Construction of empirical models for predicting Pinus sp. dead fine fuel moisture in NW Spain. I: Response to changes in temperature and relative humidity

2009 ◽  
Vol 18 (1) ◽  
pp. 71 ◽  
Author(s):  
Ana Daría Ruiz González ◽  
Jose Antonio Vega Hidalgo ◽  
Juan Gabriel Álvarez González
Keyword(s):  
Moisture Content ◽  
Time Lag ◽  
Decisive Role ◽  
Repeated Measurements ◽  
Fuel Moisture ◽  
North West ◽  
Fine Fuels ◽  
Fuel Particles ◽  
Fuel Moisture Content ◽  
Non Destructive

A statistical methodology is presented for developing moisture content models from repeated measurements made on non-destructive repeated measurements. Empirical vapour exchange models for dead fine fuels generated in Pinus radiata and P. pinaster stands are developed by using the methodology proposed. Experiments were carried out with five types of fuel particles (surface and aerial fine fuels) of the two species of pine, in Lugo (Galicia, north-west Spain). The samples of each fuel type were collected and placed inside an instrument shelter so that vapour exchange with the atmosphere was the only source of moisture in the fuels. Statistical criteria obtained from the residuals indicated that the fitted models were acceptable. The cross-validation results also confirmed the validity of the fitted models. The model underlined the decisive role played by the time lag in dead fine fuel moisture content variation.

scholarly journals Data assimilation of dead fuel moisture observations from remote automated weather stations

2016 ◽  
Vol 25 (5) ◽  
pp. 558 ◽  
Author(s):  
Martin Vejmelka ◽  
Adam K. Kochanski ◽  
Jan Mandel
Keyword(s):  
Data Assimilation ◽  
Moisture Content ◽  
Wildland Fire ◽  
Time Lag ◽  
Assessment System ◽  
Major Influence ◽  
Surface Model ◽  
Fuel Moisture ◽  
Weather Stations ◽  
Fuel Moisture Content

Fuel moisture has a major influence on the behaviour of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content (FMC) observations from remote automated weather stations (RAWS) into a time lag fuel moisture model. RAWS are spatially sparse and a mechanism is needed to estimate fuel moisture content at locations potentially distant from observational stations. This is arranged using a trend surface model (TSM), which allows us to account for the effects of topography and atmospheric state on the spatial variability of FMC. At each location of interest, the TSM provides a pseudo-observation, which is assimilated via Kalman filtering. The method is tested with the time lag fuel moisture model in the coupled weather-fire code WRF–SFIRE on 10-h FMC observations from Colorado RAWS in 2013. Using leave-one-out testing we show that the TSM compares favourably with inverse squared distance interpolation as used in the Wildland Fire Assessment System. Finally, we demonstrate that the data assimilation method is able to improve on FMC estimates in unobserved fuel classes.

Estimating live fine fuels moisture content using meteorologically-based indices

2001 ◽  
Vol 10 (2) ◽  
pp. 223 ◽  
Author(s):  
D. X. Viegas ◽  
J. Piñol ◽  
M. T. Viegas ◽  
R. Ogaya
Keyword(s):  
Moisture Content ◽  
Meteorological Data ◽  
Field Measurements ◽  
Summer Season ◽  
Fuel Moisture ◽  
Empirical Correlations ◽  
Central Portugal ◽  
Forest Fire Danger ◽  
Fine Fuels ◽  
Fuel Moisture Content

Field measurements of moisture content of several fine fuels (shrub vegetation and live foliage) were performed in Central Portugal and in Catalunya (NE Spain) for 1–10 years. Seasonal and interannual variation of live fine fuels of several species in two regions of the Iberian Peninsula are analysed. The species were grouped in three sets according to their relatively high, intermediate or low seasonal variability. Meteorological data from nearby stations were collected in each study area and used in the evaluation of some indicators of fuel moisture that are used in the Canadian Forest Fire Danger Rating System, namely the Drought Code (DC). It was found that in the summer season the slow response of live fine fuel moisture content (LFFMC) to meteorological conditions, namely to precipitation, was well described by the DC. Empirical correlations between LFFMC and DC for each species and site are proposed.

Moisture Content of Fine Forest Fuels and Fire Occurrence in Central Portugal

1992 ◽  
Vol 2 (2) ◽  
pp. 69 ◽  
Author(s):  
DX Viegas ◽  
MTSP Viegas ◽  
AD Ferreira
Keyword(s):  
Moisture Content ◽  
Meteorological Data ◽  
Test Site ◽  
Fuel Moisture ◽  
Fire Occurrence ◽  
Forest Fuels ◽  
Central Portugal ◽  
Predicted Values ◽  
Fine Fuels ◽  
Fuel Moisture Content

Moisture content of ten fine fuels frequent in the forests of CentralPortugal and in other Mediterranean areas was measured daily since 1986. Average monthly results are presented for the period of 1987-1990. Pinuspinaster sticks were used as a predictor of dead fuel moisture content. A reasonable correlation was obtained with the moisture content of Pinus pinaster dead needles and Eucalyptus globulus dead leaves. Two options of the MOISTURE module of BEHAVE system were also tested to predict the daily minimum value of fine dead fuel moisture content. Predicted values were always lower than direct measurements, specially when only meteorological data was used. A better agreement was obtained when known moisture content of the previous day was introduced. Using statistical data of oily fire occurrence in some districts around the site where the tests were made, for the same period of time, the probability of fire occurrence, the average number of daily fires and the average area burned each year was analysed as a function of dead pine needles moisture content. Three distinct zones, around and adjacent to the test site showed a very similar behaviour.

