International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH FRONT

Regional aspects of modelling burned areas in Europe

Andrey Krasovskii A C , Nikolay Khabarov A , Mirco Migliavacca B , Florian Kraxner A and Michael Obersteiner A
+ Author Affiliations
- Author Affiliations

A International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria.

B Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany.

C Corresponding author. Email: krasov@iiasa.ac.at

International Journal of Wildland Fire 25(8) 811-818 https://doi.org/10.1071/WF15012
Submitted: 15 January 2015  Accepted: 29 October 2015   Published: 2 February 2016

Abstract

This paper presents a series of improvements to the quantitative modelling of burned areas in Europe under historical climate. The Standalone Fire Model (SFM) based on a state-of-the-art large scale mechanistic fire modelling algorithm is used to reproduce historical burned areas reported in the two publicly available datasets – European Forest Fire Information System (EFFIS) and Global Fire Emissions Database (GFED). The most recent versions of these sources allow a broader validation of SFM’s modelled burned areas at a country level. Our analysis is carried out for the years 2000–2008 for 17 European countries utilising both EFFIS and GFED datasets for model benchmarking. We suggest improving the original model by modifying the fire probability function reflecting fuel moisture. This modification allows for a dramatic improvement of accuracy in modelled burned areas for a range of European countries. We also explore in detail a pixel-level parametrisation of firefighting efficiency in SFM along with modifications of the biomass map. In comparison with the aggregated country-level approach, the advantages of the finer calibration are quite minor for the most recent version of the GFED dataset. Overall, the annual burned areas modelled by this improved SFM version are in good agreement with historical observations.

Additional keywords: fire model, fuel moisture, probability of fire, validation.


References

Albini FA (1976) Estimating wildfire behaviour and effects. Intermountain Forest and Range Experiment Station, Forest Service, U.S. Department of Agriculture, USDA Forest Service General Technical Report INT-3. (Ogden, Utah)

Aragao LEOC, Shimabukuro YE (2010) The incidence of fire in Amazonian Forests with implications for REDD. Science 328, 1275–1278.
The incidence of fire in Amazonian Forests with implications for REDD.CrossRef | 1:CAS:528:DC%2BC3cXmslKqur8%3D&md5=d8ce5015f7fc533b616c7052530aa538CAS |

Arora VK, Boer GJ (2005) Fire as an interactive component of dynamic vegetation models. Journal of Geophysical Research 110, G02008
Fire as an interactive component of dynamic vegetation models.CrossRef |

Barlow J, Parry L, Gardner TA, Ferreira J, Aragão LEOC, Carmenta R, Berenguer E, Vieira ICG, Souza C, Cochrane MA (2012) The critical importance of considering fire in REDD+ programs. Biological Conservation 154, 1–8.
The critical importance of considering fire in REDD+ programs.CrossRef |

Bowman DMJS, Balch JK, Artaxo P, Bond WJ, Carlson JM, Cochrane MA, D’Antonio CM, DeFries RS, Doyle JC, Harrison SP, Johnston FH, Keeley JE, Krawchuk MA, Kull CA, Marston JB, Moritz MA, Prentice IC, Roos CI, Scott AC, Swetnam TW, van der Werf GR, Pyne SJ (2009) Fire in the Earth system. Science 324, 481–484.
Fire in the Earth system.CrossRef | 1:CAS:528:DC%2BD1MXkvVGmtb8%3D&md5=780bfbd84d8f3d0390bfe1cab7be1fd6CAS |

CIESIN (2005) Gridded Population of the World Version 3 (GPWv3): Population Density Grids. Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT), Palisades, NY: Socioeconomic Data and Applications Center (SEDAC), Columbia University. Available at http://sedac.ciesin.columbia.edu/gpw [Verified 27 November 2015]

Costa L, Thonicke K, Poulter B, Badeck F-W (2011) Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages. Regional Environmental Change 11, 543–551.
Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages.CrossRef |

Flatau PJ, Walko RL, Cotton WR (1992) Polynomial fits to saturation vapor pressure. Journal of Applied Meteorology 31, 1507–1513.
Polynomial fits to saturation vapor pressure.CrossRef |

Ganteaume A, Camia A, Jappiot M, San-Miguel-Ayanz J, Long-Fournel M, Lampin C (2012) A review of the main driving factors of forest fire ignition over Europe. Environmental Management 51, 651–662. .Available at http://link.springer.com/article/10.1007/s00267-012-9961-z [Verified 19 November 2015]

Giglio L, Randerson JT, van der Werf GR (2013) Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). Journal of Geophysical Research. Biogeosciences 118, 317–328.
Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4).CrossRef |

Intergovernmental Panel on Climate Change (2013)) Climate change 2013: the physical science basis. Available at http://www.ipcc.ch/report/ar5/wg1/ [Verified 19 November 2015]

Khabarov N, Krasovskii A, Obersteiner M, Swart R, Dosio A, San-Miguel-Ayanz J, Durrant T, Camia A, Migliavacca M (2016) Forest fires and adaptation options in Europe. Regional Environmental Change 16, 21–30.
Forest fires and adaptation options in Europe.CrossRef |

Kindermann GE, McCallum I, Fritz S, Obersteiner M (2008) A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fennica 42, 244
A global forest growing stock, biomass and carbon map based on FAO statistics.CrossRef |

