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Volume 10, issue 1 | Copyright

Special issue: Advances in Mediterranean meteorology

Nat. Hazards Earth Syst. Sci., 10, 61-72, 2010
https://doi.org/10.5194/nhess-10-61-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  14 Jan 2010

14 Jan 2010

Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events

A. Bodini1 and Q. A. Cossu2,1 A. Bodini and Q. A. Cossu
  • 1Institute of Applied Mathematics and Information Technology, Milan, Italy
  • 2Sardinian Environmental Protection Agency, Sassari, Italy

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.

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