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.

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.

scholarly journals Effects of Live Fuel Moisture Content on Wildfire Occurrence in Fire-Prone Regions over Southwest China

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 887 ◽  
Author(s):  
Kaiwei Luo ◽  
Xingwen Quan ◽  
Binbin He ◽  
Marta Yebra
Keyword(s):  
Moisture Content ◽  
Southwest China ◽  
Burned Area ◽  
Fuel Moisture ◽  
Fire Occurrence ◽  
Subtropical Zone ◽  
Wildfire Occurrence ◽  
Live Fuel Moisture ◽  
Grassland Fire ◽  
Fuel Moisture Content

Previous studies have shown that Live Fuel Moisture Content (LFMC) is a crucial driver affecting wildfire occurrence worldwide, but the effect of LFMC in driving wildfire occurrence still remains unexplored over the southwest China ecosystem, an area historically vulnerable to wildfires. To this end, we took 10-years of LFMC dynamics retrieved from Moderate Resolution Imaging Spectrometer (MODIS) reflectance product using the physical Radiative Transfer Model (RTM) and the wildfire events extracted from the MODIS Burned Area (BA) product to explore the relations between LFMC and forest/grassland fire occurrence across the subtropical highland zone (Cwa) and humid subtropical zone (Cwb) over southwest China. The statistical results of pre-fire LFMC and cumulative burned area show that distinct pre-fire LFMC critical thresholds were identified for Cwa (151.3%, 123.1%, and 51.4% for forest, and 138.1%, 72.8%, and 13.1% for grassland) and Cwb (115.0% and 54.4% for forest, and 137.5%, 69.0%, and 10.6% for grassland) zones. Below these thresholds, the fire occurrence and the burned area increased significantly. Additionally, a significant decreasing trend on LFMC dynamics was found during the days prior to two large fire events, Qiubei forest fire and Lantern Mountain grassland fire that broke during the 2009/2010 and 2015/2016 fire seasons, respectively. The minimum LFMC values reached prior to the fires (49.8% and 17.3%) were close to the lowest critical LFMC thresholds we reported for forest (51.4%) and grassland (13.1%). Further LFMC trend analysis revealed that the regional median LFMC dynamics for the 2009/2010 and 2015/2016 fire seasons were also significantly lower than the 10-year LFMC of the region. Hence, this study demonstrated that the LFMC dynamics explained wildfire occurrence in these fire-prone regions over southwest China, allowing the possibility to develop a new operational wildfire danger forecasting model over this area by considering the satellite-derived LFMC product.

Integrating geospatial information into fire risk assessment

2014 ◽  
Vol 23 (5) ◽  
pp. 606 ◽  
Author(s):  
E. Chuvieco ◽  
I. Aguado ◽  
S. Jurdao ◽  
M. L. Pettinari ◽  
M. Yebra ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Moisture Content ◽  
Information Technologies ◽  
National Level ◽  
Fire Risk ◽  
Assessment System ◽  
Fuel Moisture ◽  
Fire Occurrence ◽  
Fire Risk Assessment ◽  
Fuel Moisture Content

Fire risk assessment should take into account the most relevant components associated to fire occurrence. To estimate when and where the fire will produce undesired effects, we need to model both (a) fire ignition and propagation potential and (b) fire vulnerability. Following these ideas, a comprehensive fire risk assessment system is proposed in this paper, which makes extensive use of geographic information technologies to offer a spatially explicit evaluation of fire risk conditions. The paper first describes the conceptual model, then the methods to generate the different input variables, the approaches to merge those variables into synthetic risk indices and finally the validation of the outputs. The model has been applied at a national level for the whole Spanish Iberian territory at 1-km2 spatial resolution. Fire danger included human factors, lightning probability, fuel moisture content of both dead and live fuels and propagation potential. Fire vulnerability was assessed by analysing values-at-risk and landscape resilience. Each input variable included a particular accuracy assessment, whereas the synthetic indices were validated using the most recent fire statistics available. Significant relations (P < 0.001) with fire occurrence were found for the main synthetic danger indices, particularly for those associated to fuel moisture content conditions.

