Multivariate rainfall disaggregation at a fine timescale

Koutsoyiannis, D; Onof, C; Wheater, HS

dc.contributor.author	Koutsoyiannis, D	en
dc.contributor.author	Onof, C	en
dc.contributor.author	Wheater, HS	en
dc.date.accessioned	2014-03-01T01:19:18Z
dc.date.available	2014-03-01T01:19:18Z
dc.date.issued	2003	en
dc.identifier.issn	0043-1397	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15414
dc.subject	Disaggregation models	en
dc.subject	Hyetograph	en
dc.subject	Multivariate models	en
dc.subject	Rainfall disaggregation	en
dc.subject	Rainfall models	en
dc.subject	Stochastic models	en
dc.subject.classification	Environmental Sciences	en
dc.subject.classification	Limnology	en
dc.subject.classification	Water Resources	en
dc.subject.other	Computer simulation	en
dc.subject.other	Data reduction	en
dc.subject.other	Hydrology	en
dc.subject.other	Mathematical models	en
dc.subject.other	Rain gages	en
dc.subject.other	Hyetographs	en
dc.subject.other	Multivariate models	en
dc.subject.other	Rain	en
dc.subject.other	precipitation (climatology)	en
dc.subject.other	raingauge	en
dc.subject.other	spatial distribution	en
dc.subject.other	temporal variation	en
dc.subject.other	time series	en
dc.title	Multivariate rainfall disaggregation at a fine timescale	en
heal.type	journalArticle	en
heal.identifier.primary	10.1029/2002WR001600	en
heal.identifier.secondary	http://dx.doi.org/10.1029/2002WR001600	en
heal.identifier.secondary	1173	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	[1] A methodology for spatial-temporal disaggregation of rainfall is proposed. The methodology involves the combination of several univariate and multivariate rainfall models operating at different timescales, in a disaggregation framework that can appropriately modify outputs of finer timescale models so as to become consistent with given coarser timescale series. Potential hydrologic applications include enhancement of historical data series and generation of simulated data series. Specifically, the methodology can be applied to derive spatially consistent hourly rainfall series in rain gages where only daily data are available. In addition, in a simulation framework the methodology provides a way to take simulations of multivariate daily rainfall ( incorporating spatial and temporal nonstationarity) and generate multivariate fields at fine temporal resolution. The methodology is tested via a case study dealing with the disaggregation of daily historical data of five rain gages into hourly series. Comparisons show that the methodology results in good preservation of important properties of the hourly rainfall process such as marginal moments, temporal and spatial correlations, and proportions and lengths of dry intervals as well as a good reproduction of the actual hyetographs.	en
heal.publisher	AMER GEOPHYSICAL UNION	en
heal.journalName	Water Resources Research	en
dc.identifier.doi	10.1029/2002WR001600	en
dc.identifier.isi	ISI:000184023500001	en
dc.identifier.volume	39	en
dc.identifier.issue	7	en
dc.identifier.spage	SWC11	en
dc.identifier.epage	SWC118	en