ESTIMATING FINE DEAD FUEL MOISTURE CONTENT UNDER EQUATORIAL CLIMATE CONDITIONS

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.

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Assessing the probability of sustained flaming in masticated fuel beds

Canadian Journal of Forest Research ◽

10.1139/cjfr-2014-0294 ◽

2015 ◽

Vol 45 (1) ◽

pp. 68-77 ◽

Cited By ~ 3

Author(s):

T.J. Schiks ◽

B.M. Wotton

Keyword(s):

Wind Speed ◽

Moisture Content ◽

Fire Behavior ◽

Fire Risk ◽

Field Testing ◽

Behavior Modeling ◽

Fuel Moisture ◽

Fire Behaviour ◽

Fire Weather Index ◽

Fuel Moisture Content

Mechanical mastication is increasingly used as a fuel management treatment to reduce fire risk at the wildland–urban interface, although ignition and fire behaviour in these novel fuel beds are poorly understood. We investigated the influence of observed fuel moisture content, wind speed, and firebrand size on the probability of sustained flaming of masticated fuel beds under both laboratory and field settings. Logistic regression techniques were applied to assess the probability of sustained flaming in both datasets. Models for the field were also developed using estimated moisture from three sets of weather-based models: (i) the hourly Fine Fuel Moisture Code (FFMC) from the Canadian Forest Fire Weather Index System, (ii) the National Fire Danger Rating System (NFDRS) moisture estimates for 1 h and 10 h fuels, and (iii) a masticated surface fuel moisture model (MAST). In both laboratory and field testing, the likelihood of a successful ignition increased with decreasing moisture content and increasing wind speed; the effect of firebrand size was only apparent in laboratory testing. The FFMC, NFDRS, and MAST predictions had somewhat reduced discriminative power relative to direct moisture in predicting the probability of sustained flaming based on our field observations. Our results speak to the disparity between the fire behaviour modeling that occurs in the laboratory and the fire behavior modeling that occurs in the field, as the methodology permitted comparison of predictions from sustained flaming models that were developed for one experimental setting and applied to the other.

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

International Journal of Wildland Fire ◽

10.1071/wf08124 ◽

2010 ◽

Vol 19 (1) ◽

pp. 29 ◽

Cited By ~ 23

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.

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Fuel moisture content enhances nonadditive effects of plant mixtures on flammability and fire behavior

Ecology and Evolution ◽

10.1002/ece3.1628 ◽

2015 ◽

Vol 5 (17) ◽

pp. 3830-3841 ◽

Cited By ~ 14

Author(s):

Luke G. Blauw ◽

Niki Wensink ◽

Lisette Bakker ◽

Richard S. P. Logtestijn ◽

Rien Aerts ◽

...

Keyword(s):

Moisture Content ◽

Fire Behavior ◽

Fuel Moisture ◽

Fuel Moisture Content ◽

Nonadditive Effects

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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 ◽

10.3390/f9090507 ◽

2018 ◽

Vol 9 (9) ◽

pp. 507 ◽

Cited By ~ 3

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.

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Relationships between seasonal patterns of live fuel moisture and meteorological drought indices for Mediterranean shrubland species

International Journal of Wildland Fire ◽

10.1071/wf06081 ◽

2007 ◽

Vol 16 (2) ◽

pp. 232 ◽

Cited By ~ 56

Author(s):

G. Pellizzaro ◽

C. Cesaraccio ◽

P. Duce ◽

A. Ventura ◽

P. Zara

Keyword(s):

Moisture Content ◽

Meteorological Drought ◽

Meteorological Conditions ◽

Drought Indices ◽

Seasonal Patterns ◽

Fuel Moisture ◽

Fire Weather Index ◽

Moisture Variation ◽

Live Fuel Moisture ◽

Fuel Moisture Content

Measurements of seasonal patterns of live fuel moisture content and ignitability (in terms of time to ignition) of four Mediterranean shrub species were performed in North Western Sardinia (Italy). Relationships between the two variables were evaluated. Relationships between live fuel moisture content and environmental conditions (i.e. rainfall, air temperature and soil moisture) were analysed. Two groups of species were identified in relation to the different response of live fuel moisture content to seasonal meteorological conditions. Seasonal patterns of live fuel moisture content were also compared with five meteorological drought indices: Duff Moisture Code and Drought Code of the Canadian Forest Fire Weather Index System, Keetch–Byram Drought Index, Canopy Drought Stress Index and Cumulative Water Balance Index. In addition, the capability of the meteorological drought indices to describe moisture variation for each species was evaluated. Although the Drought Code was formulated to describe changes in the moisture content of dead fuel, it was shown to have a good potential for modelling live fuel moisture variation of a group of shrubland species that are sensitive to meteorological conditions, with a clear and large decrease of moisture content during the drought season.

