High-Resolution Modeling of Lightning Ignition Likelihood in Spain †
by
, , , ,
Marcos Rodrigues
1,*
,
Pere Joan Gelabert
2,
Víctor Resco de Dios
3,4
,
Adrián Jiménez-Ruano
1,
Luís Torres
5,
Jaime Ribalaygua
5 and
Cristina Vega-García
2 1
Department of Geography and Land Management, University of Zaragoza, 50009 Zaragoza, Spain
2
Department of Agricultural and Forest Engineering, University of Lleida, 25003 Lleida, Spain
3
School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
4
Department of Crop and Forest Sciences, University of Lleida, 25003 Lleida, Spain
5
Meteogrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
†
Presented at the Third International Conference on Fire Behavior and Risk, Sardinia, Italy, 3–6 May 2022.
Environ. Sci. Proc. 2022, 17(1), 40; https://doi.org/10.3390/environsciproc2022017040
Published: 9 August 2022
(This article belongs to the Proceedings of The Third International Conference on Fire Behavior and Risk)
Lightning-caused fires are comparatively rare in Europe, but they may affect remote forested areas and result in large-scale burnings. One of the major hot-spots of lightning fires in Europe lies in Spain, with remarkable ignition counts in the northwest part of the country (el Bierzo) and along certain Mediterranean mountain ranges (Sistema Ibérico). These regions experience frequent thunderstorms and host dense vegetation communities that lead to high rates of natural fires (30% versus the 10% national average).
Here we analyze a large and comprehensive record of hourly cloud-to-ground lightning strikes (>17,000,000), coupled with historical records of lightning fires (>11,000) to determine the biophysical controls (relief, fuel moisture and vegetation structure) and lightning characteristics (flash intensity, polarity and density of discharges) behind natural fires in Spain (2009–2015). The modeling approach combines machine learning techniques and high-resolution proxies (30 m in vegetation height and elevation; 9 km in daily fuel moisture estimates) of the listed variables to train a predictive model encompassing mainland Spain. Relief features (elevation, topographic position index and relief curvature) were computed from the NASADEM global DEM. Tree height was retrieved from the Global Forest Canopy Height. The necessary weather-related inputs to calculate FMC were obtained from the C3S. We tested multiple configurations of strike-to-fire associations and resampling techniques to explore different binary response variables.
The final model was subsequently applied to produce broad- (upscaling into 1 km) and local-scale predictions of daily lightning fire likelihood. The model attains a good predictive performance with a median AUC of 0.82. Lightning-related ignitions triggered preferably under low dead (dFMC8%) and moderate alive (DC > 250) fuel moisture conditions. Lightning strikes with negative polarity were found to trigger fires more frequently when the average density of discharges is higher than 5 at higher altitudes, especially above 500 m.a.s.l.
Author Contributions
Conceptualization, M.R. and C.V.-G.; methodology, M.R. validation, M.R. and A.J.-R.; formal analysis, M.R. and A.J.-R.; investigation, M.R. and C.V.-G.; resources, L.T., J.R. and P.J.G.; data curation, M.R., A.J.-R. and P.J.G.; writing—original draft preparation, M.R.; writing—review and editing, M.R, P.J.G., V.R.d.D., A.J.-R., L.T., J.R. and C.V.-G.; visualization, M.R.; supervision, C.V.-G.; project administration, C.V.-G.; funding acquisition, M.R. and C.V.-G. All authors have read and agreed to the published version of the manuscript.
Funding
This work was funded by projects FirEUrisk - DEVELOPING A HOLISTIC, RISK-WISE STRATEGY FOR EUROPEAN WILDFIRE MANAGEMENT, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003890; and project FIREPATHS (PID2020-116556RA-I00), supported by the Spanish Ministry of Science and Innovation.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data about lightning strikes is managed and distributed by the Spanish Meteorological Agency (AEMET), and acquired by METEOGRID S.L. to conduct this work. Data about lightning-related ignitions was provided by the Spanish and Portuguese agencies. Spanish data comes from the EGIF database (Estadística General de Incendios Forestales; https://www.miteco.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/incendios-forestales.aspx, accessed on 1 March 2021), available upon request to the “Spanish Ministry for the Ecological Transition and the Demographic Challenge” while Portuguese fire data can be accessed in the website by the ICNF (Instituto da Conservação da Natureza e das Florestas; http://www2.icnf.pt/portal/florestas/dfci/inc/estat-sgif, accessed on 1 March 2021). We retrieved elevation data from the NASADEM global digital elevation model (NASA JPL, 2020). We used the global forest canopy height map by Dubayah et al. (2020).
Conflicts of Interest
The authors declare no conflict of interest.
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MDPI and ACS Style
Rodrigues, M.; Gelabert, P.J.; Resco de Dios, V.; Jiménez-Ruano, A.; Torres, L.; Ribalaygua, J.; Vega-García, C. High-Resolution Modeling of Lightning Ignition Likelihood in Spain. Environ. Sci. Proc. 2022, 17, 40. https://doi.org/10.3390/environsciproc2022017040
AMA Style
Rodrigues M, Gelabert PJ, Resco de Dios V, Jiménez-Ruano A, Torres L, Ribalaygua J, Vega-García C. High-Resolution Modeling of Lightning Ignition Likelihood in Spain. Environmental Sciences Proceedings. 2022; 17(1):40. https://doi.org/10.3390/environsciproc2022017040
Chicago/Turabian StyleRodrigues, Marcos, Pere Joan Gelabert, Víctor Resco de Dios, Adrián Jiménez-Ruano, Luís Torres, Jaime Ribalaygua, and Cristina Vega-García. 2022. "High-Resolution Modeling of Lightning Ignition Likelihood in Spain" Environmental Sciences Proceedings 17, no. 1: 40. https://doi.org/10.3390/environsciproc2022017040
