Comparison of annual maximum and peaks-over-threshold methods with automated threshold selection in flood frequency analysis: a case study for Australia

Pan, Xiao; Rahman, Ataur

doi:10.1007/s11069-021-05092-y

Cited by 9 publications

(9 citation statements)

References 23 publications

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“…The frequencies of flood and drought events in the YRB vary from 1.42 to 2.58 and from 0.30 to 0.67, respectively. Previous studies have shown that the frequency of flood events based on the POT method is generally between 1 and 3 (Neri et al., 2020; Pan & Rahman, 2021; W. Yang, Yang, & Yang, 2020), and the frequency of drought events on the TP varies from 0.16 to 1.13 (Table S3 in Supporting Information ). Therefore, the identification of flood and drought characteristics in this study is reasonable.…”

Section: Discussionmentioning

confidence: 99%

Flood Increase and Drought Mitigation Under a Warming Climate in the Southern Tibetan Plateau

Shao

Zhang

et al. 2023

JGR Atmospheres

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Droughts and floods, two extremes in hydrological processes, are devastating natural disasters. Accounting for 48% of all natural disasters, droughts, and floods have caused property damages valued at US$ 762 billion, affecting more than 3.4 billion people globally from 1995 to 2015 (UNISDR, 2015). In addition to socioeconomic losses, they also disrupt the ecological balance, causing great disturbances with irreversible damage (Mora

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Section: Discussionmentioning

confidence: 99%

Flood Increase and Drought Mitigation Under a Warming Climate in the Southern Tibetan Plateau

Shao

Zhang

et al. 2023

JGR Atmospheres

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“…This presents a comparison of the identified threshold based on MLE and PMWU in MRLP. It can be seen that there is no remarkable distinction in the identified thresholds using the two estimators having the same p-value (Pan and Rahman, 2021).…”

Section: Independence and Threshold Selectionmentioning

confidence: 96%

“…The POT model has been employed in extreme value analysis using Generalised Pareto (GP) distribution (Bernardara, Andreewsky and Benoit 2011;Coles 2001;Coles 2003;Coles et al 2003;Liang et al 2019;Northrop and Jonathan 2011;Pan and Rahman 2021;Thompson et al 2009). The POT sampling process extracts a greater number of data points from the historical record compared to the AM model.…”

Section: Introductionmentioning

confidence: 99%

“…POT model is also advantageous in terms of flexibility of sampling process, i.e. based on the purpose of the analysis, the POT model can extract desired numbers of data points by adjusting the level of threshold (Pan and Rahman 2018). However, the additional complexity associated with the POT model in relation to data independence is a negative aspect, which is one of the reasons for its under-employment (Lang et al 1999;Pan and Rahman 2021).…”

Section: Introductionmentioning

confidence: 99%

“…based on the purpose of the analysis, the POT model can extract desired numbers of data points by adjusting the level of threshold (Pan and Rahman 2018). However, the additional complexity associated with the POT model in relation to data independence is a negative aspect, which is one of the reasons for its under-employment (Lang et al 1999;Pan and Rahman 2021). There is no unique procedure to select a threshold value in the POT modelling, and hence an iterative process is commonly adopted.…”

Section: Introductionmentioning

confidence: 99%

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Peaks-over-threshold model in flood frequency analysis: a scoping review

Pan

Rahman

Haddad

et al. 2022

Stoch Environ Res Risk Assess

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In flood frequency analysis (FFA), annual maximum (AM) model is widely adopted in practice due to its straightforward sampling process. However, AM model has been criticized for its limited flexibility. FFA using peaks-over-threshold (POT) model is an alternative to AM model, which offers several theoretical advantages; however, this model is currently underemployed internationally. This study aims to bridge the current knowledge gap by conducting a scoping review covering several aspects of the POT approach including model assumptions, independence criteria, threshold selection, parameter estimation, probability distribution, regionalization and stationarity. We have reviewed the previously published articles on POT model to investigate: (a) possible reasons for underemployment of the POT model in FFA; and (b) challenges in applying the POT model. It is highlighted that the POT model offers a greater flexibility compared to the AM model due to the nature of sampling process associated with the POT model. The POT is more capable of providing less biased flood estimates for frequent floods. The underemployment of POT model in FFA is mainly due to the complexity in selecting a threshold (e.g., physical threshold to satisfy independence criteria and statistical threshold for Generalized Pareto distribution – the most commonly applied distribution in POT modelling). It is also found that the uncertainty due to individual variable and combined effects of the variables are not well assessed in previous research, and there is a lack of established guideline to apply POT model in FFA.

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Quantifying patterns of streamflow peaks over the southeastern United States using a long‐term retrospective data set

Raczyński,

Dyer

2023

Hydrological Processes

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Utilizing simulated daily flow values for 61 948 stream nodes from the National Water Model (NWM) v.2.1 retrospective data set, which covers the period 1979–2020, streamflow peaks (SFP) were determined using an objective threshold method based on the Fisher‐Jenks breakpoint algorithm. This approach provides estimates of low probability, high in‐channel water level conditions. Strong spatial relations in temporal streamflow peak distribution were observed, with four main spatial clusters covering: (1) the central parts of Mississippi to South Carolina; (2) the south and north parts of Mississippi to South Carolina; (3) Florida, the Gulf Coast, and parts of North Carolina and Virginia; and (4) the Atlantic Coast and parts of the Gulf Coast. The first area is characterized by high multiannual SFP occurrence with long total durations, high contribution to total discharge, and occurrence throughout the year with peaks in February and March. Increasing annual peak trends are present locally. The second area is characterized by similar parameters with increased flash flooding potential. In the third area, lower occurrence and share in total discharge are observed, with two peaks of occurrence in the September–October and March periods. In the fourth region, the lowest occurrences and shortest durations are present, along with strong seasonality manifested in September–October occurrences that constitute over 80% of all SFP volumes. Decreasing trends in maximal monthly flows for the June–October period are also observed here. The results provide valuable regionalized information about historical high flow characteristics across the southeast United States, which can be used as a basis for improved long‐term flood prediction based on seasonality models and constitute a baseline for defining regional changes in high flow frequency and distribution.

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Comparison of annual maximum and peaks-over-threshold methods with automated threshold selection in flood frequency analysis: a case study for Australia

Cited by 9 publications

References 23 publications

Flood Increase and Drought Mitigation Under a Warming Climate in the Southern Tibetan Plateau

Flood Increase and Drought Mitigation Under a Warming Climate in the Southern Tibetan Plateau

Peaks-over-threshold model in flood frequency analysis: a scoping review

Quantifying patterns of streamflow peaks over the southeastern United States using a long‐term retrospective data set

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