An examination of fire spread thresholds in discontinuous fuel beds

2010 ◽  
Vol 19 (2) ◽  
pp. 163 ◽  
Author(s):  
Mark A. Finney ◽  
Jack D. Cohen ◽  
Isaac C. Grenfell ◽  
Kara M. Yedinak
Keyword(s):  
Environmental Factors ◽  
Moisture Content ◽  
High Speed ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Thermal Camera ◽  
Vegetation Canopies ◽  
Effective Depth ◽  
Fuel Particles ◽  
Fuel Moisture Content

Many fuel beds, especially live vegetation canopies (conifer forests, shrub fields, bunch-grasses) contain gaps between vegetation clumps. Fires burning in these fuel types often display thresholds for spread that are observed to depend on environmental factors like wind, slope, and fuel moisture content. To investigate threshold spread behaviours, we conducted a set of laboratory burn experiments in artificial fuel beds where gap structure, depth, and slope were controlled. Results revealed that fire spread was limited by gap distance and that the threshold distance for spread was increased for deeper fuel beds and steeper slopes. The reasons for this behaviour were found using a high-speed thermal camera. Flame movements recorded by the camera at 120 Hz suggested fuel particles experience intermittent bathing of non-steady flames before ignition and that fuel particles across the gap ignited only after direct flame contact. The images also showed that the flame profile within the fuel bed expands with height, producing greater horizontal flame displacement in deeper beds. Slope, thus, enhances spread by increasing the effective depth in the uphill direction, which produces wider flames, and thereby increases the potential flame contact. This information suggests that fire spread across discontinuous fuel beds is dependent on the vertical flame profile geometry within the fuel bed and the statistical properties of flame characteristics.

Estimating Fuel Moisture Response Times From Field Observations

1991 ◽  
Vol 1 (4) ◽  
pp. 211 ◽  
Author(s):  
NR Viney ◽  
EA Catchpole
Keyword(s):  
Moisture Content ◽  
Response Times ◽  
Continuous Process ◽  
Time Lag ◽  
Continuous Model ◽  
Step Change ◽  
Simple Relationship ◽  
Fuel Moisture ◽  
Content Model ◽  
Fuel Moisture Content

The response time of a fuel element is defined in terms of the response to a step change in moisture content, and is not measurable in the field. However the formulation of fine fuel moisture content as a continuous process leads to a simple relationship between the re- sponse time of the fuel and the time lag with respect to a diurnally varying equilibrium moisture content. This time lag is estimable from field data. This method is applied to obtain response times for fine litter in a EucaIyptus forest. The same formulation is applied to the discrete moisture content model of Fosberg and Deeming (1971) which is re-cast and solved as a continuous model.

scholarly journals Characterization of Recycled Wood Chips, Syngas Yield, and Tar Formation in an Industrial Updraft Gasifier

Environments ◽  
2018 ◽  
Vol 5 (7) ◽  
pp. 84 ◽  
Author(s):  
Ehsan Oveisi ◽  
Shahab Sokhansanj ◽  
Anthony Lau ◽  
Jim Lim ◽  
Xiaotao Bi ◽  
...  
Keyword(s):  
Moisture Content ◽  
Wood Chip ◽  
Calorific Value ◽  
Operating Conditions ◽  
Wood Chips ◽  
Biomass Fuel ◽  
Fuel Moisture ◽  
Sampling Device ◽  
Fuel Particles ◽  
Fuel Moisture Content

In this study, the moisture content, calorific value, and particle size of recycled wood chips were measured. The wood chips were used to fuel an 8.5 MWth updraft gasifier to produce syngas for combustion in a steam-producing boiler. In-situ syngas composition and tar concentrations were measured and analyzed against biomass fuel properties. No efforts were made to adjust the properties of biomass or the routine operating conditions for the gasifier. A sampling device developed by CanmetENERGY-Ottawa (Ottawa, ON, Canada) was used to obtain syngas and tar samples. Wood chip samples fed to the gasifier were taken at the same time the gas was sampled. Results indicate that as the fuel moisture content increases from 20% to 35%, the production of CO drops along with a slight decrease in concentrations of H2 and CH4. Tar concentration increased slightly with increased moisture content and proportion of small fuel particles (3.15–6.3 mm). Based on the findings of this study, biomass fuel moisture content of 20% and particles larger than 6.3 mm (1/4″) are recommended for the industrial updraft gasifier in order to achieve a higher syngas quality and a lower tar concentration.

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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