Analysis of a long record of annual maximum rainfall in Athens, Greece, and design rainfall inferences

Koutsoyiannis, D; Baloutsos, G

dc.contributor.author	Koutsoyiannis, D	en
dc.contributor.author	Baloutsos, G	en
dc.date.accessioned	2014-03-01T01:15:28Z
dc.date.available	2014-03-01T01:15:28Z
dc.date.issued	2000	en
dc.identifier.issn	0921-030X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/13525
dc.subject	extreme rainfall	en
dc.subject	extreme value distribution	en
dc.subject	intensity-frequency-duration relationship	en
dc.subject	hydrologic statistics	en
dc.subject	flood design	en
dc.subject	flood risk	en
dc.subject	Athens	en
dc.subject.classification	Geosciences, Multidisciplinary	en
dc.subject.classification	Meteorology & Atmospheric Sciences	en
dc.subject.classification	Water Resources	en
dc.subject.other	PRECIPITATION SERIES	en
dc.subject.other	DISTRIBUTIONS	en
dc.subject.other	EXTREME	en
dc.title	Analysis of a long record of annual maximum rainfall in Athens, Greece, and design rainfall inferences	en
heal.type	journalArticle	en
heal.identifier.primary	10.1023/A:1008001312219	en
heal.identifier.secondary	http://dx.doi.org/10.1023/A:1008001312219	en
heal.language	English	en
heal.publicationDate	2000	en
heal.abstract	An annual series of maximum daily rainfall extending through 1860-1995, i.e., 136 years, was extracted from the archives of a meteorological station in Athens. This is the longest rainfall record available in Greece and its analysis is required for the prediction of intense rainfall in Athens, where currently major flood protection works are under way. Moreover, the statistical analysis of this long record can be useful for investigating more generalised issues regarding the adequacy of extreme value distributions for extreme rainfall analysis and the effect of sample size on design rainfall inferences. Statistical exploration and tests based on this long record indicate no statistically significant climatic changes in extreme rainfall during the last 136 years. Furthermore, statistical analysis shows that the conventionally employed Extreme Value Type I(EV1 or Gumbel) distribution is inappropriate for the examined record (especially in its upper tail), whereas this distribution would seem as an appropriate model if fewer years of measurements were available (i.e., part of this sample were used). On the contrary, the General Extreme Value (GEV) distribution appears to be suitable for the examined series and its predictions for large return periods agree with the probable maximum precipitation estimated by the statistical (Hershfield's) method, when the latter is considered from a probabilistic point of view. Thus, the results of the analysis of this record agree with a recently land internationally) expressed scepticism about the EV1 distribution which tends to underestimate the largest extreme rainfall amounts. It is demonstrated that the underestimation is quite substantial (e.g., 1:2 for large return periods and this fact must be considered as a warning against the widespread use of the EV1 distribution for rainfall extremes.	en
heal.publisher	KLUWER ACADEMIC PUBL	en
heal.journalName	NATURAL HAZARDS	en
dc.identifier.doi	10.1023/A:1008001312219	en
dc.identifier.isi	ISI:000089610400003	en
dc.identifier.volume	22	en
dc.identifier.issue	1	en
dc.identifier.spage	29	en
dc.identifier.epage	48	en