Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/65941
標題: 臺中港防風林區林火行為之研究
Fire Behavior of Wind-break Forests at Taichung Harbor, Taiwan
作者: 盧守謙
Lu, Sohu-Chien
關鍵字: Taichung Harbor
臺中港
Casuarina spp.
Fuel type
Fire behavior
ROS
FWI
BEHAVEplus
木麻黃
燃料型
林火行為
林火擴展速率
林火氣象指數
林火行為模擬軟體
出版社: 森林學系所
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摘要: 林火行為模式具有統計學上意義,並為合乎邏輯之一種工具,能提供林火行為研究之指南。可靠之林火行為預測,已成為天然資源管理者越來越重要之管理方法,不僅能供作主管機關進行管理決策及資源經營最佳化,亦能達到自然生態破壞之最小化目的。本研究目標在瞭解臺中港防風林區之林火行為,藉由林火氣象指數、燃料量調查、電腦模擬、實驗室及田野火燒等項目,分析林火環境中氣象與燃料因子,進行一系列林火行為探討工作。 本研究使用加拿大FWI系統7種指數來分析臺中港防風林區近20年期間之林火氣象值,其於林區枯落層及分解層燃料含水率,發現地表已有較乾燥之趨勢;以logistic模式建構臺中港防風林區林火發生機率及林火危險等級,於20年期間屬極端林火危險率有11.6%,火線強度達到4,000 KW/m以上;而每年於9月至翌年1月是林火危險率較高峰期,其中最高峰為10月份。 以樣區與樣線複合式調查法進行地面燃料量調查,並完成灌木型、草本型、無地被型及綜合型等4種燃料型資料庫,其中枯枝落葉暨分解層平均燃料量為17.68 t/ha。另在燃料量推估上,除枯枝落葉層與分解層燃料量無法由其厚度建立外,分別利用植株高、冠幅及覆蓋度作為參數,建立5種地表燃料量推估式,推估式估測目前臺中港防風林區地表燃料量介於21.12-31.66 t/ha之間。 實驗室火燒方面,確認氣象與燃料因子對林火行為各自影響程度,經實驗顯示風速1 m/ s時火燒前進動力由熱浮力流之燃料因子所主導(Fc2=0.18, Nc=8.33),至風速3 m/ s時火燒已由氣象因子(風速)慣性力量所主導(Fc2=1.04, Nc=0.49)。而火燒擴展速率(ROS)於風速3 m/s時比無風速情況可達7倍差異。在燃料因子以不同燃料量對ROS影響分布可分三區域,依序從線性關係強弱程度至獨立狀態;於燃料低含水率(7.5%)與高含水率(17.0%)比較,前者燃料質量損失率較快(二者差1.5倍)且火燒溫度亦加速上昇(差1.35倍)。除此,另以Rothermel模式預測上述燃料量及風速亦呈現類似結果。 電腦模擬使用BEHAVEplus依林區4燃料型特徵差異量,在不同氣象因子情況進行模擬,呈現出不同程度之各種林火行為表現,並劃分3林火指標燃料等級,顯示臺中港防風林區79%屬於中度以上林火指標等級。在標準化燃料型比對方面,在較低風速(≦2.25 m/s)時防風林區灌木燃料型與BEHAVEplus TU5(灌木型)能合理作替代使用(R2=0.95, p<0.001)。 田野火燒方面,經實施夏季及冬季不同季節之試驗,火燒規模以林區地表引燃後自由燃燒18 min截止,火燒所紀錄燃料、氣象及林火行為參數進行迴歸等分析,建立林火行為相關統計預測模式,並進行統計值、實測值與其預測值比較,結果顯示BEHAVEplus系統在預測ROS(R2=0.85)可令人接受,但在火燒面積周長(R2=0.52)、逆風火擴展速率(R2=0.50)及火焰長度(R2=0.56)出現較多偏差;另FBP系統預測ROS及火線強度出現較大高估或低估現象,但在預測火燒面積周長及火燒面積長寬比方面,則優於BEHAVEplus系統。
Forest fire behavior model is a logically and statistically significant tool that can be used as a useful guide for fire behavior study and provids reliable predictions for natural resource managers to make decisions on fire suppression activities to minimize damages. The purpose of this study is to investigate the fire behavior of windbreak forests in the Taichung Harbor of Taiwan, focusing on the effects of weather and fuel factors. The research was conducted by fire danger rating, fuel model building, computer simulation, laboratory testing, and field burning testing. A series of forest fire behavior has been analyzed and classified. In the fire danger rating, 7 indicators of Canadian FWI System were adapted to analyze the fire weather data of Taichung Harbor in the past 20 years. In addition, fuel moisture content of litter and duff layer were also adopted in this model to predict fire danger rating distribution in windbreak forest of Taichung Harbor. Results of analysis show that 11.6% of time in this period can be classified as the extreme fire danger. The fire intensity could be more than 4,000 kW/m. The highest rate of forest fire danger occurs in the duration from September to Januaryof next year, and the highest peaks in October. Fuel survey was conducted by mixing 10 m×10 m sampling plots and line-intersect sampling, based on geographical features of the windbreak area in Taichung Harbor. The whole area was divided into 4 blocks, and a total of 33 samples of ground fuel were gathered, and then