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Projecting wildfire occurrence at regional scale from Land Use/Cover and climate change scenarios

This work aims to project wildfire occurrence at regional scale by combining information derived from future Land Use/Cover change (LUCC) and climate scenarios in Madrid region (Spain). Generalized Linear Models have been used to obtain a historical wildfire occurrence model for the 2000-2010 period at 1x1km grid cell resolution. Land Use/Cover (LUC) interfaces: Wildland Urban Interface (WUI), Forest-Agricultural interface (FAI) and Forest-Grassland interface (FGI) have been derived and used as input drivers related to human-caused wildfire ignitions along with other variables such as orientation, precipitation, maximum temperature and live fuel moisture content (LFMC). A future LUC scenario by 2050 was run up by using Land Change Modeler (LCM). LCM transition susceptibility maps were calculated by neural networks and Markov chain matrices were used to determine the quantity of change. The model was calibrated with the observed LUCC between 1998 and 2008. Real 2015 map was used to assess model performance. Overall agreement between real and modeled maps was >90%. The trend scenario was run using drivers of change and restrictions to generate the LUC map for the year 2050, obtaining the future interfaces (WUI, FAI, FGI) from this map. Average projected precipitation and temperature for the 2050s for Spain were obtained from the regional climate model RACMO22E, from the KNMI, driven by the global climate model EC-EARTH and considering the two future experiments RCP4.5 and RCP8.5, which has been developed under the European branch of the CORDEX initiative (http://www.cordex.org/), Euro-CORDEX, at 12x12 km approximately. In order to obtain the final resolution (1 km) of the climate indicators, the climate change signal (12 km), defined as the difference between the future and historical periods (delta), was added to the observed climatology (1km), obtaining the future climatology at 1km (Bedia et al., 2013). Note that this is the simplest bias calibration method which assumes a linear bias of the models which disappears when considering those deltas. LFMC from year 2005 was used for 2050 wildfire estimation as it was the most similar to 2050 in terms of climatic conditions. Wildfire occurrence prediction was finally obtained by applying the historical wildfire occurrence model to 2050 . Generally speaking future wildfire occurrence will increase in the study site.

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