Prediction of fire occurrence from live fuel moisture content measurements in a Mediterranean ecosystem

2009 ◽  
Vol 18 (4) ◽  
pp. 430 ◽  
Author(s):  
Emilio Chuvieco ◽  
Isabel González ◽  
Felipe Verdú ◽  
Inmaculada Aguado ◽  
Marta Yebra
Keyword(s):  
Logistic Regression ◽  
Moisture Content ◽  
Fire Danger ◽  
Burned Area ◽  
Mediterranean Ecosystem ◽  
Fuel Moisture ◽  
Fire Occurrence ◽  
Large Fires ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

The present paper presents and discusses the relationships between live Fuel Moisture Content (FMC) measurements and fire occurrence (number of fires and burned area) in a Mediterranean area of central Spain. Grasslands and four shrub species (Cistus ladanifer L., Rosmarinus officinalis L., Erica australis L. and Phillyrea angustifolia L.) were sampled in the field from the spring to the summer season over a 9-year period. Higher seasonal FMC variability was found for the herbaceous species than for shrubs, as grasslands have very low values in summertime. Moisture variations of grasslands were found to be good predictors of number of fires and total burned surface, while moisture variation of two shrubs (C. ladanifer L. and R. officinalis L.) was more sensitive to both the total burned area and the occurrence of large fires. All these species showed significant differences between the FMC of high and low occurrence periods. Three different logistic regression models were built for the 202 periods of analysis: one to predict periods with more and less than seven fires, another to predict periods with and without large fires (>500 ha), and the third to predict periods with more and less than 200 ha burned. The results showed accuracy in predicting periods with a high number of fires (94%), and extensive burned area (85%), with less accuracy in estimating periods with large fires (58%). Finally, empirical functions based on logistic regression analysis were successfully related to fire ignition or potential burned area from FMC data. These models should be useful to integrate FMC measurements with other variables of fire danger (ignition causes, for instance), to provide a more comprehensive assessment of fire danger conditions.

scholarly journals Dead Fuel Moisture Content (DFMC) Estimation Using MODIS and Meteorological Data: The Case of Greece

2021 ◽  
Vol 13 (21) ◽  
pp. 4224
Author(s):  
Eleni Dragozi ◽  
Theodore M. Giannaros ◽  
Vasiliki Kotroni ◽  
Konstantinos Lagouvardos ◽  
Ioannis Koletsis
Keyword(s):  
Moisture Content ◽  
Satellite Data ◽  
Spatial Scales ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Field Measurements ◽  
Fuel Moisture ◽  
Weather Station ◽  
Physically Based ◽  
Fuel Moisture Content

The frequent occurrence of large and high-intensity wildfires in the Mediterranean region poses a major threat to people and the environment. In this context, the estimation of dead fine fuel moisture content (DFMC) has become an integrated part of wildfire management since it provides valuable information for the flammability status of the vegetation. This study investigates the effectiveness of a physically based fuel moisture model in estimating DFMC during severe fire events in Greece. Our analysis considers two approaches, the satellite-based (MODIS DFMC model) and the weather station-based (AWSs DFMC model) approach, using a fuel moisture model which is based on the relationship between the fuel moisture of the fine fuels and the water vapor pressure deficit (D). During the analysis we used weather station data and MODIS satellite data from fourteen wildfires in Greece. Due to the lack of field measurements, the models’ performance was assessed only in the case of the satellite data by using weather observations obtained from the network of automated weather stations operated by the National Observatory of Athens (NOA). Results show that, in general, the satellite-based model achieved satisfactory accuracy in estimating the spatial distribution of the DFMC during the examined fire events. More specifically, the validation of the satellite-derived DFMC against the weather-station based DFMC indicated that, in all cases examined, the MODIS DFMC model tended to underestimate DFMC, with MBE ranging from −0.3% to −7.3%. Moreover, in all of the cases examined, apart from one (Sartis’ fire case, MAE: 8.2%), the MAE of the MODIS DFMC model was less than 2.2%. The remaining numerical results align with the existing literature, except for the MAE case of 8.2%. The good performance of the satellite based DFMC model indicates that the estimation of DFMC is feasible at various spatial scales in Greece. Presently, the main drawback of this approach is the occurrence of data gaps in the MODIS satellite imagery. The examination and comparison of the two approaches, regarding their operational use, indicates that the weather station-based approach meets the requirements for operational DFMC mapping to a higher degree compared to the satellite-based approach.

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.

Combining AVHRR and meteorological data for estimating live fuel moisture content

2008 ◽  
Vol 112 (9) ◽  
pp. 3618-3627 ◽  
Author(s):  
Mariano García ◽  
Emilio Chuvieco ◽  
Héctor Nieto ◽  
Inmaculado Aguado
Keyword(s):  
Moisture Content ◽  
Meteorological Data ◽  
Fuel Moisture ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

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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