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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional Autónoma de México
2023
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| Online Access: | https://www.redalyc.org/articulo.oa?id=56880050004 https://www.redalyc.org/journal/568/56880050004/ https://www.redalyc.org/journal/568/56880050004/html/ https://www.redalyc.org/journal/568/56880050004/56880050004.epub https://www.redalyc.org/journal/568/56880050004/movil |
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Table of Contents:
- Modeling Forest Wildfires at Regional Scales José de Jesús Graciano-Luna Felipa de Jesús Rodríguez-Flores Sacramento Corral Rivas José Návar Ciencias de la Tierra Stochastic Physically Probabilistic Regional scales based and Conceptual models This paper sets the following objectives: (i) presenting, (ii) testing, and (iii) evaluating a set of mathematical techniques to forecast the number of forest wildfires (No), the burned area (A), and the mean burned area (MA), on annual basis at regional scales. A comprehensive wildfire data set for coniferous forests of the State of Durango, Mexico was used to fit (1970-2011) and to validate (2012-2016) some modeling techniques. Most tested probabilistic and stochastic models hardly explain 70% of the wildfire variance. However, the teleconnection approach using a combination of large scale and local hydroclimate anomalies better predicted both data sets; explaining nearly 80% of the wildfire variance for fitting and for validating models. Results stress the complexity of interactive factors including the stochastic and underlying physical process that makes the prediction of wildfires losing precision and they should be further considered in future conceptual models. Therefore, proposing a more physical-based and conceptual models including Montecarlo models is an integral component of this paper; with the goal of increasing prediction capabilities and assisting decision-makers on the prevention activities inherent to better control wildfires. This proposed conceptual model stresses the need for using the probabilistic, stochastic and physical techniques to improve sub-model parameterization. Furthermore, the use of Monte Carlo simulation techniques would extract the most likely future scenarios for predicting the risk of high-severity wildfire regimes in temperate forests elsewhere. 2023 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56880050004 https://www.redalyc.org/journal/568/56880050004/ https://www.redalyc.org/journal/568/56880050004/html/ https://www.redalyc.org/journal/568/56880050004/56880050004.epub https://www.redalyc.org/journal/568/56880050004/movil 10.22201/igeof.2954436xe.2023.62.3.1713 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.3 Vol.62