Effects of curing on grassfires: I. Fuel dynamics in a senescing grassland

2015 ◽  
Vol 24 (6) ◽  
pp. 828 ◽  
Author(s):  
Susan Kidnie ◽  
Miguel G. Cruz ◽  
Jim Gould ◽  
David Nichols ◽  
Wendy Anderson ◽  
...  
Keyword(s):  
Moisture Content ◽  
Fuel Moisture ◽  
Fire Dynamics ◽  
Sampling Protocol ◽  
Fuel Component ◽  
Dead State ◽  
Fuel Dynamics ◽  
Green Fuels ◽  
Soil Dryness ◽  
Fuel Moisture Content

Grass senescence, or grassland curing, is a dynamic process in which grass fuels transition from a live to dead state and, in turn, influence fire dynamics. In the present study we examined the process of curing with specific consideration of changes in fuel structure that will affect potential fire behaviour. Our sampling protocol expanded the fuel component groups from two (live and dead) to four (green, senescing, new dead and old dead fuel). We found that all these components had significant fuel moisture content differences, thereby justifying our sampling protocol. Visual curing assessment predominantly resulted in an over-prediction bias of curing level and failed to capture the effect of the senescing process on fuel availability to combust due to misclassification of fuel components (e.g. senescing fuels with high fuel moisture content were classified as dead fuels because of their colouration). Models were developed to estimate the: (1) proportion of senescing and green fuels from knowledge of the current year’s dead fuel proportion; and (2) actual curing level from fuel moisture content and soil dryness level.

scholarly journals Useful Life of Prescribed Fires in a Southern Mediterranean Basin: An Application to Pinus pinaster Stands in the Sierra Morena Range

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 486
Author(s):  
Juan Ramón Molina ◽  
Macarena Ortega ◽  
Francisco Rodríguez y Silva
Keyword(s):  
Moisture Content ◽  
Prescribed Fire ◽  
Pinus Pinaster ◽  
Prescribed Fires ◽  
Fuel Moisture ◽  
Fuel Treatment ◽  
Fuel Dynamics ◽  
Useful Life ◽  
Fuel Moisture Content ◽  
Stand Characteristics

Prescribed fire is a globally relevant fuel treatment for surface fuel management and wildfire hazard reduction. However, Mediterranean ecosystems are adapted to low and moderate fires; hence, the useful life of prescribed fires is limited. Useful life is defined as the effective rotation length of prescribed fires to mitigate fire spread based on critical surface intensity for crown combustion. In this sense, the useful life of a prescribed fire focuses on surface fuel dynamics and its potential fire behavior. In Pinus pinaster stands, the useful life can be established between 0 and 4 years. Canopy base height, time elapsed from the burning, postfire precipitation, and fine fuel moisture content during the burning were identified as the most important variables in postburn fuel dynamics. Other stand characteristics and postfire precipitation can improve the fine fuel and live fuel dynamics models. Our findings support prescribed fires as an effective fuel treatment in the medium term for forest fire prevention, according to stand characteristics and burning implementation conditions. In this sense, forest managers can use the proposed decision tree to identify the useful life of each prescribed fire based on fine fuel moisture content during burning implementation.

Combustibility of a mixture of live and dead fuel components

2013 ◽  
Vol 22 (7) ◽  
pp. 992 ◽  
Author(s):  
D. X. Viegas ◽  
J. Soares ◽  
M. Almeida
Keyword(s):  
Moisture Content ◽  
Mass Fraction ◽  
Linear Models ◽  
Fuel Moisture ◽  
Fuel Component ◽  
Rate Of Spread ◽  
Fire Front ◽  
Composite Fuel ◽  
The Dead ◽  
Fuel Moisture Content

The problem of predicting the rate of spread of a linear fire front in a fuel bed composed of one live and one dead fuel component in no-slope and no-wind conditions is addressed. Two linear models based on the mass fraction of each fuel component are proposed to predict the rate of spread of a fire front as a function of the mass fraction of the dead or dry fuel component. Experimental results obtained with two different mixtures show that for each fuel mixture there is a threshold value of mass concentration of the dead fuel below which the fire front does not spread. The rate of spread results compare favourably with the proposed models. A composite fuel moisture content of the fuel bed is shown to be a good descriptor of the rate of spread of the mixture. An exponential model using composite fuel moisture content of the fuel bed is proposed to estimate the rate of spread of the mixture and a comparison is made with the concept of fuel curing that is used to characterise live fuels.

