Streamflow data preparation for regional flood frequency analysis : lessons from Southeast Australia

This paper presents a case study on streamf ow data preparation for a regional f ood 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 f ood series data for a large number of stations from Victoria and NSW, and applied various statistical techniques to prepare the f nal 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 f nal data set, as streamf ow data are affected by many sources of uncertainty. The trade-offs between quality and quantity are discussed and illustrated. The maximum rating ratio, def ned as the ratio of the largest estimated f ow and the maximum measured f ow 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 food quantiles up to 90%.