Rainfall disaggregation using adjusting procedures on a Poisson cluster model

Koutsoyiannis, D; Onof, C

dc.contributor.author	Koutsoyiannis, D	en
dc.contributor.author	Onof, C	en
dc.date.accessioned	2014-03-01T01:16:59Z
dc.date.available	2014-03-01T01:16:59Z
dc.date.issued	2001	en
dc.identifier.issn	0022-1694	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14306
dc.subject	Disaggregation	en
dc.subject	Point processes	en
dc.subject	Rainfall	en
dc.subject	Stochastic processes	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Geosciences, Multidisciplinary	en
dc.subject.classification	Water Resources	en
dc.subject.other	Algorithms	en
dc.subject.other	Computer simulation	en
dc.subject.other	Mathematical models	en
dc.subject.other	Poisson distribution	en
dc.subject.other	Rain	en
dc.subject.other	Time series analysis	en
dc.subject.other	Bartlett-Lewise process	en
dc.subject.other	Hydrology	en
dc.subject.other	algorithm	en
dc.subject.other	methodology	en
dc.subject.other	rainfall	en
dc.subject.other	United Kingdom	en
dc.subject.other	United States	en
dc.title	Rainfall disaggregation using adjusting procedures on a Poisson cluster model	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0022-1694(01)00363-8	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0022-1694(01)00363-8	en
heal.language	English	en
heal.publicationDate	2001	en
heal.abstract	A disaggregation methodology for the generation of hourly data that aggregate up to given daily totals is developed. This combines a rainfall simulation model based upon the Bartlett-Lewis process with proven techniques developed fur the purpose of adjusting the finer scale (hourly) values so as to obtain the required coarser scale (daily) values. The methodology directly answers the question of the possible extension of the short hourly time-series with the use of longer-term daily data at the same point and provides the theoretical basis for an operational use of this methodology when no hourly data an available. The algorithm has been validated in full test mode in the case where hourly data are available. Specifically, two case studies (from the UK and US) are examined whose results indicate a good performance of the methodology in preserving the most important statistical properties of the rainfall process. (C) 2001 Elsevier Science B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Journal of Hydrology	en
dc.identifier.doi	10.1016/S0022-1694(01)00363-8	en
dc.identifier.isi	ISI:000168909900008	en
dc.identifier.volume	246	en
dc.identifier.issue	1-4	en
dc.identifier.spage	109	en
dc.identifier.epage	122	en