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A modified model of direct estimation method for fine fuel moisture content prediction by considering crown density

机译:考虑冠密度的细燃料水分含量预测的直接估计方法改造模型

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Moisture content of forest fine fuel is one of the most important factors for forest fire risk assessment and fire spread prediction. The weather parameters above the fuel surface used in Catchpole's existing Direct Estimation Model are not suitable for forecast. The crown density of the forest area in the model, which may has great influence to the fine fuel moisture content in the forest, is not considered. A series of outdoor experiments were carried out in order to study the effect of the crown density, including 3 simulated crown densities and 2 real tests. In the experiments, the collected Pinus Sylvestris needles in the Da Hinggan Mountains of China are used. The dynamic variations of the weights of the needles are captured in 0.5 h or 1 h interval, and the dry weights of them are measured after 24 h kiln dry. During the experiments, the local meteorological data including the temperature, the humidity and the winds velocity, are recorded from the homepage of Weather China at the same time. Based on the experiments, a modified model for fine fuel moisture content prediction is achieved, in which the crown density is used to adjust the temperature and the humidity near the fuel surface. The comparison results show that under different conditions of crown densities, the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) of the modified model are decreased significantly, and the Mean Absolute Percentage Errors (MAPE) for different crown densities are all less than 6%. The contrast validation between forest field observation and the prediction values of the modified method indicates that the absolute errors are less than 10%. This modified method can effectively reduce the prediction errors due to different crown densities; meanwhile, the calculation is using meteorological forecast data directly, so it has better applicability.
机译:森林精细燃料的水分含量是森林火灾风险评估和火灾传播预测最重要的因素之一。在捕获的现有直接估计模型中使用的燃料表面上方的天气参数不适合预测。该模型中森林面积的冠密度可能对森林中的细燃料水分含量产生很大影响,不考虑。进行了一系列户外实验,以研究冠密度的效果,包括3个模拟表冠密度和2个真实测试。在实验中,使用了中国大望日山脉的Contined Pinus Sylvestres。针的动态变化以0.5小时或1小时间隔捕获,并且在干燥24小时后测量它们的干重。在实验期间,包括温度,湿度和风速的局部气象数据是从天气中国的同时记录的。基于实验,实现了用于精细燃料水分含量预测的修改模型,其中冠密度用于调节燃料表面附近的温度和湿度。比较结果表明,在冠密度的不同条件下,修改模型的平均绝对误差(MAE)和根均方误差(RMSE)显着降低,不同冠密度的平均绝对百分比误差(MAPE)是所有小于6%。森林场观察与修改方法的预测值之间的对比度验证表明绝对误差小于10%。由于不同的冠密度,这种改进的方法可以有效地降低预测误差;同时,计算是直接使用气象预测数据,因此它具有更好的适用性。

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