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.

scholarly journals Correction: Wang, L., et al. Assessment of the Dual Polarimetric Sentinel-1A Data for Forest Fuel Moisture Content Estimation. Remote Sensing 2019, 11(13), 1568

2020 ◽  
Vol 12 (2) ◽  
pp. 206
Author(s):  
Long Wang ◽  
Xingwen Quan ◽  
Binbin He ◽  
Marta Yebra ◽  
Minfeng Xing ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Moisture Content ◽  
Fuel Moisture ◽  
Forest Fuel ◽  
Fuel Moisture Content

The authors wish to make the following corrections to this paper [1]: 1 [...]

Forest fuel moisture content estimation from MODIS data

2005 ◽  
Author(s):  
Mei Zhou ◽  
Guangmeng Guo ◽  
Gary Z. Wang ◽  
Junhui Zhao
Keyword(s):  
Moisture Content ◽  
Fuel Moisture ◽  
Modis Data ◽  
Forest Fuel ◽  
Fuel Moisture Content

scholarly journals Corrigendum to: Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide

2020 ◽  
Vol 29 (6) ◽  
pp. 560
Author(s):  
Jane G. Cawson ◽  
Petter Nyman ◽  
Christian Schunk ◽  
Gary J. Sheridan ◽  
Thomas J. Duff ◽  
...  
Keyword(s):  
Moisture Content ◽  
Measurement Techniques ◽  
Field Measurements ◽  
Future Research ◽  
Fuel Moisture ◽  
Potential Solution ◽  
Forest Types ◽  
Wildfire Management ◽  
Forest Fuel ◽  
Fuel Moisture Content

Field measurements of surface dead fine fuel moisture content (FFMC) are integral to wildfire management, but conventional measurement techniques are limited. Automated fuel sticks offer a potential solution, providing a standardised, continuous and real-time measure of fuel moisture. As such, they are used as an analogue for surface dead fine fuel but their performance in this context has not been widely evaluated. We assessed the ability of automated fuel sticks to predict surface dead FFMC across a range of forest types. We combined concurrent moisture measurements of the fuel stick and surface dead fine fuel from 27 sites (570 samples), representing nine broad forest fuel categories. We found a moderate linear relationship between surface dead FFMC and fuel stick moisture for all data combined (R2=0.54), with fuel stick moisture averaging 3-fold lower than surface dead FFMC. Relationships were typically stronger for individual forest fuel categories (median R2=0.70; range=0.55–0.87), suggesting the sticks require fuel-specific calibration for use as an analogue of surface dead fine fuel. Future research could identify fuel properties that will enable more generalised calibration functions.

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

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.

scholarly journals Empirical Models for Spatio-Temporal Live Fuel Moisture Content Estimation in Mixed Mediterranean Vegetation Areas Using Sentinel-2 Indices and Meteorological Data

2021 ◽  
Vol 13 (18) ◽  
pp. 3726
Author(s):  
José M. Costa-Saura ◽  
Ángel Balaguer-Beser ◽  
Luis A. Ruiz ◽  
Josep E. Pardo-Pascual ◽  
José L. Soriano-Sancho
Keyword(s):  
Moisture Content ◽  
Forest Cover ◽  
Meteorological Variables ◽  
Fire Season ◽  
Fuel Moisture ◽  
Spectral Indices ◽  
Live Fuel Moisture ◽  
Spatio Temporal ◽  
Fuel Moisture Content ◽  
Sentinel 2

Live fuel moisture content (LFMC) is an input factor in fire behavior simulation models highly contributing to fire ignition and propagation. Developing models capable of accurately estimating spatio-temporal changes of LFMC in different forest species is needed for wildfire risk assessment. In this paper, an empirical model based on multivariate linear regression was constructed for the forest cover classified as shrublands in the central part of the Valencian region in the Eastern Mediterranean of Spain in the fire season. A sample of 15 non-monospecific shrubland sites was used to obtain a spatial representation of this type of forest cover in that area. A prediction model was created by combining spectral indices and meteorological variables. This study demonstrates that the Normalized Difference Moisture Index (NDMI) extracted from Sentinel-2 images and meteorological variables (mean surface temperature and mean wind speed) are a promising combination to derive cost-effective LFMC estimation models. The relationships between LFMC and spectral indices for all sites improved after using an additive site-specific index based on satellite information, reaching a R2adj = 0.70, RMSE = 8.13%, and MAE = 6.33% when predicting the average of LFMC weighted by the canopy cover fraction of each species of all shrub species present in each sampling plot.

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.

scholarly journals Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide

2020 ◽  
Vol 29 (6) ◽  
pp. 548
Author(s):  
Jane G. Cawson ◽  
Petter Nyman ◽  
Christian Schunk ◽  
Gary J. Sheridan ◽  
Thomas J. Duff ◽  
...  
Keyword(s):  
Moisture Content ◽  
Measurement Techniques ◽  
Field Measurements ◽  
Future Research ◽  
Fuel Moisture ◽  
Potential Solution ◽  
Forest Types ◽  
Wildfire Management ◽  
Forest Fuel ◽  
Fuel Moisture Content

Field measurements of surface dead fine fuel moisture content (FFMC) are integral to wildfire management, but conventional measurement techniques are limited. Automated fuel sticks offer a potential solution, providing a standardised, continuous and real-time measure of fuel moisture. As such, they are used as an analogue for surface dead fine fuel but their performance in this context has not been widely evaluated. We assessed the ability of automated fuel sticks to predict surface dead FFMC across a range of forest types. We combined concurrent moisture measurements of the fuel stick and surface dead fine fuel from 27 sites (570 samples), representing nine broad forest fuel categories. We found a moderate linear relationship between surface dead FFMC and fuel stick moisture for all data combined (R2=0.54), with fuel stick moisture averaging 3-fold lower than surface dead FFMC. Relationships were typically stronger for individual forest fuel categories (median R2=0.70; range=0.55–0.87), suggesting the sticks require fuel-specific calibration for use as an analogue of surface dead fine fuel. Future research could identify fuel properties that will enable more generalised calibration functions.

Why is the effect of live fuel moisture content on fire rate of spread underestimated in field experiments in shrublands?

2019 ◽  
Vol 28 (2) ◽  
pp. 127 ◽  
Author(s):  
F. Pimont ◽  
J. Ruffault ◽  
N. K. Martin-StPaul ◽  
J.-L. Dupuy
Keyword(s):  
Moisture Content ◽  
Field Experiments ◽  
Fire Season ◽  
Special Focus ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Power Functions ◽  
Field Evidence ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behaviour in laboratory experiments. However, field evidence linking LFMC to fire behaviour are very limited, despite numerous field experiments. In this study, we reanalyse a shrubland fire dataset with a special focus on LFMC to investigate this counterintuitive outcome. We found that this controversy might result from three causes. First, the range of experimental LFMC data was too moist to reveal a 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 number of fire experiments was smaller than 40. Finally, an analysis suggested that 10 to 15% measurement error – arising from the estimation of environmental variables from field measurements – could lead to an underestimation by 30% of the LFMC effect. The LFMC effect in field experiments is thus stronger than previously reported in the range of LFMC occurring during the 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 behaviour to refine fire-danger predictions.

Retrieval of forest fuel moisture content using a coupled radiative transfer model

2017 ◽  
Vol 95 ◽  
pp. 290-302 ◽  
Author(s):  
Xingwen Quan ◽  
Binbin He ◽  
Marta Yebra ◽  
Changming Yin ◽  
Zhanmang Liao ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Moisture Content ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Fuel Moisture ◽  
Forest Fuel ◽  
Fuel Moisture Content
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