Managing Hydrological Risks with Extreme Modeling: Application of Peaks over Threshold Model to the Loukkos Watershed, Morocco

Zoglat, Abdelhak; Adlouni, Salaheddine El; Badaoui, Fadoua; Amar, Amine; Okou, C. G.

doi:10.1061/(asce)he.1943-5584.0000996

Cited by 16 publications

(23 citation statements)

References 33 publications

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“…Compared to graphical methods, analytical methods are less subjective and the computations can easily be programmed. Zoglat et al [25] compared various threshold selection techniques. Two analytical methods outperformed the other techniques and were employed in our study: The Square Error Method (SE) and Likelihood Ratio Test method (LRT).…”

Section: Threshold Selection Methodsmentioning

confidence: 99%

“…Zoglat et al [25] suggested an algorithm based on the work of Beirlant et al [51]. The main steps of the algorithms are as follows (Adapted from Zoglat et al [25]):…”

Section: Threshold Selection Methodsmentioning

confidence: 99%

“…[25]. It is based on using the likelihood ration test statistic to test the hypothesis H 0 : u i is the optimal threshold against H 1 : u k is the optimal threshold.…”

mentioning

confidence: 99%

“…For LRT application, the maximum threshold is selected to correspond to 36 exceedances-the number of years in the record multiplied by 1.65 [24]. For more details on LRT method see Zoglat et al [25]. Further, to meet the requirements for the POT method, an independence test is applied to ensure that peaks identified with the POT method correspond to different flood events.…”

mentioning

confidence: 99%

“…For more details on LRT method see Zoglat et al [25]. Further, to meet the requirements for the POT method, an independence test is applied to ensure that peaks identified with the POT method correspond to different flood events.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

Gharib

Davies

Goss

et al. 2017

Water

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Abstract:Floods are costly natural disasters that are projected to increase in severity and frequency into the future. Exceedances over a high threshold and analysis of their distributions, as determined through the Peak Over Threshold (POT) method and approximated by a Generalized Pareto Distribution (GPD), respectively, are widely used for flood frequency analysis. This study investigates the combined effects of threshold selection and GPD parameter estimation on the accuracy of flood quantile estimates, and develops a new, widely-applicable framework that significantly improves the accuracy of flood quantile estimations. First, the performance of several parameter estimators (i.e., Maximum Likelihood; Probability Weighted Moments; Maximum Goodness of Fit; Likelihood Moment; Modified Likelihood Moment; and Nonlinear Weighted Least Square Error) for the GPD was compared through Monte Carlo simulation. Then, a calibrated Soil and Water Assessment Tool (SWAT) model for the province of Alberta, Canada, was used to reproduce daily streamflow series for 47 watersheds distributed across the province, and the POT was applied to each. The Goodness of Fit for the resulting flood frequency models was measured by the upper tail Anderson-Darling (AD) test and the root-mean-square error (RMSE) and demonstrated improvements for more than one-third of stations by averages of 65% (AD) and 47% (RMSE), respectively.

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Section: Threshold Selection Methodsmentioning

confidence: 99%

“…Zoglat et al [25] suggested an algorithm based on the work of Beirlant et al [51]. The main steps of the algorithms are as follows (Adapted from Zoglat et al [25]):…”

Section: Threshold Selection Methodsmentioning

confidence: 99%

“…[25]. It is based on using the likelihood ration test statistic to test the hypothesis H 0 : u i is the optimal threshold against H 1 : u k is the optimal threshold.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

Gharib

Davies

Goss

et al. 2017

Water

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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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Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

Thiombiano

Adlouni

St‐Hilaire

et al. 2016

Theor Appl Climatol

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In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.

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Managing Hydrological Risks with Extreme Modeling: Application of Peaks over Threshold Model to the Loukkos Watershed, Morocco

Cited by 16 publications

References 33 publications

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

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

Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

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