Design Flood Estimation in Ungauged Catchments: A Comparison Between the Probabilistic Rational Method and Quantile Regression Technique for NSW

Abstract

Design flood estimation for ungauged catchments is often required in hydrologie design. The most commonly adopted regional flood frequency analysis methods used for this purpose include the index flood method, regression based techniques and various forms of the rational method. This paper first examines the similarities and differences between the probabilistic rational method (PRM) (the currently recommended method for Victoria and eastern NSW in Australian Rainfall and Runoff) and the generalised least squares (GLS) based quantile regression technique (QRT). It then uses data from 107 catchments in NSW to compare the performance of these two methods. To make a valid comparison, the same predictor variables and data set have been used for both methods. Based on one-at-a-time and split sample validation tests and a range of evaluation statistics, it has been found that the GLS-based QRT performs better than the PRM. The particular advantage of the QRT is that it does not require a contour map of the runoff coefficient as with the PRM. The QRT also offers potential for improvement through inclusion of additional predictor variables. The QRT can also be integrated with the region of influence approach, where a region can be formed around an ungauged catchment by selecting an “appropriate number” of neighbouring gauged catchments. Overall, the QRT offers much greater flexibility and potential in terms of error analysis and further development as compared to the PRM.