of the Rothermel, and reforming the model, were evaluated for applicability in Karst ecosystems. We found that the direct use of the Rothermel model for predicting the ROS in the Karst ecosystems is not practical, and the relative error can be as high as 50%. However, no significant differences between the prediction effect of re-estimating the parameters of the Rothermel and the reformed model were found, but the reform model showed more evident advantages of being simpler, and the errors were lower. Our research proposes a new method that is more suitable for predicting the rate of forest fire spread of typical fuels in Karst ecosystems under flat and windless conditions, which is of great significance for further understanding and calculating the ROS of forest fires in the region.

Background: Forest fire risk predictions are based on the most conservation daily predictions, and the lowest litter moisture content of each day is often used to predict the day’s fire risk. Yunnan Province is the area with the most frequent and serious forest fires in China, but there is almost no research on the dynamic changes and model predictions of the litter moisture content in this area. Therefore, to reduce the occurrence of forest fires and improve the accuracy of forest fire risk predictions, it is necessary to understand these dynamic changes and establish an appropriate prediction model for the typical litter moisture content in Yunnan Province.Method: During the fire prevention period, daily dynamic changes in the litter moisture content are obtained by monitoring the daily step size, and the relationships between the litter moisture content and meteorological elements are analyzed. In this study, the meteorological element regression method, moisture code method and direction estimation method are selected to establish litter moisture content prediction models, and the applicability of each model is analyzed.Results: We found that dynamic changes in the litter moisture content have obvious lags compared with meteorological elements, and the litter moisture content is mainly related to the air temperature, relative humidity and wind speed. With an increase in the sampling interval of meteorological elements, the significances of these correlations first increase and then decrease. The moisture content value obtained by directly using the moisture code method in the Fire Weather Index (FWI) significantly different from the measured value, so this method is not applicable. The mean absolute error (MAE) and mean relative error (MRE) values obtained with the meteorological element regression method are 2.97% and 14.06%, those from the moisture code method are 3.27% and 14.07%, and those from the direct estimation method are 2.82% and 12.76%, respectively.Conclusions: The direct estimation method has the lowest error and the strongest extrapolation ability; this method can meet the needs of daily fire forecasting. Therefore, it is feasible to use the direct estimation method to predict litter moisture contents in Yunnan Province.

As a cigarette butt falls onto the forest surface fuel, it first smolders the fuel, then ignites into flames, and spreads as forest fire under certain conditions. In this study, the needles under a typical stand of P. massoniana were used as the research object. Needle beds with different moisture content and packing ratios were constructed indoors. Cigarette butt-ignition experiments were conducted under different wind velocities, and 30 experiment cycles were conducted under different conditions. There was a total of 5 (packing ratio) × 4 (moisture content) × 6 (wind velocity) = 120 sets of conditions, and a total of 3600 ignition experiments were conducted. The results showed that (1) the total ignition probability of the cigarette butts was 2.36%, which only occurred when the fuelbed moisture content was 1 m/s. The ignition time of cigarette butts ranged from 2.73 to 7.25 min. (2) The fuelbed moisture content and wind velocity significantly influenced the ignition probability and time. With an increase in moisture content, the ignition probability of cigarette butts decreased, while the time required for ignition showed an increasing trend. Wind velocity had a dual effect on ignition. The ignition effect was optimal at a wind velocity of 4 m/s. With an increase in wind velocity, the ignition probability first increased and then decreased, and the ignition time first decreased and then increased. (3) The packing ratio had no significant effect on the ignition probability; however, the ignition time significantly decreased as the packing ratio increased. (4) The logistic regression method (LRM), general linear method (GLM), and nonlinear regression method (NLM) were used to establish a prediction model of ignition probability. The prediction effect of GLM was the worst, followed by LRM, and the NLM had the best prediction effect. The GLM was selected to establish the ignition time model, and the error was also within the allowance range. This study elucidated the underlying mechanism of factors affecting cigarette butt-based fuel ignition. In addition, the established prediction model provides a reference for human-caused forest fires and is highly significant for forest fire prevention.

Flammable litter such as Pinus koraiensis needle accumulation increases the risk of wildfire. In the event of a high-intensity fire, forest resources can be severely damaged. To reduce the occurrence of forest fires, it is important to reduce loads and modify structures. This study conducted 270 indoor degradation experiments to determine physicochemical properties of Pinus koraiensis during the combustion degradation process. Combustion degradation treatment variables were constructed with different durations, Trichoderma fungi, and doses. The results show that the physicochemical properties of flammable litter changed significantly after degradation, with a maximum degradation rate of 11. The degradation rate was affected by time and microbial agents, but there was no significant difference between different doses. Principal component analysis was used to determine overall combustibility, and it was found that a dose of 4 mL of Trichoderma harzianum had the best effect on degradation for 42 days, reducing combustibility by 203%. It was found that the 6ml composite mould had the best inhibitory effect on fire spread rate, reaching the lowest value. After 42 days, the flame intensity of 4 mL Trichoderma harzianum reached its lowest value of 57.17 kw/m, which represents a decrease of 54% compared to the initial value. Similarly, the flame’s length reached its lowest value of 4.91 cm, which represents a decrease of 31% compared to the same period last year. The aim of this study is to establish the relationship between time, microbial agents, dosage, flammable physical and chemical properties, overall flammability, and potential fire behaviour. The values of the goodness-of-fit index and the comparative fit index are both >0.98, and the values of the standardised root mean square residual and the approximate root mean square error are both <0.05. This study has a positive effect on accelerating the decomposition of combustibles, reducing the content of flammable components, reducing flammability and potential fire behaviour, and reducing the risk of forest fires. It is of great significance for strengthening natural resource management and forest ecological conservation.

Forest fire have a serious impact on forest ecosystems, the safety of people’s lives and property, and social stability. The height of surface flames, as the main indicator of forest fire behavior, which is an important parameter for forest fire management. The relationship between fireline intensity and flame height proposed by Byram has been widely used in estimating flame height; however, its applicability to the surface fuel of typical forest stands in the Yunnan–Guizhou Plateau of China has not yet been analyzed. In this study, the surface fuel in the area was taken as the research object, and the flame height of different fuel bed characteristics was measured through an indoor burning experiment. The applicability of three methods—the directly used Byram’s model, corrected model, and re-established prediction model—was analyzed to estimate the flame height in the Yunnan–Guizhou Plateau. We found that the flame height of the typical forest stands in the Yunnan–Guizhou Plateau ranged from 0.05 to 1.2 m and was significantly affected by the moisture content, load, and height of the fuel bed. Although the fireline intensity exhibited a significant linear relationship with the flame height, directly using Byram’s method to predict the flame height of surface fires was impractical, as its mean prediction error exceeded 150%. The mean relative errors of the prediction model obtained by modifying Byram’s method and that based on the characteristics of the fuel bed were both within 15%, which is significantly lower than that of the original Byram’s method. Based on the results of this study, we propose two methods that are suitable for predicting the flame height of surface fires in the typical forests of the Yunnan–Guizhou Plateau in China, which is of great significance for further understanding the relationship between flame height, fireline intensity, and scientific forest fire management.