Research papersA comparison of methods for estimating climate change impact on design rainfall using a high-resolution RCM

•Nine methods were compared in estimating design rainfall using RCM simulations.•Bias correcting the AMS is more effective than correcting the total rainfall distribution.•Regional frequency analysis is recommended to provide more spatially coherent patterns of future change.•A cross validation framework is proposed that evaluates errors in probability space.

Design rainfall is used to analyse and size water infrastructure and is generally derived from historical rainfall records. Given the expected changes in extreme rainfall due to anthropogenic climate change, future hydrologic design based on historical data may not be appropriate. While a number of studies have assessed the impact of climate change on design rainfall using different methods, to date there has been no comprehensive comparison or examination of the implications of alternative methods on future design rainfall estimates. This study compares the nine methods for estimating the design rainfall for the current climate and the potential changes in the future for the Greater Sydney region. A Monte Carlo cross-validation procedure was employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It was found that bias correcting the annual maximum rainfall based on the empirical distribution combined with regional frequency analysis produces the design rainfall closest to the observations. While regional frequency analysis was found to have limited impact on the design rainfall estimation for the current climate, it provides much more spatially coherent patterns of future change and it is recommended that regionalisation be used in all design rainfall impact assessments. Despite the variations between different methods, a 20-35% increase in design rainfall over the coastal region is consistently projected. This will pose significant challenges for existing infrastructure in that area.