Regional Flood Frequency Analysis Based on Peaks-over-Threshold Model: A Case Study for South-East Australia

Pan, Xiao; Rahman, Ataur

doi:10.1061/9780784484258.039

Cited by 1 publication

(1 citation statement)

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“…Table 1 presents number of studies published which have used the POT model in flood research with at least one of the regularised linear models (LASSO, RR or EN). Scopus has captured three articles [15][16][17] which meet the search criteria, whereas Dimensions and Web of Science have found one [16] and two [15,16] published articles, respectively. When we dive deep into these three articles, it is evident that none of them fully meet the defined search criteria.…”

Section: Introductionmentioning

confidence: 99%

Peaks-Over-Threshold-Based Regional Flood Frequency Analysis Using Regularised Linear Models

Pan,

Yildirim,

Rahman

et al. 2023

Water

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Regional flood frequency analysis (RFFA) is widely used to estimate design floods in ungauged catchments. Most of the RFFA techniques are based on the annual maximum (AM) flood model; however, research has shown that the peaks-over-threshold (POT) model has greater flexibility than the AM model. There is a lack of studies on POT-based RFFA techniques. This paper presents the development of POT-based RFFA techniques, using regularised linear models (least absolute shrinkage and selection operator, ridge regression and elastic net regression). The results of these regularised linear models are compared with multiple linear regression. Data from 145 stream gauging stations of south-east Australia are used in this study. A leave-one-out cross-validation is adopted to compare these regression models. It has been found that the regularised linear models provide quite accurate flood quantile estimates, with a median relative error in the range of 37 to 47%, which outperform the AM-based RFFA techniques currently recommended in the Australian Rainfall and Runoff guideline. The developed RFFA technique can be used to estimate flood quantiles in ungauged catchments in the study region.

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