INTEGRAZIONE DELLA MODELLAZIONE DEGLI EVENTI ESTREMI CON I DATI STORICI E LA PERCEZIONE DEL RISCHIO DELLE CALAMITÀ NATURALI — IJEGE
 
 
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INTEGRATING EXTREME EVENTS MODELING WITH DIACHRONIC DATA AND RISK PERCEPTION OF NATURAL HAZARDS



Abstract:
The phenomena involved in extreme fl ood events are complex and their prediction is affected by a given degree of uncertainty, that makes the warning communication very difficult to achieve. The promotion of the natural hazards perception and the improvement in warning communication, aimed at human life losses reduction, therefore, became extremely desirable. This work analyzes the disastrous fl ash-fl ood occurred on 19 June 1996 in the mountain river basins of the Apuanian Alps in Central Italy. The event was exceptional, the impacts on the population were dramatic, the effects on building and infrastructures were catastrophic. With reference to the event, a geodatabase integrating diachronic data with the results of hydrological and sedimentological modeling, has been implemented. The purpose is to provide valuable aid to flash-floods prediction, risk assessment and mitigation activities. The attempt, to combine all the information available on the event and on the history of floods of Versilia region together with human exposure to fl ash-fl ood risk, has also been explored. The aim is to investigate the detailed hydrometeorological circumstances that lead to accidental casualties and to better understand the predominant physical factors of risk. The importance of the promotion of the hydrogeological risk perception was also highlighted during a specifi c training experience carried out after the event.

Authors:
Enrica CAPORALI - Università degli Studi di Firenze, Dipartimento di Ingegneria Civile e Ambientale
Tiziana PILEGGI - Università degli Studi di Firenze, Dipartimento di Ingegneria Civile e Ambientale
Giorgio FEDERICI - Università degli Studi di Firenze, Dipartimento di Ingegneria Civile e Ambientale
Keywords
extreme idrometeorological events, distributed hydrological and sedimentological modeling, diachronic data, human exposure to risk, risk perception
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