Prediction models and changing rules of dead fuel moisture content of 8 forest species in Beijing area
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摘要:
目的森林可燃物含水率对林火的发生蔓延，尤其是对森林火灾火行为影响重大，可燃物含水率预测模型在预报火灾和预测林火行为方面作用显著。 方法对北京地区8种常见森林树种防火期内可燃物含水率连续测定，分析不同树种不同种类可燃物含水率与当期和前期气象因子间的关系。选择影响程度较大的当期和前期气象因子为自变量建立可燃物含水率的预测模型，并在此基础上定量分析可燃物含水率的日变化和整个防火期内的变化规律。 结果不同树种可燃物含水率存在显著差异，8个树种平均可燃物含水率由大到小依次为：栓皮栎 > 槲栎 > 榆树 > 刺槐 > 五角枫 > 侧柏 > 油松 > 落叶松。不同种类可燃物含水率存在显著差异，可燃物含水率总体上表现为阔叶树大于针叶树，枯叶和枯枝1 hr大于枯枝10 hr和100 hr。枯叶和枯枝1 hr主要受当期气象因子影响，而枯枝10 hr和100 hr主要受前期气象因子影响。所建立的32个线性预测模型各检验指标显示模型拟合效果好。可燃物含水率日变化表现为夜间高白天低，夜间稳定白天变幅大，06:00—08:00达到最大值，而后急剧下降，12:00—14:00左右达到全天最低值。防火期内，可燃物含水率呈现出先上升后下降趋势，11月可燃物含水率较低，但在缓慢增加，12月至次年1月含水率较高，而3月初至4月底可燃物含水率保持很低状态。 结论不同种类不同类型可燃物含水率预测模型精度较高，可为防火工作提供理论支撑，可以实践运用。北京地区3月份和日内中午时间干燥多风，温度较高，可燃物含水率达到很低的状态，森林火险等级较高，应加强管理。 Abstract:ObjectiveThe forest fuel moisture content has great impact on the occurrence and spread of forest fire, particularly important on the fire behavior, and its prediction forecast models have significant effects on predicting forest fire and forest fire behavior. MethodThrough the continuous determination of dead fuel moisture content of 8 kinds of forest trees in Beijing area during the period of fire prevention, we researched the relationship between fuel moisture content and the current and previous meteorological data, and established the prediction models by selecting the meteorological factors, which has great influence on the fuel moisture content. On this basis, we quantitatively analyzed the diurnal variation and fire protection period variation of the fuel moisture content. ResultThe fuel moisture content of different tree species was significantly different, from descending order was Quercus variabilis, Q. aliena, Ulmus pumila, Robinia pseudoacacia, Acer truncatum, Platycladus orientalis, Pinus tabuliformis, Larix principis-rupprechtii. And the fuel moisture content of different types was also significantly different. Generally the broadleaf tree’s fuel moisture content was higher than that of coniferous trees, and the fuel moisture content of dead leaves and 1 hr dead branches were higher than 10 hr and 100 hr. That of 1 hr of dead branches was mainly affected by the current meteorological factors, while that of 10 hr and 100 hr of dead branches were affected by the early meteorological factors. The test indexes of 32 linear prediction models showed that the fitting effect was perfect. The diurnal variation of the fuel moisture content was higher and more stable at night, lower and varied greatly during the day, which peaked at 06:00−08:00, then dropped sharply, and later reached the lowest value at about 12:00−14:00. During the fire protection period, the fuel moisture content showed a trend of rising first, then decreasing. It was low in November but increased slowly and reached