scholarly journals Influence of Fuel Moisture Content, Packing Ratio and Wind Velocity on the Ignition Probability of Fuel Beds Composed of Mongolian Oak Leaves via Cigarette Butts

Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 507 ◽  
Author(s):  
Ping Sun ◽  
Yunlin Zhang ◽  
Long Sun ◽  
Haiqing Hu ◽  
Futao Guo ◽  
...  
Keyword(s):  
Moisture Content ◽  
Prediction Model ◽  
Forest Fires ◽  
Logistic Model ◽  
Fuel Moisture ◽  
Ignition Probability ◽  
Cigarette Butts ◽  
Mongolian Oak ◽  
Fuel Moisture Content ◽  
Oak Leaves

Cigarette butts are an important human firebrand and account for a significant amount of man-made fires. To better address forest fires caused by cigarette butts, the influencing factors governing the ignition probability of cigarette butts can be used to establish a prediction model. This study obtains the influencing factors of the ignition probability of cigarette butts in order to establish a prediction model by constructing fuel beds composed of Mongolian oak leaves with varied fuel moisture content and packing ratios. A total of 2520 ignition experiments were then conducted by dropping cigarette butts on the fuel beds to test the burning probability of the fuels under varied wind speeds. Moisture content, wind speed, and their interaction significantly influenced ignition probability. In the absence of wind, the ignition probability is zero. The maximum moisture content of Mongolian oak leaves that could be ignited by cigarette butts was 15%. A logistic model and self-built model for predicting the ignition probability were established using these results; the mean absolute error values for the two models were 2.71% and 1.13%, respectively, and the prediction error of the self-built model was lower than that of the logistic model. This is important research to mitigate the threat of forest fires due to cigarette butts given the frequent occurrence of these events.

Assessing ignition probability and moisture of extinction in a Mediterranean grass fuel

2010 ◽  
Vol 19 (1) ◽  
pp. 29 ◽  
Author(s):  
A. P. Dimitrakopoulos ◽  
I. D. Mitsopoulos ◽  
K. Gatoulas
Keyword(s):  
Moisture Content ◽  
Classification Tree ◽  
Weather Conditions ◽  
Stepwise Logistic Regression ◽  
Fuel Moisture ◽  
Ignition Probability ◽  
Plant Moisture ◽  
Plant Moisture Content ◽  
Fuel Moisture Content

The objective of this study was the assessment of the probability of ignition and moisture of extinction of the annual herbaceous species Slender Oat (Avena barbata Pott. ex Link) in Greece. Multiple ignition tests were conducted in situ with a drip torch during two fire seasons, with simultaneous monitoring of the weather conditions. Stepwise logistic regression was applied to assess the probability of ignition based on plant moisture content and meteorological parameters. Fuel moisture content was determined to be the only statistically significant (P < 0.0001) parameter and, therefore, it was the only variable kept in the analysis. The logistic model correctly predicted fire ignition in 93.6% of the tests and 50% ignition probability was determined at 38.5% oven-dried weight (ODW) plant moisture content. Moisture of extinction (i.e. probability of ignition at 1%) was calculated at 55.5% ODW. Furthermore, classification tree analysis was applied to determine the independent variables that explain the variability in ignition probability. Wind speed was found to have an effect on ignition probability only at relatively high (>30% ODW) fuel moisture contents. Assessment of the ignition potential and moisture of extinction of grass fuels is a prerequisite for reliable fire danger prediction.

Using fuel and weather variables to predict the sustainability of surface fire spread in maritime pine stands

2008 ◽  
Vol 38 (2) ◽  
pp. 190-201 ◽  
Author(s):  
Paulo M. Fernandes ◽  
Hermínio Botelho ◽  
Francisco Rego ◽  
Carlos Loureiro
Keyword(s):  
Moisture Content ◽  
Logistic Model ◽  
Fire Spread ◽  
Maritime Pine ◽  
Fuel Moisture ◽  
Fuel Type ◽  
Weather Variables ◽  
Surface Fire ◽  
Pinus Pinaster Ait ◽  
Fuel Moisture Content

Thresholds for surface fire spread were examined in maritime pine ( Pinus pinaster Ait.) stands in northern Portugal. Fire sustainability was assessed after ignition of 2 m fire lines or in larger burns conducted in 10–15 m wide plots. The experiments were carried out from November to June in three fuel types: litter, litter plus shrubs, and litter with a nonwoody understorey. Moisture content of fine dead fuels, on-site weather variables, and descriptors of the fuel complex all had a highly significant influence on the probability of self-sustaining fire spread. A logistic model based solely on fuel moisture content correctly classified the fire sustainability status of 88% of the observations. Nonetheless, the subjectivity of the moisture of extinction concept was apparent, and further accuracy was achieved by the consecutive addition of fire spread direction (forward or backward), fuel type, and ambient temperature. Fully sustained fire spread, in opposition to marginal burns with broken fire fronts, was similarly dependent on fuel moisture but was affected also by fire spread direction and time since rain. The models can benefit fire research and fire management operations but can be made more practical if integrated in a fire danger rating system.

scholarly journals ESTIMATING FINE DEAD FUEL MOISTURE CONTENT UNDER EQUATORIAL CLIMATE CONDITIONS

FLORESTA ◽  
2021 ◽  
Vol 51 (3) ◽  
pp. 696
Author(s):  
Benjamin Leonardo Alves White ◽  
Maria Flaviane Almeida Silva
Keyword(s):  
Moisture Content ◽  
Fire Behavior ◽  
Great Influence ◽  
Fuel Moisture ◽  
Statistical Parameters ◽  
Fire Weather Index ◽  
Ignition Probability ◽  
Climate Conditions ◽  
Equatorial Climate ◽  
Fuel Moisture Content

