Abstract

According to the Hyogo Framework for Action, increasing resilience todrought requires the development of a people-centered monitoring and early warningsystem, or in other words, a system capable of providing useful and understandableinformation to the community at risk. To achieve this objective, it is crucial to negotiate acredible and legitimate knowledge system, which should include both expert and localknowledge. Although several benefits can be obtained, the integration of local and scientificknowledge to support drought monitoring is still far from being the standard indrought monitoring and early warning. This is due to many reasons, that is, the reciprocalskepticism of local communities and decision makers, and the limits in the capacity tounderstand and assess the complex web of drought impacts. This work describes amethodology based on the sequential implementation of Cognitive Mapping and BayesianBelief Networks to collect, structure and analyze stakeholders' perceptions of droughtimpacts. The methodology was applied to analyze drought impacts at Lake Trasimeno(central Italy). A set of drought indicators was developed based on stakeholders' perceptions.A validation phase was carried out comparing the perceived indicators of droughtand the physical indicators (i.e., Standard Precipitation Index and the level of the lake).Some preliminary conclusions were drawn concerning the reliability of local knowledge tosupport drought monitoring and early warning.

Autore Pugliese

• Giordano Raffaele

Tutti gli autori

• Giordano R.; Preziosi E.; Romano E.

Titolo volume/Rivista

Natural hazards

Anno di pubblicazione

2013

ISSN

0921-030X

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

Non Disponibile

Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

Non Disponibile