clustered into 4 fuel types, namely, shrub type, herbal-based, non-cover litter types and mixed type. The average amount of fuel loading for the layer of litter and duff is 17.68 t/ha. The collected data were then used to establish fuel loading prediction model. Five regressional models have been built in this study using data including height of shrub, crown width of shrub and ground cover of grass as input parameters. Surface fuel loadings in the windbreak area of Taichung Harbor were estimated to be 21.12-31.66 t/ha according to these models. The laboratory-scale burning tests were conducted to verify the effects of weather and fuel factors on the level of fire behavior. Results of experiments showed that at wind speed lower than 1 m/s, fire spread was governed mainly by the buoyancy forces induced from burning of fuels (Fc2 = 0.18, Nc = 8.33). However, as wind speed raised to 3 m/s, the inertia force of wind dominated the spread of fire (Fc2 = 1.04, Nc = 0.49). The fire spread speed (ROS) at 3 m/s wind speed was estimated to be 7 times higher than that at windless condition. A regressional fit of experimental data between the ROS and the wind speed showed three different patterns, ranging from linear function to exponential function, and finally becomes independent state. Low moisture content fuel (7.5%) had 1.5-fold of mass loss rate compared with that of high moisture content fuel (17.0%), and the fire temperature rising rate was also more rapidly (1.35-fold). Besides, simulation results obtained with the Rothermel model showed similar tendency. All fuel types were then used as inputs to the BEHAVEplus fire model to investigate the fire behaviors, and the results of these simulations were then categorized into three levels. It was noted that 79% of windbreaks area in Taichung Harbor was higher than moderate level of fire indicator. As for the fuel type characterization, it was found that at lower wind speed (≦2.25 m/s), the shrub fuel type of windbreak area can be a reasonable alternative of BEHAVEplus TU5 (R2=0.95, p<0.01). The field burning tests were conducted in both the summer time and the winter time. The scale of fire was limited by cutting off free burning 18 minutes after ignition. All the data, including fuel, weather and fire behavior parameters, were recorded and fed into a regression model to establish a fire behavior prediction model. Measured data were then compared with the predicted values obtained from BEHAVEplus system as well as FBP model. It was noted that the prediction of BEHAVEplus on ROS was acceptable (R2 = 0.85). However, predctions on the burned area perimeter (R2=0.52), the back fire propagation rate (R2=0.50), and flame length (R2=0.55) were not very accurate. The predictions of FBP model showed different results. ROS was overestimated, and fire intensity parameters were underestimated. But predictions in fire perimeter and the area and the ratio of total length to maximum breath of fire area were better than BEHAVEplus.
URI: http://hdl.handle.net/11455/65941
其他識別: U0005-0212201113372000
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-0212201113372000
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