FINE FUEL MOISTURE CODE: CREATING A PREDICATIVE REGIONAL FIRE WEATHER MODEL FOR THE MEDITERRANEAN AREA LA PEYNE, FRANCE
Mediterranean Europe suffers from over 50,000 forest fires annually, the vast majority of which has an anthropogenic ignition source. Climatic change and related land use changes are likely to increase the problems related to forest fires. Models that provide land owners, fire fighters and authorities with daily information on potential fire behavior are therefore of high added value. In this study a Canadian model is applied that relates meteorological indices to fine fuel moisture content, an important indicator for flammability of the fuel complex. This Fine Fuel Moisture Code (FFMC) is adapted from Canadian boreal vegetation to Mediterranean vegetation. Moreover a part of the BEHAVE fire behavior prediction model is added to quantify estimations on rate of spread, fireline intensity and flame length. These three parameters are crucial in crown fire ignition but also have a big influence on the possible way of firefighting. A study area in Southern France was selected to collect fuel moisture content samples in 14 locations over a 10-day period. For each of the four dominant Mediterranean vegetation species a plot was selected that had an 11mm rainfall event simulated. The fuel moisture content data was used to calibrate and validate the FFMC model over the fieldwork period. After calibration the data was used to simulate the moisture content over the period from June 1 to September 6, 2013. This simulated moisture content was used to drive the BEHAVE model. The results showed moderate fire behavior conditions for almost the complete period in all vegetation classes. Extended fire behavior was found on the steep slopes in the dense and middle matorral but the absence of high windspeeds suppressed excessive fire behavior. The accuracy of the BEHAVE model could not be tested, such being outside the scope of this study, but it was successfully evaluated for the Mediterranean in other studies. For the calibrated FFMC model the uncertainty was estimated by a 95% confidence interval, that averaged at 4.3%. The expected accuracy (FFMC + BEHAVE) is assumed highest in dry conditions. It is concluded that this model spatially and temporally estimates summer moisture content and fire behavior with an accuracy good enough for practical use. However also several defects such as parameter generalization and the high dependency on good meteorological data are discussed in this study.