Assessing Grassland Moisture and Biomass in Tasmania - the Application of Remote-Sensing and Empirical-Models for a Cloudy Environment

1995 ◽  
Vol 5 (3) ◽  
pp. 165 ◽  
Author(s):  
MA Chladil ◽  
M Nunez
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Fire Season ◽  
Fuel Moisture ◽  
Noaa Avhrr ◽  
Dryness Index ◽  
Ground Truthing ◽  
Soil Dryness ◽  
Fuel Moisture Content ◽  
Semi Empirical

The operational feasibility of NOAA/AVHRR data and two semi-empirical moisture models were evaluated in the grasslands of southeastern Tasmania (Australia) during the 1988/89 fire season. A limited ground-truthing experiment compared the grassland dry biomass, soil moisture and fuel moisture with the satellite derived NDVI and the Soil Dryness Index (SDI) and the Grassland Curing Index (GCI). The NDVI gave good results for fuel moisture content (FMC) and soil moisture content (SMC) but unreliable image availability precludes the use of NDVI as a stand alone system for fire managers. The SDI and GCI also performed well in predicting SMC and FMC. Very good results were obtained when the NDVI and the GCI were combined. These results suggest the combination of data will provide both the accuracy and the continuity of information needed for operational use by fire managers. The methods used here could be cheaply and quickly repeated for use in other similar fire prone and cloudy environments.

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.

Effects of distribution of bulk density and moisture content on shrub fires

2013 ◽  
Vol 22 (5) ◽  
pp. 625 ◽  
Author(s):  
Ambarish Dahale ◽  
Selina Ferguson ◽  
Babak Shotorban ◽  
Shankar Mahalingam
Keyword(s):  
Moisture Content ◽  
Spatial Variation ◽  
Bulk Density ◽  
Solid Fuel ◽  
Numerical Solutions ◽  
Propagation Speed ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Combustion Heat ◽  
Fuel Moisture Content

Formulation of a physics-based model, capable of predicting fire spread through a single elevated crown-like shrub, is described in detail. Predictions from the model, obtained by numerical solutions to governing equations of fluid dynamics, combustion, heat transfer and thermal degradation of solid fuel, are found to be in fairly good agreement with experimental results. In this study we utilise the physics-based model to explore the importance of two parameters – the spatial variation of solid fuel bulk density and the solid fuel moisture content – on the burning of an isolated shrub in quiescent atmosphere. The results suggest that vertical fire spread rate within an isolated shrub and the time to initiate ignition within the crown are two global parameters significantly affected when the spatial variation of the bulk density or the variation of fuel moisture content is taken into account. The amount of fuel burnt is another parameter affected by varying fuel moisture content, especially in the cases of fire propagating through solid fuel with moisture content exceeding 40%. The specific mechanisms responsible for the reduction in propagation speed in the presence of higher bulk densities and moisture content are identified.

Modelling fine fuel moisture content and the likelihood of fire spread in blue gum (Eucalyptus globulus) litter

2014 ◽  
pp. 353-359
Author(s):  
Anita Pinto ◽  
Juncal Espinosa-Prieto ◽  
Carlos Rossa ◽  
Stuart Matthews ◽  
Carlos Loureiro ◽  
...  
Keyword(s):  
Moisture Content ◽  
Eucalyptus Globulus ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Fuel Moisture Content ◽  
Blue Gum
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