Streamflow Data Preparation for Regional Flood Frequency Analysis: Lessons from Southeast Australia

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Show simple item record Haddad, K en_US Weinmann, P en_US Rahman, Ataur en_US Kuczera, G en_US Ball, James en_US
dc.contributor.editor en_US 2011-02-07T06:23:40Z 2011-02-07T06:23:40Z 2010 en_US
dc.identifier 2009006715 en_US
dc.identifier.citation Haddad K et al. 2010, 'Streamflow Data Preparation for Regional Flood Frequency Analysis: Lessons from Southeast Australia', Engineers Media Pty. Ltd., vol. 14, no. 1, pp. 17-32. en_US
dc.identifier.issn 1324-1583 en_US
dc.identifier.other C1 en_US
dc.description.abstract This paper presents a case study on streamflow data preparation for a regional flood frequency analysis (RFFA) project for the states of Victoria and NSW, in connection with the forthcoming edition of Australian Rainfall and Runoff. The study gathered annual maximum flood series data for a large number of stations from Victoria and NSW, and applied various statistical techniques to prepare the final data set. It was found that a large primary data set, even if selected using a fairly stringent set of criteria, cannot guarantee a similarly large final data set, as streamflow data are affected by many sources of uncertainty. The trade-offs between quality and quantity are discussed and illustrated. The maximum rating ratio, defined as the ratio of the largest estimated flow and the maximum measured flow at a gauging station, is used to identify stations whose quantiles may be seriously affected by rating curve errors. In a case study involving Victorian stations, the importance of maintaining a high spatial coverage of stations was demonstrated. It was shown that a 50% reduction in the number of stations used in a RFFA resulted in an increase of the standard error of prediction of flood quantiles up to 90%. en_US
dc.language en_US
dc.publisher Engineers Media Pty. Ltd. en_US
dc.title Streamflow Data Preparation for Regional Flood Frequency Analysis: Lessons from Southeast Australia en_US
dc.parent Australian Journal of Water Resources en_US
dc.journal.volume 14 en_US
dc.journal.number 1 en_US
dc.publocation Australia en_US
dc.identifier.startpage 17 en_US
dc.identifier.endpage 32 en_US FEIT.School of Civil and Environmental Engineering en_US
dc.conference Verified OK en_US
dc.for 090500 en_US
dc.personcode 0000063250 en_US
dc.personcode 0000063251 en_US
dc.personcode 0000063252 en_US
dc.personcode 0000063253 en_US
dc.personcode 997686 en_US
dc.percentage 100 en_US Civil Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US
dc.location.activity en_US
dc.description.keywords Flood forecasting -- Australia; Flood damage prevention -- Australia; Flood forecasting -- Mathematical models; Floods -- Data processing; Flood control -- Statistical methods en_US
dc.staffid 997686 en_US

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