Wildfire growth modelling in Sweden - a suitability assessment of available data

Detta är en Master-uppsats från Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

Sammanfattning: Wildfires are worldwide problems that stress societies by damaging their economies and they cause serious, sometimes fatal, health implications among the populations. In recent years, the rate of wildfire occurrence has increased as the global average temperature has risen. Because of global climate change, this rate is expected to continue rising. In Sweden, in the aftermath of the 2014 Västmanland wildfire, the Swedish Civil Contingencies Agency called for an urgent need to develop the national emergency preparedness for disastrous events like wildfires. Maps of forecasted wildfire growth can facilitate the work of emergency services trying to limit the consequences of a wildfire. Hence, the introduction of a wildland fire growth simulation model has the potential to strengthen the Swedish societal resilience to wildfires. However, no Swedish guidelines outlining the necessary collection and preparation of spatial information, required by wildland fire growth simulation models, currently exist. Therefore, the aim of this thesis project was to assess the suitability of available spatial data in Sweden for wildfire growth modelling. This was achieved by first reviewing literature to gain the needed understanding of general wildfire behaviour to allow for the theorising of an expected wildfire propagation in the area burnt by the 2014 Västmanland wildfire. Then, the 2014 Västmanland wildfire was modelled using two wildland fire growth simulation models. Their modelled extents were reviewed and compared with real final perimeter of the modelled wildfire. Finally, based on observed deviations, weaknesses in the spatial data were identified. The study concludes that the, in Sweden, available spatial data is sufficient to allow for wildfire growth modelling. However, the temporal resolution of the ground cover information must increase to reflect changes in vegetation before the modelled forecasts can be suitable for any use.

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