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Why is the Effect of Live Fuel Moisture Content on Fire Rate of Spread Underestimated in Field Experiments in Shrublands?

10.20944/preprints201810.0459.v1 ◽

2018 ◽

Author(s):

Francois Pimont ◽

Julien Ruffault ◽

Nicolas Martin ◽

Jean-Luc Dupuy

Keyword(s):

Moisture Content ◽

Field Experiments ◽

Fire Behavior ◽

Fire Season ◽

Special Focus ◽

Fuel Moisture ◽

Power Functions ◽

Random Measurement Error ◽

Live Fuel Moisture ◽

Fuel Moisture Content

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC  data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.

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A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models

Remote Sensing ◽

10.3390/rs12111714 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1714

Author(s):

Mariano García ◽

David Riaño ◽

Marta Yebra ◽

Javier Salas ◽

Adrián Cardil ◽

...

Keyword(s):

Time Series ◽

Moisture Content ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Fire Behavior ◽

Burned Area ◽

Fuel Moisture ◽

Individual Site ◽

Live Fuel Moisture ◽

Fuel Moisture Content

Live Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into fire behavior simulation models. Nine chaparral sampling sites across three Landsat-5 Thematic Mapper (TM) scenes were used to validate the product over the Western USA. The relations between field-measured LFMC and Landsat-derived SIs were strong for each individual site but worsened when pooled together. The Enhanced Vegetation Index (EVI) presented the strongest correlations (r) and the least Root Mean Square Error (RMSE), followed by the Normalized Difference Infrared Index (NDII), Normalized Difference Vegetation Index (NDVI) and Visible Atmospherically Resistant Index (VARI). The relations between LFMC and the SIs for all sites improved after using their relative values and relative LFMC, increasing r from 0.44 up to 0.69 for relative EVI (relEVI), the best predictive variable. This relEVI served to estimate the herbaceous and woody LFMC based on minimum and maximum seasonal LFMC values. The understory herbaceous LFMC on the woody pixels was extrapolated from the surrounding pixels where the herbaceous vegetation is the top layer. Running simulations on the Wildfire Analyst (WFA) fire behavior model demonstrated that this LFMC product alone impacts significantly the fire spatial distribution in terms of burned probability, with average burned area differences over 21% after 8 h burning since ignition, compared to commonly carried out simulations based on constant values for each fuel model. The method could be applied to Landsat-7 and -8 and Sentinel-2A and -2B after proper sensor inter-calibration and topographic correction.

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Predicting the elevated dead fine fuel moisture content in gorse (Ulex europaeus L.) shrub fuels

Canadian Journal of Forest Research ◽

10.1139/x09-142 ◽

2009 ◽

Vol 39 (12) ◽

pp. 2355-2368 ◽

Cited By ~ 19

Author(s):

Stuart A.J. Anderson ◽

Wendy R. Anderson

Keyword(s):

Moisture Content ◽

Response Time ◽

Equilibrium Moisture Content ◽

Fire Danger ◽

Weather Data ◽

Fuel Moisture ◽

Fire Weather Index ◽

Ulex Europaeus ◽

Fuel Layer ◽

Fuel Moisture Content

Methods were developed to predict the moisture content of the elevated dead fine fuel layer in gorse ( Ulex europaeus L.) shrub fuels. This layer has been observed to be important for fire development and spread in these fuels. The accuracy of the Fine Fuel Moisture Code (FFMC) of the Canadian Fire Weather Index System to predict the moisture content of this layer was evaluated. An existing model was used to determine the response time and equilibrium moisture content from field data. This response time was incorporated into a bookkeeping model, combining the FFMC and this response time–equilibrium moisture content model. The FFMC poorly predicted the elevated dead fuel moisture content in gorse fuels, and attempts to improve its accuracy through regression modelling were unsuccessful. The response time of the elevated dead fine fuel layer was very fast (38–77 min) and has important implications for fire danger rating. The bookkeeping approach was the most promising method to predict elevated dead fuel moisture content. A limitation was the inability to model fuel-level meteorology. However, this model warrants further validation and extension to other shrub fuels and could be incorporated into existing fire danger rating systems that can utilize hourly weather data.

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