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

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Show simple item record Haddad, K Weinmann, PE Rahman, A Kuczera, G Ball, JE 2011-02-07T06:23:40Z 2010-01
dc.identifier.citation Australian Journal of Water Resources, 2010, 14 (1), pp. 17 - 32
dc.identifier.issn 1324-1583
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%.
dc.publisher Engineers Media Pty. Ltd.
dc.title Streamflow Data Preparation for Regional Flood Frequency Analysis: Lessons from Southeast Australia
dc.type Journal Article
dc.parent Australian Journal of Water Resources
dc.journal.volume 1
dc.journal.volume 14
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 0905 Civil Engineering
dc.personcode 997686
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.description.keywords Flood forecasting -- Australia
dc.description.keywords Flood damage prevention -- Australia
dc.description.keywords Flood forecasting -- Mathematical models
dc.description.keywords Floods -- Data processing
dc.description.keywords Flood control -- Statistical methods
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group /University of Technology Sydney/Strength - Technology in Wastewater Treatment
utslib.copyright.status Closed Access 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)
utslib.collection.history School of Civil and Environmental Engineering (ID: 334)

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