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Article << Previous     |     Next >>   Contents Vol 23(6)

Area burned in Portugal over recent decades: an extreme value analysis

M. G. Scotto A F, S. Gouveia B, A. Carvalho C, A. Monteiro C, V. Martins C, M. D. Flannigan D, J. San-Miguel-Ayanz E, A. I. Miranda C and C. Borrego C

A Center for Research & Development in Mathematics and Applications (CIDMA) and Department of Mathematics, University of Aveiro, Campus de Santiago, PT-3810-193 Aveiro, Portugal.
B Institute of Electronics and Telematics Engineering of Aveiro (IEETA) and CIDMA, University of Aveiro, Campus de Santiago, PT-3810-193 Aveiro, Portugal.
C Centre for Environmental and Marine Studies (CESAM) and Department of Environment and Planning, University of Aveiro, Campus de Santiago, PT-3810-193 Aveiro, Portugal.
D Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB, T6G 2H1, Canada.
E Institute of Environment and Sustainability, Joint Research Centre, Via Fermi 1, I-21027 Ispra, Italy.
F Corresponding author. Email address: mscotto@ua.pt

International Journal of Wildland Fire 23(6) 812-824 http://dx.doi.org/10.1071/WF13104
Submitted: 18 December 2012  Accepted: 14 January 2014   Published: 1 July 2014

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Forest fires are a major concern in Europe, particularly in Portugal where large forest fires are responsible for negative environmental, social and economic effects. In this work, a long time series of daily area burned in 18 Portuguese districts (north, coastal areas and inner–south) from 1980 to 2010 are analysed to characterise extreme area burned and regional variability. The analysis combines the peak-over-threshold method and classification techniques to cluster the time series on the basis either of their corresponding tail indices or their predictive distributions for 5- and 15-year return values, that is, the level that is exceeded on average once every 5 or 15 years. As previously reported in other wildfire studies, the results show that the distributions of area burned (1980–2010) are heavy tailed for all Portuguese districts, with considerable density in the tail, indicating a non-negligible probability of occurrence of days with very large area burned. Moreover, clustering based on tail indices identified three distinct groups with spatial pattern closely related to the percentage of shrub cover within each district. Finally, clustering based on return values shows that the largest return levels of area burned are expected to occur in districts located in the centre and south of Portugal.

Additional keywords: classification, cluster analysis, return values, tail index.


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