Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

Wi, Sungwook; Valdés, Juan B.; Steinschneider, Scott; Kim, Tae‐Woong

doi:10.1007/s00477-015-1180-8

Cited by 82 publications

(64 citation statements)

References 56 publications

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“…Methods for selecting measured data appropriate for the probabilistic determination of maximum rainfall values are described widely in the global literature -these are, namely, the annual maximum precipitation (AMP or MAP) and peak-over-threshold (POT) methods. Because many studies indicate that the AMP method provides lower maximum rainfall values, in this research the necessary data were selected using the POT method (Coles 2001;Kim, Zhang 2011;Onyutha 2012;Shinyie et al 2014;Yilmaz et al 2014;Jakubowski 2015;Wdowikowski, Kaźmierczak 2015;Kaźmierczak, Wdowikowski 2016;Wi et al 2016). For all 8 stations the 95 th percentile was found to be appropriate as the threshold level for 24-hour POT data series.…”

Section: Maximum Rainfall Modelmentioning

confidence: 99%

Maximum daily rainfall analysis at selected meteorological stations in the upper Lusatian Neisse River basin

Wdowikowski¹,

Kaźmierczak²,

Ledvinka³

2016

Meteorol. Hydrol. Water Manage.

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Abstract. The scope of this study was to assess the usefulness of top probability distributions to describe maximum rainfall data in the Lusatian Neisse River basin, based on eight IMWM-NRI meteorological stations. The research material was composed of 50-year precipitation series of daily totals from 1961 to 2010. Misssing measurement data were estimated using a weighted average method. Homogeneity for refilled data were investigated by precipitation double aggregation curve. Correlation between the measurement data varied from 96 to 99% and did not indicate a violation of the homogeneity of rainfall data series. Variability of recorded daily precipitation maxima were studied by linear regression and non-parametric Mann-Kendall tests. Long-term period changes at maximum rainfalls for four stations remained statistically insignificant, and for the other four were significant, although the structure of maximums was relatively similar. To describe the measured data, there were used the Fréchet, Gamma, Generalized Exponential Distribution (GED), Gumbel, Log-normal and Weibull distributions. Particular distribution parameters were estimated using the maximum likelihood method. The conformity of the analyzed theoretical distributions with measured data was inspected using the Schwarz Bayesian information criterion (BIC) and also by the relative residual mean square error (RRMSE). Among others, the Gamma, GED, and Weibull distributions fulfilled the compliance criterion for each meteorological station respectively. The BIC criterion indicated GED as the best; however differences were minor between GED on the one hand and the Gamma and Weibull distributions on the other. After conducting the RRMSE analysis it was found that, in comparison to the other distributions, GED best describes the measured maximum rainfall data.

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Section: Maximum Rainfall Modelmentioning

confidence: 99%

Maximum daily rainfall analysis at selected meteorological stations in the upper Lusatian Neisse River basin

Wdowikowski¹,

Kaźmierczak²,

Ledvinka³

2016

Meteorol. Hydrol. Water Manage.

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“…The isolation has been done on the basis of the Peak-Over-Threshold (POT) method [14][15][16][17][18][19]. Selected top rainfall heights were listed in descending order.…”

Section: Methodsmentioning

confidence: 99%

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

et al. 2017

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Abstract. Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

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“…The commonly used approach to incorporate non-stationarity in time series into the frequency analysis is to vary one parameter of the theoretical probability distribution while the other two are kept constant (Liuzzo and Freni, 2015;Wi et al, 2016). In this study we used a Bayesian approach to estimate distribution parameters under stationary and nonstationary assumptions (Cheng and AghaKouchak, 2014).…”

Section: Non-stationary Gev and Gpd Estimationmentioning

confidence: 99%

“…In addition, positive increases in observed precipitation linked to a warmer atmosphere also bring into question the validity of the IDF curves developed under stationary assumptions and has prompted the development of new methods for determining return periods and risk that take 20 into account the effect of non-stationary in climate extremes (Bhatkoti et al, 2016;Condon et al, 2015;Du et al, 2015;Khaliq et al, 2006;Obeysekera and Salas, 2014;Salas and Obeysekera, 2014;Serinaldi and Kilsby, 2015). A few climate studies have shown that design storm estimates from stationary models are significantly lower than estimates from nonstationary models (Cheng and AghaKouchak, 2014;Sarhadi and Soulis, 2017;Wi et al, 2016). However, the lack of observed sub-daily precipitation limits the studies to using scaling factors to temporally disaggregate daily observations or 25 use merged radar-rain gauge data (Cheng and AghaKouchak, 2014;Yu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Frequency Analysis of Extreme Sub-Daily Precipitation under Stationary and Non-Stationary Conditions across Two Contrasting Hydroclimatic Environments

Demaria

Goodrich

Keefer

2017

Preprint

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Abstract. Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration-Frequency (IDF) curves under stationary and non-stationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-10 Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5-to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the 15 semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25% for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in 20 storm design.

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Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

Cited by 82 publications

References 56 publications

Maximum daily rainfall analysis at selected meteorological stations in the upper Lusatian Neisse River basin

Maximum daily rainfall analysis at selected meteorological stations in the upper Lusatian Neisse River basin

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

Frequency Analysis of Extreme Sub-Daily Precipitation under Stationary and Non-Stationary Conditions across Two Contrasting Hydroclimatic Environments

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