a high level from December to January of the following year. From early March to the end of April, the fuel moisture content kept a very low level. ConclusionHigh-precision prediction methods of different tree species and among different fuel types could offer theoretical support for forest fire prevention, which can be used in practice. In March and at noon time in Beijing, it,s windy, drying and hot and the fuel moisture content is low, so the fire management should be reinforced in such a fire danger period. -
Key words:
- fuel moisture content /
- period of fire prevention /
- prediction model /
- change rule
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图 1 可燃物含水率与气象因子关系
Figure 1. Relations between fuel moisture content and meteorological factors
图 4 不同树种不同种类可燃物含水率日变化预测
Figure 4. Diurnal variation prediction of fuel moisture content of different tree species and different fuel types
图 5 不同种类不同树种可燃物含水率防火期变化预测
Figure 5. Variation prediction of fuel moisture content of different tree species and different fuel types during fire prevention period
表 1 不同树种可燃物含水率显著性分析
Table 1. Significance analysis on the fuel moisture content of different tree species
项目
Item平方和
Sum of
squares自由度
Degree of freedom均方
Mean squaresF 显著性
Significance组间 Intergroup 2 121.117 7 303.017 52.288 0 组内 Intragroup 6 252.933 1 079 5.795 总计
Total8 374.050 1 086 
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表 2 不同种类可燃物含水率显著性分析
Table 2. Significance analysis on the fuel moisture content of different fuel types
项目
Item平方和
Sum of
squares自由度
Degree of freedom均方
Mean squaresF 显著性
Significance组间
Intergroup11 085.522 3 3 695.174 554.101 0 组内
Intragroup3 594.471 539 6.669 总计
Total14 679.993 542
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表 3 可燃物含水率与气象因子Pearson相关系数
Table 3. Pearson correlation coefficients of fuel moisture content and meteorological factors
种类
Type当期和前期气象因子
Current and previous
meteorological factor相关系数 Correlation coefficient 榆树
Ulmus pumila槲栎
Quercus aliena刺槐
Robinia pseudoacacia油松
Pinus tabuliformis五角枫
Acer truncatum华北落叶松
Larix principis-rupprechtii栓皮栎
Quercus variabilis侧柏
Platycladus orientalis枯叶Dead leaf 温度 Temperature − 0.747** − 0.726** − 0.790** − 0.617** − 0.415** − 0.709** − 0.491** − 0.816** 湿度 Humidity 0.637** 0.445** 0.676** 0.390** 0.374** 0.363** 0.386** 0.440** 风速 Wind speed − 0.570** − 0.385** − 0.568** − 0.352** − 0.347** − 0.375** − 0.273** − 0.353** 前2 h平均温度
Average temperature of former 2 hours− 0.652** − 0.679** − 0.699** − 0.565** − 0.333** − 0.672** − 0.432** − 0.780** 前2 h平均相对湿度
Average relative humidity of former 2 hours0.498** 0.364** 0.565** 0.285** 0.249** 0.266** 0.266** 0.337** 前2 h平均风速
Average wind speed of former 2 hours− 0.158 − 0.033 − 0.156 − 0.027 − 0.037 − 0.028 0.045 0.017 1 hr 温度 Temperature − 0.563** − 0.565** − 0.433** − 0.554** − 0.488** − 0.581** − 0.665** − 0.682** 湿度 Humidity 0.433** 0.403** 0.329** 0.526** 0.374** 0.528** 0.515** 0.567** 风速 Wind speed − 0.426** − 0.371** − 0.126 − 0.451** − 0.265** − 0.335** − 0.362** − 0.521** 前2 h平均温度
