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For design and management decisions, particularly regarding hydraulic works, accurate estimates of precipitation magnitudes are needed at different durations. In this article, an objective approach of the regional frequency analysis (RFA) has been applied to precipitation data for the island of Sicily, Italy. Annual maximum series for rainfall with durations of 1, 3, 6, 12, and 24\u2009h from about 130 rain gauges were used. The RFA has been implemented using principal component analysis (PCA) followed by a clustering analysis, through the<jats:italic>k<\/jats:italic>\u2010means algorithm, to identify statistically homogeneous groups of stations for the derivation of regional growth curves. Three regional probability distributions were identified as appropriate from an initial wider selection of distributions and were compared\u00a0\u2013\u00a0the three\u2010parameter log\u2010normal distribution (LN3), the generalized extreme value (GEV) distribution, and the two component extreme value (TCEV) distribution. The regional parameters of these distributions were estimated using L\u2010moments and considering a hierarchical approach. Finally, assessment of the accuracy of the growth curves was achieved by means of the relative bias and relative root\u2010mean\u2010square error (RMSE) using a simulation analysis of regional L\u2010moments. Results highlight that for the lower return periods, all distributions showed the same accuracy while for higher return periods the LN3 distribution provided the best result. The study provides an updated resource for the estimation of extreme precipitation quantiles for Sicily through the derivation of growth curves needed to obtain depth\u2013duration\u2013frequency (DDF) curves.<\/jats:p>","DOI":"10.1002\/joc.5400","type":"journal-article","created":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T08:28:58Z","timestamp":1516177738000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["Regional frequency analysis of extreme rainfall in Sicily (Italy)"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0650-2621","authenticated-orcid":false,"given":"Angelo","family":"Forestieri","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali Universit\u00e0 di Palermo Palermo Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Lo Conti","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali Universit\u00e0 di Palermo Palermo Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen","family":"Blenkinsop","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Geosciences Newcastle University UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcella","family":"Cannarozzo","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali Universit\u00e0 di Palermo Palermo Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hayley J.","family":"Fowler","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Geosciences Newcastle University UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonardo V.","family":"Noto","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Civile, Ambientale, Aerospaziale, dei Materiali Universit\u00e0 di Palermo Palermo Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2018,1,17]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.5194\/hess-17-2449-2013"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)HE.1943-5584.0001264"},{"key":"e_1_2_7_4_1","unstructured":"BeranJ.1986.Estimation Testing and Prediction for Self\u2010similar and Related Processes. 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