Design flood estimation at ungauged catchments using index flood method and quantile regression technique: a case study for South East Australia

Abstract Flood is one of the worst natural disasters, which causes damage billions dollars each year globally. To reduce flood damage, we need to estimate design floods accurately, are used in and operation water infrastructure. For gauged catchments, frequency analysis can be floods; however, for ungauged regional (RFFA) used. This paper compares two popular RFFA techniques, namely quantile regression technique (QRT) index method (IFM). A total 181 catchments selected this study from south-east Australia. Eight predictor variables develop prediction equations. It has been found that IFM outperforms QRT general. higher annual exceedance probabilities (AEPs), generally demonstrates a smaller estimation error than QRT; AEPs (e.g. 1 100), provides more accurate estimates. The comparable estimates with Australian Rainfall Runoff—the national guide