http://www.cnr.it/ontology/cnr/individuo/prodotto/ID31570
Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events (Articolo in rivista)
- Type
- Label
- Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events (Articolo in rivista) (literal)
- Anno
- 2010-01-01T00:00:00+01:00 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- A. Bodini, Q.A. Cossu (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- Google Scholar (literal)
- ISI Web of Science (WOS) (literal)
- GeoRef (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-IMATI, ARPA Sardegna (literal)
- Titolo
- Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events (literal)
- Abstract
- In Sardinia (Italy), the highest frequency of extreme
events is recorded in the Central-East area (3-4 events
per year). The presence of high and steep mountains near the
sea on the central and south-eastern coast, causes an East-
West precipitation gradient in autumn especially, due to hot
and moist currents coming from Africa. Soil structure and
utilization make this area highly vulnerable to flash flooding
and landslides. The specific purpose of this work is to
provide a description of the heavy rainfall phenomenon on a
statistical basis. The analysis mainly focuses on i) the existence
of trends in heavy rainfall and ii) the characterization
of the distribution of extreme events. First, to study possible
trends in extreme events a few indices have been analyzed by
the linear regression test. The analysis has been carried out
at annual and seasonal scales. Then, extreme values analysis
has been carried out by fitting a Generalized Pareto Distribution
(GPD) to the data. As far as trends are concerned,
different results are obtained at the two temporal scales: significant
trends are obtained at the seasonal scale which are
masked at the annual scale. By combining trend analysis
and GPD analysis, the vulnerability of the study area to the
occurrence of heavy rainfall has been characterized. Therefore,
this work might support the improvement of land use
planning and the application of suitable prevention systems.
Future work will consider the extension of the analysis to all
Sardinia and the application of statistical methods taking into
account the spatial correlation of extreme events. (literal)
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