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You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 1: Extremes and Variability : Quantifying uncertainty in level-of-service statistics using the parametric bootstrap method
Quantifying uncertainty in level-of-service statistics using the parametric bootstrap method
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The Department of Environment and Resource Management is currently developing and implementing a number of regional water supply strategies throughout Queensland. The recent drought in Australia has highlighted the vulnerability of water supplies and the need to better account for climate variability. A level-of service (LOS) approach has been adopted that requires a stochastic model that is capable of computing statistics for events more extreme than those in the historical record. The statistics associated with these extreme events are estimates and therefore the need to quantify their associated uncertainty arises. Three methodologies are employed to compute the uncertainty: no parameter uncertainty (NPU), Stedinger and Taylor (ST) and the parametric bootstrap (PB) methods. Both the ST and PB methods give more realistic estimates of the LOS uncertainty when compared with the NPU method. The conceptually simpler PB method has the added advantage of being easy to incorporate into existing stochastic data generation models.
File Size : 775,289 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 1: Extremes and Variability
Date Published : 01/07/2011
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