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

Amir Zalnezhad, Ataur Rahman (), Farhad Ahamed, Mehdi Vafakhah and Bijan Samali
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Amir Zalnezhad: Western Sydney University
Ataur Rahman: Western Sydney University
Farhad Ahamed: Western Sydney University
Mehdi Vafakhah: Tarbiat Modares University
Bijan Samali: Western Sydney University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 119, issue 3, No 29, 1839-1862

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

Keywords: Floods; Quantile regression technique; Index flood method; Design floods; Australian rainfall and runoff (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06184-7

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