The measurement of the fine dead fuel moisture content (FDFMC) is extremely important for forest fire prevention and suppression activities, as it has a great influence on the ignition probability and fire behavior. The Fine Fuel Moisture Code (FFMC) from the Fire Weather Index (FWI), is one of the most used models to estimate the FDFMC. Nevertheless, studies that assess the efficiency of this model in Brazil or in low latitude regions are rare. The present study aimed to evaluate the efficiency of the FFMC in an equatorial climate area and to develop a new model capable of estimating the FDFMC with greater precision. For this purpose, 861 random samples of fine dead fuel had their moisture content determined through oven drying. The obtained values were compared with those estimated by the FFMC and correlated with meteorological parameters to build a regression model. The results obtained show that the FDFMC was overestimated by the FFMC. The independent variables with the greatest influence on the FDFMC were, in decreasing order of significance: air relative humidity, air temperature, amount of rainfall in the last 24 hours and number of days without rainfall. The developed model presented good statistical parameters (r2 = 0.86; p <0.0001; RMSE = 0.22) and can be used, in areas with similar characteristics of the study area, to estimate the daily fire risk and to determine ideal conditions for prescribed burns.

The effect of fuel moisture content on the spread rate of forest fires in the absence of wind or slope

2017 ◽  
Vol 26 (1) ◽  
pp. 24 ◽  
Author(s):  
Carlos G. Rossa
Keyword(s):  
Moisture Content ◽  
Forest Fires ◽  
Field Experiments ◽  
Heat Content ◽  
Current Theory ◽  
Rate Variation ◽  
Fuel Moisture ◽  
Spread Rate ◽  
Wide Range ◽  
Fuel Moisture Content

Most studies on the effect of fuel moisture content (FMC) on forest fire behaviour focus on dead fuel moisture; mechanisms of fire spread in live vegetation are considered to remain unexplained by current theory and modelling. In this work, an empirical model for quantifying the effect of FMC on the ratio between spread rate and fuel bed height of fires in the absence of wind or slope was proposed. The model was fitted using data from laboratory experiments, carried out in fuel beds representative of natural litter and shrubland fuel complexes in a wide range of FMC (6–179%), and tested against data from field experiments and wildfires. The pattern of spread rate variation with FMC, namely its reduced rate for values above ~80%, was explained by the ratio between fuel low heat content and energy required for ignition.

The likelihood of ignition of dry-eucalypt forest litter by firebrands

2015 ◽  
Vol 24 (2) ◽  
pp. 225 ◽  
Author(s):  
P. F. M. Ellis
Keyword(s):  
Wind Speed ◽  
Moisture Content ◽  
Eucalyptus Globulus ◽  
Forest Litter ◽  
Fuel Moisture ◽  
Ignition Probability ◽  
Moisture Contents ◽  
Eucalypt Forest ◽  
Fuel Moisture Content ◽  
Practical Measure

Ignition probability of litter of dry-eucalypt forest by standard flaming and glowing firebrand samples was tested in a wind tunnel. Standard flaming firebrands were sections of bamboo sate stick 50 mm long, and flamed for ~9 s in still air. Standard glowing samples were sections of shed bark of Eucalyptus globulus 50 mm long, 15 mm wide and ~2 mm in thickness. These were burnt at their terminal velocities and at deposition had a mean mass of 0.2 g and would remain glowing for 2.5 min in wind. Ignition was tested using air speeds of zero, 1 and 2 m s–1, and oven-dried fuel moisture contents between 4 and 21%. For flaming samples, ignition probability was insensitive to variation in fuel and airflow characteristics and was a function of wind (no wind or wind) and fuel moisture content. For glowing samples, ignition probability was a function of fuel moisture content and wind speed. The models confirm the dominating influence of fuel moisture, are consistent with expert observations in the field and provide a practical measure of ignition likelihood by firebrands. It is argued that airflow turbulence and relative humidity are potentially significant for ignition by glowing firebrands.

Predicting 1-H Dead Fuel Moisture Content at Regional Scales Using Machine Learning from Himawari-8 Data

2021 ◽  
Author(s):  
Chunquan Fan ◽  
Binbin He ◽  
Peng Kong ◽  
Hao Xu ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Moisture Content ◽  
Fuel Moisture ◽  
Fuel Moisture Content

scholarly journals Evaluating the Effects of Projected Climate Change on Forest Fuel Moisture Content

2014 ◽  
Vol 37 ◽  
pp. 65-69
Author(s):  
Kellen Nelson ◽  
Daniel Tinker
Keyword(s):  
Climate Change ◽  
Moisture Content ◽  
Stand Structure ◽  
Canopy Cover ◽  
Fire Season ◽  
Climate Change Scenarios ◽  
Fuel Moisture ◽  
Mature Forest ◽  
Forest Fuel ◽  
Fuel Moisture Content

Understanding how live and dead forest fuel moisture content (FMC) varies with seasonal weather and stand structure will improve researchers’ and forest managers’ ability to predict the cumulative effects of weather on fuel drying during the fire season and help identify acute conditions that foster wildfire ignition and high rates of fire spread. No studies have investigated the efficacy of predicting FMC using mechanistic water budget models at daily time scales through the fire season nor have they investigated how FMC may vary across space. This study addresses these gaps by (1) validating a novel mechanistic live FMC model and (2) applying this model with an existing dead FMC model at three forest sites using five climate change scenarios to characterize how FMC changes through time and across space. Sites include post-fire 24-year old forest, mature forest with high canopy cover, and mature forest affected by the mountain pine beetle with moderate canopy cover. Climate scenarios include central tendency, warm/dry, warm/wet, hot/dry, and hot/wet.

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