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A comparative study of fire weather indices in a semiarid south-eastern Europe region. Case of study: Murcia (Spain)

Author:
Pérez-Sánchez, Julio, Senent-Aparicio, Javier, Díaz-Palmero, José María, de Dios Cabezas-Cerezo, Juan
Source:
The Science of the total environment 2016
ISSN:
0048-9697
Subject:
case studies, coasts, drought, fire weather, forest ecosystems, forest fires, forests, prediction, rain, risk, selection methods, semiarid zones, temperature, Iberian Peninsula, Spain
Abstract:
Forest fires are an important distortion in forest ecosystems, linked to their development and whose effects proceed beyond the destruction of ecosystems and material properties, especially in semiarid regions. Prevention of forest fires has to lean on indices based on available parameters that quantify fire risk ignition and spreading. The present study was conducted to compare four fire weather indices in a semiarid region of 11,314km2 located in southern Spain, characterised as being part of the most damaged area by fire in the Iberian Peninsula. The studied period comprises 3033 wildfires in the region during 15years (2000–2014), of which 80% are >100m2 and 14% >1000m2, resulting around 40km2 of burnt area in this period. The indices selected have been Angström Index, Forest Fire Drought Index, Forest Moisture Index and Fire Weather Index. Likewise, four selection methods have been applied to compare the results of the studied indices: Mahalanobis distance, percentile method, ranked percentile method and Relative Operating Characteristic curves (ROC). Angström index gives good results in the coastal areas with higher temperatures, low rainfall and wider range of variations while Fire Weather Index has better results in inland areas with higher rainfall, dense forest mass and fewer changes in meteorological conditions throughout the year. ROC space rejects all the indices except Fire Weather Index with good performance all over the region. ROC analysis ratios can be used to assess the success (or lack thereof) of fire indices; thus, it benefits operational wildfire predictions in semiarid regions similar to that of the case study.
Agid:
5644479