Kloster S, Mahowald NM, Randerson JT, Thornton PE, Hoffman FM, Levis S, Lawrence PJ, Feddema JJ, Oleson KW, Lawrence DM (2010) Fire dynamics during the 20th century simulated by the Community Land Model. Biogeosciences 7, 1877–1902.
Fire dynamics during the 20th century simulated by the Community Land Model.CrossRef |

Kloster S, Mahowald NM, Randerson JT, Lawrence PJ (2012) The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN. Biogeosciences 9, 509–525.
The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN.CrossRef |

Lubowski RN, Rose SK (2013) The potential for REDD+: Key economic modeling insights and issues. Review of Environmental Economics and Policy 7, 67–90.
The potential for REDD+: Key economic modeling insights and issues.CrossRef |

Marlier ME, DeFries RS, Voulgarakis A, Kinney PL, Randerson JT, Shindell DT, Chen Y, Faluvegi G (2012) El Niño and health risks from landscape fire emissions in southeast Asia. Nature Climate Change 3, 131–136.
El Niño and health risks from landscape fire emissions in southeast Asia.CrossRef |

Marlon JR, Bartlein PJ, Carcaillet C, Gavin DG, Harrison SP, Higuera PE, Joos F, Power MJ, Prentice IC (2008) Climate and human influences on global biomass burning over the past two millennia. Nature Geoscience 1, 697–702.
Climate and human influences on global biomass burning over the past two millennia.CrossRef | 1:CAS:528:DC%2BD1cXhtFOlur7E&md5=93e28691564faa1f4ced449c6d533b6dCAS |

Migliavacca M, Dosio A, Camia A, Hobourg R, Houston-Durrant T, Kaiser JW, Khabarov N, Krasovskii AA, Marcolla B, San Miguel-Ayanz J, Ward DS, Cescatti A (2013a) Modeling biomass burning and related carbon emissions during the 21st century in Europe. Journal of Geophysical Research. Biogeosciences 118, 1732–1747.
Modeling biomass burning and related carbon emissions during the 21st century in Europe.CrossRef | 1:CAS:528:DC%2BC2cXptlWmtg%3D%3D&md5=ab836715d9ed0fa93fdfc1e319730c64CAS |

Migliavacca M, Dosio A, Kloster S, Ward DS, Camia A, Houborg R, Houston-Durrant T, Khabarov N, Krasovskii AA, San Miguel-Ayanz J, Cescatti A (2013b) Modeling burned area in Europe with the community land model. Journal of Geophysical Research. Biogeosciences 118, 265–279.
Modeling burned area in Europe with the community land model.CrossRef |

Rego F, Rigolot E, Fernandes P, Montiel C, Silva JS (2010) Towards integrated fire management. European Forest Institute Policy Brief 4. Available at http://www.efi.int/files/attachments/publications/efi_policy_brief_4_en.pdf [Verified 27 November 2015]

San-Miguel-Ayanz J, Camia A (2010) Forest fires. In ‘Mapping the impacts of natural hazards and technological accidents in Europe: an overview of the last decade’. (Eds A Wehrli, J Herkendell, A Jol) EEA Technical Report N13/2010, pp. 47–53. (Copenhagen, Denmark) 10.2800/62638

San-Miguel-Ayanz J, Schulte E, Schmuck G, Camia A, Strobl P, Liberta G, Giovando C, Boca R, Sedano F, Kempeneers P, McInerney D, Withmore C, de Oliveira SS, Rodrigues M, Durrant T, Corti P, Oehler F, Vilar L, Amatulli G (2012) Comprehensive monitoring of wildfires in Europe: The European Forest Fire Information System (EFFIS) In ‘Approaches to managing disaster – assessing hazards, emergencies and disaster impacts’. (Ed. J Tiefenbacher) (InTech: Croatia).10.5772/28441

Santín C, Doerr SH, Preston CM, González-Rodríguez G (2015) Pyrogenic organic matter production from wildfires: a missing sink in the global carbon cycle. Global Change Biology 21, 1621–1633.
Pyrogenic organic matter production from wildfires: a missing sink in the global carbon cycle.CrossRef | 25378275PubMed |

Schmuck G, San-Miguel-Ayanz J, Camia A, Durrant TH, Boca R, Libertá G, Petroliagkis T, Di Leo M, Rodriguez-Aseretto D, Boccacci F, Schulte E (2014) Forest fires in Europe, Middle East and North Africa 2013. Joint Research Centre, Institute for Environment and Sustainability, EUR 26791 EN. (Luxembourg: Publications Office of the European Union) Available at http://forest.jrc.ec.europa.eu/media/cms_page_media/9/FireReport2013_final2pdf_2.pdf [Verified 19 November 2015]

Sheffield J, Goteti G, Wood EF (2006) Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate 19, 3088–3111.
Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling.CrossRef |

Thonicke K, Venevsky S, Sitch S, Cramer W (2001) The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model. Global Ecology and Biogeography 10, 661–677.
The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model.CrossRef |

Van Wagner CE, Pickett TL (1985) ‘Equations and FORTRAN program for the Canadian Forest Fire Weather Index System.’ (Canadian Forestry Service, Petawawa National Forestry Institute: Chalk River, Ontario) Available at http://cfs.nrcan.gc.ca/publications/?id=19973 [Verified 19 November 2015]

Vélez R (1990) Mediterranean forest fires: a regional perspective. Available at http://www.fao.org/docrep/t9500e/t9500e02.htm [Verified 27 November 2015]



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