Average temperature of former 2 hours− 0.530** − 0.491** − 0.349** − 0.460** − 0.420** − 0.497** − 0.596** − 0.575** 前2 h平均相对湿度
Average relative humidity of former 2 hours0.355** 0.313** 0.246** 0.404** 0.253** 0.414** 0.414** 0.479** 前2 h平均风速
Average wind speed of former 2 hours− 0.102 − 0.044 − 0.032 − 0.107 0.017 − 0.113 − 0.048 − 0.145 10 hr 温度 Temperature − 0.477** − 0.454** − 0.457** − 0.397** − 0.475** − 0.359** − 0.405** − 0.392** 湿度 Humidity 0.451** 0.392** 0.293** 0.389** 0.409** 0.135 0.328** 0.339** 风速 Wind speed − 0.227** − 0.201* − 0.145 − 0.120 − 0.127 0.029 − 0.105 − 0.149 前20 h平均温度
Average temperature of former 20 hours− 0.361** − 0.316** − 0.324** − 0.302** − 0.387** − 0.301** − 0.305** − 0.384** 前20 h平均相对湿度
Average relative humidity of former 20 hours0.507** 0.451** 0.369** 0.434** 0.421** 0.274** 0.366** 0.421** 前20 h平均风速
Average wind speed of former 20 hours− 0.179* − 0.147 − 0.165 − 0.125 − 0.085 − 0.067 − 0.117 − 0.147 100 hr 温度 Temperature − 0.155 − 0.329** − 0.195* − 0.361** − 0.156 − 0.138 − 0.402** − 0.366** 湿度 Humidity 0.167 0.310** 0.238** 0.163 0.229** 0.213* 0.350** 0.369** 风速 Wind speed − 0.076 − 0.116 − 0.168 − 0.118 − 0.111 − 0.080 − 0.152 − 0.139 前100 h平均温度
Average temperature of former 100 hours− 0.387** − 0.381** − 0.288** − 0.489** − 0.269** − 0.234** − 0.510** − 0.339** 前100 h平均相对湿度
Average relative humidity of former 100 hours0.378** 0.469** 0.572** 0.594** 0.658** 0.583** 0.496** 0.376** 前100 h平均风速
Average wind speed of former 100 hours− 0.111 − 0.078 − 0.148 − 0.139 − 0.163 − 0.163 − 0.153 − 0.177* 注：“*”和“**”分别表示0.05和0.01水平下相关性显著。Notes:* and ** mean significant correlations at P < 0.05 level and P< 0.01 level, respectively.
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表 4 可燃物含水率预测模型变量选择
Table 4. Prediction model variables of fuel moisture content
可燃物种类
Fuel type变量选择 Variable selection 当期气象因子 Current meteorological factor 前期气象因子 Previous meteorological factor 枯叶
Dead leaf温度
Temperature相对湿度
Relative humidity风速
Wind speed前2 h平均温度
Average temperature of former 2 hours前2 h平均相对湿度
Average relative humidity of former 2 hours前2 h平均风速
Average wind speed of former 2 hours
1 hr温度
Temperature相对湿度
Relative humidity风速
Wind speed前2 h平均温度
Average temperature of former 2 hours前2 h平均相对湿度
Average relative humidity of former 2 hours前2 h平均风速
Average wind speed of former 2 hours
10 hr温度
Temperature相对湿度
Relative humidity风速
Wind speed前20 h平均温度
Average temperature of former 20 hours前20 h平均相对湿度
Average relative humidity of former 20 hours前20 h平均风速
Average wind speed of former 20 hours
100 hr温度
Temperature相对湿度
Relative humidity风速
Wind speed前100 h平均温度
Average temperature of former 100 hours前100 h平均相对湿度
