Regional flood modelling in the new Australian Rainfall and Runoff

![CDATA[This paper presents the regional flood estimation model being developed for the 4th edition of Australian Rainfall and Runoff (ARR). This covers the basic steps in the adopted modelling framework i.e. data collation, formation of regions, model form, and estimation of the parameters of the model. The adopted modeling framework revolves around the principles of reduction of uncertainty and the best possible use of the regional data by the reduction of the regional heterogeneity to enhance the accuracy of at-site design flood estimation. The ARR regional flood estimation model uses a Bayesian generalised least squares regression-based approach in the data-rich regions of Australia that consists of 619 stations. In the formation of the regions, it divides Australia into a number of regions. A region-of-influence approach is adopted to form regions where there are over 50 stations in the region. It also adopts a parameter regression technique where three parameters of the Log Pearson Type 3 distribution are regionalized. A Monte Carlo simulation technique is adopted to estimate the model uncertainty. The RFFA model is being re-calibrated with the new IFD data and the most up-to-date streamflow records and is expected to be released by Dec 2013.]]