Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/68894
Type: Conference paper
Title: Stochastic modelling of (not-so) long-term hydrological data: Current status and future research
Author: Thyer, M.
Frost, A.
Kuczera, G.
Srikanthan, R.
Citation: 30th Hydrology & Water Resources Symposium: past, present & future, Hotel Grand Chancellor, Launceston, 4-7 December, 2006: www1-6
Publisher: Conference Design
Publisher Place: Sandy Bay, Tasmania
Issue Date: 2006
ISBN: 0858257904
9780858257900
Conference Name: Hydrology and Water Resources Symposium (30th : 2006 : Launceston, Tas.)
Statement of
Responsibility: 
Mark Thyer, Andrew Frost, George Kuczera and Ratnasingham Srikanthan
Abstract: Stochastic 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.
Keywords: Stochastic Modelling; Annual Hydrological Data; Parameter Uncertainty; Drought Risk
Rights: Copyright status unknown
RMID: 0020109587
Published version: http://search.informit.com.au/fullText;dn=502003232661455;res=IELENG
Appears in Collections:Civil and Environmental Engineering publications
Environment Institute publications

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