Average relative humidity of former 100 hours前100 h平均风速
Average wind speed of former 100 hours
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表 5 可燃物含水率模型参数及检验指标值
Table 5. Prediction model parameters of fuel moisture content and verification indices
树种 Tree species 类型 Type b0 b1 b2 b3 b4 b5 b6 R2 MAE MRE 榆树 Ulmus pumila 枯叶 Dead leaf − 1.273 − 0.029 0.021 − 0.251 0.012 − 0.015 0.202 0.776 2.83 13.44 1 hr − 1.558 0.007 0.007 − 0.158 − 0.012 − 0.003 0.123 0.418 2.26 11.31 10 hr − 1.888 − 0.008 − 0.001 0.049 0.003 0.005 − 0.014 0.454 1.05 6.47 100 hr − 2.362 0.010 0.005 0.043 − 0.016 0.004 0.017 0.343 1.53 12.69 槲栎 Quercus aliena 枯叶 Dead leaf − 1.237 − 0.008 0.001 − 0.04 0.002 0.000 0.043 0.559 1.62 6.11 1 hr − 1.551 − 0.018 0.001 − 0.076 0.012 − 0.002 0.075 0.422 1.62 9.02 10 hr − 1.833 − 0.013 − 0.004 0.042 0.008 0.005 − 0.012 0.428 1.11 7.01 100 hr − 2.158 − 0.002 0.003 0.026 − 0.001 0.004 0.057 0.421 0.82 5.60 刺槐 Robinia pseudoacacia 枯叶 Dead leaf − 1.141 − 0.013 0.009 − 0.088 0.005 − 0.004 0.076 0.778 1.92 6.45 1 hr − 1.793 − 0.024 0.006 0.127 0.018 − 0.005 − 0.088 0.405 0.95 6.11 10 hr − 1.86 − 0.029 − 0.011 0.083 0.02 0.008 − 0.078 0.456 1.42 11.91 100 hr − 2.629 − 0.003 0.002 − 0.006 − 0.002 0.011 0.116 0.411 1.56 13.98 油松 Pinus tabuliformis 枯叶 Dead leaf − 1.439 − 0.007 0.005 − 0.041 0.003 − 0.004 0.041 0.44 1.42 6.65 1 hr − 1.648 − 0.017 0.012 − 0.122 0.013 − 0.009 0.113 0.498 1.94 10.71 10 hr − 2.235 − 0.012 0.001 0.116 0.004 0.007 − 0.027 0.376 1.56 12.47 100 hr − 2.375 − 0.004 − 0.002 0.012 − 0.004 0.008 0.040 0.578 0.76 6.76 五角枫 Acer truncatum 枯叶 Dead leaf − 1.353 − 0.018 0.012 − 0.146 0.016 − 0.012 0.138 0.370 2.69 11.84 1 hr − 1.69 − 0.012 0.01 − 0.019 0.008 − 0.008 0.043 0.359 1.47 8.33 10 hr − 2.162 − 0.009 0.002 0.100 0.001 0.005 − 0.009 0.423 1.36 9.74 100 hr − 2.391 − 0.001 0.001 0.008 − 0.001 0.006 0.054 0.514 0.67 5.64 落叶松 Larix principis-rupprechtii 枯叶 − 1.395 − 0.014 0.004 − 0.096 0.002 − 0.004 0.082 0.547 2.14 12.2 1 hr − 1.967 − 0.016 0.015 0.090 0.009 − 0.009 − 0.059 0.504 1.15 8.46 10 hr − 1.963 − 0.012 − 0.006 0.070 0.006 0.005 − 0.036 0.358 0.92 7.05 100 hr − 2.510 − 0.002 0.003 0.033 − 0.002 0.01 0.078 0.404 1.64 12.88 栓皮栎 Quercus variabilis 枯叶 Dead leaf − 1.447 − 0.005 0.011 − 0.052 0.002 − 0.008 0.075 0.371 1.94 8.39 1 hr − 1.573 − 0.011 0.008 0.009 0.004 − 0.004 0.016 0.535 1.42 7.24 10 hr − 1.644 − 0.007 − 0.001 0.046 0.003 0.003 − 0.019 0.331 1.08 5.36 100 hr − 2.221 − 0.001 0.004 0.047 − 0.006 0.005 0.036 0.509 1.09 7.64 侧柏 Platycladus orientalis 枯叶 Dead leaf − 1.300 − 0.013 0.008 − 0.019 − 0.002 − 0.005 0.044 0.707 2.05 8.90 1 hr − 1.597 − 0.040 − 0.004 − 0.145 0.030 0.003 0.114 0.652 1.58 10.39 10 hr − 2.078 0.001 0.002 0.070 − 0.008 0.005 − 0.016 0.358 1.33 8.80 100 hr − 2.349 − 0.005 0.004 0.046 0.001 0.004 0.007 0.357 0.91 7.88
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