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

Abstract

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 EastWest 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.

Consequences to flood management of using different probability distributions to estimate extreme rainfall

“…Although trend analyses have not yet observed strong evidence of increasing rainfall in Europe (e.g. Bodini and Cossu, 2010;Toretti et al, 2010;Norrant and Douguédroit, 2006;Klein Tank and Können, 2003), enhanced extreme rainfall events are anticipated as a result of climate change (e.g. IPCC, 2007;Ekström et al, 2005;Palmer and Räisänen, 2002).…”

“…Other studies (e.g. Bodini and Cossu, 2010) also advocate the use of local rainfall data to improve model results, especially at locations where local particularities affect the rainfall distribution over small areas. Properly assessing the capacity of flood defences is key to ensure that they will not be overwhelmed by extreme rainfall events.…”

“…The most common PD used in the analysis of extreme rainfall are the Generalised Extreme Value (GEV) or the Generalised Pareto (e.g. Davidson and Smith, 1990;Coles, 2001;Bodini and Cossu, 2010;Toretti et al, 2010). However, other PDs might show a better fit to some datasets and the difference in the precipitation depths for the resulting return periods can be significant.…”

Spatial coherency of extreme weather events in Germany and Switzerland

“…Finally, more advanced statistical methods for the spatial dependence of extreme events, e.g. applying multivariate statistics, as suggested by Bodini and Cossu (2010), may be used for comparative studies.…”

Bayesian trend analysis for daily rainfall series of Barcelona

“…Within the same study, the possibility of an abrupt change due to an improvement in measurement technology is discussed (Raftery, 1989). Other climatic variables such as temperatures (Parey et al, 2007) or rainfall have been also assessed for trends, through nonparametric tests (Pujol et al, 2007) or linear regression type tests (Bodini and Cossu, 2010). However, some authors (Katz et al, 2002) consider that the evidence of trends based on least squares regression does not necessarily reflect properties of extremes like heavy tails.…”