Visit by Dr Fiorucci and seminar on wildfire risk

Paolo Fiorucci from CIMA (Univ. of Genoa, Italy) will give a lunchtime seminar on the 9th of February on "A general framework for wildfire risk assessment and management in Mediterranean area" in the AGB Seminar Room at 1.15 pm. Abstract bellow.

Paolo Fiorucci has a PhD in Environmental Monitoring. He is currently project leader at CIMA. CIMA is a Joint-Foundation between the University of Genoa and the Italian Civil Protection. It supports research in the field of civilian and environmental protection. His research interests focus on forest fire risk assessment and management by means of statistical analysis and dynamic model development. He is author and coauthor of more then 30 papers, 7 published in international refereed journals. He is also teaching assistant from 1997 supporting different courses on Modelling and Simulation, Natural risk management and Forest
Fires within the undergraduate courses on Environmental Engineering and Electronic Engineering at the University of Genoa. He has been and he his Scientific Director of several national and international projects.


A general framework for wildfire risk assessment and management in Mediterranean area

The analysis of time series of burned areas combined with a detailed knowledge of topography, land cover and climate conditions allow understanding which are the main features involved in forest fire occurrences and their behaviour. Based on this information it is possible to develop statistical methods for the objective
classification of forest fire static risk at regional scale. The analysis suggests that fire regime in Mediterranean ecosystem is strictly related with species highly vulnerable to fire but highly resilient, as characterized by a significant regenerative capacity after the fire spreading. Only rarely, and characterized by negligible damage, the fire affects the areas covered by climax species in relation with altitude and soil types (i.e, quercus, fagus, abies). On the basis of these results, it is proved how the simple Drossel-Schwabl Forest Fire Model is able to reproduce the forest fire regime in terms of number of fires and burned area.
On this basis, an experimental propagation model has been developed to provide Italian Civil Protection Department (DPC) with rapid active fire risk assessment maps. The propagation model is based on stochastic cellular automata. The model provides in a fast and simple way realistic scenarios useful for active fire management, highlighting the zones where the fire attack can be more effective. Several case studies proved that the model give better results in case of complex terrain and vegetation mosaic. In case of flat terrain and homogeneous fire dependent vegetation cover, the fire perimeter is mainly determined by meteorological variability (wind speed and direction) and fire attack. In fact, extreme fire hazard situations are strictly related with extreme weather conditions mainly related with very low relative humidity and strong winds. Such extreme situations are generally well defined by Numerical Weather Prediction Models up to 48 h before the event occurs. In this connection Fire Hazard forecast systems are able to anticipate the extreme fire situation up to 48 hours. The system RISICO provides Italian Civil Protection Department (DPC) with daily wildland fire risk forecast maps relevant to the whole national territory since 2003. The RISICO system has a complex software architecture based on a framework able to manage geospatial data as well as time dependent information (e.g, Numerical Weather Prediction, real time meteorological observations, and satellite data). Within the system semi-physical models, able to simulate in space and time the variability of the fuel moisture content, are implemented. This parameter represents the main variable related with the ignition of a fire. Based on this information and introducing information on topography and wind field the model provides the rate of spread and the linear intensity of a potential fire generated by accidental or deliberate ignition. The model takes into account the vegetation patterns, in terms of fuel load and flammability. Integrating in a single framework the complete suite of all the models introduced above it is possible to critically reduce fire risk thus preventing serious environmental damages.