Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/68894
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dc.contributor.authorThyer, M.en
dc.contributor.authorFrost, A.en
dc.contributor.authorKuczera, G.en
dc.contributor.authorSrikanthan, R.en
dc.date.issued2006en
dc.identifier.citation30th Hydrology & Water Resources Symposium: past, present & future, Hotel Grand Chancellor, Launceston, 4-7 December, 2006: www1-6en
dc.identifier.isbn0858257904en
dc.identifier.isbn9780858257900en
dc.identifier.urihttp://hdl.handle.net/2440/68894-
dc.description.abstractStochastic modelling of long-tem hydrological data is one of the tools used to evaluate water supply system security. This paper summarizes the findings of recent research on stochastic modelling of annual hydrological data which has a significant impact on its practical application. Firstly, in the single-site context the relatively short lengths of observed records induce significant parameter uncertainty which severely hinders model identification. Secondly, a generalised framework has been developed which can evaluate model and parameter uncertainty for multi-site models of annual hydrological data. Two simplified reservoir simulation case studies demonstrated that estimates of drought risk were significantly increased when parameter uncertainty was incorporated. This indicates current approaches underestimate drought risk. Several issues are highlighted which need to be resolved prior to the application of this general framework to more realistic case studies. These are currently the subject of further research. The aim is that in the near future a general framework for calibrating multi-site stochastic models of hydrological data will be available for water supply authorities to improve their estimation of long-term drought risks.en
dc.description.statementofresponsibilityMark Thyer, Andrew Frost, George Kuczera and Ratnasingham Srikanthanen
dc.language.isoenen
dc.publisherConference Designen
dc.rightsCopyright status unknownen
dc.source.urihttp://search.informit.com.au/fullText;dn=502003232661455;res=IELENGen
dc.subjectStochastic Modelling; Annual Hydrological Data; Parameter Uncertainty; Drought Risken
dc.titleStochastic modelling of (not-so) long-term hydrological data: Current status and future researchen
dc.typeConference paperen
dc.identifier.rmid0020109587en
dc.contributor.conferenceHydrology and Water Resources Symposium (30th : 2006 : Launceston, Tas.)en
dc.publisher.placeSandy Bay, Tasmaniaen
dc.identifier.pubid29313-
pubs.library.collectionCivil and Environmental Engineering publicationsen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidThyer, M. [0000-0002-2830-516X]en
Appears in Collections:Civil and Environmental Engineering publications
Environment Institute publications

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