With the development of computer technology, forest fire spread simulation using computers has gradually developed. According to the existing research on forest fire spread, the models established in various countries have typical regional characteristics. A fire spread model established in a specific region is only suitable for the local area, and there is still a great deal of uncertainty as to whether or not the established model is suitable for fire spread simulation for the same fuel in other regions. Although many fire spread models have been established, the fuel characteristics applicable to each model, such as the fuel loading, fuel moisture content, combustibility, etc., are not similar. It is necessary to evaluate the applicability of different fuel characteristics to different fire spread models. We combined ground investigation, historical data collection, model improvements, and statistical analysis to establish a multi-model forest fire spread simulation method (FIRER) that shows the burning time, perimeter, burning area, overlap area, and spread rate of fire sites. This method is a large-scale, high-resolution fire growth model based on fire spread in eight directions on a regular 30 m grid. This method could use any one of four different physical models (McArthur, Rothermel, FBP, and Wang Zhengfei (China)) for fire behavior. This method has an option to represent fire breaks from roads, rivers, and fire suppression. We can evaluate which model is more suitable in a specific area. This method was tested on a single historical lightning fire in the Daxing’an Mountains. Different scenarios were tested and compared: using each of the four fire behavior models, with fire breaks on or off, and with a single or suspected double fire ignition location of the historical fire. The results show that the Rothermel model is the best model in the simulation of the Hanma lightning fire; the overlap area is 5694.4 hm². Meanwhile, the real fire area in FIRER is 5800.9 hm²; both the Kappa and Sørensen values exceed 0.8, providing high accuracy in fire spread simulations. FIRER performs well in the automatic identification of fire break zones and multiple ignited points. Compared with FARSITE, FIRER performs well in predicting accuracy. Compared with BehavePlus, FIRER also has advantages in simulating large-scale fire spread. However, the complex data preparation stage of FIRER means that FIRER still has great room for improvement. This research provides a practical basis for the comparison of the practicability and applicability of various fire spread models and provides more effective practical tools and a scientific basis for decision-making and the management of fighting forest fires.

Characterizing changes in the soil particle-size distributions (PSD) are a major issue in environmental research because it has a great impact on soil properties, soil management, and desertification. To date, the use of soil volume fractal dimension (D) is a feasible approach to describe PSD, and its calculation is mainly dependent on subdivisions of clay, silt, sand fractions as well as different soil particle-size classification (PSC) systems. But few studies have developed appropriate research works on how PSC systems affect the calculations of D. Therefore, in this study, topsoil (0–5 cm) across nine forest density gradients of Pinus sylvestris var. mongolica plantations (MPPs) ranging from 900–2700 trees ha^–1 were selected in the Mu Us sandy land, China. The D of soil was calculated by measuring soil PSD through fractal model and laser diffraction technique. The experimental results showed that: (1) The predominant PSD was distributed within the sand classification followed by clay and silt particle contents, which were far less prevalent in the study area. The general order of D values (Ds) was USDA (1993) > ISO14688 (2002) > ISSS (1929) > Katschinski (1957) > China (1987) > Blott & Pye (2012) PSC systems. (2) Ds were significantly positively related to the contents of clay and silt, and Ds were significantly negatively to the sand content. Ds were susceptible to the MPPs establishment and forest densities. (3) Ds of six PSC systems were significantly positive correlated, which indicated that they not only have difference, but also have close connection. (4) According to the fractal model and descriptions of soil fractions under different PSC systems, refining scales of clay and sand fractions could increase Ds, while the refining scale of silt fraction could decrease Ds. From the conclusions above, it is highly recommended that USDA (1993) and Blott & Pye (2012) PSC systems be used as reliable and practical PSC systems for describing and calculating D of soil PSD.

Background: The prediction accuracy for the rate of surface fire spread varies in different regions; thus, increasing the prediction accuracy for local fuel types to reduce the destructive consequences of fire is critically needed. Aims: The objective of this study is to improve the Rothermel model’s accuracy in predicting the ROS for surface fuel burning in planted forests of Pinus koraiensis in the eastern mountains of north-east China. Methods: Fuel beds with various fuel loads and moisture content was constructed on a laboratory burning bed, 276 combustion experiments were performed under multiple slope conditions, and the ROS data from the combustion experiments were used to modify the related parameters in the Rothermel model. Results: The surface fire spread rate in Pinus koraiensis plantations was directly predicted using the Rothermel model but had significant errors. The Rothermel model after modification predicted the following: MRE = 25.09%, MAE = 0.46 m min−1, and R2 = 0.80. Conclusion: The prediction accuracy of the Rothermel model was greatly enhanced through parameter tuning based on in-lab combustion experiments Implications: This study provides a method for the local application of the Rothermel model in China and helps with forest fire fighting and management in China.

Traditional wildfire fuel management faces critical barriers due to high cost, carbon emissions, and operational risks. While biochar technology offers a solution, the poor awareness of forest fuel biochar hinders its global implementation. Here we produced biochar from boreal and temperature forest surface fuels. Large-scale characterization revealed its composition, performance, and the chemical and molecular changes of the carbon components. The pyrolysis mechanism was clarified, and advanced analysis was integrated to predict functions and quantify the relationships between raw material, pyrolysis conditions, biochar properties, and functions. It was demonstrated that fuel biochar has important functions in mitigating greenhouse benefits, improving soil, and pollution control. The proposed conversion strategy enables permanent carbon dioxide sequestration of at least 383.61-712.18 kg per ton of fuel. We conclude that biochar represents an innovative alternative to conventional fuel management for more effective mitigation of both wildfires and climate warming.

The Daxinganling Region, in Heilongjiang Province, China, has experienced considerable losses to forest resources owing to a recent increase in forest fire frequency. This necessitates the predictions of fire behaviour in this region, which requires assessment of fuel moisture content (FMC) at appropriate space and time intervals. Here, we compare and extrapolate results of vapour-exchange methods for predicting hourly moisture contents of downed wood. The FMC of larch and birch twig fuels was measured at 1-h intervals at different slope positions with respect to meteorological factors. The twigs were categorised based on diameter and degree of decay. The Nelson and Simard methods (which consider equilibrium moisture content and the associated time lag) and direct regression method (which allows direct attainment of the FMC) were used. Both Nelson and Simard methods predicted hourly twig moisture content more accurately than the direct regression method. The Simard method was the most accurate, with the lowest mean absolute error and mean relative error as well as relatively small variation coefficients based on results of the extrapolation analysis. Further, the resulting models applied to needle-leaved and lightly decomposed fuels performed better than for the broad-leaved and badly decomposed fuels on evaluation parameters.

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.