Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis

Bezak, Nejc; Brilly, Mitja; Šraj, Mojca

doi:10.1080/02626667.2013.831174

Cited by 231 publications

(201 citation statements)

References 55 publications

(107 reference statements)

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“…However, LMOM estimation has been shown to yield more robust estimation results for small sample sizes (Hosking et al, 1985;Hosking et al, 1987), which can be especially beneficial when analyzing environmental data like temperature or precipitation indicators, which are derived from raw measurements at meteorological measuring stations. Regarding the overall results, LMOM estimation turned out to offer a better fit than MLE, which is consistent with previous findings (Hosking et al, 1985;Hosking et al, 1987;Bezak et al, 2014).…”

Section: Discussionsupporting

confidence: 90%

“…While some studies only provide a qualitative description of resulting parameter estimates and estimated return levels for both methods (Jarušková and Hanek, 2006), more formal assessment approaches are based on the asymptotic variance of the T -year event estimator (Cunnane, 1973) or on various goodness-of-fit tests and model performance metrics (Madsen et al, 1997a, b;Bezak et al, 2014). Controversial conclusions have been drawn.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Madsen et al (1997a) found for extreme discharges that the most suitable approach depends on the sample size and the shape parameter of the fitted functions. However, Ben-Zvi (2009) and Bezak et al (2014) argue that a generalized Pareto (GP) distribution fitted to partial duration series yields the best results for modeling rainfall and discharge extremes. Mkhandi et al (2005), again, found that AMS and PDS methods result in similar predictions of flood magnitudes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Schlögl

Laaha

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Schlögl

Laaha

2017

Nat. Hazards Earth Syst. Sci.

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“…Such an approach allows us to obtain a larger statistical sample, for which it is necessary to define a threshold value that determines whether a particular rainfall event can be classified as an extreme event (Dupuis 1998). This approach is recommended by many authors (Lang et al 1999;Re, Barros 2009;Tramblay et al 2013;Bezak et al 2014;Wdowikowski et al 2016;Gharib et al 2017) and by the Intergovernmental Panel on Climate Change (IPCC 2014), among others. A detailed description of the POT method can be found in the papers by Coles (2001), andBommier (2014).…”

Section: Methods For Determining Rainfall Maximamentioning

confidence: 99%

Criteria for identifying maximum rainfall determined by the peaks-over-threshold (POT) method under the Polish Atlas of Rainfall Intensities (PANDa) project

Burszta‐Adamiak¹,

Licznar²,

Zaleski³

2019

Meteorol. Hydrol. Water Manage.

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Abstract. Determination of rainfall maxima from long-term series is one of the more important tasks in urban hydrology. These maxima are useful both in designing land drainage systems and for flood protection in a catchment.The identification of rainfall maxima for the hierarchy of rainfall durations from 5 min to 4 320 min is a fundamental stage of the creation of the first version of the Polish Atlas of Rainfall Intensities (PANDa), which will ultimately be a source of updated and reliable information on design rainfall intensities for designing and modeling rainwater drainage and retention systems in Poland. One of the methods for identifying extreme rainfall events is to use criteria for selecting rainfall based on their depth for a given rainfall frequency and duration. Existing national experience in this respect is based on the results of analyses usually conducted with regard to records from single weather stations. This article presents the results of a study designed to verify the usefulness of the literature-based criteria for identifying rainfall maxima using the peaks-over-threshold (POT) method at a much broader nationwide scale.The study analyzed data from a previously created digital database of rainfall series, which includes 3 000 stationyears (consisting of a 30-year measurement series from 100 weather stations of the Institute of Meteorology and the Water Management -National Research Institute (IMGW-PIB). The study results show that as far as the investigated measurement series are concerned, the criteria based on the literature sources have limited application and can only be used for identifying the largest short-duration rainfall events. To determine rainfall maxima for all of the time intervals analyzed (from 5 minutes to 3 days), it was necessary to develop our own criteria that would allow the methodology for identifying extreme rainfall events to be standardized for all 100 stations.

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“…In the study of Madsen et al [9], they found that the POT model is more advantageous than the AM model in cases where only short records are available. The POT series also has some obvious disadvantages, and the major one is that the flood peaks might not form an independent time series, since some flood peaks may occur on the recession curves of the preceding flood peaks [10]. Thus, both series are used to indicate high flow extremes and compared to each other in this study.…”

Section: Introductionmentioning

confidence: 99%

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

Wang

Zhao

et al. 2016

Water

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Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM) series and the peaks over a threshold (POT) series in order to study the hydrological extremes, examines the stationarity and independence assumptions for the two series, and discusses the estimations and uncertainties of return levels from the two series using the Generalized Extreme Value (GEV) and Generalized Pareto distribution (GPD) models. For comparison, the return levels from all threshold excesses with considering the extremal index are also estimated. For the POT series, the threshold is selected by examining the mean excess plot and the stability of the parameter estimates and by using common-sense. The serial correlation is reduced by filtering out a set of dependent threshold excesses. Results show that both series are approximately stationary and independent. The GEV model fits the AM series well and the GPD model fits the POT series well. The estimated return levels are fairly comparable for the AM series, the POT series, and all threshold excesses with considering the extremal index, with the difference being less than 10% for return periods longer than 10 years. The uncertainties of the estimated return levels are the highest for the AM series, and next for the POT series and then for all threshold excesses series in turn.

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Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis

Cited by 231 publications

References 55 publications

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Criteria for identifying maximum rainfall determined by the peaks-over-threshold (POT) method under the Polish Atlas of Rainfall Intensities (PANDa) project

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

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