An Overview of Preparation of Streamflow Database for ARR Project 5 Regional Flood Method

Speaker: Ataur Rahman

Affiliation: University of Western Sydney

Time: Monday 05/05/2014 from 14:00 to 15:00

Venue: Access Grid UWS. Presented from Penrith (Y239), accessible from Parramatta (EB.1.32) and Campbelltown (26.1.50).

Abstract: Flood damage in Australia is woth over $500 million on average per annum. For designing water infrastructure, a design flood needs to be estimated. For regional flood frequency estimation (RFFE), compilation of streamflow data of the gauged catchments is an essential but tedious step. As a part of Australian Rainfall and Runoff (ARR) Project 5 (Stage 3), a database of 943 unregulated/rural catchments from all over Australia has been compiled. This has been possible due to active cooperation of various state water agencies and in-kind contribution by a large number of professionals. This paper presents important information on the streamflow database which has been used to develop Australian Rainfall and Runoff (ARR) Project 5 Regional Flood Frequency Estimation (RFFE) Model, referred to as ARR RFFE 2014 Model. A total of 877 catchments have been selected from the data-rich region and 66 catchments from the arid/semi-arid regions of Australia. The selected catchments of the data-rich region are generally smaller than 1,000 km2 with a median size of 178 km2. The length of the streamflow data from the data rich region ranges from 19 to 102 years with a median value of 37 years. In preparing the annual maximum (AM) flood series, it was found that about 7% of the data points were needed to be infilled. A Multiple Grubbs-Beck Test (MGBT), an option available in the current ARR FLIKE software, was used to censor the potentially influential low flows from the AM series – the MGBT often finds a greater number of influential lows than the original GB test. It was found that the MGBT is superior to the original GB test. In at-site flood frequency analysis, the LP3 distribution with Bayesian parameter estimation method was adopted. With regard to rating curve error, it was decided to ignore rating curve error in the ARR RFFE 2014 Model development with the understanding that further work is required.

Biography: Assoc Professor Ataur Rahman has over 20 years experiences in water industries, research and universities in Australia and South-east Asia. He obtained his PhD degree in Hydrology from Monash University in Australia. His research interest includes flood hydrology, urban hydrology and environmental risk assessment. He received ‘The G. N. Alexander Medal’ from the Institution of Engineers Australia in 2002. He has published over 230 research papers, reports and book chapters in water and environmental engineering field. He is acting as Project 5 Leader (Regional flood methods) in the forthcoming revised version of Australian Rainfall and Runoff (ARR). He is serving in the editorial board of Australian Journal of Water Resources and international journal Water.