Non-stationary frequency analysis of heavy rainfall events in southern France

Tramblay, Yves; Neppel, Luc; Carreau, Julie; Najib, K.

doi:10.1080/02626667.2012.754988

Cited by 124 publications

(101 citation statements)

References 54 publications

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“…Several studies recommended the use of peaks-over-threshold (POT) data (derived by selecting values over a certain threshold) instead of annual maxima as extreme rainfall data input to frequency analysis (e.g. Re and Barros, 2009;Tramblay et al, 2013), since the POT approach results in larger data sets, leading to more accurate parameter estimations of extreme value distribution. Therefore, this study used POT data to develop stationary and non-stationary GPD models.…”

Section: A G Yilmaz Et Al: Climate Change and Variability On Rainfmentioning

confidence: 99%

“…Park et al (2011) developed non-stationary generalised extreme value (GEV) distribution (another commonly used extreme value distribution) models for frequency analysis of extreme rainfalls in Korea considering non-stationarity similar to Sugahara et al (2009). Tramblay et al (2013) performed non-stationary heavy rainfall (it should be noted that "heavy" rainfall used here as same as "extreme" rainfall in Sugahara et al, 2009) analysis using daily rainfall data of the period in France. They incorporated the climatic covariates into the generalised Pareto distribution parameters to consider nonstationarity.…”

Section: A G Yilmaz Et Al: Climate Change and Variability On Rainfmentioning

confidence: 99%

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Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

Yilmaz

Hossain

Perera

2014

Hydrol. Earth Syst. Sci.

115

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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when nonstationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and nonstationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity-frequency-duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.

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Section: A G Yilmaz Et Al: Climate Change and Variability On Rainfmentioning

confidence: 99%

Section: A G Yilmaz Et Al: Climate Change and Variability On Rainfmentioning

confidence: 99%

Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

Yilmaz

Hossain

Perera

2014

Hydrol. Earth Syst. Sci.

115

View full text Add to dashboard Cite

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“…1) to climate (Tramblay et al, 2013;López and Francés, 2013), in order to derive flood projections under climate change. Large-scale monsoon intensity is used to explain the scale parameter of the non-stationary flood frequency distribution representing the variability of floods in the lower Mekong Basin.…”

Section: Introductionmentioning

confidence: 99%

Projecting flood hazard under climate change: an alternative approach to model chains

Delgado

Merz

Apel

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Flood hazard projections under climate change are typically derived by applying model chains consisting of the following elements: "emission scenario -global climate model -downscaling, possibly including bias correctionhydrological model -flood frequency analysis". To date, this approach yields very uncertain results, due to the difficulties of global and regional climate models to represent precipitation. The implementation of such model chains requires major efforts, and their complexity is high.We propose for the Mekong River an alternative approach which is based on a shortened model chain: "emission scenario -global climate model -non-stationary flood frequency model". The underlying idea is to use a link between the Western Pacific monsoon and local flood characteristics: the variance of the monsoon drives a non-stationary flood frequency model, yielding a direct estimate of flood probabilities. This approach bypasses the uncertain precipitation, since the monsoon variance is derived from large-scale wind fields which are better represented by climate models. The simplicity of the monsoon-flood link allows deriving large ensembles of flood projections under climate change. We conclude that this is a worthwhile, complementary approach to the typical model chains in catchments where a substantial link between climate and floods is found.

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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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Non-stationary frequency analysis of heavy rainfall events in southern France

Cited by 124 publications

References 54 publications

Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne

Projecting flood hazard under climate change: an alternative approach to model chains

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

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