The key challenges of the wildfire firefighting were long-distanced and high-lifted fire events and limited water access in wildlands. This article proposed a new low-flow and high-lift firefighting approach for the application of wildfire near transmission lines. To solve the challenges, we developed a comprehensive firefighting equipment set which consisted of a high-effective suppressant agent with properties to prevent reignition and a mobile firefighting platform with long-distance and high-lift features. The liquid suppression agent improved the effectiveness of fire suppression while reducing the consumption of water significantly. As the hydraulic flow was decreased for a given volume of water, the hydraulic pressure was increased. In this way, the platform can produce a hydraulic pressure over 120 bar for an effective lift of 500 m. The results of field experiments demonstrated that the proposed approach is able to control wildfires over a long distance and high lift, which proved the effectiveness of the approach.
Wildfire is a large-scale complex system. Insight into the mechanism that drives wildfires can be revealed by the distribution of the wildfire over a large time scale, which is one of the important topics in wildfire research. In this study, the scaling properties of four meteorological factors (relative humidity, daily precipitation, daily average temperature, and maximum wind speed) that can affect wildfires (number of wildfires per day) were investigated by using the detrended fluctuation analysis method. The results showed that the time series for these meteorological factors and wildfires have similar power exponents and turning points for the power exponents curve. The five types of time series have a lasting and steady long-range power law correlation over a certain time scale range, where the corresponding exponents were 0.6484, 0.5724, 0.8647, 0.7344, and 0.6734, respectively. They also have a reversible long-range power law correlation beyond a certain time scale, where the corresponding exponents are 0.3862, 0.2218, 0.1372, 0.2621, and 0.2678. The multifractal detrended fluctuation analysis results showed that the wildfire time series were multifractal. The results of the research based on the detrended cross-correlation analysis and the multifractal detrended cross-correlation analysis showed that relative humidity and daily precipitation have a considerable impact on the wildfire time series, while the impacts of daily average temperature and the maximum wind speed are relatively small. This study showed that identifying the factors causing the inherent volatility in the wildfire time series can improve understanding of the dynamic mechanism controlling wildfires and the meteorological parameters. These results can also be used to quantify the correlation between wildfire and the meteorological factors investigated in this study.
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