Drought-Forest Fire Relationships

Varol, Tuğrul; Ertuğrul, Mertol; Özel, Halil Barış

doi:10.5772/intechopen.68487

Cited by 3 publications

(3 citation statements)

References 56 publications

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“…4b). As previously reported, the relationship between SPEI and forest fires is very high (Varol et al 2017, Hadisuwito & Hassan 2018, McEvoy et al 2019.…”

Section: Drought Indices As Fuel Dryness Estimatorsmentioning

confidence: 51%

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Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

Vilchis-Francés¹,

Díaz-Delgado²,

Becerril-Piña³

et al. 2021

iForest

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Biogeosciences and Forestry Biogeosciences and ForestryDaily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands Aleida Yadira Vilchis-Francés (1-2) , Carlos Díaz-Delgado (1-2) , Rocío Becerril Piña (1-2) , Carlos Alberto Mastachi Loza (1) , Miguel Ángel Gómez-Albores (1) , Khalidou M Bâ (1) We analyzed the behavior of forest fires for daily prediction purposes in one of the regions with the highest fire incidence in Mexico. The main objective was to build logistic regression models (LRMs) for daily prediction of forest fire ignition based on meteorological drought indices. We built 252 LRMs for seven types of vegetation cover of greater representativeness and interest for the study area. Three dynamic variables were considered to estimate daily dryness in combustible fuels based on the effective drought index and the standardized precipitation-evapotranspiration index. Additionally, two weather data sources were included in drought indices: conventional weather stations (CWS) and automatic weather stations (AWS). Prediction efficiency assessment for LRMs was done through the relative operating characteristic (ROC) and model precision efficiency (MPE). The results show that LRMs using data from CWS performed relatively better than those based on data from AWS, as the former data sources have higher spatial density and thus generate predictions with higher accuracy (ROC ≥ 0.700, MPE ≥ 0.934). For both data sources, the use of standardized precipitation-evapotranspiration index as a fuel dryness estimator is recommended, as it reflects an atmospheric moisture balance between precipitation and reference evapotranspiration (ROC ≥ 0.734, MPE = 1). Such predictive models can be used as inputs in early warning systems for forest fire prevention or mitigation.

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“…4b). As previously reported, the relationship between SPEI and forest fires is very high (Varol et al 2017, Hadisuwito & Hassan 2018, McEvoy et al 2019.…”

Section: Drought Indices As Fuel Dryness Estimatorsmentioning

confidence: 51%

“…The use of these indices is due to their popularity and effectiveness in modeling the drought phenomenon during the last decade (Hadisuwito & Hassan 2018). Some studies have used drought indices such as SPEI to identify the occurrence of fires (Varol et al 2017 (Byun & Wilhite 1999).…”

Section: Introductionmentioning

confidence: 99%

Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

Vilchis-Francés¹,

Díaz-Delgado²,

Becerril-Piña³

et al. 2021

iForest

View full text Add to dashboard Cite

show abstract

“…In fact, the relationships between drought and wildfires are well documented for MTEs, especially in Europe [46,47], Australia [48,49] and North America [50], with wildfire occurrence and area clearly increasing in response to drought [51,52]. There is also evidence that drought interacts with other controls (wind regimes, topography, forest management activities) to affect fire intensity, severity, extent, and frequency [50,53].…”

Section: Introductionmentioning

confidence: 99%

Electrical Responses of Pinus halepensis Mill. as an Indicator of Wildfire Risk in Mediterranean Forests by Complementing Live Fuel Moisture

Zapata

Oliver-Villanueva

Lemus

et al. 2022

Forests

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Pinus halepensis forests, as Mediterranean-type ecosystems, are subject to high levels of wildfire risk in times of drought, with meteorological conditions of water stress and very high temperatures, mainly in summer. Considering the difficulty of knowing the phenological state of this species, the objective of this research was to evaluate the possibility of implementing the electrical responses (voltage and short-circuit current) as a variable in fire risk management models, compared to live fuel moisture. On the one hand, the obtained results demonstrate non-significant differences between the moisture content of the different fractions of the living branches (base and half of the branch and live fuel), even in times of drought with hydric stress and very high temperatures. Live fuel moisture of Pinus halepensis does not show significant seasonal variations under the influence of extreme fire risk factors. For this reason, it should be complemented with other variables for fire risk management models. On the other hand, the differences registered in the electrical signal show oscillations with significant variations, which are strongly correlated with the periods of extremely favourable meteorological conditions for wildfires. So, the voltages measured show ranges that correspond with great accuracy to the FWI. Voltage variation is dependent on the hydraulic dynamic plant behaviour and a result of the physiological response of pine trees to abiotic stress of drought. It is an easy-to-measure electrical parameter as well as a very reliable indicator with a high correlation with wildfire risk. Thus, electrical responses could add more knowledge about the phenological state of the trees in dependence on stress climatic conditions, allowing integration of these variables in the preventive wildfire modelling and management.

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Joint Spatio-Temporal Analysis of Various Wildfire and Drought Indicators in Indonesia

et al. 2022

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Wildfires are well known as annual disasters in Indonesia. More than 3 million ha was burned in the last 5 years. During an extreme event such as in 2019, carbon emissions can cause smog disasters in neighboring countries such as Malaysia and Singapore. Though difficult to predict, many hotspots that appear can be used to indicate the emergence of large-scale wildfires. The objective of this research is to provide suggestions in terms of used variables when analyzing fire event indication (hotspot), fire event scale (burned area), and fire event impact (carbon emissions). This research provides a spatio-temporal analysis and dependency between drought (precipitation and its derivative variables) and fire indicators (hotspot, burned area, and carbon emission). This research provides the different characteristics of each indicator when used to find joint patterns of burned areas, hotspots, and carbon emissions. Overall, using potential evapotranspiration and precipitation to calculate climate water balance gives great results in all analysis. Precipitation anomalies give the best joint spatial pattern to describe wildfire events in the area with monsoonal rainfall. Meanwhile, precipitation gives better results by capturing more wildfire events in a temporal pattern, even on robust analysis.

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Drought-Forest Fire Relationships

Cited by 3 publications

References 56 publications

Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

Electrical Responses of Pinus halepensis Mill. as an Indicator of Wildfire Risk in Mediterranean Forests by Complementing Live Fuel Moisture

Joint Spatio-Temporal Analysis of Various Wildfire and Drought Indicators in Indonesia

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