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

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%.