Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya

Fellice Gabrielle Catelo; Marcos Rodrigues; Aitor Ameztegui

doi:10.3390/environsciproc2022017109

Back

Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya

Abstract

Open access

Peer reviewed

Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya

Fellice Gabrielle Catelo, Marcos Rodrigues and Aitor Ameztegui

Environmental Sciences Proceedings, Vol.17(1), pp.1-2

International Conference on Fire Behavior and Risk, 3rd (Sardinia, Italy, 03-May-2022–06-May-2022)

2022

DOI: https://doi.org/10.3390/environsciproc2022017109

Files and links (1)

pdf

environsciproc-17-00109175.38 kBDownload View

Published Version Open Access CC BY V4.0

Abstract

Forestry fire management

Forestry management and environment

wildfire occurrence

initial attack

wildfire prediction

wildfire management

Mediterranean

In recent years, the EU has implemented several firefighting-related policies to battle and reduce the negative impacts of wildfires. However, the changing environment constantly surprises us with extreme events that cause massive losses for the entire Europe, with the Mediterranean region increasing its vulnerability to these risks. Recently, the wildfire season for the region was observed to have lengthened, and along with the rapid change in fire-weather factors, resulted to extreme wildfire events. As of 2022, total burned area for the EU is recorded to be approx. 792,902 (66% forest) (EFFIS Damage Assessment, 2022). It has long been recognized that the Mediterranean cultural landscape is fire-prone, hence decision-makers see to it that responses and solutions are devoted at mitigating and reducing fire risk. With the advocacy of a paradigm shift to coexist with fire, anticipation of fire incidents is the best approach partnered with comprehensive management. Various studies on wildfires provide geospatial insights and models to foresee fire occurrence, burning extent, success in initial attack, ignition probability, etc. This study aims to recognize and understand wildfire activity by forecasting the occurrence of extreme wildfire events in the near future. The approach is based on coupling ignition and escape models to climate (C3S) and landcover-change (SEDAC) projections to outline the spatial distribution of wildfires up to 2100. We calibrated a series of binary regression models upon historical records of wildfire ignition in Catalonia (Northeast of Spain) using machine-learning techniques under different land cover change and climate scenarios. Disaster risk reduction will be improved through this prediction by identifying wildfire management zones and prioritization of areas.

Details

Title: Anticipating Future Extreme Wildfires by Predicting the Probability of Ignition and Escape of Initial Attack in Catalunya
Authors: Fellice Gabrielle Catelo (Corresponding Author) - Universitat de Lleida
Marcos Rodrigues - Universidad de Zaragoza
Aitor Ameztegui (Author) - Universitat de Lleida
Publication details: Environmental Sciences Proceedings, Vol.17(1), pp.1-2
Conference details: International Conference on Fire Behavior and Risk, 3rd (Sardinia, Italy, 03-May-2022–06-May-2022)
Publisher: MDPI AG
Date published: 2022
DOI: 10.3390/environsciproc2022017109
ISSN: 2673-4931
Copyright note: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Data Availability: Fire records data can be freely downloaded from the website of the Ministry for Ecological Transition and the Demographic Challenge (https://www.miteco.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/ifn3_bbdd_descargas.htm.aspx). Landcover change (human population dynamics) data can also be freely downloaded from the website of Socioeconomic Data and Applications Center (SEDAC) (https://sedac.ciesin.columbia.edu/data/sets/browse?facets=theme:population). Climate prediction data were based on the EU-CORDEX project (available at Earth System Grid Federation; http://esgf.llnl.gov/). The original weather data is available at the Spanish Meteorological Agency upon request.
Grant note: This work was funded by the Spanish Ministry of Science and Innovation [grant numbers FIREPATHS (PID2020-116556RA-I00). F.G.C was funded with a scholarship by the MSc in European Forestry Programme at the University of Lleida. This work was also funded by project 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.
Organisation Unit: School of Science, Technology and Engineering; Forest Research Institute
Language: English
Record Identifier: 991223529602621
Output Type: Abstract

Metrics

1 Record Views