F. Luino, G. Nigrelli, M. Chiarle, M. Biddoccu & C. G. Cirio, 2012, A model for simulating event scenarios and estimating expected economic losses for residential buildings_ preliminary results, . Southampton_ Wit Press, 2012,
URL: http://www.cnr.it/prodotto/i/137703

Floods are very common in Italy. Annually floods occur in different parts of the peninsula and cause severe damage and sometimes result in injuries or fatalities. In the period 1980-2000 the Italian State set aside 7,4 million euro for flood damage, or roughly one million euro per day. Researching historical floods gives evidence of the frequency, magnitude, impacts, areas involved and types of damages. In spite of this wealth of information, town-and-country planning rarely takes into account these lessons of the past. With this study the CNR-IRPI of Torino (Research Institute for Geo-Hydrological Protection) developed a flood damage estimation model for simulating event scenarios and estimating expected economic losses. Potential economic loss assessment implies knowledge of the event, exposed asset values and the degree of damage. Following a widely shared simplifying assumption, flood water level was taken as the only factor indicating event magnitude. The model incorporates the following steps_ a) event description_ definition of flood parameters (inundated area and water level), utilizing real-time measurements or data from event simulation with a hydraulic model; b) asset damage and identification of the affected population; c) evaluation of the damage degree as a function of event magnitude; d) attribution of an economic value to different exposed assets; e) quantification of economic loss by multiplying economic losses and damage severity. The method could be used either as a forecasting tool to define event scenarios or for "real-time" damage assessment just after a catastrophe. This pilot effort can be useful for land administration bodies (land use planning, civil protection, and risk mitigation) and insurance companies in demonstrating the benefit of systematic acquisition and management of flood-related damage data.

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