A new flood regionalisation model for large flood estimation in Australia

Estimation of large to rare floods is needed in the design of major water infrastructure such as large bridges, weirs and dam spillways. This paper presents a simple Large Flood Regionalisation Model (LFRM) which is relatively easy to apply in practice. The proposed method assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation (CV) and inter-station correlation among the flood series data. For application of the LFRM to the ungauged catchment case, prediction equations need to be developed. In this study, a generalised least squares regression (GLSR) combined with the region-of-influence (ROI) approach is used for developing the prediction equations for the mean and CV of the annual maximum flood series as a function of easily obtainable catchment characteristics. The LFRM is developed and tested in this paper using data from 626 catchments across the Australian continent.